Abstract
Scarce historical flood data in ungauged basins make it difficult to establish empirical and conceptual model forecast in these areas. The physical-based distributed model TOPKAPI is introduced for flood prediction in an ungauged basin by parameter transplant. Five main parameters are selected, and the sensitivity is analyzed by the GLUE method. The Xixian basin and Huangchuan basin in the upper Huaihe basin in China are chosen as study areas. The Xixian basin is regarded as a gauged basin for parameter calibration, and the Huangchuan basin is regarded as an ungauged basin by ignoring the historical discharge data. The model is calibrated in gauged Xixian basin, and then parameters are directly transplanted to adjacent “ungauged” Huangchuan basin to simulate flood forecast in an ungauged basin. The sensitivity analysis shows that soil thickness and soil saturated water content are the most sensitive parameters, and the Manning coefficient of main channel with high Strahler also significantly affects forecast results. According to the simulation results, the TOPKAPI model exhibits good performance in building and the prediction of the ungauged basin, in which the qualified rate of volume and peaks reaches 69.23%, and the average NSE criterion is over 0.67, which is acceptable forecast accuracy and has positive implication for the hydrological forecasting research.
Highlights
With the advancement of geographic information technology, remote sensing technology, and computer science, even in the absence of hydrological observatories, the geography of the watershed can be obtained from remote sensing images, including digital elevation model (DEM) [5] and land use and soil classification maps [25]
Professor Ezio Todini from the University of Bologna in Italy proposed the TOPKAPI (Topographic Kinematic Approximation and Integration) hydrological model in 1995 [29]. is model refers to a physics-based distributed hydrological model based on the study of rainfall-runoff relationship to explore the potential of hydrological model prediction based on physical theory in mountain flood forecast [29]. e model consists of several modules [30]
The hydrological process in each calculation unit is generalized into three nonlinear reservoir equations, which are similar in structure, representing drainage in soil, surface runoff, and channel runoff on saturated soil and impermeable surface, respectively. e finite difference method is used in the calculation, so the correlated four surrounding grids are considered during the calculation of each grid unit [36]. e parameters used to describe the underlying surface conditions could be extracted directly from the soil type classification map and land surface utilization map
Summary
Ese parameters are relatively easy to obtain online, including the Shuttle Radar Topography Mission (SRTM) launched by the Consultative Organization for International Agricultural Research (CGIAR), which can obtain the global 90 m resolution digital elevation model free of charge from its official website; the accessible website of the University of Maryland (UMD) in the United States On this point, the hydrological model based on physical basis has obvious advantages over the conventional conceptual hydrological model when it is relatively easy to obtain the parameters required for model building in ungauged areas [28, 40]
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