Author(s): Myriam Benkirane; Nour-Eddine Laftouhi; Agustin Millares; Marina Cantalejo; Said Khabba

Linked Author(s): Myriam Benkirane

Keywords: Hydrologic modeling; Remote sensing; HEC-HMS; High Atlas Mountains; Uncertainty

Abstract: Climate change is likely to impact the seasonality of precipitation and flows in Mediterranean mountain catchments. This will lead to increasing rainfall intensity, and runoff magnitude frequency, even in arid areas particularly the Moroccan High Atlas, where extreme flood events are still difficult to predict, as this type of data is rare to be collected in a short time step. Flash floods are generally poorly observed hydrological extremes in regions where gauging stations are sparse and unevenly spatially distributed, and characterized by high interannual precipitation variability. Considering the important influence of the uncertainties of the calibration parameters of the hydrological models; this makes predicting and understanding their seasonal behavior so difficult, like in our case in the Zat and Ghdat watersheds. The High Atlas mountainous watersheds are characterized by a very significant seasonal contrast, with dry and hot summers, with infrequent flash flood events, followed by stormy autumns causing extreme flooding, then mixed winters precipitation as liquid rainfall downstream and snow upstream with a moderately stable runoff, followed by the spring where snowmelt represents a large proportion of streamflow in the study area during the spring. In this part of the year flooding as river flow is higher and more regular. The goal of this study is to understand the behavior of the Zat and Ghdat watersheds and the seasonality of runoff and precipitation while considering the uncertainty of the used model. The analysis has been developed using instantaneous rainfall and runoff data at 10 minutes time scale, from the 2 measuring stations located downstream of the two watersheds (Sidi Rahal and Taferiat) respectively during the period from 01/09/2011 to 31/08/2018. More than 100 episodes were simulated and calibrated on HEC-HMS software®. Then a remote sensing approach was elaborated to quantify the snowfall seasonal contribution to flooding. However, to analyze the uncertainty of the calibration parameters we applied the Probability Distribution Function and the Monte Carlo simulations to analyze the Curve Number and the Time of Concentration uncertainty. The results showed that observed and simulated hydrographs were highly correlated for both basins. Moreover, the model’s performance was evaluated by a Nash coefficient ranging from 61. 9% to 90% for the calibration part. The results showed also that the runoff flooding parameters uncertainties are due to the snowmelt process.

DOI: https://doi.org/10.3850/IAHR-39WC252171192022275

Year: 2022