Regionalization of Tank Model Using Landscape Metrics of Catchments

To address the challenges inherent in accessing spatiotemporal hydrological data, water resources professionals have developed various regionalization tools. The present study examines the possibility that changes in landscape metrics including mean shape index, mean perimeter-area ratio, mean patch size and patch density of land use/ land cover could result in variations in the optimized parameters of the conceptual rainfall-runoff Tank model. Data from 30 catchments that are geographically distributed in Germany was used to develop the procedure. Regression analysis-based modeling indicated that four out of twelve model parameters (r² ≥ 0.40) can be explained by changes in catchment geometrics along with a set of landscape metrics of land use/land cover. They include: coefficient of infiltration flow (r² = 0.48, p < 0.03), intermediate flow (r² = 0.77, p < 0.02), water storage level for sub-surface flow (r² = 0.57, p < 0.05) and water storage level for intermediate flow (r² = 0.85, p < 0.01). Despite developing fairly reliable regression models, uncertainty analysis also revealed that uncertainty induced unreliability of the regionalized models is of significant importance.