Soil Conservation Service Curve Number Research Articles

Towards evaluating the conditional probability of waterborne microbial risks associated with critical rainfall events following land application of animal waste — A focus on Irish pastures

ABSTRACT Modelling surface runoff and infiltration in an agricultural watershed is essential for understanding the nutrient cycle and water quality management. This research evaluates the critical rainfall events causing maximum surface runoff and infiltration. Empirical models such as Soil Conservation Service (SCS) curve number and Explicit Green-Ampt (EGA) were analysed for different soil hydraulic conditions and storm events with specific return periods. The present study forecasted the maximum daily rainfall and intensity as 113.6 mm and 19.9 cm h–1, respectively, considering a 100-year return period storm. The deterministic part of the model calculates the daily maximum surface runoff as 5.51 cm (from the SCS model). The EGA model revealed that the rainfall intensity of 0.143, 0.163, 0.175, 0.179, 0.181, 0.182, and 0.182 cm h−1 (duration of 24 h) was found critical for 1, 2, 5, 10, 25, 50, 100 year return period of the storm, respectively in different soil texture classes (sand, loamy sand, sandy loam, loam, silt loam, sandy clay loam, clay loam, silty clay soils). Exceptions imply for three occasions where the intensity of 0.407 cm h−1 and duration of 18 h produced maximum infiltration for silty clay loam, and intensity of 0.352 and 0.354 cm h−1 with 9 h rainfall (each) produced maximum infiltration for clay. The probabilistic model revealed that a daily storm event probability of 2.74 × 10–5 is associated with a simulated mean runoff depth of 0.69 cm and infiltration of 20.7 cm. Critical rainfall probabilities calculated in this study can be multiplied with the overall microbial/pollutant human health risk assessment framework to calculate conditional probability and better estimate microbial risk through the drinking water pathway. This study is very relevant for the wet climatic condition of Ireland, where most land use is pastures.

Sensitivity analysis on stormwater management response to land cover dynamics and urban expansion of developing City in Lake Hawassa watershed, Ethiopia

AbstractHawassa is a rapidly developing city in Lake Hawassa watershed of Ethiopia. Analyzing the effect of land cover dynamics on surface runoff remains imperative to adaptive urban stormwater management. This study quantified spatial variation of land cover and sensitivity of stormwater management response. Historical 30 years of daily annual rainfall, three satellite imageries, DEM, and hydrological soil group data were analyzed. A statistical‐based combined approach of geospatial techniques and Soil Conservation Service‐Curve Number (SCS‐CN) model was employed. CN and surface runoff depth for the delineated urban watersheds were determined. The result revealed that the built‐up area increased by 30.9 km2, where the rate varies spatially. The variation of impervious land cover explains 58.6% of change in CN with coefficient of 0.352. While CN is inversely correlated with agricultural and vegetation land cover variations. The finding suggests CN explains 96.78% of the change in surface runoff with a significant correlation coefficient of 3.91. The proposed integrated model approach justifies the potential to reorganize the relationship between the spatial effect of land cover variation on surface runoff at the urban watersheds. Thus, suitable local‐specific solutions can be devised for effective management of flood risk and optimize the drainage system of urban areas.

Utilization of streamflow rates for determination of precipitation thresholds for landslides in a data-scarce region (Eastern Bartın, NW Türkiye)

One of the Türkiye’s most destructive natural hazards is landslides. Although much progress has been achieved in this subject throughout the country, there are still some problems related to adequate meteorological and high-quality landslide data. The aim of this study, which was carried out in the eastern part of Bartın province in the Western Black Sea region of Türkiye, is to indirectly determine the possible threshold values for landslides known to be triggered by precipitation. For this purpose, first, data related to landslides, precipitation, and streamflow were compiled and analyzed. Although many landslides have been mapped in the area, it has been determined that the number of reliable data on the dates (only three exact dates) of landslide occurrences is quite limited in the area. The relationship between the landslides that occurred in 1985, 1998, and 2021, and the stream gauging–precipitation data was analyzed. Then, due to the data scarcity related to the precipitation data, an indirect method, called Soil Conservation Service Curve Number (SCS-CN), was used to determine the relation between runoff and precipitation. The results revealed that daily 80 mm and cumulative 160 mm could be selected as the threshold values that may trigger the landslides. This study serves as an illustration of how an indirect approach can be used to approximate potential precipitation thresholds in a data-scarce region. Therefore, it will be possible to use these precipitation thresholds as a basis for future landslide hazard and risk assessments.

Quantifying water loss in leaky micro-dam reservoir through water balance analysis and high-resolution water level data modeling

Abstract This study aimed to assess the runoff, recharge, and response of a shallow aquifer to leakage from the Arato micro-dam reservoir (MDR). The assessment was conducted using the Soil Conservation Service Curve Number (SCS-CN), soil moisture balance (SMB), and diver (automatic data logger) measurements in both the MDR and a shallow hand-dug well. Recharge was estimated using the chloride mass balance (CMB) and water table fluctuation (WTF) methods. The results revealed that the annual runoff from the catchment was 48.8 mm, which accounted for approximately 0.71 million m3. The yearly groundwater recharge was estimated to be 104, 92.8, and 100 mm using the SMB, CMB, and WTF methods, respectively. Furthermore, the water balance model of the Arato MDR indicated a leakage rate of 13.2 mm/day. It is noteworthy that the estimated leakage exceeded the seepage initially anticipated during the project's design phase (9,965 m3/year). This research project highlights the significance of utilizing local climatic and physical data from the specific watershed under investigation when planning reservoirs and other water resources. It also underscores the importance of conducting thorough site investigations to accurately quantify hydraulic conductivity for leakage estimation purposes.

Coupled and collaborative optimization model of impervious surfaces and drainage systems from the flooding mitigation perspective for urban renewal

Urban pluvial flooding mitigation is a significant challenge in city development. Many mature methods have been used to reduce the risk of flood. The optimal design of impervious surfaces (ODIS) is an adaptive solution to urban flooding from the perspective of urban renewal planning. However, existing ODIS models are limited because they do not consider the drainage systems. To address this issue, this study proposes an elastic and controllable optimization model based on assumptions about rainstorm and drainage capacity, nondominated sorting genetic algorithm-II (NSGA-II), multivariate linear programming (MLP) and soil conservation service curve number model (SCS-CN) in a case study of the old town of Guangzhou city, China. The model not only coupled the drainage systems, but also collaboratively optimized the impervious surfaces and the drainage systems. The results show that the proposed model achieved an optimized efficiency of 5.70 %, which is more than a tenfold improvement compared to existing ODIS models. The study emphasizes that the optimization of the drainage system should be the focus and the optimization of impervious surfaces should be supplementary, and different flood risk areas require different optimization strategies. Furthermore, transforming impervious surfaces into a “high-low-high” spatial distribution of impervious surface densities is the optimal design solution for impervious surfaces. In general, this study offers a novel perspective and approach to urban flooding mitigation, enabling comprehensive control of flooding from a global perspective.

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.

Predicting the peak flow and assessing the hydrologic hazard of the Kessem Dam, Ethiopia using machine learning and risk management centre-reservoir frequency analysis software

Abstract Flooding due to overtopping during peak flow in embankment dams primarily causes dam failure. The Kessem River watershed of the Awash basin in the Rift Valley of the Afar region in Ethiopia was studied intricately to predict the causes of the Kessem Dam safety using machine learning predictive models and risk management centre-reservoir frequency analysis. Recently developed recurrent neural network predictive models with hybrid Soil Conservation Service Curve Number (SCS-CN) were used for simulation of river flow. Peak daily inflow to the reservoir is predicted to be 467.72, 435.88, and 513.55 m3/s in 2035, 2061, and 2090, respectively. The hydrologic hazard analysis results show 2,823.57 m3/s and 935.21 m; 2,126.3 m3/s and 934.18 m; and 11,491.1 m3/s and 942.11 m peak discharge and maximum reservoir water level during the periods of 2022–2050, 2051–2075, and 2076–2100, respectively, for 0.0001 annual exceedance probability. The Kessem Dam may potentially be overtopped by a flood with a return period of about 10,000 years during the period of 2076–2100. Quantitative hydrologic risk assessment of the dam is used for dam safety evaluation to decide whether the existing structure provides an adequate level of safety, and if not, what modifications are necessary to improve the dam's safety.

An optimization model for the impervious surface spatial layout considering differences in hydrological unit conditions for urban waterlogging prevention in urban renewal

The expansion of impervious surfaces during urbanization, as well as the irrationality of their spatial layout, is one of the main causes of urban waterlogging. Optimizing the spatial layout of impervious surfaces through urban renewal is important for urban waterlogging prevention. The differences in hydrological conditions among different hydrological units affect the optimization efficiency of the spatial layout of impervious surfaces in different hydrological units. Therefore, this study proposes an effective optimization model for impervious surface spatial layout, employing a hybrid approach that couples the Soil Conservation Service Curve Number (SCS-CN) model, nondominated sorting genetic algorithm 2 (NSGA2), and multiple linear programming (MLP) algorithm. This approach is applied in a case study of Guangzhou, China. The results show that (1) compared to the MLP-SCS model, the enhanced model not only provides reduced runoff coefficients but also achieves a better spatial balance of the retention water volume. (2) Compared to the conditions before optimization, medium- and high-density impervious surfaces significantly change after optimization, and the connectivity between patches is reduced. The optimized layout alters the original gradient connection method, preventing the aggregation of runoff from high-density impervious surfaces and thereby reducing the risk of urban waterlogging during heavy rain. This study can provide a reference for optimizing the spatial layout of impervious surfaces aimed at urban waterlogging prevention in urban renewal planning.

An Evaluation of the Impact of Urban Growth on Runoff in Abeokuta, Southwestern Nigeria

Abeokuta is one of the urban areas in Nigeria with high cases of runoff fatalities in recent times, indicating the need for a proper understanding of prominent runoff-generating mechanisms, as well as the causative factors. Consequently, this paper, which is focused on flood-prone settlements, is aimed at providing information on the impact of change in urban land use on runoff in the study area. The specific objectives were to determine the change in average runoff in terms of the Soil Conservation Service Curve Number (SCN-CN), and to assess the impact of urban growth on runoff in the area. The SCN-CN was derived from the 30m spatial Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM). At the same time, land cover change was estimated using Landsat TM+ from 2000 and Landsat 8 OLI from 2018. Data were analysed using the Hydrologic Engineering Centre’s Hydrologic Modelling System (HEC-HMS) and ArcGIS (version 10.1). The results showed a 14% increase (from 39% in 2000 to 53% in 2018) in urban areas of selected catchments; and a relative increase in average CN from 76.9 units in 2000 to 79.9 units in 2018, suggesting an increase in runoff potential relative to the increase in urban/impermeable space in the catchment. Annual discharge depth increased from 891.84mm to 956.9mm, while peak discharge increased from 161.9m3 /s to 196.2m3 /s. Runoff in the study area tends to exhibit spatial variability that is similar to the pattern exhibited by built-up areas across the study area, suggesting that the development of built-up areas can explain runoff exacerbation in part of the area. The use of SCN-CN and satellite images makes the approach reproducible, and the mixed methods of geographic information system and hydrological model revealed the spatial variability typically hidden in stand-alone hydrological models. The paper recommends further studies with the use of less coarse datasets, as well as the implementation of policies that focus on sustainable urban growth in the region, and other cities.

Estimation of Natural Groundwater Recharge in Altun Kopri Basin NE Iraq

The main objectives of the current study are to classify and assess the climate, estimate the actual evapotranspiration and runoff, determine the soil water budget, and estimate groundwater recharge. The climate of the study area is classified as Humid to Moist and Moist to Subarid. Evapotranspiration was determined by using the Thornthwaite method, with its annual value equal to 1342.68 mm. The Runoff was estimated by using the simple and widely used method of Soil Conservation Service Curve Number, the total runoff was 127.6 mm, which represents 36.44% of total rainfall precipitation. The groundwater recharge was estimated according to the modified Thornthwaite-Mather soil water budget, which equals 58.6 mm and represents 16.74 % of the total annual precipitation. The quantity of renewal groundwater is about 47.88 MCM.

The Alteration of Flood Peak Discharge by Land Cover Change in Prek Thnot Watershed, Kampong Speu Provine, Cambodia

This study analyses the alterations of peak catchment runoff from Prek Thnot watershed using the Soil Conservation Service Curve Number (SCS-CN) methodology. Two major studies using different approaches have previously been conducted in the catchment, albeit producing inconsistent results. The Snowy Mountain Hydro-electric Authority published the first study in 1967 and found that the peak surface flow runoff over a 10-year return period was 710 m3/s. The second study was conducted by the Japanese International Cooperation Agency (JICA) between 1991 and 2006 and reported a peak catchment discharge of 1,380 m3/s. To date, there has been no discussion comparing the two studies to determine why the discharge during the later study was double that of the first. As the annual rainfall during the two study periods was similar, it is suggested that this discrepancy may be attributed to physical changes in the watershed, such as changes to forest cover. We deployed the Hydrologic Engineering Centre-Hydrologic Modeling System to simulate the peak runoff of the catchment. Our result was very similar to the JICA finding. Our data suggested that the increase in catchment discharge may be attributed to the conversion of 26% of forest cover in the catchment to agricultural land since the early 2000s. This information is useful for flood management practices, particularly with respect to managing catchment runoff in the context of rapid deforestation and the hydrological impacts of climate change within the watershed. The paper analyzes the impact of land-use changes on catchment runoff and provides valuable insights for flood management practices in the context of climate change and deforestation.

Strategi Pemetaan Genangan Banjir Sungai di Kota Pekalongan Menggunakan Model SCS-CN

Pekalongan City consistently experiences annual floods. In this research, we aimed to map the distribution of potential flood inundation in Pekalongan City under two scenarios: the existing land cover and urban planning (Rencana Tata Ruang Wilayah/RTRW). We utilized hydrological modeling to assess the suitability of the RTRW for future implementation. The Soil Conservation Service – Curve Number (SCS-CN) method was employed, incorporating Digital Elevation Model (DEM) data, soil data, precipitation data, and two sets of land cover data (existing and urban planning). The findings indicate that under the existing land cover, approximately 13.97% of the area is susceptible to flooding, while the remaining 86.03% is not at risk. Conversely, the model using the urban planning (RTRW) scenario suggests that 14.06% of the area has the potential to flood, while 85.94% is not susceptible to flooding. The increase in potential flooding in the urban planning scenario may be attributed to the expansion of residential areas and the reduction of plantation and dry land cover. Furthermore, in assessing monthly modeling results, we observed that the area with flood potential is highest in December 2022 and lowest in June 2022. Considering topographical conditions (DEM), we found that the potential for flood inundation is fairly and evenly distributed in flat areas, mostly with elevations of less than 11 meters. Areas at higher elevations are predominantly free from flood potential, but it is noteworthy that certain areas in the Pekalongan Selatan District, with elevations higher than 11 meters, still have the potential for flooding.  Keywords: Flood, hydrology model, SCS-CN, existing land cover, urban planning

GIS-driven Hydro Energy Potential Estimation for Technoeconomic Assessment of Hydro Power Plant in Bawean, Gresik

This study aims to assess the spatial distribution of hydropower capacity on Bawean Island using a Geographic Information System (GIS). The objective of this study is to provide a valuable contribution to the progress of sustainable energy transition initiatives in Indonesia. The primary objective of the hydropower map is to enhance the process of strategic planning and implementation of hydropower infrastructure, with a particular emphasis on supplying electricity to rural regions. The essential components required for the successful implementation of hydropower are the head, which represents the vertical distance between the water source and the water outflow, which refers to the rate at which water is discharged from the system. Bawean Island, located in the eastern region of Java, possesses a unique topographical structure distinguished by an abundance of rivers, making it a promising site for the establishment of hydropower infrastructure. The utilization of ArcGIS was applied for the aim of hydropower mapping. The estimation of water discharge was conducted using the Soil Conservation Service-Curve Number (SCS-CN) approach. The current investigation utilized the Multi-Criteria Decision Analysis (MCDA) framework, which incorporated the Analytical Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) to ascertain the most advantageous choice of hydropower plant types for deployment in the Bawean region. The classifications comprise pico-hydro, micro-hydro, mini-hydro, and large-scale hydropower installations.The Multi-Criteria Decision Analysis (MCDA) framework incorporates various criteria, including cost, policy, social concerns, technology assistance, integration, and natural catastrophe considerations. The results indicate that the hydropower potential on Bawean Island peaks in January, coinciding with the rainy season, while it is at its lowest in August, corresponding to the dry season. Moreover, the spectrum of hydropower installations suitable for Bawean Island includes pico-hydro systems, which have a power generation capacity of up to 5 kW. Additionally, mini-hydro plants are categorized into two classes: class A, with a power generation capacity ranging from 5 to 100 kW, and class B, with a power generation capacity ranging from 100 to 200 kW. The utilization of Multi-criterion Decision Analysis (MCDA) reveals the results of the techno-economic assessment, emphasizing the importance of cost, social factors, and policy as the key criterion for decision-making. The factors mentioned above are allocated weights of 0.44, 0.17, and 0.17, correspondingly. Pico-hydro is a suggested category of hydropower plants that are being considered for the development of hydropower infrastructure in the Bawean region.

Using remote sensing technology in estimating flood discharge

Floods are the most natural disasters occurring on earth. Recently, Egypt has been subjected to more frequent floods due to climate change. The main objective of this paper is creating hydrological analysis and estimating water discharge due to a flood hitting a hazardous zone near Safaga city. The research is divided into four main stages; 1) Morphological study, 2) Meteorological study, 3) Losses estimation, and 4) Flood discharge estimation. First, morphological study in which watershed boundaries, main streams and morphological data are delineated using geographic information system (GIS) with the aid of Landsat-8 satellite images and 30-m resolution digital elevation model (DEM). Second, meteorological study in which conventional rainfall frequency analysis is generated to estimate rainfall depth at different return periods using 15-years rainfall historical data from weather stations. Third, losses estimation is determined by using soil conservation service-curve number method (SCS-CN). Fourth, water discharge volume is carried out through hydrological modelling using a hydrologic engineering centre model. The estimated water volume is an appropriate information for decision makers to propose the adequate protection works to mitigate flood impacts.

Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model.

The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for developing sustainable strategies and viable approaches for prudent management of water resources. The central emphasis of this study is on the utilisation of SWAT model along with SWAT-CUP (SWAT calibration toolbox) to simulate streamflow in the upper Jhelum basin, the North West Himalayas, for a period of 20years from 2000 to 2019. The global sensitivity analysis algorithm, Sequential Uncertainty Fitting 2 (SUFI-2) of SWAT-CUP, is used for sensitivity and uncertainty analysis. The optimised parameter set estimated by SUFI-2 constitutes 11 parameters that are found to be sensitive with soil conservation service (SCS) curve number (CN) being the most influential parameter followed by snowmelt base temperature. Autocorrelation analysis using the autocorrelation function was conducted on the temperature and precipitation time series data, followed by a pre-whitening procedure to remove any autocorrelation effects. Subsequently, the modified Mann-Kendall (MMK) test was applied to examine trends in the annual temperature and precipitation data. The results indicated statistically significant positive trends in both datasets on an annual scale. The results for the calibration period (2003-2014) for monthly simulation displayed good model performance at three gauging stations, Rambiara, Sangam and Ram Munshi Bagh with R2 values of 0.83, 0.847, 0.829, P factor values of 0.73, 0.76, 0.75 and R factor values of 0.61, 0.58, 0.63, respectively. The validation results for monthly simulation for the 2015-2019 period showed good model agreement with R2 values of 0.817, 0.853, and 0.836, P factor values of 0.76, 0.8, and 0.75 and R factor values of 0.62, 0.53, and 0.65, respectively. The study concludes that the SWAT hydrological model can perform satisfactorily in high mountainous catchments and can be employed to analyse the impact of land use-land cover changes and the effect of climate variation on streamflow dynamics.

Identification of potential zones on the estimation of direct runoff and soil erosion for an ungauged watershed based on remote sensing and GIS techniques

An investigation of soil and water resources is essential to determine the future scenario of water management and water resources to attain food and water security. The improper management of watersheds results in a huge amount of sediment loss and surface runoff. Therefore, the present study was carried out to estimate the surface runoff and soil erosion using the Soil Conservation Service Curve Number (SCS-CN) method and RUSLE approach, respectively. These have been estimated using geospatial technologies for the ungauged Mandri river watershed from the Kanker district of Chhattisgarh State in India. The runoff potential zones, which are defined by the area's impermeable surfaces for a given quantity of precipitation were identified based on curve numbers at the sub-watershed levels. The land use data were collected from LISS IV images of 2009. The results showed that the average volume of runoff generated throughout the 16 years (2000-2015) was 14.37 million cubic meters (mM3). While average annual soil loss was found to be 17.23 tons/ha/year. Most of the eroded area was found to be around the major stream in a drainage system of Mandri River and on higher slopes of the terrain in the watershed. This study revealed that surface runoff and soil erosion are primary issues, which adversely affected the soil and water resources in this watershed. Therefore, suitable water harvesting sites and structures can be constructed based on the potential runoff zone and severity of soil erosion to conserve the soil and water in the watershed.

CN-N: A Python-based ArcGIS Tool for Generating SCS Curve Number and Manning’s Roughness

Water resources engineers and geospatial analysts often face the challenge of spatially estimating parameters such as the Soil Conservation Service (SCS) Curve Number (CN) and Manning’s roughness number (n), which are critical for predicting runoff and streamflow in hydrologic studies. Addressing the above challenge, this paper presents an innovative ArcMap tool developed using Python. This tool streamlines the SCS-CN and Manning’s n spatial calculations and is designed to handle large datasets, even at the scale of the entire US. Additionally, it offers the unique capability of geoprocessing mixed soil types and seamlessly integrating data if the watershed spans over different states. Our tool automates the integration of land cover data, hydrologic soil group data, and hydrologic boundaries. The tool reads watershed boundaries and uses the National Land Cover Database (NLCD) and the Gridded Soil Survey Geographic Database (gSSURGO) to develop SCS-CN and Manning’s n spatial layers. The tool also offers users the unique flexibility to add any desired values for CN or Manning’s n in the form of a so-called lookup table, which is a great help with the iterative process of calibrating hydrologic or hydraulic models. Our tool addressed one of the major limitations of its predecessors, acknowledging the existence of mixed hydrologic soil groups, e.g., B/C or C/D, and allowing for user adjustments to address hydrologic or hydraulic models’ calibration needs. The tool was developed with a flexible framework to incorporate additional spatial parameters soon, such as the spatial green-ampt parameters. With a user-friendly interface and integration capabilities, the tool is invaluable for hydrologic and hydraulic studies at local, regional, and global scales.

Runoff retention characteristics of forested and deforested catchments: an analysis using a spatially lumped model

ABSTRACT This study investigates the runoff characteristics of forested and deforested catchments using the Soil Conservation Services–curve number (SCS-CN) model from the perspective of the Kerala floods in 2018 and 2019. The forested and deforested catchments chosen for the study are the drainage area of the Kakkayam Dam and Punoor River respectively of Kozhikode District, Kerala. The study used input variables such as rainfall, land use/land cover (LU/LC) and soil data to estimate the runoff depth from these catchments during the floods in 2018 and 2019 using the SCS-CN model. Here, the hydrological response of these catchments is examined by different scenarios of rainfall and LU/LC change. It is found that the deforested catchment generates more runoff compared to the forested catchment under identical rainfall conditions. However, the study shows that, the runoff depth in the deforested catchment is expected to reduce if certain portion of plantations and barren land converts into the forest cover. The ability of runoff retention of the forested catchment is expected to lose if the forest-covered land is utilized for the plantation activities.

Assessing the Influence of Land Cover and Climate Change Impacts on Runoff Patterns Using CA-ANN Model and CMIP6 Data

Dhaka city is experiencing rapid land cover changes, and the effects of climate change are highly visible. Investigating their combined influence on runoff patterns is vital for sustainable urban planning and water resources management. In this work, multi-date land cover classification was performed using a random forest (RF) algorithm. To validate accuracy of land cover classification, an assessment was conducted by employing kappa coefficient, which ranged from 85 to 96%, indicating a high agreement between classified images and the reference dataset. Future land cover changes were forecasted with cellular automata-artificial neural network (CA-ANN) model. Further, soil conservation service -curve number (SCS-CN) rainfall-runoff model combined with CMIP6 climate data was employed to assess how changes in land cover impact runoff within Dhaka metropolitan development plan (DMDP) area. Over the study period (2020–2100), substantial transformations of land cover were observed, i.e., built-up areas expanded to 1146.47 km2 at the end of 2100, while agricultural areas and bare land diminished considerably. Consequently, monsoon runoff increased from 350.14 to 368.24 mm, indicating elevated hydrological responses. These findings emphasized an intricate interplay between urban dynamics and climatic shifts in shaping runoff patterns, underscoring urgency of incorporating these factors into urban planning strategies for sustainable water resources management in a rapidly growing city such as Dhaka.