Identification of dominant hydrological processes using sensitivity analysis

Abstract: Recent studies indicate that hydrological models should be customized to align with distinct objectives and the basins being examined. This underscores the importance of understanding the hydrologic processes relevant to the specific objectives. In this seminar, we discuss how a sequential sensitivity analysis using the Efficient Elementary Effect (EEE) method is employed to select the sensitive parameters. The methodology is demonstrated for a highly parameterized hydrological modeling framework, SUMMA (The Structure for Unifying Multiple Modeling Alternatives). The methodology adopted not only helped to scale down the dimensionality of the problem in terms of computational demand and complexity but also allowed us to capture the dominant hydrological process of the catchment. The findings from this study align with the existing literature, thereby confirming the method’s efficacy. By giving precedence to parameters with the most substantial influence it also helps to mitigate the challenge of parameter equifinality. The potential of the method is illustrated through one of the study basins in India. The extensive model runs required are conducted through high-performance computing.

Date/Time
Date(s) - 01/12/2023
4:00 pm - 5:00 pm