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Developing distributed conceptual hydrological models from geospatial databases

Yuqiong Liu¹, Matej Durcik¹, Hoshin V. Gupta¹ & Thorsten Wagener²

1 Sustainability of semi-Arid Hydrology and Riparian Areas (SAHRA), Department of Hydrology & Water Resources, Tucson, Arizona 85721-0158, USA

yqliu@hwr.arizona.edu

2 Department of Civil and Environmental Engineering, Pennsylvania State University, 226B Sackett Building,
University Park, Pennsylvania 16802, USA

Abstract Interest in the development and use of spatially-distributed hydrological models has increased considerably in recent years. However, the application of a model in distributed fashion significantly increases the number of model parameters that need to be estimated, and presents a serious challenge for model identification. In this paper we propose a general framework for developing a distributed conceptual hydrological model from geospatial databases based on hydrological similarity and landscape classification. The framework is applied to spatially-distributed modelling of the upper Rio Grande River basin in the southwestern USA. Preliminary results are encouraging and indicate that the proposed framework holds promise for making improved predictions in ungauged basins, while being computationally inexpensive.

Key words distributed modelling; parameter estimation; model identification; landscape classification; GIS; geospatial databases