Use of NRCS-curve number method for peak discharge estimation in Sharqu ElNeil locality, Khartoum, Sudan

Babiker, Insaf S.; Mohamed, Mohamed Abugaib A.

doi:10.1007/s12517-019-4685-5

Cited by 4 publications

(9 citation statements)

References 12 publications

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“…This result was consistent with the findings of Mashaly and Ghoneim [3], who found that basins which have short lag periods were at greater potential risk of flash floods than those which have longer lag periods. Additionally, it was found that the Wadi Hail catchment had an overall average curve number (CN) of 83, suggesting more runoff owing to the absence of surface permeability over the drainage basin, as previously documented using variable techniques [6,32,33,48].…”

Section: Flood Hydrographs and Peak Runoffsupporting

confidence: 63%

“…It is also recognized as the Natural Resources Conservation (NRCS) curve number (CN) method. It has been commonly used to compute surface runoff (Q), map potential areas of groundwater recharge in arid and semi-arid regions [31,32], estimate peak discharge [33][34][35], and simulate and assess flooding [9,36,37]. The excess rainfall (Q) is related to the effective rainfall, as shown in Equation ( 1), through what is known as maximum potential retention value (S).…”

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

“…In the equation, CN represents the purpose of the LULC and Hydrologic Soil Group (HSG), and α denotes a unit conversion constant value that equals 25.4 in SI units and 1.0 in CU units [33]. To achieve the set objectives, we computed CN values by integrating the classified land cover map (Figure 5b) and the Hydrological Soil Group (HSG) map prepared using the soil texture map (Figure 8).…”

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

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Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

Salih,

Hassablla

2024

Atmosphere

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Floods in southwestern Saudi Arabia, especially in the Asir region, are among the major natural disasters caused by natural and human factors. In this region, flash floods that occur in the Wadi Hail Basin greatly affect human life and activities, damaging property, the built environment, infrastructure, landscapes, and facilities. A previous study carried out for the same basin has effectively revealed zones of flood risk using such an approach. However, the utilization of the HEC–HMS (Hydrologic Engineering Center–Hydrologic Modeling System) model and IMERG data for delineating areas prone to flash floods remain unexplored. In response to this advantage, this work primarily focused on flood generation assessment in the Wadi Hail Basin, one of the major basins in the region that is frequently prone to severe flash flood damage, from a single extreme rainfall event. We employed a fully physical-based, distributed hydrological model run with HEC–HMS software version 4.11 and Integrated Multi-satellite Retrievals of Global Precipitation Measurement (IMERG V.06) data, as well as other geo-environmental variables, to simulate the water flow within the Wadi Basin, and predict flash flood hazard. Discharge from the wadi and its sub-basins was predicted using 1 mm rainfall over an 8-h occurrence time. Significant peak discharge (3.6 m3/s) was found in eastern and southern upstream sub-basins and crossing points, rather than those downstream, due to their high-density drainage network (0.12) and CNs (88.4). Generally, four flood hazard levels were identified in the study basin: ‘low risk’, ‘moderate risk’, ‘high risk’, and ‘very high risk’. It was found that 43.8% of the total area of the Wadi Hail Basin is highly prone to flooding. Furthermore, medium- and low-hazard areas make up 4.5–11.2% of the total area, respectively. We found that the peak discharge value of sub-basin 11 (1.8 m3/s) covers 13.2% of the total Wadi Hail area; so, it poses more flood risk than other Wadi Hail sub-basins. The obtained results demonstrated the usefulness of the methods used to develop useful hydrological information in a region lacking ungagged data. This study will play a useful role in identifying the impact of extreme rainfall events on locations that may be susceptible to flash flooding, which will help authorities to develop flood management strategies, particularly in response to extreme events. The study results have potential and valuable policy implications for planners and decision-makers regarding infrastructural development and ensuring environmental stability. The study recommends further research to understand how flash flood hazards correlate with changes at different land use/cover (LULC) classes. This could refine flash flood hazards results and maximize its effectiveness.

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Section: Flood Hydrographs and Peak Runoffsupporting

confidence: 63%

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

Section: Hydrologic Simulation Modelmentioning

confidence: 99%

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Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

Salih,

Hassablla

2024

Atmosphere

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“…Climatic trends are reflected in the hydrology of the Nile, which shows high levels of variability in the river flow records [90] and variations in peak discharge [91]. For instance, the increasing trend in the natural water storage variation of the Nile can be detected in northern Sudan [92].…”

Section: Study Areamentioning

confidence: 99%

Multispectral Satellite Image Analysis for Computing Vegetation Indices by R in the Khartoum Region of Sudan, Northeast Africa

Lemenkova

Debeir

2023

J. Imaging

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Desertification is one of the most destructive climate-related issues in the Sudan–Sahel region of Africa. As the assessment of desertification is possible by satellite image analysis using vegetation indices (VIs), this study reports on the technical advantages and capabilities of scripting the ‘raster’ and ‘terra’ R-language packages for computing the VIs. The test area which was considered includes the region of the confluence between the Blue and White Niles in Khartoum, southern Sudan, northeast Africa and the Landsat 8–9 OLI/TIRS images taken for the years 2013, 2018 and 2022, which were chosen as test datasets. The VIs used here are robust indicators of plant greenness, and combined with vegetation coverage, are essential parameters for environmental analytics. Five VIs were calculated to compare both the status and dynamics of vegetation through the differences between the images collected within the nine-year span. Using scripts for computing and visualising the VIs over Sudan demonstrates previously unreported patterns of vegetation to reveal climate–vegetation relationships. The ability of the R packages ‘raster’ and ‘terra’ to process spatial data was enhanced through scripting to automate image analysis and mapping, and choosing Sudan for the case study enables us to present new perspectives for image processing.

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Comparative study of flash flood in ungauged watershed with special emphasizing on rough set theory for handling the missing hydrological values

et al. 2021

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Use of NRCS-curve number method for peak discharge estimation in Sharqu ElNeil locality, Khartoum, Sudan

Cited by 4 publications

References 12 publications

Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

Flash Flood Risk Assessment in the Asir Region, Southwestern Saudi Arabia, Using a Physically-Based Distributed Hydrological Model and GPM IMERG Satellite Rainfall Data

Multispectral Satellite Image Analysis for Computing Vegetation Indices by R in the Khartoum Region of Sudan, Northeast Africa

Comparative study of flash flood in ungauged watershed with special emphasizing on rough set theory for handling the missing hydrological values

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