Effect of Dynamic PET Scaling with LAI and Aspect on the Spatial Performance of a Distributed Hydrologic Model

The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all models benefit from pedo-transfer functions based on the soil properties crop-vegetation dynamics. Mostly coarse-scale meteorological forcing used to estimate only water balance at catchment outlet. mesoscale Hydrologic Model (mHM) one of rare that incorporate remote sensing data, i.e., leaf area index (LAI) aspect, improve actual evapotranspiration (AET) together. user can select either LAI or aspect scale PET. However, herein we introduce new weight parameter, “alphax”, allows both together for potential (PET) scaling. With mHM code enhancement, modeler also has option using raw PET with no In this study, streamflow AET are simulated Main Basin (Germany) period 2002–2014. additional value scaling model performance investigated Moderate Resolution Imaging Spectroradiometer (MODIS) products. From 69 parameters, 26 parameters selected calibration Optimization Software Toolkit (OSTRICH). For evaluation, KGE metric balance, SPAEF evaluating patterns AET. Our results show highest when indicating contain valuable information topography canopy (e.g., forests, grasslands, croplands) should be preserved during modeling. This agronomic studies like crop yield estimations irrigation use. “alphax” parameter makes physically more flexible robust as decide weights according study domain.