Abstract. 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.

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This paper assesses the effect of climate change on water availability for consumptive use for a river basin taking into account the regulation capacity of its water supply systems and a set of management standards (restrictions, demands, reliability). A specific sensitivity index to climate change defined by the relation between the unitary variation of water availability and the unitary variation of the average annual inflow is studied. The analysis is conducted by constructing climate projections taking into consideration changes only in mean annual streamflow and changes in both the mean and the coefficient of variation of the annual streamflow. The study area includes 567 basins which cover practically the entire territory of continental Spain. The results show a significant sensitivity to changes in the coefficient of variation for regulated systems.

This paper provides and tests a methodology to compute surface water (SW) availability for irrigation on regulated systems at large scale, considering different alternatives of streamflow monthly time series derived from regional climate models. SW availability for consumptive use for a river basin is estimated through the concept of maximum potential water withdrawal (MPWW). MPWW is defined as the maximum demand that can be supplied at a given point in the river network under certain conditions: management restrictions (such as ecological flows), demand priorities, monthly distribution of demand and required reliability. Calculation was applied in 567 basins that cover the entirety of mainland Spain to evaluate adaptation needs for agriculture by comparing MPWW for irrigation in the current situation and under climate change projections. The results show that streamflow monthly time series obtained from the regional climate model simulations and bias corrected by University of New Hampshire/Global Runoff Data Centre (UNH/GRDC) dataset and Schreiber's formula provide MPWW values similar to those obtained with the observed data under current situations. Under climate change projections, the capability to satisfy water requirements for agricultural production is significantly reduced and adaptation measures are necessary to mitigate the expected long-term impact.

An important aspect to assess the impact of climate change on 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 minimize 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 naturalised 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 behavior 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 evaporation 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 also gives good results