Streamflow data are of prime importance to water-resources planning and management, and the accuracy of their estimation is very important for decision making. The Soil and Water Assessment Tool (SWAT) and Artificial Neural Network (ANN) models have been evaluated and compared to find a method to improve streamflow estimation. For a more complete evaluation, the accuracy and ability of these streamflow estimation models was also established separately based on their performance during different periods of flows using regional flow duration curves (FDCs). Specifically, the FDCs were divided into five sectors: very low, low, medium, high and very high flow. This segmentation of flow allows analysis of the model performance for every important discharge event precisely. In this study, the models were applied in two catchments in Peninsular Spain with contrasting climatic conditions: Atlantic and Mediterranean climates. The results indicate that SWAT and ANNs were generally good tools in daily streamflow modelling. However, SWAT was found to be more successful in relation to better simulation of lower flows, while ANNs were superior at estimating higher flows in all cases.

Abstract:The Segura River Basin is one of the most water-stressed basins in Mediterranean Europe. If we add to the actual situation that most climate change projections forecast important decreases in water resource availability in the Mediterranean region, the situation will become totally unsustainable. This study assessed the impact of climate change in the headwaters of the Segura River Basin using the Soil and Water Assessment Tool (SWAT) with bias-corrected precipitation and temperature data from two Regional Climate Models (RCMs) for the medium term (2041-2070) and the long term (2071-2100) under two emission scenarios (RCP4.5 and RCP8.5). Bias correction was performed using the distribution mapping approach. The fuzzy TOPSIS technique was applied to rank a set of nine GCM-RCM combinations, choosing the climate models with a higher relative closeness. The study results show that the SWAT performed satisfactorily for both calibration (NSE = 0.80) and validation (NSE = 0.77) periods. Comparing the long-term and baseline periods, precipitation showed a negative trend between 6% and 32%, whereas projected annual mean temperatures demonstrated an estimated increase of 1.5-3.3 • C. Water resources were estimated to experience a decrease of 2%-54%. These findings provide local water management authorities with very useful information in the face of climate change.

This study assessed how changes in terms of temperature and precipitation might translate into changes in water availability and droughts in an area in a developing country with environmental interest. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze the impacts of climate change on water resources of the Guajoyo River Basin in El Salvador. El Salvador is in one of the most vulnerable regions in Latin America to the effects of climate change. The predicted future climate change by two climate change scenarios (RCP 4.5 and RCP 8.5) and five general circulation models (GCMs) were considered. A statistical analysis was performed to identify which GCM was better in terms of goodness of fit to variation in means and standard deviations of the historical series. A significant decreasing trend in precipitation and a significant increase in annual average temperatures were projected by the middle and the end of the twenty–first century. The results indicated a decreasing trend of the amount of water available and more severe droughts for future climate scenarios with respect to the base period (1975–2004). These findings will provide local water management authorities useful information in the face of climate change to help decision making.

No abstract

Abstract. Any change in the components of the water balance in a coastal aquifer, whether natural or anthropogenic, can alter the freshwater–salt water equilibrium. In this sense climate change (CC) and land use and land cover (LULC) change might significantly influence the availability of groundwater resources in the future. These coastal systems demand an integrated analysis of quantity and quality issues to obtain an appropriate assessment of hydrological impacts using density-dependent flow solutions. The aim of this work is to perform an integrated analysis of future potential global change (GC) scenarios and their hydrological impacts in a coastal aquifer, the Plana Oropesa-Torreblanca aquifer. It is a Mediterranean aquifer that extends over 75 km2 in which important historical LULC changes have been produced and are planned for the future. Future CC scenarios will be defined by using an equi-feasible and non-feasible ensemble of projections based on the results of a multi-criteria analysis of the series generated from several regional climatic models with different downscaling approaches. The hydrological impacts of these CC scenarios combined with future LULC scenarios will be assessed with a chain of models defined by a sequential coupling of rainfall-recharge models, crop irrigation requirements and irrigation return models (for the aquifer and its neighbours that feed it), and a density-dependent aquifer approach. This chain of models, calibrated using the available historical data, allow testing of the conceptual approximation of the aquifer behaviour. They are also fed with series representatives of potential global change scenarios in order to perform a sensitivity analysis regarding future scenarios of rainfall recharge, lateral flows coming from the hydraulically connected neighbouring aquifer, agricultural recharge (taking into account expected future LULC changes) and sea level rise (SLR). The proposed analysis is valuable for improving our knowledge about the aquifer, and so comprises a tool to design sustainable adaptation management strategies taking into account the uncertainty in future GC conditions and their impacts. The results show that GC scenarios produce significant increases in the variability of flow budget components and in the salinity.

No abstract

Climate change afects rainfall and temperature producing a breakdown in the water balance and a variation in the dynamic of freshwater-seawater in coastal areas, exacerbating seawater intrusion (SWI) problems. The target of this paper is to propose a method to assess and analyze impacts of future global change (GC) scenarios on SWI at the aquifer scale in a coastal area. Some adaptation measures have been integrated in the deinition of future GC scenarios incorporating complementary resources within the system in accordance with urban development planning. The proposed methodology summarizes the impacts of potential GC scenarios in terms of SWI status and vulnerability at the aquifer scale through steady pictures (maps and conceptual 2D cross sections for speciic dates or statistics of a period) and time series for lumped indices. It is applied to the Plana de Oropesa-Torreblanca aquifer. The results summarize the inluence of GC scenarios in the global status and vulnerability to SWI under some management scenarios. These GC scenarios would produce higher variability of SWI status and vulnerability. Keywords Global change impacts • Adaptation measures • Seawater intrusion • Status and vulnerability • Coastal aquifer • Lumped indexThis article is a part of the Topical Collection in Environmental Earth Sciences on "Impacts of Global Change on Groundwater in Western Mediterranean Countries", guest edited by Maria Luisa Calvache, Carlos Duque and David Pulido-Velazquez.

Water availability is essential for the appropriate analysis of its sustainable management. We performed a comparative study of six hydrological balance models (Témez, ABCD, GR2M, AWBM, GUO-5p, and Thornthwaite-Mather) in several basins with different climatic conditions within Spain in the 1977–2010 period. We applied six statistical indices to compare the results of the models: the Akaike information criterion (AIC), the Bayesian information criterion (BIC), Nash–Sutcliffe model efficiency coefficient (NSE), coefficient of determination (R2), percent bias (PBIAS), and the relative error between observed and simulated run-off volumes (REV). Furthermore, we applied the FITEVAL software to determine the uncertainty of the model. The results show that when the catchments are more humid the obtained results are better. The GR2M model gave the best fit in peninsular Spain in a UNEP aridity index framework above 1, and NSE values above 0.75 in a 95% confidence interval classify GR2M as very good for humid watersheds. The use of REV is also a key index in the assessment of the margin of error. Flow duration curves show good performance in the probabilities of exceedance lower than 80% in wet watersheds and deviations in low streamflows account for less than 5% of the total streamflow.