Improving Water Productivity for Agriculture - Predicting and Preventing Crisis in Irrigated Water Use in a Changing Climate

Summary form only given. Global climate change presents challenges for mitigating and adapting natural resource use and management locally and regionally. This is particularly true in subsistence agriculture areas where natural and economic resources are limited. In the case of decreased water availability, we propose a new and innovative approach of water productivity (WP, productivity per unit of water or kgm³) mapping using advanced remote sensing data (hyperspectral-hyperspatial-advanced multispectral) that "pin-points" climate-induced water loss andor areas of poor cropland WP. This in turn will lead to informed application of management practices and associated water savings exactly where they are needed. A study conducted in the irrigated croplands of different parts of the World taking major world crops will be ideal for demonstrating the linkages between water, climate, and food that are critically important, both ecologically and economically. Therefore, the developments presented , which build upon advanced remote sensing, surface energy balance modeling, and scenario modeling, identify areas of probable WP problems and quantify the volume of "new water" that will be made available if we increase WP in the irrigated agricultural areas of these key global irrigated areas and key global irrigated crops. This "new water" can then be used to improve the sustainability of new economic developments. Two complementary goals will be to: (a) quantify the dynamics between agricultural water productivity, runoff, and percolation and their affect on related stream-flows and groundwater levels that satisfy riparian water needs and determine riparian water savings, and (b) use a systems approach to determine the ecological outcome of increased water productivity in existing and restored riparian areas, including the provision of riparian plant detritus to salmonid food webs. The approach involves: (a) water use (actual ET; m³m²) map- ing through surface energy balance models, (b) crop and riparian productivity (productivity per unit area or kgm²) mapping through spectro-biophysical modeling and interpolating the same to larger areas using remote sensing, (c) WP mapping by dividing crop productivity by water use, and (d) scenario analysis for "new water" through spatial modeling. Data products will serve as inputs to a hydrological-ecological model that relates discharge of agricultural drainage water to riparian productivity and production of plant litter and detritus, a key component of juvenile salmonid food webs. Through spatial modeling, scenarios of improved irrigated cropland water productivity will be analyzed and potential consequences for adjacent existing and restored riparian areas will be determined, information decision-makers will need with increasing pressures on water resources.