Abstract
The prediction of river discharge using hydrological models (HMs) is of utmost importance, especially in basins that provide drinking water or serve as recreation areas, to mitigate damage to civil structures and to prevent the loss of human lives. Therefore, different HMs must be tested to determine their accuracy and usefulness as early warning tools, especially for extreme precipitation events. This study simulated the river discharge in an Andean watershed, for which the distributed HM Runoff Prediction Model (RPM) and the semi-distributed HM Hydrologic Modelling System (HEC-HMS) were applied. As precipitation input data for the RPM model, high-resolution radar observations were used, whereas the HEC-HMS model used the available meteorological station data. The obtained simulations were compared to measured discharges at the outlet of the watershed. The results highlighted the advantages of distributed HM (RPM) in combination with high-resolution radar images, which estimated accurately the discharges in magnitude and time. The statistical analysis showed good to very good accordance between observed and simulated discharge for the RPM model (R2: 0.85–0.92; NSE: 0.77–0.82), whereas for the HEC-HMS model accuracies were lower (R2: 0.68–0.86; NSE: 0.26–0.78). This was not only due to the application of means values for the watershed (HEC-HMS), but also to limited rain gauge information. Generally, station network density in tropical mountain regions is poor, for which reason the high spatiotemporal precipitation variability cannot be detected. For hydrological simulation and forecasting flash floods, as well as for environmental investigations and water resource management, meteorological radars are the better choice. The greater availability of cost-effective systems at the present time also reduces implementation and maintenance costs of dense meteorological station networks.
Highlights
Precipitation, along with topography, vegetation cover, and soil types, control the rain-runoff processes within a watershed [1,2,3]
Comparing the two hydrological models (HMs) applied in this study, it was found that the distributed Runoff Prediction Model (RPM) model in combination with high-resolution radar data is more precise than the semi-distributed HEC-HMS model using the available station data, because the spatiotemporal distribution of all input parameters is considered [19]
Isolated storms are often not detected by traditional meteorological station networks, especially in tropical mountain regions, due to the high spatiotemporal precipitation variability, which is why radar systems are the better option
Summary
Precipitation, along with topography, vegetation cover, and soil types, control the rain-runoff processes within a watershed [1,2,3]. Land use changes caused by anthropogenic activities can degrade soils, which reduces their water regulation capacity and increases the flood risk [9]. In this context, different hydrological models (HMs) have been developed to estimate river discharge due to precipitation events [10,11]. Different hydrological models (HMs) have been developed to estimate river discharge due to precipitation events [10,11] By means of these models it is possible to estimate the peak flows in magnitude and time, and, to reduce the vulnerability to natural disasters related to rain-runoff processes [12]. These models allow improvement of water resource management and the design of functional civil engineering structures, such as drinking water supply systems [13,14]
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