Multidecadal High-Resolution Hydrologic Modeling of the Arkansas–Red River Basin

Abstract

Abstract Land surface heterogeneity and its effects on surface processes have been a concern to hydrologists and climate scientists for the past several decades. The contrast between the fine spatial scales at which heterogeneity is significant (1 km and finer) and the coarser scales at which most climate simulations with land surface models are generated (hundreds of kilometers) remains a challenge, especially when incorporating land surface and subsurface lateral fluxes of mass. In this study, long-term observational land surface forcings and derived solar radiation were used to force high-resolution land surface model simulations over the Arkansas–Red River basin in the Southern Great Plains region of the United States. The most unique aspect of these simulations is the fine space (1 km2) and time (hourly) resolutions within the model relative to the total simulation period (51 yr) and domain size (575 000 km2). Runoff simulations were validated at the subbasin scale (600–10 000 km2) and were found to be in good agreement with observed discharge from several unregulated subbasins within the system. A hydroclimatological approach was used to assess simulated annual evapotranspiration for all subbasins. Simulated evapotranspiration values at the subbasin scale agree well with predictions from a simple one-parameter empirical model developed in this study according to Budyko’s concept of “geographical zonality.” The empirical model was further extended to predict runoff and evapotranspiration sensitivity to precipitation variability, and good agreement with computed statistics was also found. Both the empirical model and simulation results demonstrate that precipitation variability was amplified in the simulated runoff. The finescale at which the study is performed allows analysis of various aspects of the hydrologic cycle in the system including general trends in precipitation, runoff, and evapotranspiration, their spatial distribution, and the relationship between precipitation anomalies and runoff and soil water storage anomalies at the subbasin scale.