Groundwater abstraction and depletion were assessed at a 1-km resolution in the irrigated areas of the Indus Basin using remotely sensed evapotranspiration (ET) and precipitation; a process-based hydrological model and spatial information on canal water supplies. A calibrated Soil and Water Assessment Tool (SWAT) model was used to derive total annual irrigation applied in the irrigated areas of the basin during the year 2007. The SWAT model was parameterized by station corrected precipitation data (R) from the Tropical Rainfall Monitoring Mission, land use, soil type, and outlet locations. The model was calibrated using a new approach based on spatially distributed ET fields derived from different satellite sensors. The calibration results were satisfactory and strong improvements were obtained in the Nash-Sutcliffe criterion (0.52 to 0.93), bias (−17.3% to −0.4%), and the Pearson correlation coefficient (0.78 to 0.93). Satellite information on R and ET was then combined with model results of surface runoff, drainage, and percolation to derive groundwater abstraction and depletion at a nominal resolution of 1 km. It was estimated that in 2007, 68 km 3 (262 mm) of groundwater was abstracted in the Indus Basin while 31 km 3 (121 mm) was depleted. The mean error was 41 mm/year and 62 mm/year at 50% and 70% probability of exceedance, respectively. Pakistani and Indian Punjab and Haryana were the most vulnerable areas to groundwater depletion and strong measures are required to maintain aquifer sustainability.

The availability of accurate rainfall data at proper temporal and spatial scales is vital for knowledge of renewable water resources and safe withdrawals for irrigation. Rain gauge networks in mountainous basins such as the Indus are sparse and insufficient to plan withdrawals and water management applications. Satellite rainfall estimates can be used as an alternative source of information but need area-specific calibration and validation due to the indirect nature of the radiation measurements. In this study, a calibration protocol is worked out for rainfall data from the Tropical Rainfall Measuring Mission (TRMM) satellite because uncalibrated TRMM rainfall data are inaccurate for use in rainfall-runoff studies and in soil water balance studies. Two alternative techniques, regression analysis (RA) and geographical differential analysis (GDA), were used to calibrate TRMM rainfall data for different periods and spatial distributions. The validity of these techniques was tested using Nash-Sutcliffe efficiency and the standard error of estimate. The GDA technique proved to be better, with higher efficiency and smaller error in complex mountainous terrains. The deviation between TRMMdata and rain gauge data was decreased considerably from 10.9% (pre-calibration at 625 km2) to 6.1% (post-calibration at 3125 km2) for annual time periods. For monthly periods, the deviation of 34.9% (pre-calibration at 625 km2) was decreased to 15.4% (post-calibration at 3125 km2). Calibration can be improved further if more rain gauges are available. The GDA technique can be applied to calibrate TRMM rainfall data in regions with limited rain gauge data and can provide a sufficiently accurate estimate of the key hydrological process that can be used in water management applications

[1] The surface energy fluxes and related evapotranspiration processes across the Indus Basin were estimated for the hydrological year 2007 using satellite measurements. The new ETLook remote sensing model (version 1) infers information on actual Evaporation (E) and actual Transpiration (T) from combined optical and passive microwave sensors, which can observe the land-surface even under persistent overcast conditions. A two-layer Penman-Monteith equation was applied for quantifying soil and canopy evaporation. The novelty of the paper is the computation of E and T across a vast area (116.2 million ha) by using public domain microwave data that can be applied under all weather conditions, and for which no advanced input data are required. The average net radiation for the basin was estimated as being 112 Wm À2 . The basin average sensible, latent and soil heat fluxes were estimated to be 80, 32, and 0 Wm ; RE ¼ 6.5% for annual ET). The water balance for all irrigated areas together as one total system in Pakistan and India (26.02 million ha) show a total ET value that is congruent with the ET value from the ETLook surface energy balance computations. An unpublished validation of the same ETLook model for 23 jurisdictional areas covering the entire Australian continent showed satisfactory results given the quality of the watershed data and the diverging physiographic and climatic conditions (R 2 ¼ 0.70; RMSE ¼ 0.31 mmd À1 ; RE ¼ -2.8% for annual ET). Eight day values of latent heat fluxes in Heibei (China) showed a good resemblance (R 2 ¼ 0.92; RMSE ¼ 0.04 mm d À1 ; RE ¼ 9.5% for annual ET). It is concluded that ETLook is a novel model that can be operationalized further-especially after improving the preprocessing of spaceborne soil moisture data. This preprocessing includes (1) downscaling of topsoil moisture from 25 to 1 km pixels, and (2) translation of topsoil moisture into subsoil moisture values.

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