Mapping basin level water productivity using remote sensing and secondary data in the Karkheh River Basin, Iran

Abstract

Water productivity (WP) mapping is essential to evaluate the performance of current water use at the river basin scale. WP mapping is also essential to identify opportunities to improve the net gain from water by either increasing the productivity for a given consumption of water or reducing consumption without decreasing production. This requires the computation of all benefits and overall water use at a similar spatial domain. Generally the secondary data related to agricultural, livestock and poultry production are managed at administrative district level, whereas hydrological data are collected at sub-watershed scale. This scale difference, hinders estimation at hydrological scales such as sub-catchment to river basin. Due to these limitations, estimates of WP beyond field and farm scale usually do not exist, as is the case of the Karkheh River basin of Iran. To address these issues, in this paper we demonstrate an approach to estimate WP at different scales using a range of datasets. To understand the productivity gaps within and between sub-basins of the Karkheh Basin, we assessed land and water productivity for major crops using a questionnaire survey of 298 farmers. The farm-level land and water productivity in irrigated areas was considerably higher than in rainfed areas. The yield of irrigated wheat and its WP, in terms of yield per unit of gross inflow, averaged 3320?1510 kg/ha and 0.55?0.20 kg/m3, whereas the corresponding values for rainfed wheat were 1460?580 kg/ha and 0.46?0.22 kg/m. For analysis from sub-catchment to basin scale, we assessed economic WP, in terms of gross value of production per unit of actual evapotranspiration, for all agricultural enterprises including rainfed and irrigated agriculture, livestock production and overall vegetation production using remote sensing data and routine secondary data/agricultural statistics. The sub-catchment estimates show that the water productivity variability is quite high: 0.027-0.071 $/m3 and 0.120-0.524 $/m3 for rainfed and irrigated systems respectively. Inclusion of livestock changes both the magnitude and patterns of overall water productivity and in doing so highlights the importance of fully accounting for all components in agricultural production systems. The WP mapping exercise presented in this paper identified both bright- and hot-spots for helping policy makers and managers to target better resource (re)allocation and measures to enhance productivity in the Karkheh Basin. The approach is applicable to other river basins.