SCS-CN Method Research Articles

Application of Risk Analysis in the Screening of Flood Disaster Hot Spots and Adaptation Strategies

In recent years, Taiwan has established a sound flood control foundation in terms of river management. Due to climate change and land development, surface runoff has increased. In addition, the functions of flood control engineering facilities have their limits. Surface runoff cannot be fully absorbed by rivers, and frequent floods still occur in some areas. According to the characteristics of water flowing along the terrain to low-lying land, the terrain features can be used to find out the hot areas prone to flooding and the appropriate location of flood storage space for improving flooding. On the basis of the natural terrain environment, the disaster risk framework is used to manage environmental complexity, and to carry out research on flood warning and governance decision-making systems, so that human beings can coexist with the uncertainty of flood risk. In this study, the Zhuoshuixi Basin was used as the sample area, the SCS-CN method was used to analyze the excess runoff, and the risk concept was used to establish a flood evaluation model. In addition, through the changes in land use, the SCS-CN method estimates the difference of potential maximum retention, quantifies the variation of excess rainfall in each watershed division, and uses the digital elevation model to calculate the depression site to analyze the relationship between the difference of potential maximum retention and the depression space of the watershed. The results show that the adaptation strategy for high-risk flooded areas should be strengthened, and areas with large water storage space and a small potential maximum retention difference can be the best location for offsite compensation.

Runoff Estimation by Integration of GIS and SCS-CN Method for Kanari River Watershed

Conventional water management is the only alternative to overcome the gap between demand and supply and for this surface water resource management is interpretative issue. Kanari river watershed, located between 23°33′36.73″N and 80°06′57.49″E at an elevation of about 490 m in Jabalpur district of Madhya Pradesh State, India has been used for the study. The major component of the hydrologic cycle is rainfall, directly related to runoff. Integration of GIS and SCS-CN method can be beneficial to overcome this problem of runoff estimation. The runoff varies from 465.59 to 1119.24 mm (1990–2019). The amount of rainfall varies from 1136.7 to 1592.98 mm in the Kanari river watershed. The calculated average annual runoff was 729.87 mm and average runoff volume for the period of 29 years is 218.36. The model finally depicted the runoff in the area kept on increasing as rainfall kept on increasing following a linear trend which predicted that the infiltration opportunity decrease and ultimately resulting in decreased infiltration rate causing decreased base flow. Artificial recharge structures can be recommended in the study area.

Adapting Rainfall Variability to Flood Risk: A Case Study of the Ghaggar River Basin

Abstract Floods are the most common natural disasters influenced by climatic variables and anthropogenic activities. Ghaggar is a seasonal river of north-western region of India and this basin has been experiencing moderate to high intensity of floods frequently. The present study aims to find out the impact of the rainfall variability on the flooding scenario of this basin using hydrometeorological data. The rainfall data was collected for 12 stations of the basin. The rainfall and extreme rainfall of the Ghaggar basin was determined using innovative trend analysis which was further validated by Mann-Kendall test. The runoff generated from the average annual rainfall and extreme rainfall in terms of rx1day was determined using SCS-CN method. It is found from the analysis that the southwest monsoon is dominant all over the basin and is the main reason for causing the flood. The rx1day rainfall trend is positive at the stations situated in the middle of the basin which is another factor for causing the flood. It is also found that the runoff generated at the uppermost part of the basin due to heavy rainfall at Kalka and Nahan meteorological divisions when combined with runoff generated from middle of basin is creating the flood situation at middle of the basin. Flood hazard mapping was also carried out for vulnerability analysis and found that the basin area is moderate to highly vulnerable to floods.

Automated modelling of urban runoff based on domain knowledge and equation discovery

Modelling tools are widely used to analyse the urban drainage systems and to simulate the effects of future urban development and stormwater control measures. Usually, these tools use only one mathematical model (predetermined by the modeller) at a time to describe a single hydrological process within the urban catchment. When there are alternative mathematical models for describing the same hydrological process, their suitability needs to be investigated separately, which makes the modelling task even more complex, time consuming and open for human errors. Furthermore, models have to be calibrated to achieve a better fit between measured and simulated runoff. Calibration can be performed either manually, by using a trial-and-error approach, or by employing search techniques and parameter optimization tools. To overcome the drawbacks associated with manual selection and calibration of models, automated modelling based on equation discovery was used in this study to a) find the most suitable mathematical model among multiple alternatives for describing every (environmental) process modelled and b) to calibrate the model parameters against measured data. First, knowledge on urban runoff modelling was formalized into a new library of modelling components, compliant with the equation discovery tool ProBMoT (Process Based Modelling Tool). Next, a conceptual model of the experimental urban sub-catchment within the city of Ljubljana, Slovenia, was defined. ProBMoT was used to find the structure and parameters’ values of alternative rainfall-runoff models, according to the defined conceptual model that provide optimal fit against pipe flow measurements. Three alternative methods were used to describe infiltration: the SCS CN method, the Variable UK runoff equation, and the UK Water Industry Research equation. The proposed automated model discovery approach for finding the optimal rainfall-runoff model proved to be very efficient. Nine rainfall-runoff models were created with very good performance. The best performance was achieved by the models that used a combination of two different infiltration methods, i.e. the SCS CN infiltration method for the pervious area and one of the other two infiltration methods for the impervious area.

Gravel Mining Activity Impact on Riverbed Erosion and Bridge Foundation Stability

Geomorphological processes pose a risk that deserves attention and planning to avoid that, especially in the section near to east of Tuz bridge. This section of the valley facing a dramatic increase in gravel excavation and sorting of aggregates, consequence led to a change in the pattern of river branches flow from an anabranching river to a single-channel river, which led to a concentration of river discharge during floods. On 9th December 2018, Tuz Bridge was failed due to a heavy rainstorm three days preceding the failure event. The current study aims to conduct a field survey of all the human activities in the study area to assess river changes from remote sensing data the amount of runoff and river peak discharge based on rainfall data using SCS-CN method. In this study, ArcGIS, ArcGIS Earth, Google Earth, and WMS software are incorporated in the data analysis. The revealed results indicate the severe modification of valley morphology and converting the river pattern to flow during flood within a single channel with flow speed exceeded the critical velocity to induce vertical erosion of gravel and sands under the foundations of the bridge and causing the displacement and settlement of the bridge. The study recommends the local administration prevent gravel mining from the river valley at the upstream area of the bridge

Performance evaluation of spatially distributed, CN-based rainfall-runoff model configurations for implementation in spatial land use optimization analyses

Due to their large computational burden, spatially distributed hydrological models are unsuitable for iterative spatial optimization analyses, which need to take into account location-specific runoff water accumulation and re-infiltration processes. Therefore, a computationally efficient, raster-based and spatially-explicit RR-model was conceptualized. For this purpose, the SCS-CN approach was implemented in a spatially distributed manner, adjusting CN values to antecedent soil moisture conditions (AMC) and routing runoff to the catchment outlet. To take into account spatial interaction along the overland flow paths, the SCS-CN approach was extended with a re-infiltration algorithm. Several model configurations were evaluated, based on combinations of two AMC correction methods and three re-infiltration algorithms. These model configurations were applied in three catchments in Flanders, Belgium. The results indicate a poor performance of the default SCS-CN method, which was, however, considerably improved by the implementation of AMC correction and re-infiltration. Though calibration of the RR-model configurations was limited, several model configurations achieved model performances adequate for use in spatial optimization analyses. The most performant RR-model configuration (NSE of 0.57, 0.56 and 0.64 for the three catchments) implements a λ of 0.05, the AMC correction method proposed by Neitsch et al. (2011), and the re-infiltration method of Van Loo (2018), calculating overland flow velocity with Manning’s n adjusted to seasonal vegetation cover variations. As this model allows for spatial interaction through re-infiltration, but with limited computation times, it is well applicable for iterative spatial optimization analyses, although a more extensive calibration and validation exercise on catchments with a wider range of characteristics is required to provide a general assessment of its applicability and accuracy.

MAXIMUM FLOW STUDY BY THE HYDROGRAM METHOD FOR A WATERSHED IN THE SOUTH OF SANTA CATARINA, BRAZIL

Knowing the maximum flow and its return period is extremely important for safely dimension hydraulic projects for flood prediction and control and also water erosion prediction. Thus, this study aimed to evaluate Capivari river watershed maximum flow, located in south of Santa Catarina, that has a flooding history. The method used was The United States Soil Conservation Service (SCS) Triangular Unit Hydrogram method (current Natural Resources Conservation Service), and, for effective rainfall, the US Curve Number (SCS-CN) method is used. To estimate the maximum flow in the watershed, three background moisture scenarios (CNI, CNII and CNIII) and six empirical equations proposed for rural watersheds were adopted to calculate the concentration time. To evaluate the observed upstream flow, a 34-years historical series was used, measured at the São Martinho downstream fluviometric station (code 84598002), located in the outlet section of the study watershed. The results showed that the maximum flows estimated by the SCS-CN method for the conditions of CNII and CNIII had greater differences (-198% and -287%) compared to the observed flow. The smallest differences were verified for the CNI condition for all the analyzed return periods (2, 5, 10, 15, 20, 25, 50 and 100). Also, it was observed that, the longer is the return period, smaller the difference among the maximum observed and estimated flows, and, the smallest was verified for the 50-year period, indicating that this is the most appropriate for studies of extreme events in the study watershed.

Impact of Land Use Change Due to Urbanisation on Surface Runoff Using GIS-Based SCS–CN Method: A Case Study of Xiamen City, China

Rapid urban development results in visible changes in land use due to increase in impervious surfaces from human construction and decrease in pervious areas. Urbanisation influences the hydrological cycle of an area, resulting in less infiltration, higher flood peak, and surface runoff. This study analysed the impact of land use change due to urbanisation on surface runoff, using the geographic information system (GIS)-based soil conservation service curve number (SCS–CN) method, during the period of rapid urban development from 1980 to 2015 in Xiamen, located in south-eastern China. Land use change was analysed from the data obtained by classifying Landsat images from 1980, 1990, 2005, and 2015. Results indicated that farmland decreased the most by 14.01%, while built-up areas increased the most by 15.7%, from 1980 to 2015. Surface runoff was simulated using the GIS-based SCS–CN method for the rainfall return periods of 5, 10, 20, and 50 years. The spatial and temporal variation of runoff was obtained for each land use period. Results indicate that the increase in surface runoff was highest in the period of 1990–2005, with an increase of 10.63%. The effect of urbanisation can be realised from the amount of runoff, contributed by built-up land use type in the study area, that increased from 14.2% to 27.9% with the rise of urban expansion from 1980 to 2015. The relationship between land use and surface runoff showed that the rapid increase in constructed land has significantly influenced the surface runoff of the area. Therefore, the introduction of nature-based solutions such as green infrastructure could be a potential solution for runoff mitigation and reducing urban flood risks in the context of increasing urbanization.

A GIS Based Methodology to Obtain the Hydrological Response to Storm Events of Small Coastal Basins, Prone to Flash Flooding

The present study aims to investigate the hydrological response of small coastal watersheds to storm events. Areas around the Mediterranean Sea are usually characterized by streams with intermittent flows and flash floods are common. Firstly, we analyze the geomorphological, soil and land cover characteristics of the watershed in order to estimate their effect on surface runoff. Furthermore, the rainfall characteristics of an extreme event that caused flash flooding in the past are analyzed. By combining these factors, we are able to predict the response of this basin to severe storm events. The study area is located in the island of Samos, in Eastern Greece, where flash flood events are usual and pose a risk to areas located around rivers. In this area runoff is intermittent, occurring mainly during storm events and there is a lack of discharge or other instrumental measurements. By applying the SCS-CN method we estimate the response of two of the largest watersheds in Samos Island, through the construction of a Synthetic Unit Hydrograph (SUH). Firstly, we examined the record of historic floods in the area, selecting a large flash flood event (November 2001) and then obtained the daily rainfall data, which are used by the SCS method for the calculations. We applied the SCS methodology in order to estimate various parameters (e.g. lag time, time of concentration, maximum discharge), which also required the calculation of the Curve Number (CN) for each watershed. During this event (136 mm rainfall), we calculated a direct runoff (excess rainfall) of 44%-48% for these watersheds. This methodology can be particularly useful in simulating the hydrological response of small Mediterranean watersheds and to introduce better strategies for the management of the whole drainage basin.

Rainfall-Runoff Analysis using Runoff Coefficient and SCS-CN Methods under GIS Approach

Estimation of runoff in a watershed is very important to manage the water resources efficiently. In this regard, surface runoff quantification is an essential study. The main objective of this study is to quantify the surface runoff of the catchment area of a well located in AEC & RI, TNAU, Kumulur, Trichy District of Tamil Nadu State, India. An attempt also made to analyze the surface runoff by SCS-CN event and annual basis as well as by modified runoff-coefficient method. This study identified the variation of runoff volume within different approaches of SCS-CN method and runoff coefficient method. By using GPS and GIS techniques catchment area of a well and slope direction was delineated. With the help of GIS tools and remote sensing technology with ground truth verifications, the land use/ land cover and soil maps were delineated for the study area. Sandy loam and sandy clay loam type of soils are predominating and HSG ‘C’ was identified for the study area. The highest CN value is 92 and the maximum runoff coefficient value is 0.95 for the Built-up land, the lowest CN value is 71 and the lowest runoff coefficient is 0.11 for the area covered with trees. Three AMC conditions were considered while estimating runoff volume by SCS-CN event approach. Among 15 years of rainfall data from 2004 to 2018, the highest runoff 38452.36 m3 was generated in the year 2005 and the lowest runoff 8718.29 m3 was generated in 2018 by SCS-CN event basis method. From this study between two concepts of SCS-CN and runoff coefficient models, the SCS-CN model with an event basis approach is yielding productive results. For quantifying surface runoff and for planning water conservation structures event basis calculations are more effective.

SCS-CN-Based Improved Models for Direct Surface Runoff Estimation from Large Rainfall Events

This study presents a procedure to estimate more accurate direct surface runoff from large rainfall (>25.4 mm)-runoff events. Improved models (M5-M7) are derived by coupling two concepts: (i) initial abstraction as 2% of the total rainfall and (ii) runoff coefficient = degree of saturation. Performance of ten different models including the original SCS-CN method (M1), Mishra and Singh 2002 (M2), Mishra et al. 2006 (M3), Ajmal et al. 2016 (M4), improved models (M5-M7) and their simplified forms (M8-M10) is evaluated using large (7687) number of rainfall events derived from 98 watersheds of USDA-ARS to assess the accuracy of runoff estimation. Quantitatively, it is assessed using seven performance indices, viz., R2, NSE, PBIAS, RMSE, NRMSE, RSR, and MAE; categories; and Ranking and Grading System (RGS). The resulting high values of R2, RSR, RGS, and lowest values of NSE, PBIAS, RMSE, NRMSE, and MAE for the improved models (M5-M7) reveal that improved models performed better than the existing models (M1-M4). Similarly, based on different performance categories, all improved models exhibited superior performance in most of the watersheds than did the existing models. Sensitivity analysis indicated CN to be the most sensitive parameter of the improved model. The proposed model is seen to have overcome the limitations of the original and its previous versions intended for large events and can thus be used for estimating runoff more accurately.

Rainfall runoff estimation using GIS and SCS-CN method for awash river basin, Ethiopia

Understanding hydrological behavior is an important part of effective watershed management and planning. Runoff resulted from rainfall is a component of hydrological behavior that is needed for efficient water resource planning. In this paper, GIS based SCS-CN runoff simulation model was applied to estimate rainfall runoff in Awash river basin. Global Curve Number (GCN250), Maximum Soil Water Retention (S) and Rainfall was used as an input for SCS-CN runoff simulation model. The final surface runoff values for the Awash river basin were generated on the basis of total annual rainfall and maximum soil water retention potential (S) of the year 2020. Accordingly, a runoff variation that range from 83.95 mm/year to a maximum of 1,416.75 mm/year were observed in the study region. Conversely, recently developed Global Curve Number (GCN250) data was tested with Pearson correlation coefficient to be used as an input for SCS-CN runoff simulation model. In doing so, predicted runoff generated in SCS-CN using GCN250 as a model input was validated with observed runoff obtained from station gauges in the study region. The results of validation show that, predicted runoff was well correlated with observed runoff with correlation coefficient of 0.9253. From this stand point, it is observed that the new GCN250 data can be used as an input for SCS-CN model to estimate rainfall runoff at basin level. Furthermore, correlation analysis was performed to explain the relationship between mean annual rainfall and surface runoff. The relationship between these two variables indicates a strong linear relationship with correlation coefficient of 0.9873.

Investigating impact of land-use and land cover changes on hydro-ecological balance using GIS: insights from IIT Bombay, India

The present study, for the first time, examined land-use land cover (LULC), changes using GIS, between 2000 and 2018 for the IIT Bombay campus, India. Objective was to evaluate hydro-ecological balance inside campus by determining spatio-temporal disparity between hydrological parameters (rainfall-runoff processes), ecological components (forest, vegetation, lake, barren land), and anthropogenic stressors (urbanization and encroachments). High-resolution satellite imageries were generated for the campus using Google Earth Pro, by manual supervised classification method. Rainfall patterns were studied using secondary data sources, and surface runoff was estimated using SCS-CN method. Additionally, reconnaissance surveys, ground-truthing, and qualitative investigations were conducted to validate LULC changes and hydro-ecological stability. LULC of 2018 showed forest, having an area cover of 52%, as the most dominating land use followed by built-up (43%). Results indicated that the area under built-up increased by 40% and playground by 7%. Despite rapid construction activities, forest cover and Powai lake remained unaffected. This anomaly was attributed to the drastically declining barren land area (up to ~ 98%) encompassing additional construction activities. Sustainability of the campus was demonstrated with appropriate measures undertaken to mitigate negative consequences of unwarranted floods owing to the rise of 6% in the forest cover and a decline of 21% in water hyacinth cover over Powai lake. Due to this, surface runoff (~ 61% of the rainfall) was observed approximately consistent and being managed appropriately despite major alterations in the LULC. Study concluded that systematic campus design with effective implementation of green initiatives can maintain a hydro-ecological balance without distressing the environmental services.

Estimation of surface runoff for an agricultural watershed using remote sensing and GIS based curve number method

Water is a very important part of life circle, due to which life flourishes in Earth. In today’s scenario water scarcity is becoming the major problem so there is an urgent need to conserve it. In order to manage the scare water resources efficiently estimation of runoff in a watershed is very important factor. In India the availability of accurate runoff information is rare where most of the watersheds are ungauged, which poses a serious challenge for hydrologists. Number of mathematical models is available to quantify runoff. Soil Conservation Services-Curve Number method (SCS-CN) is used for computing the runoff depth based on the rainfall depth.In the present study SCS-CN method has been applied to estimate the runoff depth in Maniari watershed in Lormi block of Mungeli District Chhattisgarh state. This method is based on one parameter i.e. curve number which is basically a coefficient that is used to estimate runoff due to rainfall. layers has been prepared namely base map, soil map, land use map and other maps of the study area using GIS and remote sensing data. Based on the rainfall data of the study area, daily runoff depth has been estimated. Integration of GIS with the SCS-CN method is used for estimating runoff from the un-gauged watersheds for better watershed management and conservation purposes.

A rapid flood inundation model in the floodplain area due to an extreme rainfall event

Extreme rainfall in East Jakarta on February 19, 2021 caused flooding in a number of subdistricts. The research was conducted in the central part of Kali Sunter, which flows through three subdistricts, namely Cipinang Melayu, Cipinang Muara, and Pondok Bambu. The purpose of the study was to do flood hazard modeling and analyze the characteristics of flood-affected areas based on land use and topography. Inundation and flood hazard maps is done by: calculating the flood discharge using the SCS-CN method, flood inundation modelling using HEC-RAS, and analyzing the characteristics of the inundated area. This combination is effective for rapid modeling during extreme rainfall events. Based on the research, the distribution of the highest flood hazard area is in RW 004 Cipinang Melayu, with the widest inundation affecting small and medium-sized houses. The characteristics of the affected area are that there is green and empty land which reduces the potential for water to inundate buildings or other land uses. Buildings located in low-hazard housing areas tend to be more organized and relatively medium to large in size. While the types of housing in the Cipinang Melayu with a high level of danger tend to be dense and small to medium in size, but the majority have two floors as a form of flood adaptation.

Surface runoff estimation of Sind river basin using integrated SCS-CN and GIS techniques

Rainfall and runoff are the significant hydrologic component in the water resources assessment. Numerous methods are available to estimate runoff from rainfall; however, the SCS-CN method remains the most popular and frequently used method as runoff curve number (CN) is a crucial factor of the SCS-CN method and depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Besides this, various parameters, such as Hydrological Soil Characteristics (HSG), precipitation (P), Potential Maximum Retention (PMR), Antecedent Moisture Condition (AMC), Weighted Curve Number (WCN), are the mandatory inputs to the SCS-CN model. In the results, the daily runoff from the Sind river basin for ten years, i.e., 2005 to 2014, has been used. As a result, the average annual surface runoff calculated for the Sind river basin is 133.71 mm. The total average volume of runoff is 35.04 × 10 8 m 3, representing 17.21% of the total average annual rainfall.

Coupled empirical–mechanical modeling of debris flows occurred in small ungauged basins

On 28 July 2013, an intense torrential rainfall occurred at the boundary of Yamaguchi and Shimane Prefectures in western Japan, and triggered a debris flow on an ungauged hillslope to bury the entrance of Shirai tunnel and to shutdown railway service in that region for 1 year. To assess this disaster, this study aims at numerically modeling this debris flow event through a methodology incorporating empirical hydrologic analysis and mechanical debris flow model. For hydrologic analysis, the SCS-CN method implemented by HEC-HMS was used to obtain direct runoff hydrograph with high-resolution precipitation data reanalyzed using observations from radars and rain gauges. Then, the obtained runoff-discharge information was applied as an input for numerically simulating the debris flow movement from source to deposition areas. The simulation result is verified by the field evidence from field survey. The study demonstrates the applicability of the proposed empirical–mechanical approach for assessing debris flows in ungauged basins.

Application of the SCS–CN Method to the Hancheon Basin on the Volcanic Jeju Island, Korea

This study investigates three issues regarding the application of the SCS–CN (Soil Conservation Service–Curve Number) method to a basin on the volcanic Jeju Island, Korea. The first issue is the possible relation between the initial abstraction and the maximum potential retention. The second is the determination of the maximum potential retention, which is also closely related to the estimation of CN. The third issue is the effect of the antecedent soil moisture condition (AMC) on the initial abstraction, maximum potential retention and CN. All of these issues are dealt with based on the analysis of several rainfall events observed in the Hancheon basin, a typical basin on Jeju Island. In summary, the results are that, firstly, estimates of initial abstraction, ratio λ, maximum potential retention, and CN were all found to be consistent with the SCS–CN model structure. That is, CN and the maximum potential retention showed a strong negative correlation, and the ratio λ and the maximum potential retention also showed a rather weak negative correlation. On the other hand, a significant positive correlation was found between CN and the ratio λ. Second, in the case where the accumulated number of days is four or five, the effect of antecedent precipitation amount is clear. The antecedent five-day rainfall amount for the AMC-III condition is higher than 400 mm, compared to the AMC-I condition of less than 100 mm. Third, an inverse proportional relationship is found between the AMC and the maximum potential retention. On the other hand, a clear linear proportional relation is found between the AMC and CN. Finally, the maximum potential retention for the Hancheon basin is around 200 mm, with the corresponding CN being around 65. The ratio between the initial abstraction and the maximum potential retention is around 0.3. Even though these results are derived by analyzing a limited number of rainfall events, they are believed to properly consider the soil characteristics of Jeju Island.

Study on the applicability of the SCS-CN-based models to simulate floods in the semi-arid watersheds of northern Algeria

Algeria has experienced catastrophic floods over the second half of the twentieth century, causing many deaths and extensive material damage. This study was conducted to find a suitable event-based rainfall-runoff (RR) model for semi-arid conditions, where continuous data are not available in all regional basins. The study compared, based on data availability, the SCS-CN model based on the antecedent moisture conditions (AMC) and four modified SCS-CN models incorporating antecedent moisture amounts (AMA) in order to find the best model to reproduce the flood hydrographs in two catchments. The modified models were predominant over the SCS-CN method. Nonetheless, the Singh et al. (Water Resour Manag 29:4111–4127, 2015. https://doi.org/10.1007/s11269-015-1048-1 ) model (M4) and the Verma et al. (Environ Earth Sci 76:736, 2017a. https://doi.org/10.1007/s12665-017-7062-2 ) model (M5) were superior and demonstrated more stable structures. Coupled with the Hayami routing model, the models showed promising results and were able to reproduce the observed hydrographs’ shape. However, it was impossible to choose the preferred model since they each excelled as to a criterion. Therefore, the corresponding outputs were combined using the simple average (SA) method and the weighted average (WA) method. We found that the WA method showed better results in the two catchments and allowed a more accurate prediction according to the performance criteria.

Integrated urban water resources management strategy for a smart city in India

Abstract Economic growth of any nation like India depends on growth of cities. In India 31% of the total population exists in urban areas. The smart city mission of India was established with the objective to deliver the basic requirements of the citizens in a sustainable manner. Madurai city located at Peninsular India with a 1.4 million population was taken for this study. The objective was to develop an integrated urban water management strategy after analysing all the components of the urban water cycle such as rainfall, runoff, groundwater and wastewater. The population forecast for 2021 was carried out for the Local Planning Area of 726.34 km2 and the water demand was calculated as 109 Mm3/year. To meet the demand, runoff from the average rainfall was estimated as 393 Mm3/yr using the SCS-CN method. The storage capacity in the water bodies to store the surface water was estimated as 156 Mm3/yr and groundwater recharge potential was estimated as 22 Mm3/yr. The integrated urban water management strategy developed, shows that there is a huge potential for rainwater storage at the surface level and subsequent recharge through artificial recharge techniques.