GIS preprocessing for rainfall-runoff modeling using HEC-HMS in Nekkor watershed (Al-Hoceima, Northern Morocco)

Abstract

All Discharge data are among the most critical factors that must be considered when evaluating the management of water resources in a watershed. Simulation of rainfall-runoff is therefore an important element in assessing the impacts of serious flooding. In the present study, rainfall-runoff in the Nekkor watershed in Al Hoceima province was simulated using GIS, remote sensing and the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) model. The applicability, capacity and suitability of this model for rainfall runoff in the watershed were examined. The watershed parameters were generated using (HEC-GeoHMS) and ArcGIS. The model was calibrated using a daily data set that occurred in the watershed between 2003 and 2007, the validation period was from 2009 to 2012. Model performance was evaluated using a variety of different statistical indices to study the response and impact of rainfall-runoff. Model parameters were changed and calibration was performed using the Soil Conservation Service Curve Number loss method. Consistent and satisfactory performance in terms of peak discharge, total flood volume, timing of peak discharge and overall hydrograph adjustment effect was found. The determination coefficient (R2) for the validation period reached 0.73 versus 0.71 for the calibration period. The root mean square error (RMSE) is within the acceptable range. The relative bias (RE) demonstrates an overestimation in the calibration period and an underestimation in the validation period in the peak flows. These results will help decision makers to better manage water resources in this watershed and mitigate flood risks.

Watershed Hydrological Response in Developing Climate Change Resilience and Adaptation Strategies, case of Gilgal Gibe Watershed, Ethiopia

“…Currently, there are tremendous watershed hydrological modeling tools across the globe. For instance, Soil and Water Assessment Tools (SWAT) (Ghadei1 et al 2018;Karakoyun and Kaya 2022;Koltsida et al 2021;Sisay et al 2017), Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) (Guduru et al 2023;Oleyiblo and Li 2010;El Yousfi et al 2023), Bayesian model (Han et al 2014;Thiemann et al 2001;Yang et al 2007), artificial neural network and machine learning (Yang et al 2020) are the most widely applicable hydrological modeling tools. Depending on the simplicity, data availability, number of input parameters need for the model, the calibrated and validated HEC-HMS model was used within this study.…”

Streamflow Simulation in Semiarid Data-Scarce Regions: A Comparative Study of Distributed and Lumped Models at Aguenza Watershed (Morocco)

“…In addition, there is an urgent need to characterize the rapid response of runoff to extreme precipitation events that are becoming more frequent in arid and semi-arid and Mediterranean regions [14,15], as they often generate extremely damaging flash floods and inundations [16][17][18]. Since accurate simulations of flow are possible in arid and semi-arid regions, effective water resource management and flood warning require accurate and precise simulations of streamflow [19][20][21][22][23][24][25].…”