Inter-Comparison of Rain-Gauge, Radar, and Satellite (IMERG GPM) Precipitation Estimates Performance for Rainfall-Runoff Modeling in a Mountainous Catchment in Poland

Abstract

Precipitation is one of the essential variables in rainfall-runoff modeling. For hydrological purposes, the most commonly used data sources of precipitation are rain gauges and weather radars. Recently, multi-satellite precipitation estimates have gained importance thanks to the emergence of Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG GPM), a successor of a very successful Tropical Rainfall Measuring Mission (TRMM) mission which has been providing high-quality precipitation estimates for almost two decades. Hydrological modeling of mountainous catchment requires reliable precipitation inputs in both time and space as the hydrological response of such a catchment is very quick. This paper presents an inter-comparison of event-based rainfall-runoff simulations using precipitation data originating from three different sources. For semi-distributed modeling of discharge in the mountainous river, the Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS) is applied. The model was calibrated and validated for the period 2014–2016 using measurement data from the Upper Skawa catchment a small mountainous catchment in southern Poland. The performance of the model was assessed using the Nash–Sutcliffe efficiency coefficient (NSE), Pearson’s correlation coefficient (r), Percent bias (PBias) and Relative peak flow difference (rPFD). The results show that for the event-based modeling adjusted radar rainfall estimates and IMERG GPM satellite precipitation estimates are the most reliable precipitation data sources. For each source of the precipitation data the model was calibrated separately as the spatial and temporal distributions of rainfall significantly impact the estimated values of model parameters. It has been found that the applied Soil Conservation Service (SCS) Curve Number loss method performs best for flood events having a unimodal time distribution. The analysis of the simulation time-steps indicates that time aggregation of precipitation data from 1 to 2 h (not exceeding the response time of the catchment) provide a significant improvement of flow simulation results for all the models while further aggregation, up to 4 h, seems to be valuable only for model based on rain gauge precipitation data.

The Role of the Spatial Distribution of Radar Rainfall on Hydrological Modeling for an Urbanized River Basin in Japan

“…This method of estimating river runoff data is conventional and accepted worldwide. However, there have been several discussions on the advantages and disadvantages of using rain gauge data for hydrological modeling [1][2][3][4][5][6]. Rainfall measurements from rain gauge data provide some of the best ground truth rainfall information at single point stations.…”

“…One of these is the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS), which has been widely used worldwide. The accuracy and performance of this model using radar rainfall has also been widely recognized [4,5,17,19,22,23]. Since many types of hydrological models have been developed for research and operational purposes, no standard exists for selecting the type of hydrological model used.…”

“…Since many types of hydrological models have been developed for research and operational purposes, no standard exists for selecting the type of hydrological model used. In many cases, semi-distributed or lumped models have been used [5,17,19,[22][23][24][25][26][27][28], whereas physically distributed models have been used in certain other cases [20,21,29]. Each type of hydrological model has its merits and demerits depending on performance and the objectives for which it is used.…”

“…Several researchers agree that the use of accurate spatiotemporal rainfall variation data in hydrological models is essential for monitoring river discharge and may help to improve our understanding of water balances [8,22,24,25,30,31]. Therefore, the use of high-resolution weather radar data in hydrological applications has grown significantly as an alternative to traditional rainfall observations with rain gauges [5,8,17,[19][20][21][22]31], and several studies suggest that the use of high-resolution rainfall data in hydrological models may offer a more realistic output [4,8,16,21,22,24,25,30,31]. However, there is no clear guideline on the optimum spatiotemporal radar rainfall resolution for this purpose.…”

“…In most cases, the effects of the spatial resolution of rainfall on the results of hydrological modeling for a river basin were evaluated based on available rain gauge networks and using interpolation techniques [1,2,6,7,18]. However, such interpolations of rainfall data from networks where data availability is low can produce misleading results for the real spatial distribution of rainfall [1,[5][6][7]11]; notably, such hydrological applications have been carried out for a long time. Therefore, many studies have commented on the possible errors associated with the spatial resolution of rainfall data based on such work, and have recommended that the optimal spatial resolution of rainfall be derived for hydrological modeling of any river basin [7,29].…”