Rainfall distributional properties control hydrologic model parameter importance.

Abstract

Study region: Semi-arid region of the Western United States of America in 16.6 km2 WS10 watershed using data from the highly instrumented Walnut Gulch Experimental Watershed managed by the USDA-Agricultural Research Services. Study focus: Hydrologic model parameters are generally designed to represent watershed physiographic properties. This study investigates the possible impact of climate forcing, particularly precipitation across a watershed, on model parameter identification – a topic that has historically received minimal attention. To address this gap, we conducted time-varying and time-aggregate sensitivity analysis of a physically based distributed hydrologic model on a heavily instrumented watershed under various observed and synthetic storm events to assess how the distributional properties of rainfall in space and time influence the importance model parameters. Particularly, we focused on a semi-arid watershed with an area larger than the typical convective storms in the region. New hydrologic insight: Results show that there is a significant variation in parameter importance following rainfall spatial and temporal properties and that characterizing the relationship between parameter importance and rainfall properties is essential for identifying parameter values that adequately capture the watershed behaviors. We further showed that a power-law function linking parameter importance to precipitation properties can extrapolate results to other climate regimes. More analyses across different watersheds, climate forcing, and models are required to improve our understanding and strategies for parametrization and calibration of watershed models.

Keywords

• Dynamic parameter importance
• VARS
• KINEROS2
• Walnut gulch
• Zonal calibration
• Watershed modeling