Juan B. Valdés

Climate-change impacts in a regional karst aquifer, Texas, USA

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 × CO2 conditions to create aquifer recharge scenarios in a warmer climate. Several pumping scenarios were combined with 2 × CO2 climate scenarios to assess the sensitivity of water resources impacts to human-induced stresses on the Edwards BFZ aquifer. The 2 × CO2 climatechange 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 × CO2 climate scenarios. Our simulations indicate that 2 × 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. 2000 Elsevier Science B.V. All rights reserved.

Frequency and Spatial Characteristics of Droughts in the Conchos River Basin, Mexico

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.

Increasing Social–Ecological Resilience by Placing Science at the Decision Table: the Role of the San Pedro Basin (Arizona) Decision-Support System Model

We have analyzed how the collaborative development process of a decision-support system (DSS) model can effectively contribute to increasing the resilience of regional social-ecological systems. In particular, we have focused on the case study of the transboundary San Pedro Basin, in the Arizona- Sonora desert region. This is a semi-arid watershed where water is a scarce resource used to cover competing human and environmental needs. We have outlined the essential traits in the development of the decision- support process that contributed to an improvement of water-resources management capabilities while increasing the potential for consensual problem solving. Comments and feedback from the stakeholders benefiting from the DSS in the San Pedro Basin are presented and analyzed within the regional (United States-Mexico boundary), social, and institutional context. We have indicated how multidisciplinary collaboration between academia and stakeholders can be an effective step toward collaborative management. Such technology transfer and capacity building provides a common arena for testing water- management policies and evaluating future scenarios. Putting science at the service of a participatory decision-making process can provide adaptive capacity to accommodate future change (i.e., building resilience in the management system).

Non-stationary frequency analysis of extreme precipitation in South Korea using peaks-over-threshold and annual maxima

The conventional approach to the frequency analysis of extreme precipitation is complicated by non-stationarity resulting from climate variability and change. This study utilized a non-stationary frequency analysis to better understand the time-varying behavior of short-duration (1-, 6-, 12-, and 24-h) precipitation extremes at 65 weather stations scattered across South Korea. Trends in precipitation extremes were diagnosed with respect to both annual maximum precipitation (AMP) and peaks-over-threshold (POT) extremes. Non-stationary generalized extreme value (GEV) and generalized Pareto distribution (GPD) models with model parameters made a linear function of time were applied to AMP and POT respectively. Trends detected using the Mann–Kendall test revealed that the stations showing an increasing trend in AMP extremes were concentrated in the mountainous areas (the northeast and southwest regions) of South Korea. Trend tests on POT extremes provided fairly different results, with a significantly reduced number of stations showing an increasing trend and with some stations showing a decreasing trend. For most of stations showing a statistically significant trend, non-stationary GEV and GPD models significantly outperformed their stationary counterparts, particularly for precipitation extremes with shorter durations. Due to a significant-increasing trend in the POT frequency found at a considerable number of stations (about 10 stations for each rainfall duration), the performance of modeling POT extremes was further improved with a non-homogeneous Poisson model. The large differences in design storm estimates between stationary and non-stationary models (design storm estimates from stationary models were significantly lower than the estimates of non-stationary models) demonstrated the challenges in relying on the stationary assumption when planning the design and management of water facilities. This study also highlighted the need of caution when quantifying design storms from POT and AMP extremes by showing a large discrepancy between the estimates from those two approaches.

Merging and error analysis of regional hydrometeorologic anomaly forecasts conditioned on climate precursors

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.

Decision Support Systems in Water Resources Planning and Management: Stakeholder Participation and the Sustainable Path to Science-Based Decision Making

This chapter will focus on decision support systems (DSS) as they relate to water resources management and planning. Water is a resource that touches and is interwoven with numerous human activities as well as the environment we live in. Its availability and beneficial use depend on the timing and manner of its arrival (rainfall intensity, rain or snow, duration, frequency), the physical setting of the region (climate and weather, topography, geology), the engineering structures in place, the environmental constraints (existing ecosystems), the legal regulatory context and institutional policies. In most contexts, cultural values and preferences are also very important. To make good decisions, it is clear that a detailed understanding of how the system works and behaves is necessary. It is equally important to understand the implications of these decisions what consequences are likely to ripple through the interwoven system, and what parties will be affected as a result of a particular set of actions? Understanding the coupled human and physical system is essential. In addition to looking at the evolution of decision support tools and methods for water resources management (Section 2), this chapter focuses on how integrative science and multi-resolution models provide the basis for a decision support system (Section 3), on the overall setting of the decision making process and ways in which a DSS for water resources should be developed (Section 4). We make the argument that for a DSS to be successful and informative, the process by which it is developed will be as important, or even more so, than the finished decision support tool itself. A description of successful participatory planning approaches and collaborative modeling methods is presented, as well as a comparison of several case studies. Section 5 presents an overview on how to deal with uncertainty. We present our vision to merge adaptive management, integrative modeling and stakeholder participation to face the water management challenges of the arriving future. A synthesis and future challenges are presented in the last section.

Vegetation responses to precipitation and temperature: a spatiotemporal analysis of ecoregions in the Colorado River Basin

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.

A platform for probabilistic Multimodel and Multiproduct Streamflow Forecasting

NASA-USAID [11-SERVIR11-58]; International Center for Integrated Water Resources Management (ICIWaRM-UNESCO); Australian Research Council through the Centre of Excellence for Climate System Science [CE110001028]; EU [INCO-20011-7.6, 294947]

Characterizing the water extremes of the new century in the US South-west: A comprehensive assessment from state-of-the-art climate model projections

The impact of climate change scenarios in the hydrology of the Verde River basin (Arizona) is analyzed using an ensemble of downscaled climate model results, SPI analysis, and two hydrologic models of different complexity. To assess model uncertainty, 47 ensemble members combining simulations from 16 global climate models and 3 emission scenarios were used to provide an uncertainty envelope in the hydrologic variables. The analysis shows that simple lumped models and more complex distributed runoff models can yield similar results. Results show that under all scenarios, the distribution functions of hydrologic states will shift towards lower values and droughts will progressively become more frequent, longer and more intense.

Spatial characterization of droughts in the conchos river : Basin based on bivariate frequency analysis

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.