water Article Optimization of Hydrologic Response Units (HRUs) Using Gridded Meteorological Data and Spatially Varying Parameters David Poblete 1,* , Jorge Arevalo 2,3 , Orietta Nicolis 4,5 and Felipe Figueroa 6 1 School of Civil Engineering, Universidad de Valparaíso, Valparaíso 2340000, Chile 2 Department of Meteorology, Universidad de Valparaíso, Valparaíso 2340000, Chile;
[email protected] 3 Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ 85721, USA 4 Faculty of Engineering, Univesidad Andres Bello, Viña del Mar 2520000, Chile;
[email protected] 5 Research Center for Integrated Disaster Risk Management (CIGIDEN), ANID/FONDAP/15110017, Santiago 8320000, Chile 6 Plataforma de Investigación en Ecohidrología y Ecohidráulica (EcoHyd), Santiago 8320000, Chile; felipe.fi
[email protected] * Correspondence:
[email protected] Received: 3 November 2020; Accepted: 10 December 2020; Published: 18 December 2020 Abstract: Although complex hydrological models with detailed physics are becoming more common, lumped and semi-distributed models are still used for many applications and offer some advantages, such as reduced computational cost. Most of these semi-distributed models use the concept of the hydrological response unit or HRU. In the original conception, HRUs are defined as homogeneous structured elements with similar climate, land use, soil and/or pedotransfer properties, and hence a homogeneous hydrological response under equivalent meteorological forcing. This work presents a quantitative methodology, called hereafter the principal component analysis and hierarchical cluster analysis or PCA/HCPC method, to construct HRUs using gridded meteorological data and hydrological parameters. The PCA/HCPC method is tested using the water evaluation and planning system (WEAP) model for the Alicahue River Basin, a small and semi-arid catchment of the Andes, in Central Chile.