Incorporating Spatio-Temporal Changes of Well Irrigation Into a Distributed Hydrologic Model To Improve Groundwater Anomaly Estimations for Basins With Expanding Agricultural Lands

Abstract

This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change. © The Author(s) 2024.