Juan B Valdes

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Courses

Scholarly Contributions

Chapters

• Schneier-Madanes, G., Valdes, J. B., & Curley, E. (2016). Water and urban development challenges of urban growth. In Water Bankruptcy in the Land of Plenty(pp 141-157). CRC Press.
• Serrat-Capdevila, A. -., Valdes, J. B., Gupta, H. V., & Schneier-Madanes, G. (2013). Towards a Comprehensive Assessment of Climate Change Projections in the Tarim Basin region. How can uncertain predictions inform adaptive police?. In WATARID 3 Uses and Policy of Water Resources in Arid and Sem-Arid Regions(pp 129-137). Editions Hermann.
• Serrat-Capdevila, A. -., Valdes, J. B., Gupta, H. V., & Schneier-Madanes, G. (2013). Water Governance Tools" The Role of Science, Decision Support Systems in Participatory Management. In Water Governance(pp 241-259). Springer.

Journals/Publications

• Roy, T., Gupta, H. V., Serrat-Capdevila, A., & Valdes, J. B. (2017). Using Satellite-based Evapotranspiration to Improve the Structure of a Simple Conceptual Rainfall-Runoff Model. Hydrology and Earth System Sciences (HESS). doi:10.5194/hess-21-879-2017
• Valdes-Pineda, R., Canon, J., & Valdes, J. B. (2017). Multi-decadal 40- to 60-year cycles of precipitation variability in Chile (South America) and their relationship to the AMO and PDO signals. Journal of Hydrology. doi:10.1016/j.hydrol.2017.01.031
• Duran-Barroso, P., Gonzalez, J., & Valdes, J. B. (2016). Improvement of the integration of Soil Moisture Accounting into the NRCS-CN model. JOURNAL OF HYDROLOGY, 542, 809-819.
• Gonzalez-Leiva, F., Valdes-Pineda, R., Valdes, J. B., & Ibanez-Castillo, L. (2016). “Assessing the Performance of Two Hydrologic Models for Forecasting Mean Daily Streamflows in the Cazones River Basin (Mexico),”. International Journal of Modern Hydrology, 6(3), 168-181. doi:10.4236/OJMH.2016.63014
• Serrat-Capdevila, A. -., Merino, M., Valdes, J. B., & Durcik, M. (2016). Evaluation of the Performance of Three Satellite Precipitation Products over Africa. Remote Sensing, 8(10), 836. doi:10.3390/rs8100836
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  We present an evaluation of daily estimates from three near real-time quasi-global Satellite Precipitation Products—Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center (CPC) Morphing Technique (CMORPH)—over the African continent, using the Global Precipitation Climatology Project one Degree Day (GPCP-1dd) as a reference dataset for years 2001 to 2013. Different types of errors are characterized for each season as a function of spatial classifications (latitudinal bands, climatic zones and topography) and in relationship with the main rain-producing mechanisms in the continent: the Intertropical Convergence Zone (ITCZ) and the East African Monsoon. A bias correction of the satellite estimates is applied using a probability density function (pdf) matching approach, with a bias analysis as a function of rain intensity, season and latitude. The effects of bias correction on different error terms are analyzed, showing an almost elimination of the mean and variance terms in most of the cases. While raw estimates of TMPA show higher efficiency, all products have similar efficiencies after bias correction. PERSIANN consistently shows the smallest median errors when it correctly detects precipitation events. The areas with smallest relative errors and other performance measures follow the position of the ITCZ oscillating seasonally over the equator, illustrating the close relationship between satellite estimates and rainfall regime.
• Valdes-Pineda, R., Demaria, E., Valdes, J. B., Wi, S., & Serrat-Capdevila, A. (2016). Bias Correction of Daily Satellite-based Rainfall Estimates for Hydrologic Forecasting in the Upper Zambezi, Africa. Hydrologic and Earth System Sciences Discussion. doi:10.5194/hess-2016-473
• Gonzalez-Leiva, F., Alicia Ibanez-Castillo, L., Valdes, J. B., Alberto Vazquez-Pena, M., & Ruiz-Garcia, A. (2015). Streamflow Forecasting for the Turbio River using the Discrete Kalman Filter. TECNOLOGIA Y CIENCIAS DEL AGUA, 6(4), 5-24.
• Valdes-Pineda, R., Pizarro, R., Valdes, J. B., Carrasco, J. F., Garcia-Chevesich, P., & Olivares, C. (2015). Spatio-temporal trends of precipitation, its aggressiveness and concentration, along the Pacific coast of South America (36° - 49° S).. Hydrological Sciences Journal, 61(11), 2110-2132.
• Wi, S., Valdes, J. B., & Kim, T. (2015). “Non-stationary frequency analysisof extreme precipitation in South Korea using peaks-over-threshold and annual maxima,”. Stochastic Environmental Research and Risk Assessment.
• Demaria, E. M., Nijssen, B., Valdés, J. B., Rodriguez, D. A., & Fengge, S. u. (2014). Satellite precipitation in southeastern South America: how do sampling errors impact high flow simulations?. International Journal of River Basin Management.
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  Abstract: Satellite precipitation estimates are increasingly available at temporal and spatial scales of interest to hydrological applications and with the potential for improving flood forecasts in data-sparse regions. This study evaluates the effect of sampling error on simulated large flood events. Synthetic precipitation fields were generated in Monte Carlo fashion by perturbing observed precipitation fields with sampling errors based on 1, 2 and 6 h intervals. The variable infiltration capacity hydrological model was used to assess the impact of these errors on simulated high flow events in the Iguazu basin, a rain-dominated, subtropical basin in southeastern South America. Results showed that unbiased errors in daily error-corrupted precipitation fields introduced bias in the simulated hydrologic fluxes and states. The overall bias for error-corrupted daily streamflows was positive and its magnitude increased with larger sampling intervals. However, for high flow events, the bias was negative as a result of an increase in simulated infiltration and changes in precipitation variability. Errors in precipitation also affected the magnitude and volume of the peak events but did not change the first two statistical moments of the peaks indicating that non-linearities in the hydrological system preserve the statistical properties of high flows in the basin. Caution is needed when using satellite products for hydrological applications that require the estimation of large peaks and volumes. © 2014 © 2014 International Association for Hydro-Environment Engineering and Research.
• Ivon Morales-Velazquez, M., Aparicio, J., & Valdes, J. B. (2014). Flood Forecasting Using the Discrete Kalman Filter. TECNOLOGIA Y CIENCIAS DEL AGUA, 5(2), 85-110.
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  This study evaluates the usefulness and applicability of the discrete Kalman filter algorithm for predicting short-term floods. The algorithm is applied to the basin of the Angel Albino Corzo (Penitas) dam, which is part of the Grijalva Hydroelectric System, as well as to the Sayula Hydrometric Station. It is used to determine the response function for the basin and thus forecast flows into the reservoir. To that end, both flow data and precipitation recorded at weather stations located in the study area are used, as well as calculated inflows to the basin. This analysis evaluates multiple time increments and different response functions, as well as their associated parameters, using the Nash-Sutcliffe coefficient. Highly acceptable values were obtained, such that the filter is found to be useful for short-term flow forecasting, highlighting its usefulness as a tool to support policy development and the operational control of reservoirs.
• Pizarro, R., Jofré, P., Vera, M., Olivares, C., Garcia-Chevesich, P. A., Alvarado, S., Neary, D. G., Valdes, R., Valdes, J., Aguirre, J. J., & Mena, M. (2014). Respiratory disease and particulate air pollution in Santiago Chile: Contribution of erosion particles from fine sediments. Environmental Pollution, 187, 202-205.
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  Abstract: Air pollution in Santiago is a serious problem every winter, causing thousands of cases of breathing problems within the population. With more than 6 million people and almost two million vehicles, this large city receives rainfall only during winters. Depending on the frequency of storms, statistics show that every time it rains, air quality improves for a couple of days, followed by extreme levels of air pollution. Current regulations focus mostly on PM10 and PM2.5, due to its strong influence on respiratory diseases. Though more than 50% of the ambient PM10s in Santiago is represented by soil particles, most of the efforts have been focused on the remaining 50%, i.e. particulate material originating from fossil and wood fuel combustion, among others. This document emphasizes the need for the creation of erosion/sediment control regulations in Chile, to decrease respiratory diseases on Chilean polluted cities. © 2014 Elsevier Ltd. All rights reserved.
• Serrat-Capdevila, A., Valdes, J. B., & Stakhiv, E. Z. (2014). WATER MANAGEMENT APPLICATIONS FOR SATELLITE PRECIPITATION PRODUCTS: SYNTHESIS AND RECOMMENDATIONS(1). JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 50(2), 509-525.
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  This article is an assessment of the current state of the art and relative utility of satellite precipitation products (SPPs) for hydrologic applications to support water management decisions. We present a review of SPPs, their accuracy in diverse settings including the influence of geography, topography, and weather systems, as well as the pros and cons of their use for different water management applications. At the end of this broad synthesizing effort, recommendations are proposed for: (1) SPP developers to improve the quality, usability, and relevance of precipitation products; and (2) SPP users to improve the reliability of their predictions and hydrologic applications to better support water management.
• Valdes-Pineda, R., Pizarro, R., Garcia-Chevesich, P., Valdes, J. B., Olivares, C., Vera, M., Balocchi, F., Perez, F., Vallejos, C., Fuentes, R., Abarza, A., & Helwig, B. (2014). Water governance in Chile: Availability, management and climate change. JOURNAL OF HYDROLOGY, 519, 2538-2567.
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  Chile has a unique geography that provides an extraordinary variety of climatic conditions and availability of water resources. The objective of this manuscript was to describe and analyze the spatial and temporal distribution patterns, as well as the management of water resources, along a country with a narrow distance from the Andes Mountains to the Pacific Ocean. This presents challenges to water governance from data collection and analysis perspectives, and for administration of the resource. The Water Resources Directorate (Direccion General de Aguas, DGA), is the federal government organization in charge of the water resources of the country. The DGA and other relevant public and private institutions are examined in terms of competition and conflict resolution across different scales and levels of interaction associated with water resources governance. Both monitoring stations (rainfall, streamflow, water quality, groundwater, sediment and snowfall), and the Chilean management and legislation of water resources are also analyzed. Finally, the success (or lack) of the national administration to upgrade its monitoring stations and equalize water resources distribution throughout the country is discussed including the influence of climate change on data collection, and decision making across different scales of water governance. (C) 2014 Elsevier B.V. All rights reserved.
• Valdes-Pineda, R., Valdes, J. B., Diaz, H., & Pizarro, R. (2015). Analysis of long-term changes in annual and seasonal precipitation in Chile and related large-scale atmospheric circulation patterns. International Journal of Climatology, 36(8), 2979-3001.
• Miller, W. P., DeRosa, G. M., Gangopadhyay, S., & Valdes, J. B. (2013). Predicting regime shifts in flow of the Gunnison River under changing climate conditions. WATER RESOURCES RESEARCH, 49(5), 2966-2974.
• Serrat-Capdevila, A., Valdes, J. B., Dominguez, F., & Rajagopal, S. (2013). Characterizing the water extremes of the new century in the US South-west: a comprehensive assessment from state-of-the-art climate model projections. INTERNATIONAL JOURNAL OF WATER RESOURCES DEVELOPMENT, 29(2), 152-171.
• Canon-Barriga, C., Valdes, J. B., & Gupta, H. V. (2012). Modeling the Effect of Irrigation Practices in Flash Floods: A Case Study for the US Southwest. Journal of Water Resource and Protection.
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  Canon-Barriga C, J Valdes and H Gupta (2012), Modeling the Effect of Irrigation Practices in Flash Floods: A Case Study for the US Southwest, Journal of Water Resource and Protection, 4, 415-422, doi: 10.4236/jwarp.2012.47048, Published Online July 2012 (www.SciRP.org/journal/jwarp)
• Sungwook, W. i., Dominguez, F., Durcik, M., Valdes, J., Diaz, H. F., & Castro, C. L. (2012). Climate change projection of snowfall in the Colorado River Basin using dynamical downscaling. Water Resources Research, 48(5).
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  Abstract: Recent observations show a decrease in the fraction of precipitation falling as snowfall in the western United States. In this work we evaluate a historical and future climate simulation over the Colorado River Basin using a 35 km continuous 111 year simulation (1969-2079) of the Weather Research and Forecasting (WRF) regional climate model with boundary forcing from the Hadley Centre for Climate Prediction and Research/Met Office's HadCM3 model with A2 emission scenario. The focus of this work is to (1) evaluate the simulated spatiotemporal variability of snowfall in the historical period when compared to observations and (2) project changes in snowfall and the fraction of precipitation that falls as snow during the 21st century. We find that the spatial variability in modeled snowfall in the historical period (1981-2005) is realistically represented when compared to observations. The trends of modeled snowfall are similar to the observed trends except at higher elevations. Examining the continuous 111 year simulation, we find the future projections show statistically significant increases in temperature with larger increases in the northern part of the basin. There are statistically insignificant increases in precipitation, while snowfall shows a statistically significant decrease throughout the period in all but the highest elevations and latitudes. The fraction of total precipitation falling as snow shows statistically significant declines in all regions. The strongest decrease in snowfall is seen at high elevations in the southern part of the basin and low elevations in the northern part of the basin. The regions of most intense decreases in snow experience a decline of approximately 50% in snowfall throughout the 111 year simulation period. The regions of strongest declines in snowfall roughly correspond to the region of migration of the zero degree Celsius line and emphasize snowfall dependence on both altitude and latitude. © Copyright 2012 by the American Geophysical Union.
• Cañón, J., Domínguez, F., & Valdes, J. B. (2011). Vegetation responses to precipitation and temperature: A spatiotemporal Analysis of ecoregions in the Colorado River Basin. International Journal of Remote Sensing, 32(20), 5665-5687.
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  Abstract: Predicting vegetation response to precipitation and temperature anomalies, particularly during droughts, is of great importance in semi-arid regions, because ecosystem and hydrologic processes depend on vegetation conditions. This article studies vegetation responses to precipitation and temperature in 10 ecological regions within the semi-arid Colorado River Basin (CRB). The Normalized Difference Vegetation Index (NDVI) from Global Inventory Modeling and Mapping Studies (GIMMS) database and the Standardized Precipitation Index (SPI) and temperature series from Parameter-Elevation Regressions on Independent Slope Models (PRISM) database were jointly evaluated for the period 1986-2006, using Multichannel Singular Spectrum Analysis (MSSA) to determine common oscillations and significant lags in vegetation response to seasonal and annual precipitation and temperature. Results show high correlations between lagged SPI series and standardized NDVI: From 1-month lag in the warm deserts (Sonora, Chihuahua and Mojave) to two months in the Temperate Sierras and Semi-Arid Highlands and three months in the Colorado and Arizona/New Mexico Plateaus and the Western Cordillera. Temperature anomalies are negatively correlated to NDVI in the lower CRB and positively correlated in the upper CRB. Notably, we see a basin-wide response to SPI anomalies, and consequently, the identified latitudinal and altitudinal lags between SPI and NDVI will allow an early, basin- wide assessment of lagged vegetation responses to precipitation along the CRB ecoregions. © 2011 Taylor & Francis.
• Cañón, J., Domínguez, F., & Valdés, J. B. (2011). Downscaling climate variability associated with quasi-periodic climate signals: A new statistical approach using MSSA. Journal of Hydrology, 398(1-2), 65-75.
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  Abstract: A statistical method is introduced to downscale hydroclimatic variables while incorporating the variability associated with quasi-periodic global climate signals. The method extracts statistical information of distributed variables from historic time series available at high resolution and uses Multichannel Singular Spectrum Analysis (MSSA) to reconstruct, on a cell-by-cell basis, specific frequency signatures associated with both the variable at a coarse scale and the global climate signals. Historical information is divided in two sets: a reconstruction set to identify the dominant modes of variability of the series for each cell and a validation set to compare the downscaling relative to the observed patterns. After validation, the coarse projections from Global Climate Models (GCMs) are disaggregated to higher spatial resolutions by using an iterative gap-filling MSSA algorithm to downscale the projected values of the variable, using the distributed series statistics and the MSSA analysis. The method is data adaptive and useful for downscaling short-term forecasts as well as long-term climate projections. The method is applied to the downscaling of temperature and precipitation from observed records and GCM projections over a region located in the US Southwest, taking into account the seasonal variability associated with ENSO. © 2010 Elsevier B.V.
• Demaria, E. M., Rodriguez, D. A., Ebert, E. E., Salio, P., Su, F., & Valdes, J. B. (2011). Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach. Journal of Geophysical Research D: Atmospheres, 116(8).
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  Abstract: In this study, an object-based verification method was used to reveal the existence of systematic errors in three satellite precipitation products: Tropical Rainfall Measurement Mission (TRMM), Climate Prediction Center Morphing Technique (CMORPH), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN). Mesoscale convective systems (MCSs) for the austral summer 2002-2003 in the La Plata river basin, southeastern South America, were analyzed with the Contiguous Rain Area (CRA) method. Errors in storms intensity, volume, and spatial location were evaluated. A macroscale hydrological model was used to assess the impact of spatially shifted precipitation on streamflows simulations. PERSIANN underestimated the observed average rainfall rate and maximum rainfall consistent with the detection of storm areas systematically larger than observed. CMORPH overestimated the average rainfall rate while the maximum rainfall was slightly underestimated. TRMM average rainfall rate and rainfall volume correlated extremely well with ground observations whereas the maximum rainfall was systematically overestimated suggesting deficiencies in the bias correction procedure to filter noisy measurements. The preferential direction of error displacement in satellite-estimated MCSs was in the east-west direction for CMORPH and TRMM. Discrepancies in the fine structure of the storms dominated the error decomposition of all satellite products. Errors in the spatial location of the systems influenced the magnitude of simulated peaks but did not have a significant impact on the timing indicating that the system's response to precipitation was mitigating the effect of the errors. Copyright 2011 by the American Geophysical Union.
• Dominguez, F., Cañon, J., & Valdes, J. (2010). IPCC-AR4 climate simulations for the Southwestern US: The importance of future ENSO projections. Climatic Change, 99(3), 499-514.
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  Abstract: Future climate trends for the Southwestern US, based on the climate models included in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report, project a more arid climate in the region during the 21st century. However, future climate variability associated with El Niño Southern Oscillation (ENSO)-an important driver for winter climate variability in the region-have not been addressed. In this work we evaluate future winter ENSO projections derived from two selected IPCC models, and their effect on Southwestern US climate. We first evaluate the ability of the IPCC coupled models to represent the climate of the Southwest, selecting the two models that best capture seasonal precipitation and temperature over the region and realistically represent ENSO variability (Max Planck Institute's ECHAM5 and the UK Met Office HadCM3). Our work shows that the projected future aridity of the region will be dramatically amplified during La Niña conditions, as anomalies over a drier mean state, and will be characterized by higher temperatures (~0. 5°C) and lower precipitation (~3 mm/mnt) than the projected trends. These results have important implications for water managers in the Southwest who must prepare for more intense winter aridity associated with future ENSO conditions. © Springer Science+Business Media B.V. 2009.
• Gastélum, J. R., Valdés, J. B., & Stewart, S. (2010). A system dynamics model to evaluate temporary water transfers in the Mexican Conchos Basin. Water Resources Management, 24(7), 1285-1311.
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  Abstract: The flows of the Rio Conchos are of vital economic importance not only to the agricultural sector in the Mexican side of the Rio Grande basin but also for meeting Mexico's obligation to deliver water to the United States. During the previous decade, a severe drought dramatically decreased the basin's runoff, generating serious economic, social, and political problems in both countries. A System Dynamics (SD) model designed to serve as a decision-support system (DSS) for water managers has been created. This DSS is a lumped semi-distributed model operating on a monthly basis. This DSS incorporates the most important elements of the Conchos basin's water resources system: main rivers, irrigation distribution canals, reservoirs, aquifer, and the three Irrigation Districts. The DSS simulates different short and long term scenarios combining inside and outside Irrigation Districts (IDs). Also, different short scenarios are implemented to investigate the benefits of water transfer from México to the United States. This study has prompted awareness with regards to the degree of complexity and uncertainty of the water right allocation process to different economic variables such as crop yield, production costs, crop prices, subsidies, and water distribution efficiencies. © 2009 Springer Science+Business Media B.V.
• Cañón, J., González, J., & Valdés, J. (2009). Reservoir operation and water allocation to mitigate drought effects in crops: A multilevel optimization using the drought frequency index. Journal of Water Resources Planning and Management, 135(6), 458-465.
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  Abstract: The drought frequency index (DFI) is employed in this study as a drought indicator and as a trigger mechanism for multireservoir system operations during drought. The DFI characterizes droughts according to their duration and intensity, using a probabilistic criterion that takes into account the persistence of extreme low precipitation values. Performances with and without the DFI are evaluated, using reliability and resilience indices, for the Conchos river basin-a tributary of the Rio Grande/Bravo basin between United States and Mexico-through a multilevel nonlinear optimization procedure oriented to reduce water deficits to the United States and maximize net benefits for farmers in Mexican irrigation districts. Results show that the inclusion of the DFI improves the reliability of both reservoirs and water deliveries to users during periods of drought, which reflects an overall improvement of net benefits associated with crop production in Mexican irrigation districts. © 2009 ASCE.
• Cañón, J., Valdes, J., & Gonzalez, J. (2009). Developing academic software for teaching time series analysis: A case study. Computers in Education Journal, 19(2), 49-59.
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  Abstract: The academic training on time series analysis requires not only a sound theoretical background on the methods but also the use of specific academic software to appreciate the methods' capabilities, limitations and proper applicability. It is desirable for students to program the routines and algorithms by themselves but this is not always feasible, particularly during short courses and workshops in which the interest is to understand the information supplied by several analytical methods. Considering the time constraints and the need to stress the interpretative rather than the computational skills, the authors have developed the software package UATSA (University of Arizona Time Series Analysis) that incorporates many analytical tools commonly used in time series analysis in an organized and sequential manner: exploratory statistics, markovian processes, univariate and multivariate analyses (ARMA models), frequency decomposition algorithms, principal components, canonical correlations and cluster analyses are included within the current version of the package. UATSA is a stand-alone executable file compiled in MATLAB ® that has been used in courses of time series analysis in hydrology at the University of Arizona and in several workshops offered by the authors between 2004 and 2007. The software aims to easily illustrate the use of algorithms in the synthesis and decomposition of time series, providing a background to the methods and a visual platform that is user friendly and data extensive. The software has evolved through the years, incorporating suggestions made by students to improve its appearance and widen its scope. The software also has contributed to a shift in teaching dynamics by allowing students and instructors to focus on interpreting and analyzing outcomes rather than just learning the set of mathematical tools.
• Gastélum, J. R., Valdés, J. B., & Stewart, S. (2009). A decision support system to improve water resources management in the conchos basin. Water Resources Management, 23(8), 1519-1548.
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  Abstract: The Conchos basin is the largest tributary to the lower part of the Rio Grande/Rio Bravo basin. During recent years a severe drought has affected México's ability to deliver water from the Conchos basin as required by the 1944 Treaty. In addition, it has generated not only economic problems in the USA and México but also political frictions between these two countries. The Mexican Conchos river has historically contributed with the highest amount of water to USA as established on the water treaty. A Decision Support System (DSS) was developed for the Conchos basin in order to gain a better understanding of the water resources management process in the basin, and to identify the alternatives to improve the cited process. The DSS is a semi-distributed model, based on System Dynamics, and developed using Powersim software. The DSS has been used to evaluate 25 long and short tem water resources allocation alternatives for the two main basin's users: Irrigation Districts and Water Treaty. Some of the most important factors being tested on the 25 water management alternatives include National Commission of Water's yearly water allocation policy, reservoir operation rules, improvement on water distribution efficiencies, etc. The DSS model shows that the historic water resources allocation implemented by the Federal government produces adequate results as compared with the other tested water management alternatives. However, for short term drought scenarios, it is showed that there could be other management alternatives that could perform better than the current water management allocation. In general, the DSS shows what we already expect of dynamic models of systems to provide that understanding the effects of multiple interacting variables in necessary to develop good natural resource management policies. © Springer Science+Business Media B.V. 2008.
• Gastélum, J. R., Valdés, J. B., & Stewart, S. (2009). An analysis and proposal to improve water rights transfers on the Mexican Conchos basin. Water Policy, 11(1), 79-93.
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  Abstract: Water rights transfers are allowed in México under the National Waters Law (LAN) promulgated in 1992. However, water transfers to date have not been widely used and those that have occurred have done so in small quantities and mainly at the level of the irrigation district (ID). We evaluate water policy in México as it relates to transfers and propose alternatives to current policy along the lines of Howe et al. (Water Resources 22(4), 439-445, 1986). Howe et al. proposed guidelines for water markets that comply with efficiency and equity. This guideline is the basis for implementing the approach proposed in this paper. Even though this research targets the Conchos basin, which is the most important tributary to the Rio Grande/Rio Bravo system, the analysis contains experiences and examples of water rights transfers of other Mexican regions. The paper focuses on two main aspects: first, a summarized and structured effort characterizing water resources policy in México in terms of involved institutions, legal aspects, stakeholder roles, etc; second, a series of proposals and recommendations oriented to improving the performance of this policy. © IWA Publishing 2009.
• Minjares-Lugo, J. L., Salmón-Castelo, R. F., Valdés, J. B., Oroz-Ramos, L. A., & López-Zavala, R. (2009). Economic index for inter-annual water management: The case of irrigation District No. 041, Río Yaqui, Mexico. Ingenieria Hidraulica en Mexico, 24(1), 41-54.
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  Abstract: In the agricultural system of Irrigation District No. 041, Río Yaqui, the volume of water for agricultural purposes is supplied by the reservoir system and the aquifers in the region. The efficient operation of this irrigation system is extremely important for the economic, political and social activities of the Yaqui Valley. These activities have had a negative impact in the period from 1996 to 2006, in which the Yaqui River watershed faced a severe drought The objective of this research is to develop, present, and validate an index for the inter-annual water management in this agricultural system. This index, which tries to attenuate the drought effect, includes information about the economic efficiency of the operation rules employed in the Irrigation District. For the development of the index, the Yaqui River simulation-optimization model developed by Minjares et al. (2008) from CONAGUA's Northwest Watershed Organization was used. Results show that this index is a very useful tool during the irrigation planning process (for short- and long-term planning) and allows administrators to make the important decision whether: 1) to maintain water stored in the reservoir system for future use and drought event prevention, or 2). to use the water in the system in the present agricultural year in the most profitable crops.
• Bartolini, P., Carcano, E. C., Piroddi, L., & Valdes, J. B. (2008). Forecasting daily streamflows using NARMAX models: How disturbances may affect model performance. World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008, 316.
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  Abstract: The realization of a random event (e.g. basin outflows, rainfall depths) may be represented by a deterministic link between forcings (input system series) and outputs. In those circumstances when such a non-linear link (e.g. rainfall-runoff models) is not known or when sufficient physical insight of the process is not available, non linear empirical models may be applied with fairly good chances of success. Moreover, even if knowledge of the process causality produces a deterministic relationship between input and output, randomness still remains in the realization of the event, e.g. streamflow events. NARMAX models, initially developed by Leontaritis and Billings (1985) are an example of non-linear models that may be used in this application. Herein the original and simplified version of NARMAX models (NARX) is introduced in a comparative study in the reproduction of daily streamflows data for two small catchments in the Ligurian region (Italy). NARMAX models, in general, yield an input-output representation of a non linear system where the current output a function of lagged inputs, outputs and noise. The influence of disturbances in rainfall-runoff modeling at daily scale using NARMAX models is evaluated in this paper. The corresponding NARX models are used when the focus is on the deterministic input- output relationship with a crude simplification of the disturbance model. © 2008 ASCE.
• Cañón, J., Domínguez, F., & Valdés, J. (2008). Downscaling climate projections: A method to tackle spatial and temporal variability associated with quasi-periodic signals and first two statistical moments. World Environmental and Water Resources Congress 2008: Ahupua'a - Proceedings of the World Environmental and Water Resources Congress 2008, 316.
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  Abstract: In this paper we introduce a statistical downscaling method that incorporates the spatial and temporal variability associated with quasi-periodic climate signals, such as ENSO, by using Multichannel Singular Spectrum Analysis (M-SSA). In addition, the method preserves the expected values and variances of downscaled climate variables. The lump value of a climate variable is dissagregated over a grid of higher spatial resolution by using time series projections calculated on a cell-by-cell basis. To do this, we use a stochastic model consisting of the sum of the mean value, a quasi-periodic component related to climate signals, and a random component associated with the residual variance of historic records. The technique is employed to downscale standardized precipitation values, from historic records and projections of coupled climate models, taking into account the variability associated with ENSO. © 2008 ASCE.
• González, J., & Valdés, J. B. (2008). A regional monthly precipitation simulation model based on an L-moment smoothed statistical regionalization approach. Journal of Hydrology, 348(1-2), 27-39.
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  Abstract: Using rain-gauge station records for the statistical characterization and simulation modeling of spatio-temporal precipitation field involves many issues and simplistic assumptions. One major issue is related to dealing with uncertainty at-site sample statistical inference, because of the limited length of records. Regional frequency analysis uses the idea of substituting space for time in order to reduce uncertainty. It assumes equal shapes of the precipitation statistical distributions in a region. However, this assumption limits the area of the analyzed region where this assumption is valid. The extension is dependent on terrain complexity. This work presents a new approach for the statistical regionalization of a large precipitation field, replacing the shape constancy assumption for the hypothesis of smooth spatial variation. The approach accounts for every uncertainty on site information, using an L-moment method for inference analysis. Additionally, the orographic effect is introduced in the regionalization, which substantially improves the interpolation performance and estimation of areal precipitation. The approach is used for modeling the monthly precipitation field in the Júcar River Basin Authority Demarcation (Spain), incorporating its stochastic structure, and spatial dependency coming from a geostatistical analysis. Issues related to the estimation of regional precipitation, and mean areal precipitation are discussed in the exposition. © 2007 Elsevier B.V. All rights reserved.
• Cañón, J., González, J., & Valdés, J. (2007). Precipitation in the Colorado River Basin and its low frequency associations with PDO and ENSO signals. Journal of Hydrology, 333(2-4), 252-264.
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  Abstract: The spatial and temporal distribution of point precipitation quantiles representing abnormal moisture conditions over the Colorado River Basin (CRB) is analyzed by means of the Standardized Precipitation Index (SPI), calculated in annual and seasonal aggregations. From a cell-by-cell analysis, the area covered by abnormally wet and dry conditions during the last century shows an inverse relationship with their frequency of occurrence, with frequent events (occurring 80% of the time) in which abnormal conditions cover less than 10% of the basin and infrequent events (occurring 5% of the time) in which abnormal conditions cover around 50% of the basin. During El Niño years, both extremely wet and dry conditions are likely to occur, while only extremely dry conditions are probable during La Niña years. Regions of homogeneous SPI realizations were delimited using principal components analysis (PCA) to highlight major variation modes distinguishable in the basin, and a frequency analysis was performed over the reconstructed values of SPI to identify their multiannual oscillation modes. Common multiannual oscillations between the SPI index, the Pacific Decadal Oscillation (PDO) and the Bivariate El Niño-Southern Oscillation (BEST) time series were explored using multichannel singular spectrum analysis (M-SSA). The coupled impact of PDO-ENSO indicates the presence of a trend and two significant oscillations around 5 and 15 years on the SPI time series. The occurrence of extreme SPI values associated with ENSO and PDO was also evaluated as a common product of these indices that highlights moisture conditions affected by common enhancement phases of ENSO and PDO. © 2006 Elsevier B.V. All rights reserved.
• González, J., & Valdés, J. B. (2006). New drought frequency index: Definition and comparative performance analysis. Water Resources Research, 42(11).
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  Abstract: Drought periods appear as extreme events whose characterization encompasses several issues. Many issues are related to the multiple natures that a drought may have: meteorological, hydrological, agricultural, or socioeconomical. There are also issues related to the complexity of the phenomena, which may be characterized by many magnitudes, such as duration, severity, or intensity. None of them alone may be used as a general drought characterization criterion. Others arise from the kind of methodologies that are available for their significance evaluation, which focus on different aspects for specific objectives. However, most have a common aspect: the extreme persistent realization of a random hydroclimatic variable. For the goal of general drought analysis, in this paper a new index for drought characterization is presented: the drought frequency index (DFI). The index focuses on this common aspect of the drought origins, with a purely probabilistic treatment. Because droughts are persistent phenomena, the index is based on the stochastic characterization of extreme persistent deviation sequences using a novel probabilistic criterion. In this way, the DFI is related to the mean frequency of recurrence of extreme persistent events. Therefore the mean frequency of recurrence is adopted as the scale for drought significance evaluation. The index performance is analyzed and compared with respect to the different issues that result from applying other methodologies: magnitude selection, univariate versus multivariate, threshold selection (related to the run theory), and timescale issues (related with the standard precipitation index (SPI) application). Furthermore, to apply runs theory for any magnitude number, an original generalization of drought multivariate recurrence models is presented. Finally, the spatial comparability of the indexes is analyzed. Results reveal the ability of the DFI to reduce the sensitivity to practical issues. The DFI provides a consistent index for spatial comparisons and for application to general drought characterization goals. Copyright 2006 by the American Geophysical Union.
• Kim, G., Valdés, J. B., North, G. R., & Hong, T. K. (2006). Assessment of sampling error associated with soil moisture estimation designs. Journal of the American Water Resources Association, 42(1), 213-224.
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  Abstract: A spectral formalism was developed and applied to quantify the sampling errors due to spatial and/or temporal gaps in soil moisture measurements. A design filter was developed to compute the sampling errors for discrete measurements in space and time. This filter has as its advantage a general form applicable to various types of sampling design. The lack of temporal measurements of the two-dimensional soil moisture field made it difficult to compute the spectra directly from observed records. Therefore, the wave number frequency spectra of soil moisture data derived from stochastic models of rainfall and soil moisture were used. Parameters for both models were estimated using data from the Southern Great Plains Hydrology Experiment (SGP97) and the Oklahoma Mesonet. The estimated sampling error of the spatial average soil moisture measurement by airborne L-band microwave remote sensing during the SGP97 hydrology experiment is estimated to be 2.4 percent. Under the same climate conditions and soil properties as the SGP97 experiment, equally spaced ground probe networks at intervals of 25 and 50 km are expected to have about 16 percent and 27 percent sampling error, respectively. Satellite designs with temporal gaps of two and three days are expected to have about 6 percent and 9 percent sampling errors, respectively. JAWRA Copyright © 2006.
• Kim, T., Valdés, J. B., & Aparicio, J. (2006). Spatial characterization of droughts in the Conchos River Basin based on bivariate frequency analysis. Water International, 31(1), 50-58.
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  Abstract: The spatial characterization of droughts in the Conchos River Basin, which includes the regional drought recurrence and areal coverage, was performed to provide information for integrated water resources management in the basin. The application presented in this study was based on the semi-nonparametric model and the nonparametric bivariate frequency analysis developed for characterizing droughts in a basin. The drought characterization curves constructed in this study describe the spatial and recurrent pattern of droughts in the basin with respect to drought severities and return periods. Based on the synthetic Palmer Drought Severity Index, historical droughts were evaluated. The results show that the 1990s drought has affected large areas with longer durations and greater severities than the 1960s drought. © 2006 International Water Resources Association.
• Kim, T., Valdés, J. B., & Yoo, C. (2006). Nonparametric approach for bivariate drought characterization using palmer drought index. Journal of Hydrologic Engineering, 11(2), 134-143.
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  Abstract: A drought is usually represented by duration and severity, and may last several months or years. Multidimensional characteristics of a drought make univariate analysis unable to reveal the significant relationship among drought properties. Furthermore, historical records tend to be too short to fully evaluate drought characteristics. A practical method was proposed in this study to estimate the bivariate return period of droughts based on the use of synthetic data to overcome the above considerations. The bivariate return period of droughts is dependent on the drought interarrival time and the joint distribution of drought properties. A nonparametric method was employed in this study to estimate the joint distribution of drought properties. The historical droughts in the Conchos River Basin, Mexico were evaluated based on their return period estimated by the proposed method. The proposed method allowed a better understanding of the joint probabilistic behavior of droughts beyond the limitation of the univariate/parametric frequency analysis. © 2006 ASCE.
• Kim, T., Valdés, J. B., Nijssen, B., & Roncayolo, D. (2006). Quantification of linkages between large-scale climatic patterns and precipitation in the Colorado River Basin. Journal of Hydrology, 321(1-4), 173-186.
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  Abstract: This study analyzed the linkages between large-scale climate patterns and regional precipitation variability, in particular the interannual variation of seasonal precipitation in the Colorado River Basin. Two climate indices, the Southern Oscillation Index (SOI) and the Pacific Decadal Oscillation (PDO), were selected to represent climate patterns. Conceptual influence indices, which quantify the strength of linkages between climate patterns and precipitation variability, were developed based on the Standardized Precipitation Index (SPI). In turn, the spatial variability of the influence indices within the Colorado River Basin was examined for different combinations of SOI and PDO phases and lead times from zero to three seasons. Precipitation in two seasons (winter and summer) significantly responded to the El Niño-Southern Oscillation (ENSO) phases by decreasing winter precipitation in the lower basin (to high ENSO phase) and by increasing summer precipitation in the upper basin (to low ENSO phase). The PDO phase enhanced those relationships both in intensity and frequency. The overall results of this study revealed that the precipitation of the Colorado River Basin was significantly influenced by climate fluctuation phases. © 2005 Elsevier B.V. All rights reserved.
• Valdés, J., González, J., Cañón-Barriga, J., & Woodard, G. (2006). Water resources management under drought conditions. WIT Transactions on Ecology and the Environment, 99, 445-453.
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  Abstract: The semi-arid/arid US Southwest and Northwestern Mexico are experiencing severe droughts while at the same time having significant increases in their water demands. This paper evaluates the demand and the efforts to manage water resources under drought conditions. Innovative water resources management techniques need to be implemented to address this scarcity which is aggravated under drought conditions. This paper also presents an application of a new drought index (Gonzalez and Valdes, 2006ab) in characterizing the spatial and temporal variability of droughts and its use in water resources management, particularly multi-reservoirs.
• González, J., Valdés, J. B., & Mata, L. J. (2005). Resilience and vulnerability of water resources management in the conchos river basin to climate change. World Water Congress 2005: Impacts of Global Climate Change - Proceedings of the 2005 World Water and Environmental Resources Congress, 506-.
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  Abstract: Abstract only available. The Conchos River Basin is one of the most important river systems in northern Mexico, and the most important tributary of the Lower Río Bravo/Rio Grande. The Conchos contributes approximately 2/3 of the total inflows to the Lower Rio Bravo/Rio Grande. As such, the flows are subject to the 1944 International Treaty between the United States and Mexico. Irrigation is the largest consumptive use in the basin, followed by industrial and municipal use. In addition there are flows required to satisfy the treaty. The region had a significant population growth in the last two decades, which combined with a severe drought in the 1990s, significantly impacted management of the water resources in the basin. The flows are regulated by a system of multiple reservoirs, one of them as large as Elephant Butte. In this work, an optimal water resources policy management is developed for a complex multi-reservoir system in a semi-arid region like the Conchos. The policy is adjusted for current climate conditions. To analyze its resiliency, this policy is simulated under predicted climate change scenarios. Using the MAGICC software package, variations in mean precipitation and temperature are estimated for several GCMs models, with different greenhouse emission scenarios, and for the following time horizons: 2025, 2050 and 2100. For each time horizon, the probability of variation in precipitation and temperature are estimated. The study evaluates the resilience of the current optimal policy to predicted climate changes. It also analyzes the adaptability of the policies as a function of the rate of climate change, allowing the quantification of the vulnerability of the system. Copyright ASCE 2005.
• Kim, T., & Valdés, J. B. (2005). Synthetic generation of hydrologic time series based on nonparametric random generation. Journal of Hydrologic Engineering, 10(5), 395-404.
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  Abstract: Synthetic hydrologic time series can be used to quantify the uncertainty of a water resources system. Conventional parametric models, such as autoregressive moving average or Markovian models, assume that the variable under consideration is Gaussian. This assumption, however, is a shortcoming of parametric models and motivates the development of nonparametric approaches. Nonparametric models based on a kernel function have an innate low-order structure and are restricted to highly persistent variables. This study presented a seminonparametric (SNP) model that takes advantage of both parametric and nonparametric models to generate monthly precipitation and temperature in the Conchos River Basin in Mexico. By adopting a consistent and robust scheme from the Markovian model and a nonparametric mechanism to generate a distribution-free random component, the SNP model reliably reproduced sample properties such as mean, variance, correlation, and multimodality in the probability density function. Journal of Hydrologic Engineering © ASCE.
• Seoane, R. S., Valdés, J. B., & Mata, L. J. (2005). Climate variability and climate change in Patagonian rivers. IAHS-AISH Publication, 26-34.
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  Abstract: Climate variability and change in precipitation and streamflows of several Patagonian basins are analysed using both parametric and non-parametric tests and simulation models. Additional hydroclimatic (e.g. soil moisture, evapotranspiration, etc.) time series, obtained using a parametric monthly water balance model, were also analysed. The climate change characteristics are defined using results from several GCMs using a climate scenario generator (MAGICC/ SCENGEN software). All GCM model results for the region show increases in temperature but are more variable in their estimates of precipitation. Synthetic traces of hydroclimatic variables, based on the GCM results, were then generated as inputs to the rainfall-runoff model. A non-parametric technique was used to evaluate the feasibility of early detection of climate change impact in the traces. The impact of climatic precursors such as ENSO (El Niño/ Southern Oscillation) in the hydroclimatology of the Patagonian basins is also analysed in this work.
• Yoo, C., Kim, S., & Valdes, J. B. (2005). Sensitivity of soil moisture field evolution to rainfall forcing. Hydrological Processes, 19(9), 1855-1869.
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  Abstract: In this paper the temporal behaviour of soil moisture is modelled and statistically characterized by use of the zero-dimensional model for soil moisture dynamics and the rectangular pulses Poisson process model for rain all forcing. The mean, covariance and spectral density function of soil moisture (both instantaneous and locally averaged cases) are analytically derived to evaluate its sensitivity to the model parameters. Finally, the probability density function of soil moisture is derived to evaluate the effect of rainfall forcing. All the model parameters used have been tuned to the Monsoon '90 data. Results can be summarized as follows. (1) Only the soil moisture model parameters (η and nZr) are found to affect the autocorrelation function in a distinguishable manner. On the other hand, both the rainfall model parameter (φ) and the effective soil depth (nZr) are found to be of impact to the soil moisture spectrum. However, as the smoothing (or damping) effect of soil is so dominant, about ±20% variation of one parameter seems not to affect significantly the second-order statistics of soil moisture. (2) More difference can be found by applying a longer averaging time, which is found to obviously decrease the variance but increase the correlation even though no overlapping between neighbouring soil moisture data was allowed. (3) Among rainfall model parameters, the arrival rate λ was found to be most important for the soil moisture evolution. When increasing the arrival rate of rainfall, the histogram of soil moisture shifts its peak to a certain value as well as becomes more concentrated around the peak. However, by decreasing the arrival rate of rainfall, a much smaller (almost to zero) mean value of soil moisture was estimated, even though the total volume of rainfall remained constant. This indicates that desertification may take place without decreasing the total volume of rainfall. Copyright © 2005 John Wiley & Sons, Ltd.
• Bartolini, P., Calcagno, M., & Valdés, J. B. (2004). Regionalization of a model for design storms. Joint Conference on Water Resource Engineering and Water Resources Planning and Management 2000: Building Partnerships, 104.
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  Abstract: A stochastic precipitation model, which is able to capture the main characteristics of heavy rainfalls in Liguria (northern Italy), has been examined to investigate the possibility to regionalize its parameters. The alternative between explicitly or implicitly taking into account the physical characteristics of a site (elevation, distance from the sea, exposition) directly or by means of the geographical coordinates has been considered. In this first approach, the comparison was restricted to the influence of elevation on the parameters of the model. It has been observed that better results have been obtained when the elevation is explicitly taken into account, even if the number of parameters of the interpolating function is lower. This seems to point out the other physical characteristics may also be regionalized explicitly, but with a greater difficulty to find an appropriate value. Copyright ASCE 2004.
• González, J., & Valdés, J. (2004). The mean frequency of recurrence of in-time-multidimensional events for drought analyses. Natural Hazards and Earth System Science, 4(1), 17-28.
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  Abstract: Droughts are related with prolonged periods when moisture is significantly below normal values. Drought indices attempt to scale the main drought features to facilitate comparisons. Numerous indices are found in the literature based on different drought features. Many of them were created for particular places and specific objectives, and therefore not suitable to generalize the results. However, there have been attempts to develop a general index, which would provide full characterization of drought events. Two of the most well known are the Palmer Drought Severity Index (PDSI) and the Standard Precipitation Index (SPI). Each one has particular advantages and disadvantages. Still neither of them or any other includes a full representation of droughts in a single value index, being useful for all general application. The fact that droughts have a random nature prescribes the statistical theory for the foundation of a complete and generic index, which would meet this goal. In this work, a procedure that allows a complete statistical characterization of drought events is presented. Droughts are characterized, from a statistical point of view, based both on the deviation from a normal regime and persistence. The events are represented as multivariate ones, whose dimensionality depends on the duration. Equal duration events are discriminated through their deviations from normality. The mean frequency of recurrence (MFR) is theoretically derived for such multivariate events, and it is used to scale such deviations. Therefore, events with different dimensionalities can be compared on a common dimension of interest, the MFR. This may be used as a drought index for drought characterization, both for analyzing historical events and monitoring current conditions. It may also be applied to analyze precipitation, streamflows and other hydroclimatic records. Its statistical nature and its general conception support its universality. Results may be applied not only to drought analysis, but also to analyze other random natural hazards. Applications of the procedure for drought analysis in Texas (USA) and in Gibraltar (Iberian Peninsula) are made and compared with PDSI and SPI results. The MFR applied over drought analysis allows the representation of the main drought characteristics in a single value, based on the statistical feature of the phenomenon, and scaled on the mean frequency of recurrence. © European Geosciences Union 2004.
• Velasco, I., Aparicio, J., Valdés, J. B., Velázquez, J., & Kim, T. (2004). Drought index assessment in the watersheds of affluents from the Río Bravo/Río Grande River. Ingenieria Hidraulica en Mexico, 19(3), 37-53.
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  Abstract: There are several methods and indices to characterize drought, but none of them is superior to the others in all circumstances. The most frequently used indices in North America are the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI). Each one has characteristics which can be advantageously used to characterize drought and trigger actions established in Drought Mitigation Plans. The 1944 Mexico-US Treaty on conjunctive management of the Colorado, Tijuana and Bravo/Grande Rivers, for example, foresees ways to modify the mutual water allocations between the two countries in case of extreme drought. However, it does not define precisely such concept. Therefore, it is important to examine in detail the applicability and characteristics of both methods to characterize droughts. This paper shows the application of the SPI, which is based only on precipitation data and reflects the temporary rain efficiency, considered as the hydrological component that determines, to a great extent, the occurrence and characteristics of a drought. The PDSI method is also studied. This index is based on soil moisture balance for the soil layer where crops grow, and, therefore, not only precipitation and temperature have influence in water availability, but also soil characteristics are decisive. Both indices are applied to the Conchos and Pecos watersheds, in order to evaluate their behavior. When time scales are appropriate for both methods, the results obtained are similar, and they show that droughts have been persistent and recurrent over the region during the last few years. Besides, a sensitivity analysis of PDSI to some parameters is presented.
• González, J., & Valdés, J. B. (2003). Bivariate drought recurrence analysis using tree ring reconstructions. Journal of Hydrologic Engineering, 8(5), 247-258.
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  Abstract: Droughts may be represented by two main characteristics-duration and severity. In this paper, a general methodology to evaluate the frequency and risk of the occurrence of droughts is presented using a bivariate drought characterization. The theory of runs is applied to model drought recurrence as an alternating renewal process, describing droughts simultaneously in terms of their durations and severities. Short historical records usually do not allow reliable bivariate analyses. However, tree ring reconstructions of droughts provide information about past events, allowing the analysis. An approach to adapt and include dendrochronology reconstructions combined with historical records to characterize droughts is presented. The proposed approach uses the stochastic structure of the residuals of paleo reconstructions to generate equally likely representations of past drought events. The procedure was applied to paleo and historical records in Texas Climatic Division 5 and compared with univariate analyses. The application shows the bivariate analysis advantages in drought characterization.
• Kim, T., & Vald́es, J. B. (2003). Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. Journal of Hydrologic Engineering, 8(6), 319-328.
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  Abstract: Droughts are destructive climatic extreme events that may cause significant damage both in natural environments and in human lives. Drought forecasting plays an important role in the control and management of water resources systems. In this study, a conjunction model is presented to forecast droughts. The proposed conjunction model is based on dyadic wavelet transforms and neural networks. Neural networks have shown great ability in modeling and forecasting nonlinear and nonstationary time series in a water resources engineering, and wavelet transforms provide useful decompositions of an original time series. The wavelet-transformed data aid in improving the model performance by capturing helpful information on various resolution levels. Neural networks are used to forecast decomposed subsignals in various resolution levels and reconstruct forecasted subsignals. The model was applied to forecast droughts in the Conchos River Basin in Mexico, which is the most important tributary of the Lower Rio Grande/Bravo. The performance of the conjunction model was measured using various forecast skill criteria. The results indicate that the conjunction model significantly improves the ability of neural networks to forecast the indexed regional drought.
• Kim, T., Valdés, J. B., & Yoo, C. (2003). Nonparametric approach for estimating return periods of droughts in arid regions. Journal of Hydrologic Engineering, 8(5), 237-246.
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  Abstract: Droughts cause severe damage in terms of both natural environments and human lives, and hydrologists and water resources managers are concerned with estimating the relative frequencies of these events. Univariate parametric methods for frequency analysis may not reveal significant relationships among drought characteristics. Alternatively, nonparametric methods provide local estimates of the univariate and multivariate density function by using weighted moving averages of the data in a small neighborhood around the point of estimation and opposed to parametric methods. A methodology for estimating the return period of droughts using a nonparametric kernel estimator is presented in order to examine the univariate as well as the bivariate behavior of droughts. After evaluating and validating a nonparametric kernel estimator, a drought frequency analysis is conducted to estimate the return periods of droughts for the Conchos River Basin in Mexico. The results show that, for the univariate analysis, the return periods of the severe drought occurring in the 1990s are 100 years or higher. For the bivariate analysis, the return periods are approximately 50 years for joint distributions and more than 120 years for the conditional distributions of severity and duration.
• Kim, T., Valdés, J. B., & Aparicio, J. (2002). Frequency and spatial characteristics of droughts in the Conchos River Basin, Mexico. Water International, 27(3), 420-430.
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  Abstract: The temporal and spatial characteristics of droughts are investigated to provide a framework for sustainable water resources management in a semi-arid region. Using the Palmer Drought Severity Index (PDSI) as an indicator of drought severity, the characteristics of droughts are examined in the Conchos River Basin in Mexico. This basin is important to both the United States and Mexico, because the Conchos River supplies approximately 80 percent of the flows of the Lower Bravo/Grande River above the binational reservoirs of Amistad and Falcon. The temporal and spatial characteristics of the PDSI are used to develop a drought intensity - areal extent - frequency curve that can assess the severity of a regional drought in the basin. The analysis of the PDSI suggests that the Conchos River Basin had a severe drought in the 1990s, which the basin has not experienced before. Based on this analysis, the recent drought that occurred in the 1990s has an associated return period of about 80 to 100 years over the basin.
• Loáiciga, H., Maidment, D. R., & Valdes, J. B. (2000). Climate-change impacts in a regional karst aquifer, Texas, USA. Journal of Hydrology, 227(1-4), 173-194.
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  Abstract: Climate-change scenarios were created from scaling factors derived from several general circulation models to assess the likely impacts of aquifer pumping on the water resources of the Edwards Balcones Fault Zone (BFZ) aquifer, Texas, one of the largest aquifer systems in the United States. Historical climatic time series in periods of extreme water shortage (1947-1959), near-average recharge (1978-1989), and above-average recharge (1975-1990) were scaled to 2 x CO2 conditions to create aquifer recharge scenarios in a warmer climate. Several pumping Scenarios were combined with 2 x CO2 climate scenarios to assess the sensitivity of water resources impacts to human-induced stresses on the Edwards BFZ aquifer. The 2 X CO2 climate-change scenarios were linked to surface hydrology and used to drive aquifer dynamics with alternative numerical simulation models calibrated to the Edwards BFZ aquifer. Aquifer simulations indicate that, given the predicted growth and water demand in the Edwards BFZ aquifer region, the aquifer's ground water resources appear threatened under 2 x CO2 climate scenarios. Our simulations indicate that 2 X CO2 climatic conditions could exacerbate negative impacts and water shortages in the Edwards BFZ aquifer even if pumping does not increase above its present average level. The historical evidence and the results of this article indicate that without proper consideration to variations in aquifer recharge and sound pumping strategies, the water resources of the Edwards BFZ aquifer could be severely impacted under a warmer climate. (C) 2000 Elsevier Science B.V.
• Bartolini, P., Montereggio, F., & Valdes, J. B. (1998). Problems in calibrating conceptual rainfall runoff models. Proceedings of the Annual Water Resources Planning and Management Conference, 171-175.
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  Abstract: Rainfall-Runoff Models (RRM) allow the use of most of the fast procedures (like the Rational Method) aimed at transferring the probability laws from the rainfalls to the discharges. In fact, the time of concentration of a basin (in order to select a proper rainfall from the IDF curves) as well as the infiltration rate, highly affect the estimation of the T-years discharge; it follows the necessity of calibrating an RRM, for deriving the characteristics of the basin under observation, by using the ones obtained for a similar, gaged, basin. A complete model of the rainfall-runoff transformation (i.e. a model which takes into account the underground portion of the hydrograph, even if the maximum discharge during a flood is mainly due to the surface runoff) is needed. Also it is required to handle the almost unavoidable asynchronism between rainfall and discharge records during the calibration of a model. After a particular RRM is chosen, the proposed solution (i.e., the introduction of an extra unknown, the time-lag between rainfall and discharges, and the contemporaneous fitting of a set of different events) is tested with respect to two small mountain basin in northern Italy.
• Batchelor, B., Valdés, J., & Araganth, V. (1998). Stochastic risk assessment of sites contaminated by hazardous wastes. Journal of Environmental Engineering, 124(4), 380-388.
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  Abstract: Stochastic risk assessment models offer the potential for being more objective by explicitly considering variability. Such a model has been developed for a site contaminated with polychlorinated biphenyls (PCBs) by representing the parameters used in the risk assessment as probability distribution functions (pdf) rather than single values. The pdf for total risk calculated by the model is approximately lognormal, although the pdf of parameters in the model take on a variety of forms. A first-order approximation to the model provides good estimates for the high end of the distribution, which is of concern when conservative risk assessments are desirable. The first-order approximation provides good estimates even when the level of variation of the parameters is increased well above levels that are normally expected. A procedure was developed to apply the stochastic risk assessment model in a series of calculations to determine preliminary remediation goals for the site. In addition, a simplified technique was developed to calculate preliminary remediation goals using only results from simulating risk with initial site conditions. ©ASCE.
• Liu, Z., Valdés, J. B., & Entekhabi, D. (1998). Merging and error analysis of regional hydrometeorologic anomaly forecasts conditioned on climate precursors. Water Resources Research, 34(8), 1959-1969.
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  Abstract: Forecasts of hydroclimatic variables and incorporation of their error bounds are invaluable in water resources planning and operations under uncertainty. In this study, regional long-term operational hydrologic forecast models conditioned on climatic precursor are presented. The forecasts also include uncertainty intervals and confidence limits. The forecasts are based on the temporal and spatial variability of hydrometeorologic anomalies and their relationships with climatic interannual and intraseasonal El Nino-Southern Oscillation (ENSO). The forecast skills of the proposed model, which incorporates ENSO forecasts on tropical rainfall and streamflow, are compared with those that are unconditional and do not incorporate ENSO. Significantly improved skills are achieved by incorporating forecasted ENSO indices and their errors. The seasonal variability of the forecast model skills are also evaluated. These ENSO-based forecasts of regional and seasonal-to-interannual hydrometeorologic variables consistently merged with systematic error analysis can provide outputs for direct use in water resources planning and operation under uncertainty.
• Marco, J. B., & Valdés, J. B. (1998). Partial area coverage distribution for flood frequency analysis in arid regions. Water Resources Research, 34(9), 2309-2317.
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  Abstract: Convective rainfalls of high intensity are largely responsible for most large floods occurring in arid regions. Convective storms are limited in size and rarely cover an entire basin. Therefore flood frequency is affected by the distribution of storm coverage c, which is the fraction of basin area upon which rainfall occurs. Analytical probability density function (pdf) estimates of partial storm coverage are presented as a function of basin area S(c) and the probability distribution function for storm radius r(s). Conditional pdfs for the covered area fraction c, given the storm radius f(c/r(s)), are obtained as a compound distribution with finite probability for maximum coverage and continuous density for smaller values. The conditionality assumption is removed by assuming an exponential storm radius marginal distribution to obtain the catchment coverage pdf. This pdf is compound, with discrete probability for complete catchment coverage P(c = 1) and a continuous function for partial overlap. The continuous function combines a Weibull pdf and linear functions of c. Both P(c = 1) and f(c) depend on χ, the average catchment-to-storm radius ratio. The distribution explains the partial coverage data for the Walnut Gulch basin in Arizona. Departures were observed, however, for slightly less than complete coverage, namely, for 0.9 < c < 1. A conceptual event classification and a method were designed to include partial coverage effects on flood frequency distribution.
• Yoo, C., Valdés, J. B., & North, G. R. (1998). Evaluation of the impact of rainfall on soil moisture variability. Advances in Water Resources, 21(5), 375-384.
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  Abstract: The impact of rainfall on the spatial-temporal soil moisture variability is investigated by using a model of the soil moisture dynamics and two rainfall models, the noise-forced diffusive precipitation model and the WGR model. The study shows that the variability of the soil moisture field is impacted during the limited time of the storm period. During the interstorm period, the variability of the soil moisture field is closely related with the soil texture, as supported by the analysis of the Washita '92 data set. As the impact of rainfall on the variability of the soil moisture field is limited to the short time period of precipitation, the role of the rainfall is simplified as a source of water to the soil moisture field without any consideration of its variability and/or organization in space. A simulation study of the soil moisture field temporal evolution also supports this result, i.e. a strong relationship between the soil moisture field and the variability of its medium. Also, larger variabilities of the loss field coefficient result in easier removal of moisture from the soil. © 1998 Elsevier Science Limited. All rights reserved.
• Bartolini, P., & Valdes, J. B. (1997). Alternative method to evaluate design storms. Proceedings of the Annual Water Resources Planning and Management Conference, 82-87.
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  Abstract: An alternative approach to the definition of a project Design Storm that does not require prior definition of the IDF curves for the site under study is presented. The procedure is based on a two-peak hyetograph that allows a better fit to observed maximum annual events. The approach requires estimation of six to eight parameters, which are based on the historic records of maximum annual events for a given duration. The study concentrated on convective events with a duration up to three hours which have produced the largest peaks in the Ligurian region. Preliminary results show that some of the parameters remain constant for the region, thereby facilitating the estimation or regionalization of the others. The impact of alternative definitions of the design storm on the design hydrographs is evaluated.
• Loaiciga, H. A., Valdes, J. B., Vogel, R., Garvey, J., & Schwarz, H. (1996). Global warming and the hydrologic cycle. Journal of Hydrology, 174(1-2), [d]83-127.
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  Abstract: This paper examines the current predictive capability of general circulation models linked with macroscale and landscape-scale hydrologic models that simulate regional and local hydrologic regimes under global warming scenarios. Issues concerning hydrologic model calibration and validation in the context of climate change are addressed. Greenhouse-warming scenarios in midlatitudinal basins of the United States, predict shorter winter seasons, larger winter floods, drier and more frequent summer weather, and overall enhanced and protracted hydrologic variability. All these predictions point to potentially worsening conditions for flood control, water storage, and water supply in areas of semiarid midlatitudinal climates currently dependent of spring snowmelt. Practice of sound water resources engineering principles ought to be adequate to cope with additional hydrologic uncertainty that might arise from global warming. -from Authors
• Sastri, T., Valdés, J., & Flores, B. (1996). Nonlinear control charts for jump detection. International Journal of Production Research, 34(4), 1023-1044.
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  Abstract: This paper presents a new class of nonlinear control charts which respond quickly to small shifts and jump patterns in tme series. The underlying disturbance models for the control charts are nonlinear extensions of the IMA(1,1) model. The Kalman filtering algorithm generates Bayesian estimates of the process level for the control chart plotting. The single-parameter chart is identical to the EWMA, while the two- and three-parameter designs are much more effective in detecting small shifts mixed with local trends. The nonlinear control charting scheme is also capable of detecting a mean shift in independent observation.
• Soman, V. V., Valdés, J. B., & North, G. R. (1996). Estimation of sampling errors and scale parameters using two- and three-dimensional rainfall data analyses. Journal of Geophysical Research D: Atmospheres, 101(21), 26453-26460.
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  Abstract: This paper presents the analysis of rainfall data based on radar echoes collected in the vicinity of Darwin, Australia, during special observation periods in 1988. The study was conducted to estimate the scale parameters (such as timescale and length scale) present in the rainfall data, which are important in parameterizing many stochastic rainfall models. Another equally important issue addressed here is that of sampling errors in the rainfall observations from space. To address these issues, precipitation analyses were conducted in two and three dimensions. To perform two-dimensional analyses, precipitation fields were averaged along one dimension (i.e., x, y, or t) at a time. Three-dimensional analyses were performed on the complete time series of temporal-hourly averaged spatially distributed observations. Important results obtained from the two-dimensional analyses include isotropy of precipitation fields in space, variations in the rainfall data primarily in time, and length scales of 50 km (for Darwin I) and 52 km (for Darwin II) in both (i.e., north-south and west-east) directions. Length scales were estimated using the results from two-dimensional analyses of the data. Time-domain correlograms obtained for the time series of area-averaged precipitation were used to estimate the timescales (6 hours for Darwin I and 8 hours for Darwin II). These results could be used in simulation studies using various stochastic rainfall models. The estimates of space-time spectra obtained in three-dimensional analyses were used to evaluate the sampling errors. The sampling errors thus estimated using these data sets were quite significant (about 25% to 30% for a 12-hour sampling interval). Sampling errors were as high as 65% for Darwin I and 45% for Darwin II for a 24-hour sampling time interval, which is a possibility if the Defense Meteorology Satellite Program (DMSP) satellite is used. These results are useful in satellite mission planning activities.
• Yoo, C., Valdés, J. B., & North, G. R. (1996). Stochastic modeling of multidimensional precipitation fields considering spectral structure. Water Resources Research, 32(7), 2175-2187.
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  Abstract: A multidimensional stochastic precipitation model with major emphasis on its spectral structure is proposed. As a hyperbolic type of stochastic partial differential equation, this model is characterized by a small set of easily estimable parameters. These characteristics are similar to those of the noise-forced diffusive precipitation model, but the representation of the physical and statistical features of the precipitation field is similar to that of the Waymire-Gupta-Rodriguez-Iturbe (WGR) precipitation model. The derivation was based on the autoregressive process considering advection and diffusion, the dominant statistical and physical characteristics of the precipitation field propagation. The model spectrum showed a good match with the Global Atlantic Tropical Experiment spectrum. This model was also compared with the WGR model and the noise-forced diffusive precipitation model both analytically and through applications such as the sampling error estimation from spaceborne sensors and rain gauges. The sampling error from spaceborne sensors based on the proposed model was similar to that of the noise-forced diffusive precipitation model, but much smaller than that of the WGR model. Similar results were also obtained in the estimation of the sampling error from rain gauges.
• Bartolini, P., & Valdes, J. B. (1995). Issues in the estimation of IDF curves. Array, 794-798.
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  Abstract: A common procedure to estimate intensity duration frequency (IDF) curves is to fit the different sets of historical depths, for different durations, with the same function of duration and return period, thereby giving rise to depth-duration-frequency (DDF) curves. The shortcoming of this simple procedure is addressed. An alternative approach to the problem is proposed.
• Grayman, W. M., Valdes, J. B., & Harley, B. M. (1995). Modeling the Rio Colorado in 1970: how modeling has changed in the past 25 years. Array, 1053-1056.
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  Abstract: A suite of five interacting simulation and optimization models were developed and applied as part of a study of the development of the Rio Colorado in Argentina in 1970-1972. The characteristics of these models and their interaction are presented. Changes that have occurred in the past 25 years in modeling are discussed.
• Soman, V. V., Valdes, J. B., & North, G. R. (1995). Satellite sampling and the diurnal cycle statistics of Darwin rainfall data. Journal of Applied Meteorology, 34(11), 2481-2490.
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  Abstract: This paper presents an analysis of rainfall data based on the radar echoes collected in the vicinity of Darwin, Australia, during the special observation periods in 1988, available for approximately 19 days in the first subset and for 22 days in the second. Since the rainfall data were taken over both the land and the ocean, separate analyses were performed for land and ocean surfaces; thus, three univariate time series (for land, ocean, and combination) are presented for each set. Time series analysis was performed in both time and frequency domains, and both the correlogram and periodogram showed the presence of a strong diurnal cycle in all the time series. To analyze the effect of the diurnal cycle on the sampling errors, flush visits of idealized satellites were simulated. The root-mean-square errors were especially large for satellites with sampling intervals of 6 and 12 h. -from Authors
• Awwad, H. M., Valdes, J. B., & Restrepo, P. J. (1994). Streamflow forecasting for Han River Basin, Korea. Journal of Water Resources Planning & Management - ASCE, 120(5), 651-673.
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  Abstract: A linear stochastic model based on the ARMAX class of models is developed for each of 17 forecasting locations and the Kalman filter is used to forecast and update optimal estimates of the flows. Two other filters are used to update the model parameters and noise statistics in real-time. The structure of the models, in flexible black-box forms, provide for several exogenous inputs, including precipitation, antecedent soil moisture effect, natural inflows from upstream subcatchments, and controlled releases from reservoirs. This work extends the real-time forecasting models introduced by Awwad and Valdes in 1992 to include meteorological terms essential to carrying out multiple-step-ahead hydrologic forecasting. It introduces the rainfall-runoff process as part of an adaptive stochastic model, with the catchment's repsonse coefficients updated on-line as information becomes available. -from Authors
• Bartolini, P., & Valdes, J. B. (1994). Evaluation of the return period of the September 1992 flood in Genova, Italy. Proceedings of the 21st Annual Conference on Water Policy and, 102-106.
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  Abstract: The September 1992 flood in Genova caused great damage and loss of life. The flood peak, at the outlet of a 12.5 km2 basin, was estimated at 200 m3/s. Detailed rainfall measurements in a nearby raingage station during the flood were used in a rainfall- runoff model (RRM), which was adapted to reproduce the estimated maximum discharge. It was necessary to consider various sets of parameters, with the common ability to reproduce the observed maximum discharge. Thirteen sets were selected and assumed to have the same likelihood of being the true parameter set. In order to find the return period of the event under consideration, an equivalent population of rainfall was examined, namely, the family of constant-intensity rainfalls which, for different durations, had the same distribution for the annual maxima as the known distribution of the historical rains. First, equivalent rains for different durations were evaluated such as to reproduce the observed peak discharge, for each of the 13 parameter sets. The return period was then estimated by using the Monte Carlo method, i.e., generating sequences of annual maxima for the equivalent rainfalls for different durations and enumerating the cases in which at least one of them was, each year, greater or equal to those previously calculated. The comparison between the statistics of the generated sequences of rainfall maxima and those of the historical records necessitated modification of the generation procedure. This was done by introducing a distortion in the conditional distributions, which yielded a closer fit to the historical statistics.
• Bartolini, P., & Valdes, J. B. (1994). Parameter regionalization of a daily baseflow runoff model. Proceedings of the 21st Annual Conference on Water Policy and, 97-101.
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  Abstract: Daily baseflow values are required to characterize the environmental measurements being carried out in several basins in the Province of Genova, northern Italy. The main purpose of these measurements is the characterization of the environmental quality of the streams by means of the Extended Biological Index (EBI). The discharge values for the month preceding the EBI measurement are useful in distinguishing the different causes of index variation, which may be due to stage variations in a given period before measurement. Frequently, when the EBI was measured, the daily discharges were not known. The data at our disposal was limited to nearly 120 discharge measurements. Places and times of discharge measurement were different from those of EBI measurements. Information on the marginal distribution of daily flows, assumed to be a two-parameter log normal, was available for 16 other stations in the region, as well as for daily rainfalls at 20 stations. The research reported herein compares three different criteria used to obtain an estimate of the unknown daily flows and the mean discharge in the month preceding the EBI measurements.
• Bartolini, P., & Valdes, J. B. (1994). Representation of spatial variability of rainfall in aggregated rainfall-runoff models. Journal of Hydraulic Engineering, 120(10), 1199-1219.
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  Abstract: The aggregated-precipitation input to a catchment was defined as one that minimizes an objective measure of the difference between the calculated and the observed hydrograph. This measure is different from the evaluated mean areal precipitation using, for example, Thiessen polygons. Once the aggregated inputs are derived for a set of storm events over a given basin, the relationships between the mean areal precipitation, the precipitation at a point inside the basin, and the derived aggregated input may be analyzed to detect linkages among them. This study may help in the evaluation of the aggregated input for ungaged storm events.
• North, G. R., Valdes, J. B., Eunho, H. a., & Shen, S. S. (1994). The ground-truth problem for satellite estimates of rain rate. Journal of Atmospheric & Oceanic Technology, 11(4 part 1), 1035-1041.
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  Abstract: A scheme is proposed to use a point raingage to compare contemporaneous measurements of rain rate from a single-field-of-view estimate based on a satellite remote sensor such as a microwave radiometer. A space-time spectral formalism is combined with a simple stochastic rain field to find the mean-square deviations between the two systems. It is found that by combining about 60 visits of the satellite to the ground-truth site, the expected error can be reduced to about 10% of the standard deviation of the fluctuations of the systems alone. This seems to be a useful level of tolerance in terms of isolating and evaluating typical biases that might be contaminating retrieval algorithms. -from Authors
• Valdes, J. B., Entekhabi, D., & Bartolini, P. (1994). Long term predictability of river stages under ENSO influence. Proceedings - National Conference on Hydraulic Engineering, 366-370.
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  Abstract: The paper explores the bases for alternative approaches to river flow and hydrologic time series forecasting. The precipitation that forces river flow contains significant modes of variability beyond simple noise randomness and these structured statistical properties may be used advantageously in forecasting river flow. Despite the high degree of spatial and temporal intermittency observed in precipitation records, there are often deterministic signals embedded in the time series. These deterministic components of the random variable are related to the physical processes that constitute precipitation formation.
• Valdes, J. B., Eunho, H. a., Yoo, C., & North, G. R. (1994). Stochastic characterization of space-time precipitation: implications for remote sensing. Advances in Water Resources, 17(1-2), 47-59.
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  Abstract: A scheme is used to compare contemporaneous measurements of rain rate from a single-field-of-view estimate, based on a satellite remote sensor such as a microwave radiometer, with those coming from a point raingauge. Using this scheme the errors are computed for several observed rainfall fields, either from the data estimated spectra or from analytically derived and characterized ground measurements. This quantification provides a lower bound to total errors, since perfect instruments are assumed in this work, and it helps in terms of isolating and evaluating typical biases that might be contaminating retrieval algorithms. -Authors
• Valdes, J. B., Seoane, R. S., & North, G. R. (1994). A methodology for the evaluation of global warming impact on soil moisture and runoff. Journal of Hydrology, 161(1-4), 389-413.
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  Abstract: Presents a numerical evaluation of the variability of soil moisture and direct surface runoff due to global warming. An analytical model of the soil moisture balance based on our previous work is used to evaluate the probability distribution of the soil moisture concentration and resulting surface runoff. Our results show that not only the mean of the distribution of both soil moisture and runoff change, as expected, but that the variability of the values around the means also changes. -from Authors
• Brazil, L. E., Laurine, D. P., Day, G. N., & Valdes, J. B. (1993). Hydrologic forecasting - what are the issues?. Water Resources Planning and Management and Urban Water Resources, 235-239.
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  Abstract: The paper briefly describes hydrologic forecasting techniques that are being used today and raises issues that should be addressed as new hydrologic forecast systems are developed and implemented. The issues represent concerns that will become more important as operations begin to take advantage of some of the new technology that is becoming available to make better forecasts. A list of references on hydrologic forecasting is provided.
• Graves, C. E., Valdes, J. B., Shen, S. S., & North, G. R. (1993). Evaluation of sampling errors of precipitation from spaceborne and ground sensors. Journal of Applied Meteorology, 32(3), 374-385.
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  Abstract: The autocorrelation function and the spectrum are obtained directly from both processing the raingage data and using a theoretical stochastic model of space-time precipitation. This theoretical model serves as an intermediate step to obtain more information from the raingage records. The spectra obtained are then compared with those obtained from oceanic precipitation in the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE) and with that obtained from analyzing raingage records in east Texas. Finally, the spectra are used to evaluate the sampling errors that are due to the spatial gaps in measurements. The sampling error is expressed as an integral over the product of the spectral density of the stochastic rain field and a filter function. It is found that sampling errors of land precipitation are higher than those reported for ocean precipitation. -from Authors
• Raines, T. H., & Valdes, J. B. (1993). Estimation of flood frequencies for ungaged catchments. Journal of Hydraulic Engineering - ASCE, 119(10), 1138-1154.
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  Abstract: A typical procedure uses a simulation model to compute peak discharges where the recurrence interval is assumed to be equal to that of the design storm. Derived flood frequency distributions provide an alternative to this approach. The Diaz-Granados derived flood frequency distribution is modified to use the Soil Conservation Service (SCS) curve number method instead of the Philip equation because the required data are more readily available. The derived approach, the methods of Hebson and Wood and Diaz-Granados, and a HEC-1 simulation model are evaluated for four catchments in Texas with different climate, geomorphology, soil-type, and land-use characteristics. The procedure derived in this work is an improvement of the previous approach but none of these methods provided consistently better results when compared to Log-Pearson type III distributions of historic data for all four catchments. Improvement in the parameter estimation procedure to provide more reproducible parameters may yield consistently better results. -from Authors
• Seoane, R. S., & Valdes, J. B. (1993). Derived flood frequency distribution for ungaged catchments. Water Resources Planning and Management and Urban Water Resources, 384-387.
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  Abstract: Flood frequency distribution for ungaged catchments are described in the article. The various parameters that effect the flood frequency distribution are describes. Influence of the climate introducing the precipitation process is presented. The influence of the basic structure and the dynamic characteristics on the runoff is also presented.
• Stedinger, J. R., Karamouz, M., McCrodden, B., McMahon, G., Palmer, R., & Valdes, J. (1993). Using forecasts to improve reservoir operations. Water Resources Planning and Management and Urban Water Resources, 240-243.
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  Abstract: This review considers methodologies that have or can be employed to incorporate streamflow forecasts into reservoir policies and operating decisions. These include the use of streamflow forecasts in deterministic optimization models, use of multiple stage decision trees, stochastic analytical optimization models with linearized reservoir dynamics, and sophisticated stochastic models that can describe the joint distribution of streamflows and forecasts in the optimization of reservoir operations.
• Valdes, J. B., Seoane, R. S., & North, G. R. (1993). Methodology for the evaluation of global warming impact on soil moisture and runoff. Water Resources Planning and Management and Urban Water Resources, 425-428.
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  Abstract: Global warming is expected to increase the intensity of the global hydrologic cycle. Precipitation and temperature patterns, soil moisture requirements, and the physical structure of the vegetation canopy play important roles in the hydrologic system of drainage basins. In this work a methodology for the evaluation of impact on soil moisture concentration and direct surface runoff is presented.
• Humphries, J. W., Restrepo, P. J., & Valdes, J. B. (1992). Demodulation-remodulation revisited: theory and application. Water Resources Research, 28(7), 1823-1831.
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  Abstract: In modelling periodic hydrologic series, the amplitudes and phase angles of the harmonics reflect the magnitudes and timing of the seasonal peaks. Demodulation-remodulation captures the temporal variations in these stochastic parameters, thereby providing useful information and more accurate models than traditional Fourier series models. The technique is applied to the streamflow record of the Uda Walawe River which exhibits a strong bimodal annual pattern. Fourteen models are developed, providing a comparison between moving average filters commonly used in demodulation studies, the Fourier filter used in Fourier series analysis, and composite models which incorporate both filters. In addition, the development of a prototype forecasting filter demonstrates the viability of using demodulation-remodulation for forecasting. -from Authors
• Raines, T. H., & Valdes, J. B. (1992). Assessment of derived flood frequency distributions. Water Resources Planning and Management: Saving a Threatened Resource - In Search of Solutions, Proceedings of the Water Resources Sessions at Water Forum, 268-273.
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  Abstract: Derived flood frequency distributions based on the geomorphologic IUH are evaluated in this work. Two existing approaches, the methods of Hebson and Wood (1982) and Diaz-Granados et al. (1984), are evaluated for four catchments in Texas with different climate, geomorphology, soil type, and land use characteristics. The Diaz-Granados et al. technique was modified to use the SCS Curve Number method because the required data are more readily available than the parameters in the original formulation. The extreme value distributions from the three techniques are compared with those obtained from historic records using standard techniques. Sensitivity analysis of the parameters of the model derived in this work were carried out to provide an understanding of the evaluation of the parameters and their impact on the final distributions.
• Valdes, J. B., Filippo, J. M., Strzepek, K. M., & Restrepo, P. J. (1992). Aggregation-disaggregation approach to multireservoir operation. Journal of Water Resources Planning & Management - ASCE, 118(4), 423-444.
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  Abstract: A group of optimization models for the real-time operation of a hydropower system of reservoirs is presented in this paper. The dimensionality problems usually found in dynamic programming formulations are solved by a space-time aggregation/disaggregation procedure that combines stochastic dynamic programing and linear programming techniques. The reservoirs in a hydropower system are aggregated in power units rather than in water units, and an optimal operating policy for the equivalent aggregated reservoir is found in the first part of this work. The objective function in this first part is to mimimize the total cost or energy production for a hydrothermal system. The aggregated policy obtained is used in real-time operation of the system to determine the recommended daily releases and power production from each reservoir of the system. The proposed methodology is applied to a case study, the Lower Caroni system in Venezuela, which is composed of four reservoirs in series and a total installed capacity of 17 000 MW, with satisfactory results. -Authors
• Awwad, H. M., & Valdes, J. B. (1991). Adaptive parameter estimation for multisite streamflow forecasting. Water Resources Planning and Management and Urban Water Resources, 32-36.
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  Abstract: An adaptive procedure for parameter identification and noise statistics estimation for multisite streamflow forecasting is presented in this work. The model is a multivariate ARMAX model, formulated in a state-space form, with the Kalman filter used to obtain the optimal forecasts and updates of the states. Model parameters, as well as noise statistics, are updated on-line in an adaptive manner along with the states.
• Koepsell, R. W., & Valdes, J. B. (1991). Multidimensional rainfall parameter estimation from sparse network. Journal of Hydraulic Engineering, 117(7), 832-850.
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  Abstract: The multidimensional precipitation model proposed by Waymire et al. provides realistic representations of the rainfall process. The model, however, in its most simplified form requires the numerical evaluation of nine parameters. Islam et al. developed a parameter estimation procedure and they applied the methodology to a small experimental basin with a dense network of rain gauges. In this paper the same estimation procedure is attempted over a larger area where only a sparse rain-gauge network is available. Parameter estimates are determined for cyclonic-midlatitude and convective storms, which are characteristic of the winter and summer rain seasons over the test basin. Using the seasonal storm parameter estimates, multidimensional model storms are generated over the Brazos Valley in Texas, and the storms are assessed qualitatively.
• Valdes, J. B., & Bartolini, P. (1991). Evaluation of Intensity-Duration-Frequency curves by point precipitation models. Water Resources Planning and Management and Urban Water Resources, 22-26.
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  Abstract: In this work an alternative approach to estimate the Intensity-Duration-Frequency curves is used. This approach which uses point precipitation models recently proposed in the literature are used to obtain the IDF curves. This is based in the works of Rodriguez-Iturbe et al. (1987) and Burlando and Rosso (1989). The ability of these point models to represent extreme rainfall characteristics, when only daily records are available is also analyzed in this paper. This will greatly enhance the applicability of site specific IDF curves instead of using regionalized values which may not represent appropriately the rainfall characteristics at a specific site. The approach was applied to the historical records in Harris County, Texas.
• Nakamoto, S., Valdes, J. B., & North, G. R. (1990). Frequency-wavenumber spectrum for GATE phase I rainfields. Journal of Applied Meteorology, 29(9), 842-850.
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  Abstract: In the low frequencies-low wavenumber region the results coincide with those obtained by using the stochastic model proposed by North and Nakamoto. From the derived spectrum the inherent time and space scales of the stochastic model were determined to be approximately 13 hours and 36 km. The space-time correlation function evaluated from the frequency-wavenumber spectrum and that obtained directly from GATE Phase I records agreed. The sampling error was estimated to be on the order of 10%, for monthly mean rainfall averaged over 500 × 500 km boxes, which meets the scientific requirements of the TRMM mission. -from Authors
• Valdes, J. B., Nakamoto, S., Shen, S. S., & North, G. R. (1990). Estimation of multidimensional precipitation parameters by areal estimates of oceanic rainfall. Journal of Geophysical Research, 95(D3), 2101-2111.
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  Abstract: The procedure followed was the fitting of the first- and second-order moments at different aggregation scales by nonlinear regression techniques. The numerical estimates of the parameters using different subsets of GATE information were reasonably stable, i.e., they were not affected by changes of the area-averaging size, temporal length of the records, and percentage of areal coverage of rainfall. This suggests that the estimation procedure is relatively robust and suitable to estimate the parameters of the multidimensional model in areas of sparse density of rain gages. -from Authors
• Valdes, J. B., North, G. R., & Raines, T. (1990). Evaluation of global warming impact on soil moisture and water runoff in Texas. Array, 392-395.
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  Abstract: In this paper a numerical evaluation of the variability of soil moisture and surface runoff due to global warming is carried out. An analytical model of the soil moisture balance based on the authors' previous work is used to evaluate the probability distribution of the soil moisture concentration and resulting surface runoff. The input of hydroclimatic values is based on point precipitation models but modifications were carried out to account for the other variables following the approach suggested by C.W. Richardson. Preliminary results show that not only the mean of the distribution of both soil moisture and runoff charge, as expected, but the variability of the values around the means also does.
• Valdés, J. B., Díaz-Granados, M., & Bras, R. L. (1990). A derived PDF for the initial soil moisture in a catchment. Journal of Hydrology, 113(1-4), 163-176.
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  Abstract: The probability distribution of the initial soil moisture concentration of a catchment was derived based on the one-dimensional infiltration-exfiltration process of a layer of soil. Analytical expressions were found for the initial and final soil moisture concentration during a storm event. These analytical expressions were then used in simulation experiments for different combinations of climate and soil characteristics to evaluate the average soil moisture concentration at the beginning of a storm and its variance. A beta PDF was then fitted to completely characterize its probability distribution. Finally, a general expression for both the mean and the variance of the initial soil moisture is given based only on climate and soil characteristics. © 1990.
• Sastri, T., & Valdes, J. B. (1989). Rainfall intervention analysis for on-line applications. Journal of Water Resources Planning and Management, 115(4), 397-415.
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  Abstract: Rainfalls during summer season are a major cause of sporadic nonlinear transient drops in daily municipal water consumption. The nonhomogeneous, nonlinear effects induced by rainfall interventions on water use complicate time series model identification and estimation. An iterative computer algorithm, that employs a model-switching transfer function, is proposed for sequential estimation of the transient drops in the water consumption, so that they can be removed from the time-series data. Existing time series analysis techniques, which are based on homogeneous, covariance stationary assumptions are not directly applicable, since the water-use time series never reaches statistical equilibrium. The practical data transformation procedure introduced in this paper is useful for achieving approximately homogeneous and stationary time series prior to model identification and estimation of rainfall intervention effects. The resulting empirical model is a transfer function of intervention time, number of uninterrupted raining days, a moving average of maximum daily temperatures, and a moving average of the most recent water-use observations. This rainfall intervention model can also be used for inline prediction of temporal changes in daily water consumption of a city, given rainfall forecasts. An example is included to illustrate the applicability of this approach, using a record of municipal water use.
• Sastri, T., Flores, B., & Valdés, J. (1989). Detecting points of change in time series. Computers and Operations Research, 16(3), 271-293.
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  Abstract: A performance comparison study of six time-series change detection procedures via forecast-monitoring simulation is presented. Four of the procedures are due to Brown [1], Page [2], Box and Tiao [3] and Gardner [4]. The other two sequential detection schemes are developed in this paper; the first is based on Bagshaw and Johnson [5], while the second employs a moving-block estimator of innovations autocovariance. Eighty synthetic time series were generated, using an autoregressive model, an integrated-moving average model and a time-regression model having step changes in the parameters. The statistics being employed are based upon cumulative sum (cusum), squared cusum and discounted cusum of the innovations from the corresponding forecasting models. Results of this study indicate that the procedures which employ squared cusum and nondiscounted cusum of innovations yield smaller rates of false detection. The two best change-detection statistics of this study appear to possess good potential for industrial and business forecast monitoring applications. © 1989.
• Rodriguez-Iturbe, I., Febres, B., & Valdes, J. B. (1987). Rectangular pulses point process models for rainfall: analysis of empirical data. Journal of Geophysical Research, 92(D8), 9645-9656.
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  Abstract: A detailed analysis of some rainfall data from Denver, Colorado, is carried out at different levels of aggregation which range from 1 to 24 hours. Two classes of models are then fitted to the data. In the first class of models, storm events arise in a Poisson process, each such event being associated with a period of rainfall of random duration and constant but random intensity. Total rainfall intensity is formed by adding the contributions from all storm events. In the second class of models, storms arise in a Poisson process, each storm giving rise to a cluster of rain cells and each cell having a random duration and constant but random intensity. -from Authors
• Valdes, J. B., & Rodriguez-Iturbe, I. (1985). Approximations of temporal rainfall from a multidimensional model.. Water Resources Research, 21(8), 1259-1270.
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  Abstract: The feasibility of representing the temporal structure of a multidimensional rainfall process with simpler stochastic models and a study of the effect of parameter robustness on the time scale is investigated here via performing ccntrolled numerical experiments. A multidimensional representation for precipitation, given in the theory recently proposed by E. Waymire et al. (1984), is used for simulating rainfall in space and time. -from Authors
• Diaz-Granados, M., Valdes, J. B., & Bras, R. L. (1984). A physically based flood frequency distribution.. Water Resources Research, 20(7), 995-1002.
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  Abstract: The geomorphoclimatic instantaneous unit hydrograph theory, the joint probability density function of storm duration and intensity, and Philip's representation of the infiltration process are used to derive a flood frequency distribution that could be used in regions with no streamflow records. The resulting flood frequency distribution is in analytical form containing only few climatologic and physiographic parameters of the catchment.-from Authors
• Valdes, J. B., Rodriguez-Iturbe, I., & Vicens, G. J. (1980). CHOOSING AMONG HYDROLOGIC REGRESSION MODELS - 2. EXTENSIONS TO THE STANDARD MODEL.. Water Resources Research, 16(3), 507-516.
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  Abstract: Bayesian methods are used to discriminate among alternative structures of the covariance matrix of the disturbances of hydrologic regression schemes; moreover, the covariance matrix is allowed to be nonscalar. Different alternative functional forms, which the hydrologic regression may also have, are also discriminated through the proposed methodology.
• Rodriguez-Iturbe, I., Devoto, G., & Valdes, J. B. (1979). Discharge response analysis and hydrologic similarity: the interrelation between the geomorphologic IUH and the storm characteristics.. Water Resources Research, 15(6), 1435-1444.
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  Abstract: It is shown that the dynamic parameter v of the geomorphologic instantaneous unit hydrograph (IUH) can be taken as the velocity at the peak discharge time for a given rainfall-runoff event in a basin. This transforms the time variant IUH throughout the event into a time invariant IUH in each storm occurrence. The errors which the a priori estimation of the velocity in the IUH may cause in the calculation of the peak and time to peak of the runoff discharge are estimated for different types of basins and storms; the relative weights of the storm characteristics and the drainage network parameters in the prediction procedure are also studied in detail. -from Authors
• Valdes, J. B., Fiallo, Y., & Rodriguez-Iturbe, I. (1979). A rainfall-runoff analysis of the geomorphologic IUH.. Water Resources Research, 15(6), 1421-1434.
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  Abstract: To analyze this geomorphologic IUH in real world basins, a study was carried out on several basins in Venezuela and Puerto Rico. The geomorphologic IUH for each basin was compared with the IUH's derived from the discharge hydrograph produced by a physically based rainfall-runoff model of the same basins. The effects that the nonlinearities of the rainfall-runoff model have on the derivation of the IUH are analyzed, and further, controlled experiments are carried out in which the IUH is derived under constant velocity conditions. The geomorphologic IUH's and the ones obtained in the experiments are remarkably similar in all the basins analyzed. -from Authors
• Valdes, J. B., Vicens, G. J., & Rodriguez-Iturbe, I. (1979). Choosing among alternative hydrologic regression models.. Water Resources Research, 15(2), 347-358.
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  Abstract: Bayesian theory provides for the explicit accounting of both parameter and model uncertainties. It is used in this work to derive a procedure for discriminating among alternative hydrologic regression models. In particular, the procedure was used to discriminate among alternative exogeneous variables in regression models. Controlled experiments were designed to test the proposed procedure under different assumptions on model prior probabilities, length of sample, and model subset. These examples showed that besides its theoretical advantages, the use of the Bayesian procedure unambiguously selects the correct model in most of the applications. - Authors
• Wilson, C. B., Valdes, J. B., & Rodriguez-Iturbe, I. (1979). ON THE INFLUENCE OF THE SPATIAL DISTRIBUTION OF RAINFALL ON STORM RUNOFF.. Water Resour Res, 15(2), 321-328.
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  Abstract: This study is an assessment of the importance of precipitation accuracy on the rainfall-runoff modeling of a small catchment. Two mathematical models were used in the investigation: a deterministic rainfall-runoff model based on the kinematic wave approximation and a nonstationary time-varying multidimensional rainfall generation model. It is implicitly assumed that this rainfall generation model is an appropriate mathematical representation of the natural phenomenon of rainfall. The deterministic rainfall-runoff model is used to represent the 26. 5-mi**2 catchment of the Rio Fajardo in northeastern Puerto Rico. The rainfall model generates synthetic rainfall which serves as the input to this runoff model. The influence of the spatial distribution of the rainfall input on the discharge is analyzed by using 1 rain gage or 20 rain gages to record the synthetic storms. The isohyetal maps and hyetographs of the synthetic storms, together with the storm hydrographs produced by the runoff model, are analyzed, with specific attention given to the volume of storm runoff, time-to-peak runoff, and peak runoff.
• Rodriguez-Iturbe, I., Valdes, J. B., & Velasquez, J. M. (1978). APPLICATIONS OF KALMAN FILTER IN RAINFALL-RUNOFF STUDIES.. Array, 233-253.
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  Abstract: A description is made of the Kalman filter algorithm and of its applications to the study of rainfall-runoff relationships. The applications cover classical hydrologic techniques like the instantaneous unit hydrograph, as well as schemes for real time hydrologic forecasting. Emphasis is made on the body of information necessary for the application of the Kalman filter as well as the uncertainties which in hydrology are imbedded in this necessary information. The identification of the noise covariance matrices are specifically discussed. The effect of the uncertainty in the lag-structure of the model as well as the difference between transients and real changes in the system is treated in a hydrologic context. Refs.
• Valdes, J. B., Velasquez, J. M., & Rodriguez-Iturbe, I. (1978). BAYESIAN DISCRIMINATION OF HYDROLOGIC FORECASTING MODELS BASED ON THE KALMAN FILTER.. Array, 369-384.
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  Abstract: The Kalman filter algorithm very well suits real time prediction of streamflow. The state of the system is assumed to be either the ordinates of the response function of the system or streamflows themselves. In the first case assumptions have to be made about the initial state of the system, the lag structure of the model and the covariance matrix of the measurement noise. In this paper the use of Bayesian theory is proposed to discriminate alternative assumptions on the values of these variables. Controlled and real world experiments were carried out to examine the performance of these discrimination criteria and the results were quite satisfactory.
• Valdes, J. B., & Rodriguez-Iturbe, I. (1976). LINEAR MODEL DISCRIMINATION THEORY APPLIED TO THE CHOICE OF STRUCTURE AND FORM OF HYDROLOGIC REGRESSION MODELS.. MIT Dep Civ Eng Ralph M. Parsons Lab Water Resour Hydrodyn Rep.
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  Abstract: The use of regression models whose coefficients are not fixed but vary randomly was investigated in an attempt to represent uncertainties which are not only additive but also of the multiplicative form. Bayesian theory allows to explicitly account for both parameter and model uncertainties and it was used in this work to derive a procedure to discriminate alternative hydrologic regression models. In particular the procedure was used to discriminate alternative exogenous variables, to compare different structural forms of regression models and different assumptions on the covariance matrix of the distrubances. Artificial and real world examples in water resources were designed to test the proposed procedure under different assumptions on the prior probability of the models, length of the sample, model subset and covariance matrix of the disturbances.

Presentations

• Alemayehu, T., Roy, T., Serrat-Capdevila, A., Valdes, J. B., Alemayehu, T., Roy, T., Serrat-Capdevila, A., & Valdes, J. B. (2016, December). Simulating Streamflow Using Multiple Bias-Corrected Satellite Rainfall Products in the Tekeze Basin, Ethiopia. AGU Fall Meeting. San Francisco.
• Duran-Barroso, P., Gonzalez-Perez, J., & Valdes, J. B. (2016, March). Reduction of Uncertainty for estimating runoff with the NRCS CN Model by adaptation to local climate conditions. European Geophysical Union General Assembly. Vienna, Austria.
• Roy, T., Gupta, H. V., Serrat-Capdevilla, A., & Valdes, J. B. (2016, Fall). Using satellite based actual evapotranspiration estimates to improve streamflow forecasting. 2016 Fall Meeting of the American Geophysical Union.
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  Roy T, H Gupta, A Serrat-Capdevila and J Valdes (2016), Using satellite based actual evapotranspiration estimates to improve streamflow forecasting, 2016 Fall Meeting of the American Geophysical Union, San Francisco CA, Dec 12-16
• Valdes, J. B. (2016, November). Water Resources and Climate Change. II Venezuelan Symposium on Climate Change. University of the Andes (Venezuela): Invited.
• Valdes, J. B., Demaria, E. M., Wi, S., Serrat-Capdevila, A. -., Valdes, R., & Durcik, M. (2016, December). Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa. 2016 AGU Fall Meeting, Abstract GC44A-06. San Francisco.
• Valdes, J. B., Demaria, E., Wi, S., Serrat-Capdevila, A., Valdes-Pineda, R., & Durcik, M. (2016, December). Evaluating the performance of real-time streamflow forecasting using multi-satellite precipitation products in the Upper Zambezi, Africa. AGU Fall Meeting. San Francisco.
• Roy, T., Serrat-Capdevilla, A., Gupta, H. V., & Valdes, J. B. (2015, Fall). Streamflow Forecasting using Satellite Products: A Benchmark Approach. Can We Reduce Uncertainty by using Multiple Products and Multiple Models?. 2015 Fall Meeting of the American Geophysical Union, San Francisco CA. San Francisco CA: American Geophysical Union.
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  Roy T, A Serrat-Capdevila, H Gupta and J Valdes (2015) Streamflow Forecasting using Satellite Products: A Benchmark Approach. Can We Reduce Uncertainty by using Multiple Products and Multiple Models? Paper H51H-1471, Session XXX: xxx. 2015 Fall Meeting of the American Geophysical Union, San Francisco CA, Dec 14-18
• Roy, T., Serrat-Capdevilla, A., Gupta, H. V., & Valdes, J. B. (2015, Summer). Estimating uncertainties in streamflow forecasts using a Bayesian multi-model and multi-product approach. 2015 UCOWR/NIWR/CUAHSI Annual Conference “Water is Not for Gambling: Utilizing Science to Reduce Uncertainty”, Green Valley Ranch Resort Henderson, NV. Green Valley Ranch Resort Henderson, NV: UCOWR/NIWR/CUAHSI Annual Conference.
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  Roy T, A Serrat-Capdevila, H Gupta and J Valdes (2015) Estimating uncertainties in streamflow forecasts using a Bayesian multi-model and multi-product approach, 2015 UCOWR/NIWR/CUAHSI Annual Conference “Water is Not for Gambling: Utilizing Science to Reduce Uncertainty”, Green Valley Ranch Resort Henderson, NV, June 16-18
• Serrat-Capdevila, A., Fonseca, C., Valdes, J. B., Mitheu, F., & Durcik, M. (2015, December). Characterizing Decision-Making for Earth Observation Applications in Water Management. AGU Fall Meeting. San Francisco.
• Valdes, J. B., Serrat-Capdevila, A., Demaria, E., Durcik, M., Valdes, J. B., Serrat-Capdevila, A., Demaria, E., & Durcik, M. (2015, December). A Satellite Driven Real-time Forecasting Platform in the Upper Zambezi Basin: A Multi-model Comparison. AGU Fall Meeting.
• Valdes, J. B., Wi, S., Serrat-Capdevila, A. -., Demaria, E., & Durcik, M. (2015, December). A Satellite Driven Real-time Forecasting Platform in the Upper Zambezi Basin: A Multi-model Comparison. 2015 AGU Fall Meeting, Abstract H23L-07. San Francisco.
• Roy, T., Serrat-Capdevilla, A., Valdes, J. B., Durcik, M., Gupta, H. V., & Mukherjee, R. (2014, Dec 15-19). Multi-model and multi-product streamflow forecasting in the African basins. 2014 El Dia Del Agua, Department of Hydrology and Water Resources, The University of Arizona. Tucson, Arizona: Department of Hydrology and Water Resources, The University of Arizona.
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  Roy T, A Serrat-Capdevila, JB Valdes, M Durcik, HV Gupta and R Mukherjee (2014), Multi-model and multi-product streamflow forecasting in the African basins, presented at El Dia Del Agua, Department of Hydrology and Water Resources, The University of Arizona, Apr 9
• Valdes, J. B., Schneier-Madanes, G., Curley, E., & Maddock, T. (2016, December). Water and Wastewater in the Limitless City: Tucson Metropolitan Region in the Arizona Sun Corridor. UNESCO International Conference: Water, Megacities and Climate Change. Paris, France.

Poster Presentations

• Valdes-Pineda, R., Valdes, J. B., & Henry, D. (2016, March). Reconstruction of Long-Ter Hydro-Climatic Variability in Santiago de Chile. AMERIDENDRO 2016. Mendoza, Argnetina.
• Valdes-Pineda, R., Valdes, J. B., Serrat-Capdevila, A., Demaria, E., Robert, J., & Robertson, F. (2016, December). Skill Analysis of Seasonal Streamflow Forecasting for the Upper Zambezi, Africa. American Geophysical Union (AGU Fall Meeting). San Francisco CA.
• Serrat-Capdevila, A. -., Fonseca, C., Valdes, J. B., Durcik, M., & Mithieu, F. (2015, December). Characterizing Decision-Making for Earth Observation Applications in Water Management. 2015 AGU Fall Meeting, Abstract PA31A-2146. San Francisco.