Estimation of Land Surface States and Fluxes using a Land Surface Model Considering Different Irrigation Systems.

Food security can be improved by increasing the extent of agricultural land or by increasing agricultural productivity, including through intensive management such as irrigation. The objectives of this study were to incorporate practical irrigation schemes into land surface models of the NASA Land Information System (LIS) and to apply the tool to estimate the impact of irrigation on land surface states and fluxes—including evapotranspiration, soil moisture, and runoff—in the Murray-Darling basin in Australia. Here we present results obtained using Noah Land Surface Model v3.2 within LIS without simulated irrigation (IR0) and with three irrigation simulation routines: flood irrigation (IR1), drip irrigation (IR2), and sprinkler irrigation (IR3). Moderate Resolution Imaging Spectrometer (MODIS) vegetation index was used to define crop growing seasons. Simulations were performed for a full year (July 2002 to June 2003) and evaluated against hydrologic flux estimates obtained in previous studies. Irrigation amounts during the growing season (August 2002 to March 2003) were simulated as 104.6, 24.6, and 188.1 GL for IR1, IR2, and IR3, respectively. These preliminary results showed water use efficiency from a drip irrigation scheme would be highest and lowest from a sprinkler irrigation scheme, with a highly optimized version of flood irrigation falling in between. Irrigation water contributed to a combination of increased evapotranspiration, runoff, and soil moisture storage in the irrigation simulations relative to IR0. Implications for water management applications and for further model development will be discussed.