Using satellite-based estimates of evapotranspiration and groundwater changes to determine anthropogenic water fluxes in land surface models

Abstract

Abstract. Irrigation is a widely used water management practice that is often poorly parameterized in land surface and climate models. Previous studies have addressed this issue via use of irrigation area, applied water inventory data, or soil moisture content. These approaches have a variety of drawbacks including data latency, accurately prescribing irrigation intensity, and conservation of water volume for soil moisture approach. In this study, we parameterize irrigation fluxes using satellite observations of evapotranspiration (ET) against ET from a suite of land surface models without irrigation. We then apply this water flux into the Community Land Model (CLM) and use an iterative approach to estimate groundwater recharge and partition the water flux between groundwater and surface water. The ET simulated by CLM with irrigation matches the magnitude and seasonality of observed satellite ET well, with a mean difference of 6.3 mm month−1 and a correlation of 0.95. Differences between the new CLM ET values and observed ET values are always less than 30 mm month−1 and the differences show no pattern with respect to seasonality. The results reinforce the importance of accurately parameterizing anthropogenic hydrologic fluxes into land surface and climate models to assess environmental change under current and future climates and land management regimes.