Curve Number Research Articles

Variability of urban drainage area delineation and runoff calculation with topographic resolution and rainfall volume.

Designing green stormwater infrastructure (GSI) requires an accurate estimate of the contributing drainage area and a model for runoff generation. We examined some factors that add to the uncertainty associated with these two design steps in the urban environment. Delineated drainage areas at five GSI sites in southeastern Pennsylvania (PA) were compared for digital elevation model (DEM) resolutions (grid cell sizes) ranging from 8 to 300 cm. The findings point to an optimal DEM resolution range of 30-60 cm, with up to 100 cm resolution providing acceptable results for some sites. The delineated areas were validated with the observed flow and rainfall records at three sites by examining curve number (CN) values calculated for individual storms. The calculated CNs decreased with increasing rainfall volume, which supports a recommendation to consider a range of CNs in the GSI design process. The variation in calculated CNs was higher for the overestimated drainage areas derived from coarser DEM resolutions. We hypothesize that the observed continued decrease of CNs at high rainfall is the result of inlet bypass, a potentially significant factor in urban hydrology. The findings from this study provide insight into the variability in expected delineated drainage areas using standard methods in GSI design.

Estimating the runoff response from hillslopes treated with soil and water conservation structures in the semi-arid Ethiopian highlands: Is the curve number method applicable?

Planning and management of water resources is crucial to enhance agricultural productivity and ensure food security in drylands. For this, adaptable and reliable runoff prediction models are urgently needed to support water harvesting and irrigation development. In this study we explored the potential of the runoff Curve Number (CN) method to estimate daily surface runoff from representative land use types and management conditions in Tigray (north Ethiopia). For this, we use the National Engineering Handbook (NEH-Tables) to derive CN values for runoff plots treated with and without soil and water conservation (SWC) structures. Moreover, the rainfall-runoff data collected from 21 large (600–1000 m2) runoff plots during three years (2010 to 2012) were used to calculate CN-values. Results show that CN values derived from the NEH-Tables are larger by 21% compared to those values calculated from plot data. The calculated CN values vary widely (34 to 91) in response to land use type, slope gradient, and applied SWC structures. Our results show that land use and SWC structures strongly influence runoff production. Considering plots with otherwise similar characteristics, CN values are consistently larger for rangeland sites as compared to those values for cropland sites. Likewise, SWC structures greatly reduce runoff production and their presence also leads to a clearly lower performance of the CN model. The results of this study are relevant contributions towards addressing several goals of agenda 2063 of the African union either directly or indirectly and also international sustainable development goals (SDG). Based on our analysis and field observations, we propose calibrated CN values that may be used for runoff yield assessments in similar environments.

Calculating the Environmental Impacts of Low-Impact Development Using Long-Term Hydrologic Impact Assessment: A Review of Model Applications.

Low-impact development (LID) is a planning and design strategy that addresses water quality and quantity while providing co-benefits in the urban and suburban landscape. The Long-Term Hydrologic Impact Assessment (L-THIA) model estimates runoff and pollutant loadings using simple inputs of land use, soil type, and climatic data for the watershed-scale analysis of average annual runoff based on curve number analysis. Using Scopus, Web of Science, and Google Scholar, we screened 303 articles that included the search term "L-THIA", identifying 47 where L-THIA was used as the primary research method. After review, articles were categorized on the basis of the primary purpose of the use of L-THIA, including site screening, future scenarios and long-term impacts, site planning and design, economic impacts, model verification and calibration, and broader applications including policy development or flood mitigation. A growing body of research documents the use of L-THIA models across landscapes in applications such as the simulations of pollutant loadings for land use change scenarios and the evaluation of designs and cost-effectiveness. While the existing literature demonstrates that L-THIA models are a useful tool, future directions should include more innovative applications such as intentional community engagement and a focus on equity, climate change impacts, and the return on investment and performance of LID practices to address gaps in knowledge.

The NRCS curve number equation derived from an instantaneous unit hydrograph: Some consequences

The NCRS-curve number equation allows calculating the storm runoff from a rainfall event for specific types of land use. It was based on an analysis of direct runoff data using baseflow corrected hydrographs and rainfall. Given this basis, the curve number equation can be derived assuming a constant effective rainfall intensity and a cubic reciprocal function as the instantaneous unit hydrograph. The instantaneous unit hydrograph and the resulting curve number equation are further generalized by adding a lag time. The equation for a curve number related hydrograph is presented, allowing to fit this curve number-based hydrograph to event data. The curve number itself is shown be a function of a catchment response time and the average event rainfall intensity. As the catchment response time is linked to the time of concentration the curve number equation and the storage index can be linked to catchment- and flow type characteristics. First results suggest that including the rainfall intensity duration frequency function in the curve number equation may explain systematic deviations observed when fitting the NCRS curve number equation to measured data.

Estimating surface runoff using the curve number method in an ungauged watershed in Jalisco, Mexico evaluating its morphometric parameters

The surface runoff was estimated using the curve number (CN) method for different storm events and it was associated with the morphometric parameters of an ungauged watershed in Jalisco, México. The land use and land cover map from 2019 was derived from the unsupervised classification of a Sentinel-2 image at 10 m resolution. The morphometric analysis revealed that the study area is dominated by areas of gentle slope and moderate to high permeability with dense vegetation and low relief. It is a well-drained watershed with low flood potentiality as well as a groundwater potential zone. About 69% of the study area corresponds to natural cover with tropical dry forest and evergreen forest as the most representative classes. A total of 77 storm events were identified from 2013 to 2019, with runoffs that ranged from 0.05 to 227.2 Mm3. September and October were the months with the most intense rainfall and, therefore, the months with the highest runoff volume. The average runoff was 14.52 Mm3, corresponding to an average runoff coefficient of 12.86%. Together, the methods used here provide useful results for delineating conservation strategies at the watershed level.

Hydrological modeling using the Soil and Water Assessment Tool in urban and peri-urban environments: the case of Kifisos experimental subbasin (Athens, Greece)

Abstract. SWAT (Soil and Water Assessment Tool) is a continuous-time, semi-distributed, river basin model widely used to evaluate the effects of alternative management decisions on water resources. This study examines the application of the SWAT model for streamflow simulation in an experimental basin with mixed-land-use characteristics (i.e., urban/peri-urban) using daily and hourly rainfall observations. The main objective of the present study was to investigate the influence of rainfall resolution on model performance to analyze the mechanisms governing surface runoff at the catchment scale. The model was calibrated for 2018 and validated for 2019 using the Sequential Uncertainty Fitting (SUFI-2) algorithm in the SWAT-CUP program. Daily surface runoff was estimated using the Curve Number method, and hourly surface runoff was estimated using the Green–Ampt and Mein–Larson method. A sensitivity analysis conducted in this study showed that the parameters related to groundwater flow were more sensitive for daily time intervals, and channel-routing parameters were more influential for hourly time intervals. Model performance statistics and graphical techniques indicated that the daily model performed better than the subdaily model (daily model, with NSE = 0.86, R2 = 0.87, and PBIAS = 4.2 %; subdaily model with NSE = 0.6, R2 = 0.63, and PBIAS = 11.7 %). The Curve Number method produced higher discharge peaks than the Green–Ampt and Mein–Larson method and better estimated the observed values. Overall, the general agreement between observations and simulations in both models suggests that the SWAT model appears to be a reliable tool to predict discharge in a mixed-land-use basin with high complexity and spatial distribution of input data.

Hydrological Estimation for the Runoff of Qalachwalan Basin Using Hydrological Estimation for the Runoff of Qalachwalan Basin Using (SCS – CN) Method (2000 – 2020)

The surface water is a reflection of the climatic and topographical conditions of the basin in the study area, and affects the estimation of the amount of runoff water on the surface inside the basin. It is also possible to measure the amount of running water in the basin and know the periods of increase, and water scarcity in this quantity, on the other hand, take advantage from water for all fields and uses. Qalachwalan basin is one of the water basins located at north of the city of Sulaymaniyah with an area of (876.1) km2, and all of its water sources are within the borders of the Kurdistan Region of Iraq. Due to unsteady rain and heavy precipitation in the recent years, therefore, it was necessary to conduct some researches to know the size and amount of runoff, besides, to see if it is possible to benefit from it for the development and investment of the study areas. Accordingly, Soil Conservation Service- Curve Number (SCS – CN) Method has been used used to estimate the depth and amount of the annual runoff. From this study it became clear to us that the area has seven uses )Bodies of water, dense forests, agricultural lands, grasslands, residential lands, barren lands, paved roads. Besides, it appeared that the greatest amount of runoff, which lies in the grassland equals to (588523320) m3, and the smallest amount with (4442480) m3 lies in the forest area. So, we discover that the total amount of the basin water reached about (700141140) m3. Finally, our data are very vital for the local government and stakeholders in the future to how to deal with this water basin especially with unsteady precipitations.

Soil erosion modelling of burned and mulched soils following a Mediterranean forest wildfire

AbstractSoil erosion modelling applied to burned forests in different global regions can be unreliable because of a lack of verification data. Here, we evaluated the following three erosion models: (1) Water Erosion Prediction Project (WEPP), (2) Morgan‐Morgan‐Finney (MMF) and (3) Universal Soil Loss Equation‐Modified (USLE‐M). Using field plots that were either untreated or mulched with straw, this study involved observations of soil loss at the event scale at a burned pine forest in Central Eastern Spain. The erosion predictions of the three models were analysed for goodness‐of‐fit. Optimization of the MMF model with a new procedure to estimate the C‐factor resulted in a satisfactory erosion prediction capacity in burned plots with or without the mulching treatment. The WEPP model underestimated erosion in the unburned areas and largely overestimated the soil loss in burned areas. The accuracy of soil loss estimation by the USLE‐M model was also poor. Calibration of the curve numbers and C‐factors did not improve the USLE‐M model estimation. Therefore, we conclude that an optimized MMF model was the most accurate way to estimate soil loss and recommend this approach for in Mediterranean burned forests with or without postfire mulching. This study gives land managers insight about the choice of the most suitable model for erosion predictions in burned forests.

Spatial Analysis to Estimate Runaff Using Scs (CN) to Wadi Al mur Watershed North of Iraq

The study aims at analyzing spatial and DEM data by the use of ArcGis, WMS, Global Mapper, and Erdas programas for finding hydrological Such data as climate and soil components have been analysed ,in addition to the classification of soil utilization and soil covering. The present study concludes by the use of the American soil conservation Service hypothesis SCS) which is known as Curve Number (CN)through the integrating of Remote Sensing (RS)technigue and the GIS to evaluate the water flow rate (QV) at times of rainfall (40185278 m3/ per – year).Implementing this model shows that the basin of Wadi Almur has such hydrological conditions that help in generating water flow in times of rainfall clue to the rise of(CN)value when isabout (81,86).

Assessment of Water Balance of Deme Watershed, Omo-Gibe Basin, Ethiopia Using SWAT Model and ARC-GIS for Water Resources Management

To deal with water management issues, one must analyse and quantify the different elements of hydrologic processes taking place within the area of interest. Obviously, this analysis must be carried out on a watershed basis because all these process are taking place within individual micro watersheds. Only after understanding the spatial and temporal variation and the interaction of these hydrologic components one can scientifically formulate strategies for water conservation. To achieve this goal the choice and use of an appropriate watershed model is a must. All the thematic maps and attribute information of the watershed have been collected from various Government agencies. SWAT model has been set up for the Deme watershed by inputting the digital thematic maps, physical properties of soil and climatic parameters. Total area of the watershed corresponding to the outlet chosen at Deme watershed is 11284.35km ² and its elevation varies from 1138 to 3269m. Calibration and validation of the model have been done by comparing the river flow prediction with the observed values. Nash Sutcliff Efficiency (NSE), coefficient of determination (R ²) and Percent bias (PBIAS) has given very high values for the calibration 0.75, 0.75 and -0.7% respectively and validation 0.73, 0.74 and 6.3% respectively. The calibrated model has been used to predict the important hydrologic processes. The water balance components of Deme watershed resulted PET 388.5mm, Evaporation and transpiration 293.8mm, Precipitation 1147.5mm, Average curve number 76.38, Surface runoff 189.7mm, Revap from shallow aquifer 7.7mm, Percolation to shallow aquifer 37.59mm, Lateral flow 624.33mm and Recharge to deep aquifer 0.28mm. The study has revealed that SWAT model can effectively be used in the simulation of river flow and for predicting the water balance of a watershed. Water balance information of the basin is of great use in planning water conservation, drainage and flood control.

An Improved Curve-Number Method

The standard curve-number method has shown limited accuracy in estimating observed rainfall-runoff relations, particularly for less extreme rainfall events. Consequently, the Natural Resources Conservation Service is considering revising the standard initial abstraction ratio and associated published curve numbers to improve the performance of the method. A form of the curve-number equation is presented here that improves the prediction accuracy of the curve-number method without the need to adjust the initial abstraction ratio or the existing guideline curve numbers, and the improved runoff estimation is at least as good as could be achieved by adjusting the initial abstraction ratio. The improved curve-number equation can also be used to analytically estimate curve numbers corresponding to any given initial abstraction ratio, and it is demonstrated that these estimates are supported by field measurements.

Estimation of Annual Water Income Using (SCS-CN) Method based RS-GIS for Wadi Abu Khashab Watershed-North of Iraq

The Annual Water income for Wadi Abu Khashab watershed estimatedas about(47.416 km2) by employing a set of software (ArcGIS, ErdasImagine) using the US Soil Conservation Method (SCS-CN) and fourdifferent methods resulting in an average annual water flow rate of thefour Techniques were (7,049,316 m3), based on the spatial data of thesatellite (Landsat-8) with spatial accuracy (30) meters and for bands(7,5,3) respectively, which is dated (5-2-2016) for two methods, while twomethods are based on the geological background based on the geologicalmap, this is the first time that the four methods have been used together inone search to ensure accurate and scientific results, the soil cover wasclassified and the nature of its uses, the soil hydrology and theidentification of its varieties, the quantities of Rainfall, and thedetermination of the Curve Numbers (CN).

The Revised Curve Number Rainfall–Runoff Methodology for an Improved Runoff Prediction

The Curve Number (CN) rainfall–runoff model is a widely used method for estimating the amount of rainfall and runoff, but its accuracy in predicting runoff has been questioned globally due to its failure to produce precise predictions. The model was developed by the United States Department of Agriculture (USDA) and Soil Conservation Services (SCS) in 1954, but the data and documentation about its development are incomplete, making it difficult to reassess its validity. The model was originally developed using a 1954 dataset plotted by the USDA on a log–log scale graph, with a proposed linear correlation between its two key variables (Ia and S), given by Ia = 0.2S. However, instead of using the antilog equation in the power form (Ia = S0.2) for simplification, the Ia = 0.2S correlation was used to formulate the current SCS-CN rainfall–runoff model. To date, researchers have not challenged this potential oversight. This study reevaluated the CN model by testing its reliability and performance using data from Malaysia, China, and Greece. The results of this study showed that the CN runoff model can be formulated and improved by using a power correlation in the form of Ia = Sλ. Nash–Sutcliffe model efficiency (E) indexes ranged from 0.786 to 0.919, while Kling–Gupta Efficiency (KGE) indexes ranged from 0.739 to 0.956. The Ia to S ratios (Ia/S) from this study were in the range of [0.009, 0.171], which is in line with worldwide results that have reported that the ratio is mostly 5% or lower and nowhere near the value of 0.2 (20%) originally suggested by the SCS.

Development of a New Event-Based Rainfall-Runoff Equation Based on Average Rainfall Intensity During an Event

Event-based rainfall-runoff models are practical tools commonly used to predict catchments’ response to a rainfall event. However, one of the main concerns is that the characteristics of rain events are neglected in the model development. This paper develops a novel event-based rainfall-runoff equation to incorporate rainfall characteristics into account. The performance of the new equation is evaluated based on the root mean square error, Nash–Sutcliffe efficiency coefficient, and per cent bias for 13,339 rainfall-runoff events between 2005 and 2020 over 23 catchments across New Zealand and Australia with oceanic, mediterranean, tropical, subtropical, and semiarid climates. Compared to the previous event-based models, the new equation shows an improvement in runoff estimation in almost all case studies. Furthermore, considering the new equation is simple, efficient, and takes the rain event duration into account, the new equation has the potential to become a robust alternative method to the conventional curve number method in hydrological engineering projects.

Genetics of spot blotch resistance in bread wheat (Triticum aestivum L.) using five models for GWAS.

Genetic architecture of resistance to spot blotch in wheat was examined using a Genome-Wide Association Study (GWAS) involving an association panel comprising 303 diverse genotypes. The association panel was evaluated at two different locations in India including Banaras Hindu University (BHU), Varanasi (Uttar Pradesh), and Borlaug Institute for South Asia (BISA), Pusa, Samastipur (Bihar) for two consecutive years (2017-2018 and 2018-2019), thus making four environments (E1, BHU 2017-18; E2, BHU 2018-19; E3, PUSA, 2017-18; E4, PUSA, 2018-19). The panel was genotyped for 12,196 SNPs based on DArT-seq (outsourced to DArT Ltd by CIMMYT); these SNPs included 5,400 SNPs, which could not be assigned to individual chromosomes and were therefore, described as unassigned by the vendor. Phenotypic data was recorded on the following three disease-related traits: (i) Area Under Disease Progress Curve (AUDPC), (ii) Incubation Period (IP), and (iii) Lesion Number (LN). GWAS was conducted using each of five different models, which included two single-locus models (CMLM and SUPER) and three multi-locus models (MLMM, FarmCPU, and BLINK). This exercise gave 306 MTAs, but only 89 MTAs (33 for AUDPC, 30 for IP and 26 for LN) including a solitary MTA detected using all the five models and 88 identified using four of the five models (barring SUPER) were considered to be important. These were used for further analysis, which included identification of candidate genes (CGs) and their annotation. A majority of these MTAs were novel. Only 70 of the 89 MTAs were assigned to individual chromosomes; the remaining 19 MTAs belonged to unassigned SNPs, for which chromosomes were not known. Seven MTAs were selected on the basis of minimum P value, number of models, number of environments and location on chromosomes with respect to QTLs reported earlier. These 7 MTAs, which included five main effect MTAs and two for epistatic interactions, were considered to be important for marker-assisted selection (MAS). The present study thus improved our understanding of the genetics of resistance against spot blotch in wheat and provided seven MTAs, which may be used for MAS after due validation.

Analisis Debit Banjir Rencana Daerah Tangkapan Air Waduk Tugu Menggunakan HEC-HMS

Over the course construction of Tugu Reservoir, it is proposed to build a spillway gate to increase its performance as a flood control infrastructure. The construction planning of spillway gate requires a calculation of design flood discharge for Tugu Reservoir Catchment Area. The latest calculation was carried out during its construction planning in 2010. Therefore, it is necessary to evaluate and recalculate the design flood discharge using the latest data. This study aims to model design flood discharge of Tugu Reservoir Catchment Area using HEC-HMS software. This software is able to simulate rainfall-runoff modeling in a catchment area. Based on field conditions, Tugu Reservoir catchment has parameters, curve number value of 79, impervious value of 5%, and a lag time of 4.81 minutes. The result of the HEC-HMS modeling shows that the design flood discharge of Tugu Reservoir for Q100 is 369,30 m3/s; Q1000 is 656,70 m3/s; and QPMF is 995.30 m3/s. Based on the test using Creager Graph, the design flood discharge for Tugu Reservoir is still in the reasonable category with C value below 100. The result of the HEC-HMS modeling is not much different from the calculation result of Tugu Reservoir Construction Planning in 2010.

Evaluation of soil-vegetation interaction effects on water fluxes revealed by the proxy of model parameter combinations.

The coupled development of soil and vegetation leads to a close interaction between their attributes and impacts the sustainability of eco-hydrology at different scales. In this study, a distributed hydrological model of a watershed was created with the Soil and Water Assessment Tool (SWAT) in a representative tributary watershed for investigating such effects. The results quantify the intensity and interval of the relationship and the impacts on hydrological composition between major model parameters. Among the examined interactions, SCS runoff curve number (CN2) and soil bulk density (BD) show the strongest interaction and effects on surface runoff, lateral flow, percolation, groundwater flow, and soil water content. The interaction between CN2 and BD highlights the importance of the soil surface and topsoil for runoff generation processes. In addition, the soil-vegetation interactions show clear seasonal effects due to impacts from the changes in land use and precipitation patterns, which influence the river discharge and flow variability more significantly at the sub-basin scale than at the watershed scale. The insight into the interactions and hydrological effects of soil and vegetation may help improve the spatial planning for ecological sustainability and hydrological extrema mitigation with a more reliable reflection of the spatial heterogeneity.

Identification of suitable zones and sites for rainwater harvesting using GIS and multicriteria decision analysis

Identifying suitable zones for surface water storage and groundwater recharge is needed to enhance irrigation water availability. This study was undertaken to map rainwater harvesting (RWH) potential zones using geospatial tools and analytic hierarchy process (AHP). The suitable locations for RWH were also mapped using the Boolean logic concept. The surface runoff is a vital factor to demarcate the appropriate zones for RWH. The curve number approach was used to estimate the surface runoff potential. The runoff coefficient (RC) map was generated based on rainfall and surface runoff depth. Weights have been allocated to selected themes of RC, drainage density, and slope. The themes were integrated using geographic information system (GIS) and AHP to demarcate the suitable zones for RWH. The derived RWH potential map was categorized into zones like "very good," "good," "moderate," "poor," and "very poor" with an aerial extent of 14.3%, 24.7%, 28.3%, 20.2%, and 12.6%, respectively. The area suitable for farm ponds was found to be about 9% (408 km2), 13% (329 km2), and 4% (244 km2) in Mirzapur, Chandauli, and Sonbhadra districts, respectively. Furthermore, 22, 15, and 21 locations were found suitable for check dams in Mirzapur, Chandauli, and Sonbhadra districts, respectively. At a large scale, effective planning of water management strategies based on multicriteria decision analysis and GIS offers increased availability of surface and groundwater resources and may help for enhancing the agricultural land use options. The higher resolution maps may be further utilized to plan RWH strategies at village level.

SCS-CN and GIS-Based Approach for Estimating Runoff in Western Region of Saudi Arabia

Designing reservoir operations, hydraulic structure, and soil erosion management techniques all require an estimation of a potential runoff. Accurate runoff in-formation is typically scarce in Saudi Arabia—a significant challenge for hydrologists. Wadi-Rahjan catchment in Western Saudi Arabia has been taken as a case study to determine the potential runoff estimates. The study integrates the soil conservation service curve number (SCN-CN) technique, remote sensing (RS), and geographical information system (GIS). Critical parameters including the digital elevation model (DEM), land use/land cover (LULC), hydrologic soil groups (HSGs), and rainfall data were also employed. The curve number (CN), which shows the catchment’s reaction to a storm was estimated based on LULC and HSG layers. The CN map obtained and rainfall data were employed in the GIS-based SCS-CN model to develop the potential runoff map. Based on the results of calculations, the study area is classified into three HSGs, namely, B, C, D. Averagely, CN for a normal condition is 90 while wet and dry conditions are 97 and 80, respectively. Results obtained from the SCS-CN method’s calculations reveal a yearly runoff result that varies from 194 mm to 295 mm. A higher percentage of runoff water (35%) in a runoff range from 289 to 295 mm, followed by 24%, ranged 269 to 288 mm. An interesting rainfall-runoff regression evaluation reveals a good 0.90 correlation. Other watersheds in Saudi Arabia may use this method for planning and development.

Effect of land use land cover change on runoff characteristics using curve number: a GIS and remote sensing approach

Effect of land use land cover change on runoff characteristics using curve number: a GIS and remote sensing approach