Abstract
Distributed and semi-distributed hydrological modeling approaches commonly involve the discretization of a catchment into several modeling elements. Although some modeling studies were conducted using triangulated irregular networks (TINs) previously, little attention has been given to assess the impact of TINs as compared to the standard catchment discretization techniques. Here, we examine how different catchment discretization approaches and radiation forcings influence hydrological simulation results. Three catchment discretization methods, i.e., elevation zones (Hypsograph) (HYP), regular square grid (SqGrid), and TIN, were evaluated in a highly steep and glacierized Marsyangdi-2 river catchment, central Himalaya, Nepal. To evaluate the impact of radiation on model response, shortwave radiation was converted using two approaches: one with the measured solar radiation assuming a horizontal surface and another with a translation to slopes. The results indicate that the catchment discretization has a great impact on simulation results. Evaluation of the simulated streamflow value using Nash–Sutcliffe efficiency (NSE) and log-transformed Nash–Sutcliffe efficiency (LnNSE) shows that highest model performance was obtained when using TIN followed by HYP (during the high flow condition) and SqGrid (during the low flow condition). Similar order of precedence in relative model performance was obtained both during the calibration and validation periods. Snow simulated from the TIN-based discretized models was validated with Moderate Resolution Imaging Spectroradiometer (MODIS) snow products. Critical Success Indexes (CSI) between TIN-based discretized model snow simulation and MODIS snow were found satisfactory. Bias in catchment average snow cover area from the models with and without using imputed radiation is less than two percent, but implementation of imputed radiation into the Statkraft Hydrological Forecasting Toolbox (Shyft) gives better CSI with MODIS snow.
Highlights
Accurate runoff prediction is one of the fundamental challenges for effective and sustainable water resource management in the Himalaya region
Most of the reductions in the number of computational cells when using triangulated irregular networks (TINs) were obtained in this elevation range (Figure 4)
This study was focused on evaluation of the effect of three catchment discretization approaches: hypsography (HYP), square grid (SqGrid), and TIN on hydrological model simulation results, i.e., streamflow and snow cover
Summary
Accurate runoff prediction is one of the fundamental challenges for effective and sustainable water resource management in the Himalaya region. Reliable meteorological forcing data and accurate land cover information at a range of spatial and temporal scales are critical to effective runoff prediction, and for water resource management [1]. Spatial variability of topography and land use cover types adds to the complexity of the problem [2]. Several hydrological models have been developed for use in various applications. Some of these models include SRM [3], HEC-HMS [4], J2000 [5], Statkraft’s Hydrological Forecasting
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