Improving runoff estimates from regional climate models: a performance analysis in Spain

An important step to assess water availability is to have monthly time series representative of the current situation. In this context, a simple methodology is presented for application in large-scale studies in regions where a properly calibrated hydrologic model is not available, using the output variables simulated by regional climate models (RCMs) of the European project PRUDENCE under current climate conditions (period 1961–1990). The methodology compares different interpolation methods and alternatives to generate annual times series that minimise the bias with respect to observed values. The objective is to identify the best alternative to obtain bias-corrected, monthly runoff time series from the output of RCM simulations. This study uses information from 338 basins in Spain that cover the entire mainland territory and whose observed values of natural runoff have been estimated by the distributed hydrological model SIMPA. Four interpolation methods for downscaling runoff to the basin scale from 10 RCMs are compared with emphasis on the ability of each method to reproduce the observed behaviour of this variable. The alternatives consider the use of the direct runoff of the RCMs and the mean annual runoff calculated using five functional forms of the aridity index, defined as the ratio between potential evapotranspiration and precipitation. In addition, the comparison with respect to the global runoff reference of the UNH/GRDC dataset is evaluated, as a contrast of the “best estimator” of current runoff on a large scale. Results show that the bias is minimised using the direct original interpolation method and the best alternative for bias correction of the monthly direct runoff time series of RCMs is the UNH/GRDC dataset, although the formula proposed by Schreiber (1904) also gives good results

A bivariate return period based on copulas for hydrologic dam design: accounting for reservoir routing in risk estimation

A multivariate analysis on flood variables is needed to design some hydraulic structures like dams, as the complexity of the routing process in a reservoir requires a representation of the full hydrograph. In this work, a bivariate copula model was used to obtain the bivariate joint distribution of flood peak and volume, in order to know the probability of occurrence of a given inflow hydrograph. However, the risk of dam overtopping is given by the maximum water elevation reached during the routing process, which depends on the hydrograph variables, the reservoir volume and the spillway crest length. Consequently, an additional bivariate return period, the so-called routed return period, was defined in terms of risk of dam overtopping based on this maximum water elevation obtained after routing the inflow hydrographs. The theoretical return periods, which give the probability of occurrence of a hydrograph prior to accounting for the reservoir routing, were compared with the routed return period, as in both cases hydrographs with the same probability will draw a curve in the peak-volume space. The procedure was applied to the case study of the Santillana reservoir in Spain. Different reservoir volumes and spillway lengths were considered to investigate the influence of the dam and reservoir characteristics on the results. The methodology improves the estimation of the Design Flood Hydrograph and can be applied to assess the risk of dam overtopping

Irrigation efficiency and water-policy implications for river-basin resilience

Rising demand for food, fiber, and biofuels drives expanding irrigation withdrawals from surface water and groundwater. Irrigation efficiency and water savings have become watchwords in response to climate-induced hydrological variability, increasing freshwater demand for other uses including ecosystem water needs, and low economic productivity of irrigation compared to most other uses. We identify three classes of unintended consequences, presented here as paradoxes. Ever-tighter cycling of water has been shown to increase resource use, an example of the efficiency paradox. In the absence of effective policy to constrain irrigated-area expansion using "saved water", efficiency can aggravate scarcity, deteriorate resource quality, and impair river basin resilience through loss of flexibility and redundancy. Water scarcity and salinity effects in the lower reaches of basins (symptomatic of the scale paradox) may partly be offset over the short-term through groundwater pumping or increasing surface water storage capacity. However, declining ecological flows and increasing salinity have important implications for riparian and estuarine ecosystems and for non-irrigation human uses of water including urban supply and energy generation, examples of the sectoral paradox. This paper briefly considers three regional contexts with broadly similar climatic and water-resource conditions – central Chile, southwestern US, and south-central Spain – where irrigation efficiency directly influences basin resilience. The comparison leads to more generic insights on water policy in relation to irrigation efficiency and emerging or overdue needs for environmental protection.