Estimation of Flood Discharge in Ungauged Basin Using GPM-IMERG Satellite-Based Precipitation Dataset in a Moroccan Arid Zone

Ouaba, Mounir; Khalki, El Mahdi El; Saidi, Mohamed El Mehdi; Alam, Md. Jobair Bin

doi:10.1007/s41748-022-00296-z

Cited by 11 publications

(6 citation statements)

References 46 publications

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“…The reduction of parameters is an essential factor addressed in this approach to determine the maximum rainfall amounts, in addition to considering the continuous modeling for all days, months, and years of simulation. Furthermore, the SCS-CN method is widely used for hydrologic studies in an ungauged basin for the National Water Commission (CONAGUA) [75][76][77][78][79][80][81][82][83][84][85][86][87][88].…”

Section: Discussionmentioning

confidence: 99%

Extreme Runoff Estimation for Ungauged Watersheds Using a New Multisite Multivariate Stochastic Model MASVC

Hernández-Bedolla,

García-Romero,

Franco-Navarro

et al. 2023

Water

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Precipitation is influential in determining runoff at different scales of analysis, whether in minutes, hours, or days. This paper proposes the use of a multisite multivariate model of precipitation at a daily scale. Stochastic models allow the generation of maximum precipitation and its association with different return periods. The modeling is carried out in three phases. The first is the estimation of precipitation occurrence by using a two-state multivariate Markov model to calculate the non-rainfall periods. Once the rainfall periods of various storms have been identified, the amount of precipitation is estimated through a process of normalization, standardization of the series, acquisition of multivariate parameters, and generation of synthetic series. In comparison, the analysis applies probability density functions that require fewer data and, consequently, represent greater certainty. The maximum values of surface runoff show consistency for different observed return periods, therefore, a more reliable estimation of maximum surface runoff. Our approach enhances the use of stochastic models for generating synthetic series that preserve spatial and temporal variability at daily, monthly, annual, and extreme values. Moreover, the number of parameters reduces in comparison to other stochastic weather generators.

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Section: Discussionmentioning

confidence: 99%

Extreme Runoff Estimation for Ungauged Watersheds Using a New Multisite Multivariate Stochastic Model MASVC

Hernández-Bedolla,

García-Romero,

Franco-Navarro

et al. 2023

Water

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“…HEC-HMS provides transformation tools, a number of different processing methods are provided by HEC-HMS. The Clark Unit Hydrograph and Snyder Unit Hydrograph methods, which have been successfully applied to simulate flooding in the Moroccan watershed [11,25,26,27,28]. In this study, direct runoff was transformed into Clark unit hydrograph.…”

Section: Clark Unit Hydrographmentioning

confidence: 99%

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

et al. 2023

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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.

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“…Several studies have also employed IMERG products in flood simulations and forecasting on a fine temporal scale (e.g., event-based or hourly [26][27][28]). Predicting the amount and timing of peak flows in flood events is crucial for addressing flood control and disaster reduction.…”

Section: Introductionmentioning

confidence: 99%

“…Saouabe (2020) explored the applicability of hourly IMERG-E data to hydrological modeling in the mountainous river basins of Morocco [26]. Ouaba (2022) used hourly IMERG-E and IMERG-F data to simulate the river flow in the Bourrous basin of Morocco [28]. These studies provide feasible methods for flood modeling and forecasting with satellite data sources.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of GPM IMERG Satellite Precipitation Products in Event-Based Flood Modeling over the Sunshui River Basin in Southwestern China

Lyu,

Li,

2024

Remote Sensing

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This study evaluates the applicability of hourly Global Precipitation Measurement Mission (GPM) Integrated Multi-satellitE Retrievals for GPM (IMERG) data for event-based flood modeling in the Sunshui River Basin, southwestern China, using the hydrologic modeling system (HEC-HMS) model. The accuracies of IMERG V6, IMERG V7, and the corrected IMERG V7 satellite precipitation products (SPPs) were assessed against ground rainfall observations. The performance of flood modeling based on the original and the corrected SPPs was then evaluated and compared. In addition, the ability of different numbers (one–eight) of ground stations to correct IMERG V7 data for flood modeling was investigated. The results indicate that IMERG V6 data generally underestimate the actual rainfall of the study area, while IMERG V7 and the corrected IMERG V7 data using the geographical discrepancy analysis (GDA) method overestimate rainfall. The corrected IMERG V7 data performed best in capturing the actual rainfall events, followed by IMERG V7 and IMERG V6 data, respectively. The IMERG V7-generated flood hydrographs exhibited the same trend as those of the measured data, yet the former generally overestimated the flood peak due to its overestimation of rainfall. The corrected IMERG V7 data led to superior event-based flood modeling performance compared to the other datasets. Furthermore, when the number of ground stations used to correct the IMERG V7 data in the study area was greater than or equal to four, the flood modeling performance was satisfactory. The results confirm the applicability of IMERG V7 data for fine time scales in event-based flood modeling and reveal that using the GDA method to correct SPPs can greatly enhance the accuracy of flood modeling. This study can act as a basis for flood research in data-scarce areas.

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Estimation of Flood Discharge in Ungauged Basin Using GPM-IMERG Satellite-Based Precipitation Dataset in a Moroccan Arid Zone

Cited by 11 publications

References 46 publications

Extreme Runoff Estimation for Ungauged Watersheds Using a New Multisite Multivariate Stochastic Model MASVC

Extreme Runoff Estimation for Ungauged Watersheds Using a New Multisite Multivariate Stochastic Model MASVC

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

Evaluation of GPM IMERG Satellite Precipitation Products in Event-Based Flood Modeling over the Sunshui River Basin in Southwestern China

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