Curve Number Method Research Articles

Assessing climate change threats and urbanization impacts on surface runoff in Gdańsk (Poland): insights from remote sensing, machine learning and hydrological modeling

AbstractThis study investigates the impacts of Land Use/Land Cover (LULC) changes and climate change on surface runoff in Gdańsk, Poland, which is crucial for local LULC planning and urban flood risk management. The analysis employs two primary methodologies: remote sensing and hydrological modeling. Remote sensing was conducted using Google Earth Engine and Land Change Modeler in IDRISI Terrset software to analyze historical (1985–2022) and future (2050–2100) LULC. Hydrological modeling was performed using the Natural Resources Conservation Service curve number method to assess the overall impact of LULC changes on Gdańsk’s hydrology at the local scale. The Orunia basin, a critical area due to intensive LULC development, was selected for detailed hydrological analysis using the Hydrologic Modeling System (HEC-HMS). The analysis encompassed three scenarios: LULC changes, climate change, and combined LULC and climate change effects. The LULC analysis revealed a marked increase in urban area, a shift in forest and vegetation cover, and a reduction in agricultural land. HEC-HMS simulations showed an increase in the runoff coefficient across selected decades, which was attributed to the combined effect of LULC and climate change. The projected increases under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios for 2050 and 2100 are projected to surpass those observed during the baseline period. The findings highlight that the synergistic effects of LULC and climate change have a more significant impact on Gdańsk’s hydrology at both local and basin scales than their separate effects. These insights into LULC shifts and urban hydrological responses hold implications for sustainable urban planning and effective flood risk management in Gdańsk and similar urban settings.

Application of the NRCS-curve number method in humid tropical basins of southeastern Nigeria: a statistical analysis

In the south-eastern region of Nigeria, the application of rainfall (P) and runoff (Q) data directly into the Natural Resources Conservation Service Curve Number (NRCS-CN) method hasn’t been thoroughly studied. This research aimed to determine representative values of the initial abstraction ratio (λ) and corresponding curve number (CN), fit the P and Q data using theoretical probability distributions, and establish confidence intervals for CN. The least squares minimization method and Kolmogorov-Smirnov test were employed on data from 129 sub-basins across 4 major basins. Findings revealed optimal initial abstraction ratio (λopt) = 0.24 and optimal CN (CNopt) = 80, with rainfall best fitted by Gamma, runoff by Weibull, and CN by Normal distributions. However, the study was limited to the available 8-year record period with 96 storm events. The 96 storm events over an 8-year period may seem limited for a humid tropical region, the available data were the most comprehensive and reliable dataset for this study area. Additional data collection over a longer time frame could enhance future studies. The localized CN value and associated confidence intervals can enhance runoff prediction accuracy for flood mitigation and water resources management in this humid tropical region, though further validation is recommended.

A Critical Review of the Soil Conservation Services – Curve Number Method in Hydrological Modelling

A Critical Review of the Soil Conservation Services – Curve Number Method in Hydrological Modelling

Runoff Dynamics and Soil Erosion Assessment using a SWAT Model at Upper Cauvery River Basin

The increasing availability of geospatial datasets on watershed characteristics and hydro-meteorological variables emphasises the importance of integrated hydrological models for effective catchment management. Climatic and physiographic determinants such as topography, land use, soil properties, and anthropogenic interventions substantially influence a catchment's hydrological equilibrium. The SWAT model was used to elucidate rainfall-runoff dynamics in the Upper Cauvery River Basin, Karnataka, India (36,682 km²), applying the SCS Curve Number (CN) method for runoff estimation. Runoff was estimated for 2012–2021 using rainfall data from the Indian Meteorological Department (IMD), soil data from the FAO, and land use/land cover and slope datasets.Soil erosion, exacerbated by intensified agricultural practices, was evaluated using the Revised Universal Soil Loss Equation (RUSLE) model integrated with Geographic Information Systems (GIS). The SWAT model results showed that runoff accounted for 15-20% of the total precipitation, with an annual soil loss of 2027.95 tons. The predominance of agricultural land use, covering 66.29% of the basin, significantly contributed to high runoff, whereas the forested areas (26.48%) demonstrated a low runoff potential. About 38% of the basin exhibited a very low soil loss risk, while 11% was classified as high risk and 9% as very high risk. The SWAT model is recognized for its robustness, and this research aims to leverage its capabilities to validate its effectiveness in estimating runoff and erosion, providing crucial insights for advancing sustainable catchment resource management.

EVALUACIÓN DEL IMPACTO DE LOS CAMBIOS EN EL USO Y COBERTURA DE LA TIERRA EN EL ESCURRIMIENTO SUPERFICIAL

The aim of this study was to analyze the behavior of surface runoff as a result of changes in land use and land cover (LULC), using the Rio Novo basin (Brazil) as the analysis site. To estimate surface runoff, the curve number (NRCS-CN) method was used; as input data, the LULC classifications provided by the MapBiomas project and the pedological map of the state of São Paulo (1:250,000) were used. The Rio Novo basin was discretized into ten sub-basins. The results showed major changes in LULC between 1992 and 2022, with a reduction in pasture areas and an increase in annual crops and sugarcane fields, as well as in urban areas. Such alterations are conditioning factors of changes in Curve Number (CN) values, which imply changes in surface runoff values. For a rainfall of 130 mm (roughly 10-year return period), the surface runoff depth values ranged from 3.21 mm (areas with forest cover on soils in hydrological group A) to 101.35 mm (for urban areas on soils in hydrological group C). The urbanization process that occurred in sub-basins 1, 6, and 9 led to an increase in areas with the highest CN values (CN equal to 85 and 90). Locations with increased surface runoff values should be considered as critical areas, where soil and water losses may occur, thereby compromising water security in the basin. Keywords: NRSC-CN method, Geographic Information System, Water Resources Management, MapBiomas.

Runoff Estimation in Kajurli Watershed Using SCS-CN and GIS Techniques

The study focuses on estimating surface runoff using the Soil Conservation Service Curve Number (SCS-CN) method, combined with Remote Sensing (RS) and Geographic Information System (GIS) techniques, for the Kajurli Watershed in Ratnagiri District, Maharashtra. Surface runoff is a key factor influencing agricultural productivity, soil erosion, and water management at the watershed level. The SCS-CN method, a widely used tool for runoff estimation, utilizes rainfall, land use, and soil type data. By integrating RS and GIS, the study achieves a more accurate assessment of land use and soil characteristics, which are critical inputs for runoff calculations. The Kajurli Watershed falls under hydrological soil group B, known for moderate runoff potential. The study uses 33 years of historical rainfall data (1990-2022) to compute annual runoff using the SCS-CN method. Key parameters such as Curve Numbers (CN) are derived based on land use, hydrological soil groups, and antecedent moisture conditions (AMC). The average annual rainfall in the watershed is found to be 3392.8 mm, with 39.69% of this rainfall contributing to surface runoff. The integration of RS and GIS simplifies spatial analysis, enabling accurate and efficient runoff estimation. The study highlights the sensitivity of the SCS-CN method to CN values, emphasizing the importance of precise land use and soil data for reliable hydrological modelling. These findings offer crucial insights for water resource management, flood control, and agricultural planning in the region.

Applying Low-Impact Development Techniques for Improved Water Management in Urban Areas

Worldwide, the increase in impervious surfaces due to urbanization has led to significant water cycle issues such as groundwater depletion, urban heat islands, and flooding. To address these challenges, Low-Impact Development (LID) techniques are increasingly being applied in stormwater management. This study focuses on Ulsan, designated as a water cycle model city in South Korea, with a particular emphasis on the highly urbanized Okgyo drainage watershed. Using the Stormwater Management Model (SWMM) version 5.1, long-term runoff simulations were conducted to evaluate the effects of LID implementation on water cycle change rates and recovery rates. The model incorporates detailed hydrological and hydraulic parameters, including inflow, runoff, infiltration, and evapotranspiration for six subcatchments within the watershed. The SWMM was calibrated and validated using 30 years of historical rainfall data (1987–2016) from the Ulsan weather station. Calibration and validation processes used the NRCS-CN (Curve Number) method to ensure accuracy in simulating runoff patterns and water balance. The study specifically evaluated the effectiveness of two LID techniques: bioretention and permeable pavements. Three scenarios were modeled: bioretention applied to 5% of the area, permeable pavements applied to 5% of the area, and a combined application of both techniques. The results showed that the combined scenario provided the best outcome, with a 7.80% reduction in surface runoff and a 14.56% improvement in water cycle health. The LID application scenario confirmed the potential to achieve the water cycle management target of handling 25.5 mm of rainfall. These findings demonstrate that the introduction of LID techniques in public spaces can significantly enhance water management. This research provides insights into effective water cycle management methods tailored to specific urban land uses, laying a foundation for future urban planning and sustainable development.

Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia

Abstract Rainfall–runoff modeling is essential for the hydrological analysis of basins; however, the traditional modeling approach does not incorporate geological features such as fractures and fissures in the modeling task. These features are significant in the water loss during a rainstorm, which should be incorporated to obtain realistic rainfall–runoff results. A novel approach is presented here in to quantify the geological features and link them to the curve number (CN) method. The proposed methodology has not been applied in the literature. This approach is validated on five gauged basins, namely, Yiba, Al Lith, Liyya, Habawnah, and Tabalah, in the southwest part of Saudi Arabia. Four major stages are conducted. The first stage is the extraction of the geological lineaments using remote sensing and geographical information system technology; the second stage is estimating CN from rainfall–runoff data; the third stage is developing a relationship between CN and lineament density (LD); and the final stage is evaluating the developed equations on hydrological response. The least-squares method is employed to minimize the difference between observed and predicted runoff and determine the optimum range of CN. The research provides a comprehensive understanding of hydrological processes in fractured geologic systems and explores the influence of fractures on curve number. This study identifies two major lineament trends aligned with the Arabian trend direction, namely, north-northwest (NNW)–south-southeast (SSE) and north-northeast (NNE)–south-southwest (SSW). Furthermore, a moderate inverse correlation is established between LD and CN, highlighting the significance of geologic fractures on the hydrological response. The findings of this study provide insight into how the geological fissures in the mountainous region affected the rainfall–runoff response that leads to a low value of CN due to the water loss in the fissures and faults. As a result, this study clearly demonstrates the importance of the geological structures on rainfall–runoff responses.

Application of the Modified Universal Soil Loss Equation (MUSLE) for the prediction of sediment yield in Agewmariam experimental watershed, Tekeze River basin, Northern Ethiopia

The study utilized the Modified Universal Soil Loss Equation (MUSLE) to predict sediment loss and evaluate the model's performance in the Agewmariam experimental watershed in order to support the planning, management, and appropriate use of the soil and water resources in the watershed. The natural resources conservation service (NRCS) curve number method was used to model runoff energy factor. By overlaying maps of runoff energy, soil erodibility, slope length and steepness, cover management, and support practice factors with assigned values, the cumulative effect of these parameters for the suspended sediment yield was calculated using the ArcGIS raster calculator. The runoff energy factor was the most sensitive parameter, followed by slope length and steepness factor. To improve the model's fit to the local conditions, the initial abstraction to storage ratio (λ) of the runoff energy factor was reduced to 0.023, and the MUSLE model coefficient and exponent were adjusted to 1 and 0.59, respectively. During calibration, the mean observed and estimated suspended sediment yields were 0.2 and 0.23 ton/ha, respectively, while during validation, they were 0.7 and 0.53 ton/ha, respectively. The model evaluation showed that the MUSLE model, without calibration, was not appropriate for estimating runoff and sediment yield. However, with appropriate calibration, the model showed good performance with a coefficient of determination (R2), coefficient of efficiency (E), and index of agreement (d) of 0.85, 0.85, and 0.96 respectively, during calibration and 0.84, 0.65, and 0.83 respectively, during validation. Based on these findings, this study suggests that the calibrated MUSLE model can be used to prioritize soil and water conservation interventions within the watershed or can be extrapolated to neighboring similar watersheds. Further refinement of model input parameters using more data from the watershed is recommended to increase the prediction accuracy of the model.

Temporal land-use change of a reclaimed land in greater Dhaka and its impact on natural water cycle

This study aims to explore the land-use induced impact on runoff and recharge of an impending urban growth on reclaimed land filled with sands in greater Dhaka to concede the low impact development through practicable methods. Having analyzed the temporal land-use change by Curve Number (CN), GIS-based Soil Conservation Service - Curve Number (SCS-CN) method has been used to evaluate the runoff of the study area. Initial land-use in 2010 with a higher CN 86 resulted in a lower CN 72 in 2020-2022 due to land-use change (pre-developed/existing condition) with permeable soil for urban development. However, the gradual land-use change resulted in more imperviousness and an increasing trend in CN. With ultimate CN 84, approximately 243% more runoff was predicted during complete urbanization in 2040 and beyond as opposed to CN 72 in 2020-2022. Due to the existing higher groundwater table of the area, the Water Table Fluctuation (WTF) method has been used to find the natural recharge potential. As higher CN results in more runoff and recharge loss, ultimate natural recharge potential with CN 84 declines to more than 50% of the pre-developed condition. Results from the methods suggested a comprehensive hydrological forecasting due to land-use change on reclaimed land with assorted options for natural water cycle balance.

The Study of Levee Flood Control at Pengkol River - Meteseh, Tembalang Sub District - Semarang City

The Pengkol River, situated in Meteseh, Tembalang sub-district of Semarang City, underwent three significant flood occurrences from January to February 2023. An approach involving a structural flood control system, specifically a levee, was suggested as a solution to this issue. The objective of this research is to establish the arrangement and highest elevation of the levee flood control and evaluate its effectiveness in mitigating floods. To determine flood hydrographs, a hydrological analysis was carried out using the Rainfall-Runoff simulation with the SCS Curve Number method. Additionally, a hydraulic analysis was performed using Unsteady Flow simulation with HECRAS 1D/2D hydrodynamic models to define the river body, water profile, inundation, and levee design. The hydrologic analysis indicates that the flood discharge for the 50, 100, and 200-year return periods are 209.5 m³/sec, 225.1 m³/sec, and 240.6 m³/sec, respectively. Based on the hydraulic analysis, the maximum water levels resulting from these return periods' flood discharges are +35.62 m (Q50 years), +35.77 m (Q100 years), and +36.43 m (Q200 years). The Q200 years of return period was chosen for 2D modeling because it resembles documented flood occurrences. Using the HECRAS 2D Unsteady Flow model, it was found that before the levee implementation, the flooded area within the residential zone spanned 9462 m², with a peak water level of +37.3 m. With the levee application, using an existing layout with a total length of 230 m and a top levee level of +37.5 m, flooding was effectively prevented, reducing the maximum water surface elevation to +37.17 m. This demonstrates the levee's effectiveness in preventing floods.Keywords: levee, flood, HECRAS 1D 2D model, inundation. Unsteady flow.

An artificial neural network and SCS–CN-based model for runoff estimation: a case study of the Peddavagu watershed

ABSTRACT The accurate prediction of runoff from rainfall events is crucial for effective water resource management, especially in regions with diverse climatic patterns like India. This study proposes a novel approach by integrating the soil conservation service (SCS)–curve number (CN) method with artificial neural networks (ANNs) to model rainfall–runoff relationships. In this research, an SCS–CN method is utilized to estimate initial runoff volumes, accounting for local soil and land-cover characteristics. Subsequently, an ANN-based model is developed to capture the complex nonlinear relationships between rainfall inputs and runoff outputs. Taking the rainfall of the watershed as the inputs, an ANN model was developed in MATLAB for runoff simulation at the main outlet of the Peddavagu watershed. A feed-forward back-propagation method is employed in the ANN model. The architecture with a 1-10-1 configuration based on tan–sig transfer function performed well in terms of MSE 0.019. The model efficiency was satisfactory with the coefficient of correlation (R), 0.96 for training, 0.98 for validation, and 0.98 for testing period. The overall value of R (0.96) indicates the utility of this ANN–SCS-based coupled model for rainfall–runoff simulation.

Assessing the Impact of Modified Initial Abstraction Ratios and Slope Adjusted Curve Number on Runoff Prediction in the Watersheds of Sulaimani Province.

A popular way for describing the link between storm rainfall depth and direct runoff is the curve number (CN) method. It is a straightforward approach that has been extensively studied and widely adopted. However, there has been less focus on the impact of slope and the initial abstraction ratio, which is a crucial factor for accurately estimating direct runoff when utilizing the soil conservation service- Curve Number (SCS-CN) method. The initial abstraction ratio is typically assumed to be 0.20, as initially proposed by the method's developers. In this study, we analyzed daily rainfall data from seventeen watersheds in different physiographic locations in the Kurdistan region of Iraq, recorded between 2022 and 2023. Our aim was to assess the effect of slope adjusted curve number and modified the initial abstraction ratio (0.1) on estimation of direct runoff. The results demonstrated that adjusting the CN for slope and using a modified initial abstraction ratio increased the estimated runoff compared to the original method (without adjustment for slope and initial abstraction ratio=0.2). Therefore, when applying the SCS-CN method, it is crucial to correct the CN for slope in steeper areas and consider the initial abstraction ratio rather than relying on the suggested value of 0.2. this study highlights the importance of considering local conditions and estimating the initial abstraction ratio based on specific watershed characteristics to enhance the accuracy of direct runoff estimation using the CN method.

Cost-Benefit Analysis of Minor Irrigation Tank Rehabilitation Using Run-Off and Storage Capacity: A Case Study from Ambuliyar Sub-Basin, Tamil Nadu, India

This research examines the significance of restoring efficient water management systems in India’s semiarid environment, with special emphasis on the role of traditional irrigation structures, such as tanks, in collecting and storing limited water resources. Assessing the benefits of any restoration program, especially when socioeconomic and environmental benefits are involved, is challenging. In the context of tank rehabilitation, a cost-benefit analysis will be conducted regarding economic and ecological returns in the post-desiltation phase. Since the restoration process requires a significant investment, assessing the project’s viability during the planning stage is better. The present study proposes a novel method to indirectly analyse the cost-benefit of the tank restoration process by correlating run-off and storage capacity of tanks before the planning phase. The Ambuliyar sub-basin, which covers an area of 930 square kilometres in Tamil Nadu, India, comprising 181 tanks (water bodies) of varying sizes and shapes, was taken for this study. This study employed the Soil Conservation Service Curve Number (SCS-CN) method, incorporating factors such as soil type, land cover, land use practices, and advanced remote sensing and Geographic Information System (GIS) tools to simulate surface run-off. Run-off volume and tank capacity were compared for all seasons at the micro-watershed level. The results demonstrated that the run-off volume in each micro-watershed significantly exceeded the tank capacity across all seasons. Even during the summer, the run-off volumes in the micro-watershed were considerably higher than the tank capacity. The findings suggest tank restoration can effectively store run-off and significantly fulfil agricultural and other essential needs throughout the year, thereby improving the local rural economy. This study also highlights the need for periodic maintenance and rehabilitation of these tank systems to retain their functionality.

Application of GIS & RS in Rainwater Harvesting for an Arid Region

In dry areas with variable rainfall, water shortages severely affect the livelihoods of local populations. Rainwater harvesting from land sites and roof-tops is a readily available solution to this problem. This study presents a GIS & RS-based methodology to identify potential land sites and roof-top rainwater harvesting potential using easily obtainable and freely available data. Slope, land cover, soil, and drainage maps were used to identify suitable rainwater harvesting land sites, which were further analyzed for surface runoff using the curve number method. This research also incorporated obtainable socio-economic factors in identifying the suitable locations of dams considering the implementation stage. Based on the proposed criteria, 44 suitable locations for dams were identified and validated using a validation map and Google Earth images. CROPWAT model analysis revealed that paddy water demand in Batticaloa would increase threefold if all available land for paddy cultivation was utilized. Therefore, abandoned lands can be utilized by erecting dams at those identified locations. Analysis of Google Earth images also revealed that roof rainwater harvesting would be sufficient to meet the basic water demand in the area. This study demonstrates that rainwater harvesting can be an effective strategy for addressing water scarcity in dry areas.

Comparison of two hydrodynamic models for their rain-on-grid technique to simulate flash floods in steep catchment

In this study, two hydrodynamic models, TELEMAC-2D and HEC-RAS 2D, were compared for their Rain-on-Grid (RoG) technique with a particular focus on runoff generation processes in a small and steep catchment. Curve number (CN) method was applied in both the models to simulate two single storm events up to 20 h of duration, whereas the Green-Ampt Redistribution (GAR) method was additionally applied in HEC-RAS 2D for a multi-peak flood event with sustained flow between the peaks. CN and GAR methods were compared for this flood event, and a sensitivity analysis of the GAR parameters was also done. Moreover, the two models were compared for their calibration process, computational time, mesh size and shape, and model availability, in general, as well as the results including inundated areas, water depth, and velocity. The results indicate that both the models are capable of reproducing short duration single storm floods. NSE and R2 for both models ranged from 0.70 to 0.90 and from 0.93 to 0.95. However, the models struggled to reproduce the long- duration multi-peak flood event. The sensitivity analysis showed that the results are not very sensitive to the two GAR parameters which are responsible to influence the flow of the second peak in the flood event. Neither the CN nor the GAR infiltration method successfully replicated such events because the hydraulic models permanently lose infiltrated water from the domain. The returned sub-surface flow significantly contributes to river flow during these flood events; however, none of the model incorporates a return flow algorithm.

Prediction of Peak Discharge Using the SCS Curve Number Method in the Manikin Watershed

Surface runoff is a crucial hydrological variable in the analysis of water infrastructure planning. A reliable method for predicting surface runoff resulting from rainfall in an ungauged watershed is the SCS CN method. This research aims to represent the effectiveness of the Curve Number (CN) method in calculating peak discharge in the Manikin Watershed. The data used for this analysis includes rainfall data from three rain stations, each with a 25-year dataset, water level data of 11 years, digital elevation model (DEM) data, land use maps, and hydrogeological maps. The SCS curve number method is the most commonly used method for the estimation of peak discharge in a watershed. The calculated flood discharge values for the Manikin River Basin, with return periods of 5, 10, 20, 25, 50, 100, 500, and 1000 years, are as follows: 60.32 m3/s, 84.74 m3/s, 111.98 m3/s, 121.41 m3/s, 153.25 m3/s, 188.79 m3/s, 287.24 m3/s, and 337.30 m3/s, respectively. The reliability testing of the method in the Manikin Watershed was determined by a Nash–Sutcliffe efficiencies (NSE) value of 0.93 and root mean square error (RMSE) value of 19.70. As a result, the Curve Number Method proves to be highly reliable in representing the peak discharge in the Manikin Watershed.

High-resolution Annual Dynamic dataset of Curve Number from 2008 to 2021 over Conterminous United States

The spatial distribution and data quality of curve number (CN) values determine the performance of hydrological estimations. However, existing CN datasets are constrained by universal-applicability hypothesis, medium resolution, and imbalance between specificity CN tables to generalized land use/land cover (LULC) maps, which hinder their applicability and predictive accuracy. A new annual CN dataset named CUSCN30, featuring an enhanced resolution of 30 meters and accounting for temporal variations in climate and LULC in the continental United States (CONUS) between 2008 and 2021, was developed in this study. CUSCN30 demonstrated good performance in surface runoff estimation using CN method when compared to observed surface runoff for the selected watersheds. Compared with existing CN datasets, CUSCN30 exhibits the highest accuracy in runoff estimation for both normal and extreme rainfall events. In addition, CUSCN30, with its high spatial resolution, better captures the spatial heterogeneity of watersheds. This developed CN dataset can be used as input for hydrological models or machine learning algorithms to simulate rainfall-runoff across multiple spatiotemporal scales.

Energy potential assessment and techno–economic analysis of micro hydro–photovoltaic hybrid system in Goda Warke village, Ethiopia

Abstract Rural Ethiopia has significant untapped potential for hydro and solar energy generation systems. However, challenges arise from seasonal variations and unfavourable topographic positions of flowing rivers, hindering the efficient exploitation of these resources. Despite the country’s abundance in hydro and solar energy resources, >75% of the population still lack access to electricity from the national grid. This work deals with energy resource potential assessment and techno–economic analysis of micro hydro–photovoltaic (PV) hybrid systems, considered in the case study of Goda Warke village, located in the Yaya Gulele district. A novel framework is proposed that utilizes the Natural Resource Soil Conservation Service curve number method to assess the energy potential of micro-hydro energy in ungauged basins, specifically at the exit point of the Girar River basin catchment. The average monthly flow rate in the basin is 0.975 m3/s, while the area exhibits a solar radiation potential of 5.39 kWh/m2/day. Energy policy promotes expanding access to modern energy sources and utilization of indigenous energy resources. Simulation results indicate that the hydro/PV/diesel generator (DG)/battery and hydro/PV/battery systems are the most optimal choices based on net present cost, with the inclusion of a DG for economic comparison. Micro-hydro energy covers most of the electric load in the area, achieving a capacity factor of 47.5%. The cost of energy and net present cost were found to be sensitive to variables such as the price of diesel fuel, pipe head loss, and the growth of the village load. The optimized system demonstrated a hydro energy potential of 1405.37 MWh/year and a PV energy output of 274.04 MWh/year, resulting in a levelized cost of energy of 0.0057 and 0.049 $/kWh for the hydro and PV components, respectively.

Integrated Hydrological Modeling for Watershed Analysis, Flood Prediction, and Mitigation Using Meteorological and Morphometric Data, SCS-CN, HEC-HMS/RAS, and QGIS

Flooding is a natural disaster with extensive impacts. Desert regions face altered flooding patterns owing to climate change, water scarcity, regulations, and rising water demands. This study assessed and predicted flash flood hazards by calculating discharge volume, peak flow, flood depth, and velocity using the Hydrologic Engineering Centre-River Analysis System and Hydrologic Modelling System (HEC-HMS and HEC-RAS) software. We employed meteorological and morphological data analyses, incorporating the soil conservation service (SCS) curve number method for precipitation losses and the SCS-Hydrograph for runoff transformation. The model was applied to two drainage basins (An-Nawayah and Al-Rashrash) in southeastern Cairo, Egypt, which recently encountered several destructive floods. The applied model revealed that 25-, 50-, and 100-year storms produced runoff volumes of 2461.8 × 103, 4299.6 × 103, and 5204.5 × 103 m3 for An-Nawayah and 6212 × 103, 8129.4 × 103, and 10,330.6 × 103 m3 for Al-Rashrash, respectively. Flood risk levels, categorised as high (35.6%), extreme (21.9%), and medium (21.12%) were assessed in low- and very-low-hazard areas. The study highlighted that the areas closer to the Nile River mouth faced greater flood impacts from torrential rain. Our findings demonstrate the effectiveness of these methods in assessing and predicting flood risk. As a mitigation measure, this study recommends the construction of five 10 m high dams to create storage lakes. This integrated approach can be applied to flood risk assessment and mitigation in comparable regions.