SCS Curve Number Method Research Articles

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.

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.

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.

Runoff Estimation for the Central Region of the Lesser Zab River Watershed Using the SCS-Curve Number Method and GIS

Runoff Estimation for the Central Region of the Lesser Zab River Watershed Using the SCS-Curve Number Method and GIS

Rainfall-Runoff Modelling Using HEC-HMS Model, Remote Sensing and GIS in Middle Gujarat, India

Hydrological modeling is a widely used approach for estimating the hydrological response of a basin to precipitation. Floods are among the most catastrophic natural disasters in small urban watersheds, inflicting loss of life, massive property destruction, and a severe danger to the economy. As a result, appropriate modeling can be a useful tool in preventing and mitigating such flood hazards. Despite this, flash flood prediction remains one of the challenges of hydrological modeling in ungauged basins due to a lack of runoff observations. This study aims to calibrate and validate the rainfall-runoff transformation model for Hathmati river sub watershed in the Sabarmati River basin using HEC-HMS (Hydrologic Engineering Centre Hydrology Modeling System). For the loss rate, SCS Curve Number method was selected while Clark Unit Hydrograph and SCS unit hydrograph was used for the transform method. The model is calibrated and verified using two rainfall-runoff events from 2006 and 2007 year The model calibration and validation efficiency were verified for both methods using the Nash-Sutcliffe efficiency (NSE), The coefficient of determination (R2), and the Percent Bias (PBIAS) As a result, the model calibration and validation were found to be satisfactory with the acceptable value of NSE between 0.869 to 0.914, with R2 0.901 to 0.947 and PBIAS from 9.76 to 14.8. it is observed that the model shows a very good correlation between simulated flow and observed flow. As a result, the model can be used to forecast river flow and aid in flood mitigation efforts to lessen their effects and associated costs. Additionally, the findings of this study can serve as guidelines for future assessments of the flood risk in the study area.

A Modified SCS Curve Number Method for Temporally Varying Rainfall Excess Simulation

The SCS curve number (SCS-CN) method has gained widespread popularity for simulating rainfall excess in various rainfall events due to its simplicity and practicality. However, it possesses inherent structural issues that limit its performance in accurately simulating rainfall excess and infiltration over time. The objective of this study was to develop a modified CN method with temporally varying rainfall intensity (MCN-TVR) by combining a soil moisture accounting (SMA) based SCS-CN method with the SMA method in the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS). In the MCN-TVR, the SMA-based SCS-CN method is utilized to simulate the cumulative rainfall excess and infiltration, while the SMA method in the HEC-HMS serves as an infiltration control function. A key advantage of the MCN-TVR is that it eliminates the need for additional input parameters by inherently linking the parameters in the two SMA-based methods. Sixteen hypothetical 24 h SCS Type II rainfall events with different soil types and five real rainfall events for the Rush River Watershed in North Dakota were used to assess the performances of the MCN-TVR method and the SMA-based SCS-CN method. In the hypothetical simulations, the rainfall excess simulated by the SMA-based SCS-CN and MCN-TVR models was compared to that simulated by a Green–Ampt model. Discrepancies were observed between the rainfall excess simulated by the SMA-based SCS-CN and Green–Ampt models, especially for coarse soils under relatively light rainfall. However, the MCN-TVR model, incorporating an infiltration control function, demonstrated its improved performance closer to the Green–Ampt model. For all the hypothetical events, the Nash–Sutcliffe efficiency (NSE) coefficient of the rainfall excess simulated by the MCN-TVR method compared to the Green–Ampt model was greater than 0.99, while the root mean standard deviation ratio (RSR) was less than 0.03. In the real applications, the SMA-based SCS-CN model failed to provide acceptable simulation of the direct runoff for rainfall events with durations of less than the time of concentration. In contrast, the MCN-TVR model successfully simulated the direct runoff for all the events with NSE values ranging from 0.65 to 0.91 and RSR values from 0.31 to 0.56.

Hydrologic Design of Soil and Water Conservation Structures Using Probability Analysis and Machine Learning Techniques in Saurashtra Region of Gujarat, India

The soil and water conservation structures are constructed to overcome water scarcity as a result of interannual rainfall variability and paucity of the perennial source of water. The present study was aimed to estimate the design runoff for the efficient hydrologic design of various soils and water conservation structures using machine techniques for enabling efficient harvesting of available rainfall with economical design which can support in developing climate resilience for the Saurashtra region of Gujarat, India. The design rainfall at various return periods was predicted by Annual One Day Maximum Rainfall (ADMR) using three technics i.e. Probability Distribution Fitting, Artificial Neural Network (ANN) and Gaussian Process Regression (GPR) for 11 stations. Various goodness of fit tests revealed that ADMR was efficiently predicted by log-logistic (3P) distribution for six stations, generalized extreme value distribution for two stations and lognormal (3P), gamma (3P) and lognormal distribution for one station each. Among ANN and GPR, the performance indicators revealed that GPR has shown a higher capability to predict ADMR as compared to ANN with correlation coefficient ranging from 0.97 to 0.99, mean absolute error from 15 mm to 411 mm and root mean squared error from 40 mm to 494 mm for various stations. The design runoff estimation was demonstrated based on predicted ADMR for return periods suitable for various soil and water conservation structures like field bunding, terrace outlets and vegetative outlets, field diversion, permanent masonry gully control structures, earthen dam, etc. using SCS-Curve Number method for curve number 70 and 85. The study is useful for researchers, planners and engineers to implement the economical, efficient and safe design of various soil and water conservation structures.

A Comparative Evaluation of Using Rain Gauge and NEXRAD Radar-Estimated Rainfall Data for Simulating Streamflow

Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic Engineering Center’s event-based distributed Hydrologic Modeling System (HEC-HMS). The model was run using the curve number (CN) and the Green and Ampt infiltration methods. The results show that the streamflow simulated with rain gauge data compared better with the observed streamflow than the streamflow simulated using radar data. However, when the Mean Field Bias (MFB) corrections were applied, the quality of the streamflow results obtained from radar rainfall data improved. The results showed no significant difference between the simulated streamflow using the SCS and the Green and Ampt infiltration approach. However, the SCS method is reasonably more appropriate for modeling the runoff at the sub-basin-scale than the Green and Ampt infiltration approach. With the SCS method, the simulated and observed runoff amount obtained using rain gauge rainfall showed an R2 value of 0.88 and 0.78 for MFB-corrected radar and 0.75 for radar only. For the Green and Ampt modeling option, the R2 value for the simulated and observed runoff amounts were 0.87 with rain gauge, 0.66 with radar only, and 0.68 with MFB-corrected radar rainfall inputs. The NSE values for rain gauge input ranged from 0.65 to 0.35. Overall, three values were less than 0.5 for streamflow for both the methods. For seven radar rainfall events, the NSE was greater than 0.5, with a range of very good to satisfactory. The analysis of RSR showed a very good comparison of stream flow using the SCS curve number method and Green and Ampt method using different rainfall inputs. Only one value, the 2 November 2003 event, was above 0.7 for rain gauge-based streamflow. The other RSR values were in the range of “very good”. Overall, the study showed better results for the simulated runoff with the MFB-corrected radar rainfall when compared with the simulations obtained using radar rainfall only. Therefore, MFB-corrected radar could be explored as a substitute rainfall source.

Performance evaluation of HEC-HMS hydrological model applied to the Tibagi river watershed in the State of Paraná – Brazil

The present work performs statistical evaluations of the HEC-HMS hydrological model for the six sub-basins that form the Tibagi River watershed, located in the central-eastern region of the state of Paraná, Brazil. The physical characterization of the study area is developed by techniques of geographic information systems. The effective rainfall is estimated using the SCS curve number method, the baseflow is determined by a recession curve method, and hydrographs are simulated using the SCS unity hydrograph method. The simulated hydrographs are compared with measured outflow data of the six sub-basins for a selected period of 2017. The performance of the models is assessed using a validation criterion based on RSR, NSE e PBIAS statistical indexes. After input parameters calibration, the comparisons of the hydrographs show excellent agreement with measure data according to the classification adopted in the work. The simulated peak flows range from 3.3 to 8.6% when compared to the observed peak flows, indicating that the model can assist in the prediction of maximum discharges.

Estimation of Runoff from River Asa Watershed Using SCS Curve Number and Geographic Information System (GIS)

The study aims to determine the runoff depth using Soil Conservation Service Curve Number (SCS-CN) method in Geographical Information System (GIS) environment. For River Asa Watershed, the SCS Curve Number method has been adopted for estimating the runoff depth using Rainfall data from 1987-2018. Land use and change cover map were used for the classification of soil type, in order to determine the Hydrological Soil Group (HSG) using ArcGIS. The runoff was estimated from the rainfall runoff equation. The Antecedent Moisture Condition (AMC), potential maximum retention(s) and initial abstraction were computed. Thematic maps such as Soil and Land Use / Land cover and have been used in conjunction with hydrological data for determining hydrological soil Group (HSG) and Curve Number (CN) for land used and change cover classes over the watershed. The values of Hydrological Soil Group, Curve Number and Annual runoff depth varied (6.28-914.22) km2, (65-100) and (16.50-144.89) × 106 m3. The study shows that the high runoff depth was observed in Hydrological soil group (HSG), when compared with curve number (CN), this is due to dense vegetation cover.

Studies on Water Balance and Groundwater Budgeting in Godawari-Purna Sub-basin

The Godawari-Purna sub basin is located between 76°36' to 77°59' E and 19°07' to 19°17' N with an area of 34413.87 ha falls in assured rainfall region. The basin boundary was updated using the updated drainage and terrain information from high resolution satellite data of LISS-IV using GIS tool. Based on the last 30 years rainfall records, the runoff potential was estimated using SCS curve number method. Marathwada region of Maharashtra state has always been a water deficit area which calls for immediate remedial measures to address the critical water resources situation in the region. The entire Godawari-Purna sub basin (GP sub basin) is hard rock terrain. It suffers from growing water scarcity, which is aggravated by frequent droughts. The various water balance components viz. soil moisture storage, ground water recharge and surface storage were estimated for the GP basin. Similarly, the input from the rainfall was also worked out. The various losses such as runoff, evaporation from water bodies were estimated and accordingly the water available in the basin was estimated. The estimated values of ground water recharge were considered for water balance analysis. The surface water storage in each sub basin was estimated considering the water storage area as per satellite image and thus the storage volume was estimated. Combining the soil moisture storage, surface water storage and ground water recharge, water availability was estimated for each sub basin. The surface runoff was estimated by water balance method considering the rainfall volume and losses in each sub basin. Water balance study reflected that sub-catchment No. I, IV, VI and VIII of GP sub basin are under total water deficit and require urgent attention for water management to meet out the water deficit

Studies on Rainfall-Runoff Relationship for Assessment of Rainwater Harvesting Potential under Marathwada Region

The rainfall available in the watershed is key factor for determining the availability of water to fulfill the different demand mainly for agriculture, hydropower water supply, industry, etc. A watershed is that contributes runoff water to a common point Runoff is one of the important hydrologic variables used in most of the water resource applications. Runoff is the total surface flow from a given drainage area. Rainfall duration, intensity and aerial distribution influence the rate and volume of runoff. Watershed characteristics such as slope, shape and size, cover of soil and duration of rainfall have a direct effect on the peak flow and volume of runoff from any area (Chandler and Walker, 1998). Rainfall and runoff are significant constitute the sources of water for recharge of ground water in the watershed. Estimation of runoff in a watershed is very important to manage the water resources efficiently. Most of the part of the Marathwada region is comes under assured rainfall zone. The region receives mean annual rainfall of 880 mm. Rainfall in uncertain and erratic in this region and sometimes suffers from severe droughts. The rainfall data for Aurangabad, Parbhani and Nanded stations were collected from the Agro-meteorological station under VNMKV, Parbhani. Runoff was estimated using SCS curve number method considering the all parameters like soil type, vegetation etc. The rainfall runoff relationship was worked out for further planning of small water harvesting structures like farm ponds. The runoff potential for Aurangabad, Parbhani and Nanded station is found to be 20.07 %, 28.31 % and 31.69 % respectively, indicating a good scope for rainwater harvesting and thereby, many more rainwater harvesting structures can be constructed based on site specific conditions. A relation between rainfall and runoff for Aurangabad, Parbhani and Nanded stations were worked out as Y = 0.301X - 55.711 ( R2 value - 0.75), Y = 0.4043X - 88.882 (R2 value - 0.8687) and Y = 0.6018X - 209.2 (R2 value -0.9575) respectively. The linear rainfall-runoff relation obtained can be used for finding out runoff corresponding to any rainfall occurring in the area. The rainfall runoff relationship will be useful for determination of rainwater harvesting potential and its reuse for enhancing production potential of various rainfed crops.

Simulation of runoff in Baitarani basin using composite and distributed curve number approaches in HEC-HMS model

The present study was conducted in Baitarani basin up to Anandapur gauging station of Odisha covering an area of 8603.7 km2. Pre-processing of basin from digital elevation model (DEM) was done using HEC-Geo-HMS extension and spatial analyst tool in ArcGIS. These pre-processed files were then imported to HEC-HMS for simulating runoff. In this study, runoff simulation was done using two methods, viz., composite and distributed curve number (CN) approaches. SCS curve number method was used for computation of runoff volume, SCS UH method for direct runoff, constant- monthly varying base flow method for base flow and Muskingum method for flow routing. The model was calibrated and validated using both composite and distributed CN approaches. Data from 1st January, 2007 to 31st December, 2013 were used for calibration and 1st January, 2014 to 31st December, 2016 were used for validation. During the calibration period of composite CN approach, the statistical parameters like Nash-Sutcliffe efficiency (NSE), Coefficient of determination (R2), Percent bias (PBIAS) and RMSE-observations standard deviation ratio (RSR) were found to be 0.51, 0.63, 12.82 and 0.7, respectively and during the validation period they were found to be 0.53, 0.54, -19.73 and 0.7, respectively. In case of distributed CN approach, the statistical parameters like NSE, R2, PBIAS and RSR were found to be 0.62, 0.63, -8.64 and 0.6, respectively during the calibration period and 0.67, 0.66, -2.25 and 0.6, respectively during the validation period. The study indicated that distributed CN approach is more accurate than composite CN approach in simulation of runoff using HEC-HMS model.

Calibration and validation of hydrological model using HEC-HMS for Kuantan River Basin

Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. This study aims to calibrate and validate the rainfall-runoff transformation model for Bukit Kenau Station in Kuantan River Basin (KRB) using HEC-HMS (Hydrologic Engineering Centre Hydrology Modeling System). For the loss rate, SCS Curve Number method was selected while Clark Unit Hydrograph was used for the transform method. The model calibration and validation efficiency were verified using the Nash-Sutcliffe model efficiency (ME). As a result, the model calibration and validation were found to be satisfactory with ME between 0.5 to 0.8. The model can be used to forecast the river flow and helps in the flood mitigation works to reduce the impacts along with the cost use. Besides, the result obtained from this study can be used as a guideline for future flood risk assessment works in the study area.

Modelling of rainfall and runoff using HEC-HMS in Oghani Micro-watershed of Azamgarh District Uttar Pradesh

The present study was conducted using HEC-HMS, based on the SCS Curve Number method, Muskinghum method and Unit Hydrograph method, with the primary objective of developing a hydrological simulation model to forecast rainfall and runoff in the Oghani micro-watershed of Azamgarh district of Uttar Pradesh. Ten years rainfall-runoff peak events were used for this study purpose. Out of these ten events six events were selected for calibration and the rest of four events were used for validation. An initial calibration parameter was extracted from the data using geomorphological characteristics. The final parameter of validation was obtained from the optimization methodology and called the model's global values. For these rainfall-runoff events, the total surface runoff hydrograph was computed using the SCS unit hydrograph method that was compared with the hydrographs observed. For these rainfall-runoff occurrences, the cumulative surface runoff hydrograph was determined using the SCS unit hydrograph system that was correlated with the hydrographs observed. Error functions were measured using HEC-HMS for expected values and associations were also determined between observed and predicted values. Error functions include root mean square error (RMSE), mean absolute relative error (RMSE), and mean absolute relative error (MARE). The HEC-HMS model used for rainfall-runoff simulation in the selected watershed shows various errors within the permissible limits (RMSE -1.47, MARE - 0.0035, RMSE - 1.965 and MARE - 0.00595) which indicates the satisfactory performance of HEC-HMS model in predicting runoff. Comparison of the computed peak runoff discharge with measured values shows good result despite limited data availability.

FLOOD RISK, COASTAL MEGACITIES, AND URBAN POOR: ASSESSING THE FUTURE URBAN FLOOD RISK IN THE H/E WARD OF MUMBAI

In India, Mumbai city is highly vulnerable to the threats posed by climate change, such as sealevel rise, storm, and floods. The vulnerability of the city was demonstrated on the 26 July 2005 when thousands of houses were submerged in the water, and assets worth billions of rupees were damaged. The flood severely impacted the residents in informal settlements known as slums, which incurred substantial financial losses. With the increasing vulnerability of coastal megacities to urban floods, there is a need for an effective risk assessment and Adaptation Planning. Hence this study aims to assess the current amd future Flood Risk faced by the H/E Ward (study area) of Mumbai. The flood risk assessment is performed using the standard catastrophe Risk modeling, which combines Hazard, exposure, and vulnerability. Various data sources such as Historical rainfall data, Elevation Data, Soil Database, Landsat Imagery, and census data were collected from multiple online sources to achieve this objective. The data processing is done using GIS, Hydrological and Hydraulic Processes. As the H/E ward lies in the Mithi River catchment area, we processed the DEM and used the SCS-Curve Number and kinematic routing method to generate the peak discharge at the River Sub basins in HEC-HMS software. The River geometry is prepared in HEC-RAS software, and Flood Hazard Maps were prepared. The current & future Risk analysis shows an increase in the inundation extent for the 100 year return period in the H/E Ward, which highlights that there would be an increase in the total affected Population and losses incurred by them. The study also highlights that the people's adaptive capacity is deficient. Most of the affected Population are poor people, employed in menial jobs, chosen to stay in the riskier site because of proximity to work. Hence this study highlights an urgent need for an effective Risk Management and Adaptation planning in the H/E ward of Mumbai.

Pengaruh Perubahan Kondisi DAS terhadap Debit Sungai Studi Kasus DAS Waduk Jatigede

Changes in land use in the upstream of Jatigede watershed cause discharge and sedimentation problems in the Jatigede Reservoir. The objective of this study is to analyse the affect of land use changes in the Jatigede Reservoir watershed to the inflow and sediment to the reservoir. SCS Curve Number method and HEC-HMS modeling system are used to discharge analysis. Flood discharges in the reach of Cimanuk River close to the reservoir using data of 2009 are Q2=1,751.5 m3/sec, Q5=2,280 m3/sec, Q25=3,064.5 m3/sec, Q50=3,589 m3/sec. Flood discharges in the reach of Cimanuk River close to the reservoir using data of 2018 are Q2=2,053.8 m3/sec, Q5= 2,616.7 m3/sec, Q25 = 3,439.2 m3/sec, Q50=3,984.9 m3/sec. Discharges increase in 10 years (based on 2009 data and 2018 data). For example discharge increment for Q25 is 375 m3/sec. The increment is due to the increment of CN number as the consequences of land use changes. In other words along with the time, flood discharge in the rainy season increases, however discharge in the drought season decreases.

ASSESSMENT OF RAIN WATER HARVESTING SYSTEM

The life of the inhabitants of the globe is greatly dependant on water. Providing portable water to communities is of prime interest. Scarcity of water is a threat in near future in Pakistan. There is a need to search for alternate sources of water to fulfil the community requirement. Rainwater Harvesting (RWH) system is a better alternative. Keeping in view the vast application of this system, it is adopted as an alternative source of water in a village of Abbottabad city where there is scarcity of water. According to Public Health Engineering Department (PHED), the currently available gravity system and three tube wells are not sufficient to supply water to all the population. For this study, first, the rainfall data is collected and then by using the principle of rainwater harvesting system, the quantity of available water is calculated. The calculations were made using SCS curve number method using mean monthly rainfall depth. From calculation, we found that not only for current population but for population in 2028 can also be served by storing the water that we get from Rainwater Harvesting system if stored in a reservoir. But after 20 years i.e. in 2038, there will be deficiency of 146, 449 gallons per day of water for entire community which can easily be arranged from a small tube well. Therefore, on the basis of this study, it was recommended to the PHED of Abbottabad city to store the rainwater in a reservoir so that it can be easily utilised.

Evaluation and planning of existing drainage project for reclamation of waterlogged area: a case study

Due to the flat topography and poor drainage condition, major parts of the Mahanadi delta command suffer from waterlogging problems. The sustainability of farm operations are highly affected by spatial and temporal rainfall variability. Thus, estimation of drainage design layout and identification of vulnerable area for waterlogging is the most vital operation for achieving maximum yield of paddy in cultivated land. This research investigation aimed to achieve an optimum level of soil moisture in the study area so that the yield of crops could be enhanced. Probability analysis of 25 years daily rainfall data was done to evaluate the appropriate drainage coefficient and runoff. Drainage coefficient for the study area was estimated to be 35.50 mm/day by SCS-Curve Number (CN) method, which was adopted for the design of surface drainage system with the 7 consecutive day storm and 10-year return period. The design discharge and peak discharge were evaluated to be 0.43 m3/s by SCS-CN method and 4.92 m3/s by the rational formula respectively, which were used for the design of the channel and the outlet structure, respectively. Standard procedures were adopted for the design of the channel as well as dimensions of the broad-crested drop spillway as outlet structure, respectively. The benefit-cost ratio of the new designed drainage system was found to be 2.48, which proved the new drainage system to be more efficient than the existing design.

Development of a new method for estimating SCS curve number using TOPMODEL concept of wetness index (case study: Kasilian and Jong watersheds, Iran)

In recent years, several empirical and mathematical methods have been developed to estimate runoff, among which the SCS curve number (SCS-CN) method is one of the simplest and most widely used methods. The SCS-CN depends mainly on a CN parameter which corresponds to various soil, land cover, and land management conditions, selected from look-up tables. An application of GIS and RS techniques along with filed investigations made it possible to enhance the method from a lumped one to the level of semi-distributed models in which a specific value can be assigned to each cell in raster maps. The up-to-date procedures require several datasets, field measurements and overlying issues which limits the use of SCS-CN in data-scarce regions. In this research a new method has been developed which estimates the SCS-CN over the catchment with a minimum input dataset and acceptable accuracy and is based on the saturation-excess concept, which is used in the semi-distributed model: TOPMODEL. The proposed method depends on three parameters, including ndrain (soil porosity), $${\bar{\text{z}}}$$ (average distance to watershed water table surface) and m (which controls the effective depth of the saturated soil) and one input dataset, the so-called topographic index. Results showed that the maximum and minimum differences between the basin-averaged CN based on the GIS and RS techniques and the proposed method for Kasilian and Jong watersheds are 12% and 0.3%, respectively. Also, the findings indicated that, of the three parameters of proposed method, the m parameter plays a key role and that by increasing this parameter the basin-averaged CN tends to decrease and vice versa. Because of the dependence on a topographic index, the proposed method is strongly affected by DEM resolution and there are significant differences between low and high-resolution DEMs. However, for a small scale watershed, similar to Kasilian, using DEMs with resolution lower than 100 m considerably decreases the above differences. As an overall conclusion, the proposed method provides acceptable values of SCS-CN which is important for running rainfall-runoff model in a data-limited or data-scarce regions. In addition, creating the gridded map for CN, which is required in most hydrological models, is one of the most important advantages of the proposed method.