Evaluation of geomorphological approaches combined with digital elevation models for the Nash's instantaneous unit hydrograph. (April 2021) - Martim de Moura, Maíra; Beskow, Samuel; da Silva Terra, Fabrício; Rogério de Mello, Carlos; Almeida da Cunha, Zandra; Cassalho, Felício
Abstract: Methodologies for estimation of direct surface runoff (DSR) hydrographs have been proposed, especially for the Unit Hydrograph (UH) and Instantaneous Unit Hydrograph (IUH). The widely used IUH developed by Nash (NIUH) has two main parameters: number of reservoirs (n) and storage coefficient (k), which by definition are determined based on observed rainfall-runoff events. In order to overcome the need for hydrological data for application of NIUH, geomorphological approaches (GAs) have been developed to provide the aforementioned parameters for ungauged watersheds, thus allowing for the estimation of DSR hydrographs using only relief information. The aim of this study was to evaluate the performance of 4 GAs (GA1 - Nash, 1960; GA2 - Wu, 1963; GA3 - Rosso, 1984; GA4 - Bhaskar et al., 1997). Moreover, this study sought to investigate the influence of different digital elevation models (DEMs) (TOPO, ASTER, SRTM-30 and SRTM-90) on the determination of geomorphological attributes necessary for the application of the above-mentioned GAs. Twenty rainfall-runoff events observed in a small Brazilian watershed were used to evaluate the performance of NIUH combined with different GAs and DEMs for estimation of DSR hydrographs. In view of the results found in this study, the main conclusions are: i) the GAs exert more influence on the parameters n and k than the DEMs; ii) GA1 and GA2 outperformed GA3 and GA4 ; and iii) GA2 coupled with the ASTER DEM results in the best estimates of DSR hydrographs. Graphical abstract: Image 1 Highlights: Four geomorphological approaches (GAs) were used to determine n and k (Nash's IUH). TOPO, STRM and ASTER DEMs were used for derivation of geomorphological attributes. GAs result in greater variation in n and k than the DEM. GA1 and GA2 outperform GA3 and GA4 . GA2 combined with ASTER DEM yields the best estimates of hydrographs.