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The Soil Conservation Service Curve Number (SCS-CN) method is popular for predicting surface runoff due to its simplicity, ease of application, and widespread acceptance. However, it has limitations, such as the neglect of storm duration, a lack of guidance on antecedent moisture conditions, and the assumption of a constant initial abstraction coefficient (λ = 0.2), leading to uncertainty. Its reliance on static land use classifications and empirical assumptions limits its accuracy across diverse geographic regions and complex hydrological scenarios, particularly under extreme weather conditions. Furthermore, selecting the most suitable watershed CN values remains a subject of global debate. Moreover, the model is widely applied beyond its originally intended purpose. Its basic assumptions, flexibility in dealing with different hydrological conditions, and susceptibility to variables including soil type, land use, and antecedent moisture conditions have all drawn criticism for the method. To overcome the original curve number method limitations, many studies have been made on improving the SCS-CN method. Despite these advancements, significant gaps remain, particularly in the method's applicability across diverse geographic regions and its accuracy in extreme weather events. This paper revisits the popular SCS-CN method, its history, development of methodology, limitations, and refinements that occurred to the original method with the progress of science and technology. It also explores the need for further research to improve its applicability, highlighting opportunities for more robust, flexible runoff estimation models. [ABSTRACT FROM AUTHOR]

【Objective】 Drainage modulus is an important parameter for designing drainage systems in farmland. Taking Suibin county in Sanjiang Plain as an example, this paper analyzes its runoff and drainage modulus. 【Method】 The study site was an area prone to waterlogging. We first calculated the runoff (RO) using historical data on precipitation, pumping stations and land usage, and then estimated it using the runoff generation method (RGM) and the SCS-CN method (RSCS). The drainage modulus associated with each runoff was calculated using both empirical formulae (QE) and the average draining method (QA). The runoff and drainage modulus calculated by different methods were tested against measured data in the field. 【Result】 In the same year and under the same rainfall return period, the measured runoff increased with rainfall duration, while under the same rainfall duration and the same rainfall return period, it decreased with passage of years. The runoff and drainage modulus calculated from different methods differed from the experimentally measured data. For heavy rainfalls, the runoff estimated from different methods was ranked in the order of RGM>RSCS>RO, while for other rainfalls, it was ranked in the order of RSCSQE, whereas for rainfalls lasting 3 days, QA

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The curve number (CN) method is widely recognised as a valuable tool for assessing the correlation between storm rainfall depth and direct runoff. Despite its simplicity, extensive research, and widespread application, the influence of slope and the initial abstraction ratio (λ) on direct runoff, particularly when employing the soil conservation service-curve number (SCS-CN) method, has not received adequate attention. Accurate predictions necessitate accounting for these critical variables. Traditionally, the initial abstraction ratio (λ) has been assumed to be 0.20, in line with the original recommendations of the method's developers. This study scrutinised daily precipitation data from seventeen watersheds across diverse physiographic regions within Iraq's Kurdistan region, collected between 2022 and 2023. The objective was to evaluate the impact of adjusting the curve number for slope and modifying the initial abstraction ratio (λ = 0.1) on direct runoff estimation. Findings revealed that incorporating slope adjustments and employing a revised initial abstraction ratio resulted in more precise runoff predictions compared to the conventional method, which neglected slope and utilised λ = 0.2. Therefore, in the application of the SCS-CN approach, it is essential to adjust the curve number for slopes in mountainous areas and consider the initial abstraction ratio, rather than solely relying on the standard value of 0.2. This study underscores the significance of accounting for local conditions and determining the initial abstraction ratio based on watershed-specific characteristics to enhance the accuracy of direct runoff estimation using the CN method. [ABSTRACT FROM AUTHOR]

Flood simulation in sub-humid regions is one of the difficult issues in hydrology. Liulin experimental watershed, a typical sub-humid region in northern China, was selected for flood simulation. 20 rainfall–runoff events from 1995 to 2021 were selected to calibrate and validate the sub-distributed HEC-HMS model. The applicability of the model to flood simulation in the Liulin experimental watershed was explored. The influences of different runoff generation methods (SCS-CN method and initial constant method) and simulation time steps (1 h and 30 min) on flood simulation were compared. The applicability of the model to different antecedent moisture conditions and different flood characteristics was also analyzed. The results showed that all the schemes of rainfall–runoff models with different runoff generation methods and time steps have satisfactory performance in simulating floods. When the time step is 1 h, the initial constant runoff generation method was more suitable for runoff simulation, however, when the time step is 30 min, the SCS-CN runoff generation method was more robust. As the simulation time step decreased, the model performance was improved, but the improvement amplitude was greater when the SCS-CN method was used. In addition, the model performed better when antecedent moisture was higher, and the flood was single-peak. When the measured peak discharge was lower than 100 m3/s, the model could simulate the peak discharge and peak time better, and conversely, the model could simulate the flood volume and flood hydrograph better. This study is valuable for flood forecasting in sub-humid areas. [ABSTRACT FROM AUTHOR]

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

Soil Conservation Service Curve Number (SCS-CN) method is one of the most widely used, popular, stable, reliable, and attractive rainfall-runoff methods, initially designed for direct surface runoff estimation in small and medium agricultural watersheds. It, in various forms, is now being employed to several areas other than the intended one, such as infiltration, sediment yield, pollutant transport and so on. In this study, the proportionality concept of the SCS-CN method is further extended to the field of flood routing and is shown to either parallel or be analogous to the Muskingum routing method, which is a simplified variant of St. Venant equations. When employed to various real (typical) flood events of four different river reaches available in literature from different sources, and thus, of varying flow and channel settings, the results of SCS-CN concept compare well with those due to Muskingum method in terms of their evaluation for performance through root mean square error (RMSE) for overall hydrograph, and relative error (RE) for peak discharge (Qp) and time to peak (Tp) of all four flood events. It thus underscores not only the efficacy but also the versatility of the SCS-CN concept in application to one more field of flood/flow routing, which forms to be an element of paramount importance in distributed hydrologic modeling. [ABSTRACT FROM AUTHOR]

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

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

Managing groundwater resources in urban areas requires an adequate understanding and assessment of urban hydrogeological systems (structure, components, connections, and imposed conditions) as a part of a larger, dynamically evolving environment. Urbanization and climate change are amongst the widely recognized signs of such a continuous evolution. Within this context, the present study gives a quantitative assessment of the impact of these two factors threatening water resources in urban environments. The Soil Conservation Service-Curve Number (SCS-CN) method is used to conduct a long-term quantitative analysis of the temporal evolution of the potential natural groundwater recharge from precipitation at the scale of Algiers city for an 80-year-long period (1936–2016). The length of the study period allowed us to account for and analyze important changes in urban settings and climatic conditions within the study zone. Overall, two trend shifts over three distinct periods were found to characterize the temporal evolution of precipitation, several climate change indicators defined for the study, and the potential natural aquifer recharge. A strong, approximately 1:4, linear correlation between the estimated city-scale potential natural aquifer recharge and precipitation was observed for the studied period (R2 = 0.748). Moreover, even though the urban area has known a rapid (2nd order polynomial) increase from 1936 to 2016, climate change (accounted for via the changes in precipitation regime) impacted the city-scale potential natural groundwater recharge with higher magnitudes than urbanization. Finally, the computed climate change indicators show that starting in the mid-1980s, Algiers has started receiving less precipitations, with fewer heavy rain events and longer dry condition periods. [ABSTRACT FROM AUTHOR]

This present study investigates different techniques for estimating the surface runoff using the Soil Conservation Service Curve Number (SCS-CN) method for the Aghanashini River in Karnataka, India. The SCS-CN method is a simplified approach for runoff estimation, but it does not take into account the actual moisture content in the soil. Consequently, insignificant moisture level changes could induce significant variations in the runoff. The study analyzes six different models based on the SCS-CN method, including the original SCS-CN model and several variations with added features (SCS-CN with slope correction, SCS-CN with λ-optimization, Mishra and Singh, Michel-Vazken -Perrin (MVP), Activation Soil Moisture Accounting SCS-CN). The accuracy of each model was compared using several goodness-of-fit statistics. Furthermore, based on the flood frequency analysis, three large flood events were reported in 2005, 2013, and 2014. The results showed that the MVP model was the best-performing method in simulating runoff. The outcomes of this study can provide valuable information to the local authorities in making informed decisions about flood forecasting and water conservation. HIGHLIGHTS Six mathematical models have been prepared on the basis of SCS-CN for a coastal river basin.; The long-term hydrological simulation of the Aghanashini River has been carried out by taking AMC changes.; Seven statistical indices were used to judge the efficiency of the developed models.; The developed models compute surface runoff with the desired accuracy.;

This study aimed to develop a hydrologic model for the central region (central catchments) located between Dokan and Al-Dibis dams in the Lesser Zab River (LZR) watershed, in Iraq. The hydrologic structure of the study area was prepared based on the DEM layer with 12.5 m spatial resolution by using the GIS environment, and then the HEC-HMS software was used for simulating the main hydrological processes like the infiltration losses, transformation, channel routing, and the baseflow contribution by using the SCS-CN, SCS-UH, Muskingum, and the Recession methods respectively. The corrections of the CN parameter due to the effects of the slope and initial abstraction were used and the resulting CN values for the entire LZR watershed were ranging from 56 to 100. This study concluded the effectivity of using the GIS environment and HEC-HMS software in the continuous rainfall-runoff modelling and achieved very good performance with R2 and NSE criteria of 0.9115 and 0.9 under the calibration phase, while 0.925 and 0.91 values were achieved for the same criteria under the validation phase respectively, also the CN was the most sensitive parameter in the proposed hydrologic model. [ABSTRACT FROM AUTHOR]

Due to the limited number and sparse distribution of meteorological and hydrometric stations in most watersheds, the runoff estimation based on these stations may not be accurate. However, the accurate determination of the Antecedent Soil Moisture (ASM) in watersheds can improve the accuracy of runoff forecasting. The objective of this study is to utilize the ASM derived from satellite imagery to enhance the accuracy of runoff estimation in a mountainous watershed. In this study, a range of Remote Sensing (RS) data, including surface biophysical and topographic features, climate data, hydrometric station flow data, and a ground-based measured SM database for the Balikhli-Chay watershed in Iran, were utilized. The Soil Conservation Service Curve Number (SCS-CN) method was employed to estimate runoff. Two approaches were used for estimating the ASM: (1) using the precipitation data recorded in ground stations, and (2) using the SM data obtained from satellite images. The accuracy of runoff estimation was then calculated for these two scenarios and compared. The mean Nash–Sutcliffe statistic was found to be 0.63 in the first scenario and 0.74 in the second scenario. The inclusion of ASM derived from the satellite imagery in the precipitation–runoff model resulted in a 51% increase in the accuracy of runoff estimation compared to using precipitation data recorded in ground stations. These findings have significant implications for improving the accuracy of ASM and runoff modeling in various applications. [ABSTRACT FROM AUTHOR]

In the West Bank, extreme floods are becoming more frequent. This can be attributed to the expansion of urban areas together with the climate change impacts (the increasing rainfall intensity). This situation worsens given the lack of proper hydraulic infrastructures required to safely dispose of the accumulated floods. Thus, it becomes essential to estimate extreme flood values so as help decision-makers in formulating proper corrective and preventive strategies. This study utilizes the SCS-CN approach to estimate extreme flood values at the different West Bank data-scarce catchments. Maximum annual daily rainfall (MADR) values were used to obtain extreme rainfall daily grids for different selected return periods (10, 25, 50, and 100 years). The GIS was heavily used to apply the SCS-CN method for the entire West Bank catchments. Results show that extreme daily rainfall values are increasing with the increase of the return period. Further, catchments draining into the west (into the Mediterranean Sea) have more extreme daily rainfall values than those draining to the east (into the Dead Sea and the Jordan river) and as such, the expected extreme floods in these catchments are high for the selected return periods. Moreover, based on the average expected extreme flood values, a flood hazard map was developed that classifies West Bank catchments into 5 flood hazard zones. By area, about 42% of the total West Bank catchments are under high to very high flood hazard zone. The results of this research can be adapted to realize any administrative strategy changes for cohesive catchment-based extreme flood hazard management and to prioritize flood remedial plans at the different West Bank catchments. [ABSTRACT FROM AUTHOR]

The Soil Conservation Service Curve Number methodology is widely practiced world over for computation of runoff generated from rainfall in a watershed. It was originally developed for the purpose of conservation of soil from the effect of runoff, which is a major factor governing the soil erosion and its transport, in small agricultural watersheds. Since inception in 1956, its application has been extended to a number of areas such as infiltration, flood, drainage, and water availability, sediment yield, water quality and climate change studies. In an attempt to suggest an improved version, the effect of rainfall intensity (i.e., the ratio of rainfall to rain duration) and antecedent moisture, greatly affecting the runoff quantity but originally ignored, has been studied by postulating different variations of the method. The effect of rainfall intensity is considered by Models M1 and M2, an explicit form. Model M3 incorporates both initial soil moisture and rainfall intensity, and its explicit form (with constant model parameter λ = 0.2) is M4. A comparative performance evaluation on a very large dataset containing 48,386 rainfall–runoff events of 140 USA watersheds using several indicators leads to the proposition of Model M3 and its further sensitivity analysis describes the model to be the most sensitive to the amount of input rainfall. The study not only supports the incorporation of storm intensity and initial soil moisture in the model formulation but also proposes an alternative version for rainfall–runoff studies required for enhanced water use efficiency through irrigation scheduling. [ABSTRACT FROM AUTHOR]

The use of the soil conservation service (SCS) curve number (CN) model for estimation of the rainfall excess and the SCS-unit hydrograph (UH) model are common tools for flood studies in arid regions. In this research, we are investigating the capability of these models to simulate flood events in the arid region under the common parametrization provided by the SCS model (SCS-CN, the initial abstraction ratio, λ, and UH theory) and the optimum parameterization for best simulating the hydrologic response. A case study is performed in Al-Lith basin in the west of Saudi Arabia (SA). The study simulates measured rainfall-runoff events in the area using seven scenarios (various SCS-CN estimation methods: least-squares method (CNLSM), asymptotic fitting method (CN∞), SCS-CN tables (CNdesign), and antecedent moisture content CN (CNI, CNII, and CNIII), λ = 0.2 and 0.01, and SCS-UH and UH derived from streamflow data) and a comparison is made between the observations and model results under the common parameterization of the SCS model and parameterization estimated from the Saudi arid environment. The comparison between simulated and observed peak flow and runoff volume of the studied events shows high scatter which is a common feature in arid regions due to the inherent uncertainties in the hydrological processes which are not yet resolved due to the lack of detailed measurements of the rainfall-runoff processes. Statistical analysis showed that λ = 0.01 provides a minimum root mean square error (RMSE) in the peak flow (24.8 m3/s) and the runoff volume (0.31 million m3) with CNLSM obtained by LSM. CN∞ is bad to simulate the hydrologic response. The SCS-CN Tables cannot be used for hydrological simulation. They can rather be used for the design purposes of mitigation structures.

This study attempts to validate an infiltration model, the Soil Conservation Service–Curve Number (SCS–CN) method, using the nonofficial intermittent occurrence data of Eongtto Falls on Jeju Island, Korea. Simply due to the limited official continuous runoff data concerning Jeju Island, the validation of a newly set SCS-CN method for Jeju Island was practically impossible. Instead, this study tries to use nonofficial data for this purpose. This study focuses on the intermittent occurrence of Eongtto Falls, which is one of the most famous tourist attractions on the island. Various records of Eongtto Falls can be collected from newspapers, personal homepages, and various social networking services. The SCS-CN method is, in this study, used to check if effective rainfall occurs or not. In fact, this approach is quite effective on Jeju Island, as most streams are fully dry during non-rain periods. Evaluation of the SCS-CN method is based on the analysis of a contingency table, which measures the consistency of the occurrence of effective rainfall events and waterfall records. Additionally, to quantify the results of the contingency table, some measures such as accuracy, hit ratio, and false alarm ratio are used. This analysis is carried out using all the rainfall events from 2011 to 2019, and the derived results confirm that the newly set SCS-CN method is far better than the conventional one used thus far. [ABSTRACT FROM AUTHOR]

Nitrogen (N) loss by surface runoff inevitably results in severe N pollution and eutrophication of aquatic ecosystems. In this study, surface runoff from different land uses in the East Tiaoxi River watershed was collected, and the N concentrations, sources and losses were measured using the dual isotope (δ15N-NO3− and δ18O-NO3−), a Bayesian isotopic mixing (SIAR) model and Soil Conservation Service Curve Number (SCS-CN) method. The results showed that the N concentrations in surface runoff from agricultural lands were higher than those from urban areas and forestlands, and nitrate (NO3−), particulate nitrogen (PN) and dissolved organic nitrogen (DON) were the major forms of N in surface runoff in the East Tiaoxi River watershed. The total loss rate of total nitrogen (TN) from surface runoff in the East Tiaoxi River watershed was 5.38 kg·ha−1·a−1, with NO3−-N (46%) contributing the most to TN loss. The TN, and NO3−-N loss rates in surface runoff from tea planting lands (21.08 kg·ha−1·a−1, 11.98 kg·ha−1·a−1) and croplands (16.93 kg·ha−1·a−1, 10.96 kg·ha−1·a−1) were high, those from vegetable lands and urban areas were medium, and those from economic and natural forestlands were low in the East Tiaoxi River watershed. The NO3−-N contributions of chemical fertiliser (CF), soil N (SN), sewage/manure (SM), and atmospheric deposition (AD) in surface runoff in the East Tiaoxi River watershed were 124.32 × 103, 104.84 × 103, 82.25 × 103 and 58.69 × 103 kg·a−1, respectively. The N pollutant losses in surface runoff from agricultural lands (croplands with rice growing, vegetable lands and tea planting lands) were responsible for most of the N pollutants being transported into the East Tiaoxi River systems. [ABSTRACT FROM AUTHOR]

IntroductionIn complex mountain basins, hydrological forecasting poses a formidable challenge due to the intricacies of runoff generation processes and the limitations of available data. This study explores the enhancement of short-term runoff forecasting models through the utilization of long short-term memory (LSTM) networks.MethodsTo achieve this, we employed feature engineering (FE) strategies, focusing on geographic data and the Soil Conservation Service Curve Number (SCS-CN) method. Our investigation was conducted in a 3,390 km2 basin, employing the GSMaP-NRT satellite precipitation product (SPP) to develop forecasting models with lead times of 1, 6, and 11 h. These lead times were selected to address the needs of near-real-time forecasting, flash flood prediction, and basin concentration time assessment, respectively.Results and discussionOur findings demonstrate an improvement in the efficiency of LSTM forecasting models across all lead times, as indicated by Nash-Sutcliffe efficiency values of 0.93 (1 h), 0.77 (6 h), and 0.67 (11 h). Notably, these results are on par with studies relying on ground-based precipitation data. This methodology not only showcases the potential for advanced data-driven runoff models but also underscores the importance of incorporating available geographic information into precipitation-ungauged hydrological systems. The insights derived from this study offer valuable tools for hydrologists and researchers seeking to enhance the accuracy of hydrological forecasting in complex mountain basins.

In this paper, we aim to define a procedure of flood hazard assessment applicable to large river basins in which flood events can be induced/sustained by the full basin area or by fractions of the total area as functions of the extent of the triggering precipitation event. The proposed procedure is based on a combined approach accounting for (1) the reconstruction of intensity–duration–frequency curves expressing the magnitude in terms of intensity for multiple return periods; (2) the application of the soil conservation service method for runoff estimation from a selected rainfall scenario considering some characteristics of the basin (i.e. soil type, land use/treatment, surface condition, and antecedent moisture conditions); (3) 2D hydrodynamic modelling conducted by the HEC-RAS model using runoff hydrographs as hydrological input data; (4) the reconstruction of flood hazard maps by overlaying multiple inundation maps depicting flood extent for different return periods. To account for the variability in the extent of the triggering precipitation event and the resulting input hydrograph, multiple contributing areas are considered. The procedure is tested at the archaeological site of Sybaris in southern Italy, which is periodically involved in flood events of variable magnitude. The obtained results highlight that the variable extent of the floodable area is strongly conditioned by the extent of the contributing area and return period, as expected. The archaeological site is always involved in the simulated flooding process, except for the smallest contributing area for which only a 300-year event involves this part of the site. Our findings may be useful for developing and supporting flood risk management plans in the area. The developed procedure might be easily exported and tested in other fluvial contexts in which evaluations of multiple flood hazard scenarios, due to the basin geometry and extent, are needed. [ABSTRACT FROM AUTHOR]

Contextualization: Wetlands are deteriorated, mainly due to human activities that cause degradation processes in the wetlands, due to changes in land use, causing conflicts between people living near to the wetlands, as well as consequences in the supply of resources for the population. Anthropic activities affect water resources, which limits the ecosystem services that wetlands provide. Knowledge gap: There is no information about the availability of water resources in the wetland area, that information would contribute for an efficient and inclusive water governance in the area and could support the formulation of public policies about the integrated management of water resources, thus it would maximize social and economic welfare in the municipality. To achieve those objectives, it is necessary to determine the mentioned availability to conserve the wetland ecosystems of regional importance. Purpose: This research estimated the [net] available surface water supply, using the rainfall-runoff method, in El Gallinazo wetland, located on Aguachica (Cesar-Colombia), as a contribution to the integral management of the hydric resource. Methodology: It was identified the vegetation cover of the area, using the Corine Land Cover method adapted for Colombia, the hydrological group was determined by examining the soil texture; with these two inputs the number of curves was determined through tables. The research included the calculation of the mean annual precipitation, using the Kriging interpolation method, with the help of ArcGIS software and the meteorological data extracted from IDEAM stations to determine the effective precipitation of the area. In addition, the rainfall-runoff method, based on the number of curves (SCS-CN), and the resolution 865 of 2004 were used to establish the net available water supply of El Gallinazo wetland. Results and conclusions: The area has two types of vegetation cover, three hydrologic soil groups, and an average NC of 59,29, demonstrating a moderately high runoff potential and a moderate infiltration capacity; the available annual water supply was estimated at 42573,6 m³. The behavior of water availability depends on the anthropic activities developed inside and outside the wetland, as well as on the precipitation regime. [ABSTRACT FROM AUTHOR]

In this study, a hybrid approach has been used to increase the predictive efficiency of the SCS-CN model. A recently proposed Ajmal model (developed after randomized configuration) that ignored initial abstraction and maximum potential retention has been given the conceptual framework of the SCS-CN model and a new outcome-based hybrid model (Miv) was formulated. A total of 78 watersheds (7817 events) were used for calibration and the remaining 36 watersheds (3967 events) for validation to develop this hybrid model. The numerical value of hybrid model parameters Lc, λ and S were calibrated using calibration dataset and a simple non-linear one-parameter model has been developed. The performance of the Ajmal (Miii) and hybrid model (Miv) was compared with the original SCS-CN method (λ = 0.2 as Mi and λ = 0.05 as Mii). The performance of models was compared by using four statistical error indices i.e. RMSE, NSE, PBIAS, and n(t) and applying ranking and grading system (RGS). The mean RMSE, NSE, PBIAS, and n(t) values were found superior for Miv (5.60 mm, 0.71, 6.97%, 1.15) model followed by Miii (5.98 mm, 0.65, 16.52%, 1.01), Mii (6.27 mm, 0.61, 20%, 0.90) and Mi (6.98 mm, 0.46, 24.2%, 0.72) model for tested watersheds. The hybrid model (Miv) exhibited consistently well performance for all size watersheds. On the basis of the agreement between watershed runoff coefficient (C) and calibrated model parameter (Lc or CN), R2 value was found relatively higher for hybrid model (Miv) than other models. HIGHLIGHTS The Ajmal model, which was tested on South Korean watersheds, has been investigated in a large set of US watersheds having different sizes.; The Ajmal model has been given the conceptual framework of SCS-CN model by merging both Ajmal and SCS-CN models and a hybrid model having three parameters (Lc, λ and S) has been evolved.; The three-parameter model was calibrated and a simplified version of the one-parameter hybrid model has been developed.; The performance of the hybrid model was found superior than other models.;

The increased risks of storm flood occurrences in large cities are the result of land use changes due to rapid urbanization. This study examines the influence of land use changes in Khulna City Corporation (KCC) area on surface runoff over a period of 15 years, from 2005 to 2020. Land use–land cover (LULC) maps for 2005, 2010, 2015, and 2020 were created employing support vector machine (SVM)-based supervised image classification using time-series satellite data, and the surface runoff was determined using Soil Conservation Service-Curve Number model. The major land use change drivers of surface runoff were determined through a correlation analysis. Surface runoff was observed to follow a similar trend as that of impervious urban areas, which went up by 5.44% from 2005 to 2020 (17.00 mm increment in average runoff) and the opposite trend was found in vegetation land cover, which declined by 13.34% in areal extent throughout the study period. In comparison with other types of land use, surface runoff changes were most significantly associated with the changes in urban impervious areas and vegetation land use-land cover (LULC) class. In fast-growing cities across the world, and especially in developing nations, the results of this study may serve as a guide for urban storm flood management and urban planning efforts. HIGHLIGHTS Between 2005 and 2020, the urban area increased by 9.82%, while vegetation cover dropped by 13.24%.; During 2005–2020, the relative degree of average runoff depth on a particular day with a 100-year rainfall event rose by 5.44% (17.00 mm).; The increase in runoff depth was found to be positively and negatively correlated with the expansion of urban impervious areas and changes in vegetation land cover class, respectively.;

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

Rainwater harvesting is an important step towards maximizing the water availability and land productivity in arid and semi-arid areas. The present study shows that the area of Ghazi Tehsil within Khyber Pakhtunkhwa Province, Pakistan, has great potential for rainwater harvesting due to its feasible climatic and topographic conditions. This area of 348 km2 normally receives high rainfall annually, but, due to hilly terrain, the bulk of rainwater is lost in the runoff process. In order to enhance agricultural output for such a large area, the practice of rainwater harvesting is a sustainable and decisive approach. However, the selection of appropriate sites for rainwater harvesting on a large scale presents a critical challenge. In such areas, geospatial technology has proved very decisive in the identification of potential sites. In this study, we have used the HEC-GeoHMS tool (ArcGIS 9.3) to compute a curve number to represent the effects of rainfall against the hydrological soil group and landcover. Subsequently, the curve number was used as an input parameter in the soil conservation service runoff-curve number (SCS-CN) method to estimate surface runoff potential for different combinations of landcover and hydrological soil groups. It was observed that runoff was higher in mountainous areas and relatively low in plain areas. Finally, to identify the potential sites for rainwater harvesting, weighted overlay analysis-based related thematic map layers were further reclassified, and weights were assigned according to the technical guidelines of suggested international standards and under consideration of the study area's topographic, hydrological, and climatic factors. As a result, about 20% of the area was found suitable, 52% less suitable, and 29% as not suitable. Furthermore, relative suitability was assigned to the results of suitable sites as an input for the identification of potential sites for different rainwater harvesting storage structures. These results show that 10% of the area was suitable for farm ponds, 5.74% for check dams, 21.5% for Nigarims, and 8.9% was found to be suitable for gully plugs. The comparison of our GIS-derived and field-based results spatially affirms that the analyzed results were agreeably overlaid in the context of spatial results for check dams, gully plugs, and Nigarims. [ABSTRACT FROM AUTHOR]

The Soil Conservation Service Curve Number (SCS-CN) method is one of the popular methods for calculating storm depth from a rainfall event. The previous research identified antecedent rainfall as a key element that controls the non-linear behaviour of the model. The original version indirectly uses five days antecedent rainfall to identify the land condition as dry, normal or wet. This leads to a sudden jump once the land condition changes. To obviate this, the present work intends to improve the performance of antecedent rainfall-based SCS-CN models. Two forms of SCS-CN model (M1 and M2), two recently developed P-P5 based models (M3 and M4), and an alternate approach of considering P5 in the SCS-CN model (M5 and M6), as proposed here, were investigated. Based on the evaluation of several error metrics, the new proposed model M6 has performed better than other models. The performance of this model is evaluated using rainfall-runoff events of 114 watersheds located in the USA. The median value of Nash-Sutcliffe Efficiency was found as 0.78 for the M6 model followed by M5 (0.75), M3 (0.73), M4 (0.72), M2 (0.63) and M1 (0.61) model. HIGHLIGHTS The study has been done on significant runoff producing events for which runoff coefficient is greater than 0.12.; Research supports the superior performance of the proposed model in US watersheds.; It acknowledges the applicability of five days antecedent rainfall (P5) on runoff prediction and shows improvement in model performance under all statistical indices.;

The aims of this paper are to (I) clarify some issues related to the popular rainfall–runoff SCS-CN (Soil Conservation Service Curve Number) methodology and (II) propose enhanced SCS-CN inspired models for simulation of long-duration (viz., bimonthly, monthly, seasonally, and annually) rainfall-generated runoff and compares its performance with the existing SCS-CN models and Mishra and Singh 1999 model. Issues of SCS-CN are: (a) both C (runoff coefficient) and CN (curve number) with P (rainfall) in contrast to that exhibited by field data, (b) F (infiltration) with Q (direct runoff), (c) Ia (initial abstraction) with S (potential maximum retention), and (d) CN that is also taken as an index of runoff potential. The performance of the proposed SCS-CN inspired models (M3-M8), the existing SCS-CN models (M1 and M2), Mishra and Singh 1999 model (M9), and a special case of M9 that hypothesizes that initial abstraction coefficient (λ) = 0 (M10) are tested using rainfall–runoff data of four different agro-climatic river basins in Ethiopia. The performance of the models is evaluated using three statistical criteria involving NSE, RSR, and PBIAS. The resulting high NSE values and lowest RSR and PBIAS for the proposed models reveal that proposed models performed better to different (majority) duration datasets than the existing models. Similarly, the proposed models, when employed to the observed datasets of different timescales, performed satisfactorily in both calibration and validation for all watersheds, underlining the efficacy of the proposed models in field applications. [ABSTRACT FROM AUTHOR]

The northern dry zone of Karnataka in Southern India is frequently affected by drought, and the overdraft of groundwater resulted in declining groundwater levels. In this context, spatial estimation of available runoff potential, planning and adoption of site-specific interventions for in-situ moisture conservation, supplementing irrigation and groundwater recharge are of prime concern. Therefore, spatial runoff estimation models were developed subdistrict-wise for the northern dry zone of Karnataka using the Soil Conservation Service Curve Number (SCS-CN) method and GIS. The estimated runoff was validated using the recorded data and was found satisfactory (R2 = 0.90). The results indicated that for major portion of the study area (61.8%), the mean annual rainfall varied spatially from 550 to 800 mm, and the runoff potential ranged from 10.0% to 20.0% of mean annual rainfall from 1951 to 2013. The higher rainfall and runoff potential was observed in the Khanapur subdistrict which lies in the western part of the selected area. It was observed that the number of subdistricts under the low-rainfall category (<550 mm) has increased, whereas the high-rainfall category (>1100 mm) has decreased over the years. Considerable variation in rainfall and runoff potential was observed during above normal, normal and drought years. The runoff generated from most of the study area was below 10.0% of mean annual rainfall in drought year, <30.0% in above normal year and <15.0% in normal year. The northern dry zone of Karnataka is vulnerable to drought and water scarcity, and the runoff potential was estimated under future scenarios using ENSEMBLE data of CMIP 5 to enable planners to design water-harvesting structures effectively. Finally, based on the modeling results, it was found that by 2050s (2040 to 2069), the runoff potential is expected to increase by 20.0% to 30.0% under RCP 8.5 and by 10.0% to 20.0% under RCP 4.5 and RCP 2.6 scenarios. By 2080s (2070–2099), the runoff is predicted to increase by >30.0% under RCP 8.5, by 20.0% to 30.0% under RCP 4.5 and by 10.0% to 20.0% under RCP 2.6, respectively. Even though considerable increase in runoff potential is predicted for the northern dry zone of Karnataka in the coming years, the current runoff potential itself is relatively high, and there is tremendous scope for its harvesting and utilization for in-situ moisture conservation, supplemental irrigation and groundwater recharge to ensure the long-term sustainability of the region [ABSTRACT FROM AUTHOR]

The traditional Soil Conservation Service)SCS(process for calculating the runoff depth tends to be a very tedious and time time-consuming hydrological modeling process. Therefore, a geographic information system (GIS) is now being utilized as a tool alongside the common SCS-CN method for runoff calculations. This research aims to estimate the spatial distribution of runoff depth from Ratga, an agricultural watershed from the Iraqi Western Desert, using the SCS-CN method, GIS, generalized regression neural network (GRNN), field observation dataset, and remote sensing data. The GRNN model was used to predict the soil type based on spectral reflectance data. The results refer to an excellent performance of this model with the maximum absolute error was 8.44%, 14.11%, and 4.15% for sand, silt, and clay soil, respectively, and the sandy soil has the highest correlation coefficient (0.83). The outcome of the SCS method showed the CN value ranged from 70 to 85 of normal conditions. This investigation outline that the maximum volume of surface runoff of the 2018 to 2020 years was 4,324,528 m3. This paper proves that incorporating GIS with the SCS-CN model and ANN provides a robust tool for calculation runoff depth in the Iraqi Western Desert, representing barren catchments of Iraq. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to evaluate the impact of land cover resolution, in comparison with the digital elevation model (DEM) resolution, on hydrological modeling outputs. Three different basins in the various resolutions of DEM (12.5, 25, 50, 100, 500 and 1,000 m) and land-use maps (250, 1,000 and 2,500 m) were collected in this study, and the hydrological modeling process was performed using the Soil and Water Assessment Tool (SWAT) model. The soil type resolution was 1,000 m for all basins, and the runoff modeling was done based on the Soil Conservation Service Curve Number (SCS-CN) method. The final model outputs showed that the DEM cell size variations affect significantly the topographical characteristics of a catchment such as area, mean slope, river network and time to concentration which alter the flood modeling outputs especially in hilly watersheds (mean slope more than 15%) up to 15% for a DEM cell size of 1,000 m in comparison to 12.5 m. Also, the resolution and spatial distribution of land cover maps which directly specify SCS-CN values, can change the output simulated runoff results up to 49% for a land cover cell size of 2,500 m in comparison to 250 m. These results indicated that the quality of the land cover map is more important than the quality of DEM in hydrological modeling. Also, the results showed that for an identical land-use cell size, the differences between model outputs using DEM cell sizes less than 100 m were not very significant. Furthermore, in all models by increasing the DEM cell size, the simulated runoff depth was decreased. HIGHLIGHTS The study attempts to show the impact of land-use resolution on hydrological model outputs.; The effect of the resolution of land-use data, CN estimating and uncertainties of SWAT outputs are discussed in this paper.; This paper shows that land-use land cover resolution is more important than DEM resolution in hydrological modeling.; This paper would be useful to improve hydrological model outputs.; This paper suggests the best DEM resolution for hydrological modeling.;

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.

The paper presents the results of a case study that was prepared as a basis for decision-making processes in the context of the impacts of global climate change. The article is focused on a very important part of the urban environment, namely urban forests. When taking planning measures in periurban forests, two realities must always be addressed, i.e., adaptation measures to mitigate the effects of climate change on the forest complex in question and its use to mitigate the effects of climate change in its surroundings must both be considered. It is a well-known fact that forest communities (of any kind) are on the one hand affected by the impacts of climate change, but on the other hand are able to mitigate its effects on their surroundings. The case study was of land near the town of Mladá Boleslav. The aim was to analyse the hydrological regime of the Štěpánka Forest Park, nicknamed "the lungs of Mladá Boleslav". Modelling of the runoff coefficient was made for the whole park area, as well as for the part on the left bank of the Klenice River (forested part). The runoff conditions of the site and their subparameters are addressed in the study by comparing the current state with the modelled state after deforestation of the site, e.g., due to drought. As far as the spatial layout of the forest is concerned, it is absolutely essential to maintain an integrated stand on the site with a lower stem cover (fewer individuals per plot) and a lower regeneration period. These aspects of a growing matrix forest stand will ensure its sustainability, in particular the sustainable water management of the trees in the context of lower water reserves in the rhizosphere and the greater ability of younger individuals to adapt to changes in site conditions (replacement of stress-resistant types by resilient types). [ABSTRACT FROM AUTHOR]

This study investigated the suitable Initial abstraction ratio (λ) for estimating the depth of runoff in northern Thailand. The Initial abstraction ratio (λ) and curve number (CN) are two catchment parameters in the Natural Resources Conservation Service-Curve Number method (NRCS-CN). In addition, the λ is considered a regional parameter, therefore, a rainfall-runoff model for estimating streamflow in first-order and ungauged headwater of the tropically medium-sized watersheds in northern Thailand should be created to gain the more accurate runoff for this particular region. NRCS-CN was employed to determine the λ in five watersheds, evaluating the performance of the modified λ values and determining the correlation for potential maximum retention (S0.2) from the original Curve Number (CN) equation with the revised Sλ value. A set of instruments comprised a rain gauge and a water stage recorder installed at each watershed. The initial abstraction (Ia), λ and CN of 80 storm events in 2018 and the Sλ-S0.20 correlation equation were calculated. The runoff model assessment from 72 selected events in 2019 was validated. The results revealed a median λ of 0.045. The runoff model assessment used the data from the measuring station compared to those calculated from the created rainfall-runoff model provided more accurate runoff and better responded to Nash-Sutcliff coefficient (NSE), coefficient of determination (R²) and percent of bias (PBIAS) (0.92, 0.92 and 1.91 respectively). Regarding the Watershed-Specific S correlation equation based on the S correlation equation between S0.045 and S0.20 values, R² was 0.97. It is recommended that the created model with the λ of 0.045 should be used for future simulations in the 100 to 250 km2 tropically medium-sized watershed. [ABSTRACT FROM AUTHOR]

ABSTRACT Synthetic unit hydrographs (SUH) are useful tools for the estimation of maximum flows in basins lacking historical records of measurements. However, these methods have many uncertainties and do not always produce results consistent with reality. This study comparatively analyzed the uncertainty of the application of the Snyder, SCS, and Clark HUS methods, widely used, in relation to the observed hydrographs, in the Pequeno River and the Espingarda River basins, located in the State of Paraná, considered small from the point of view of the drainage area. The simulation was performed using the HEC-HMS 4.2.1 software considering a combination of parameters that produced the higher and lower peak flow, respectively named as conservative and bold approaches. It was verified that the SUH methods, in general, overestimated the peak flows for both basins under study. In addition, the results obtained showed that SUH are fundamentally conservative models so that a bold approach in estimating the parameters input leads to results with smaller errors in simulated peak flows. Even running the SUH with the real excess rainfall as input there is an overestimation of the peak flow. SCS SUH produced the highest peak flows and consequently the largest errors while Snyder’s SUH produced the smallest errors. The magnitude of the overestimation of the peak flow for the Pequeno River was up to 60 folds. Its geology features suggest a Dunnian runoff generation process, which explains the larger errors.

Rainwater harvesting is an important step towards maximizing the water availability and land productivity in arid and semi-arid areas. The present study shows that the area of Ghazi Tehsil within Khyber Pakhtunkhwa Province, Pakistan, has great potential for rainwater harvesting due to its feasible climatic and topographic conditions. This area of 348 km2 normally receives high rainfall annually, but, due to hilly terrain, the bulk of rainwater is lost in the runoff process. In order to enhance agricultural output for such a large area, the practice of rainwater harvesting is a sustainable and decisive approach. However, the selection of appropriate sites for rainwater harvesting on a large scale presents a critical challenge. In such areas, geospatial technology has proved very decisive in the identification of potential sites. In this study, we have used the HEC-GeoHMS tool (ArcGIS 9.3) to compute a curve number to represent the effects of rainfall against the hydrological soil group and landcover. Subsequently, the curve number was used as an input parameter in the soil conservation service runoff-curve number (SCS-CN) method to estimate surface runoff potential for different combinations of landcover and hydrological soil groups. It was observed that runoff was higher in mountainous areas and relatively low in plain areas. Finally, to identify the potential sites for rainwater harvesting, weighted overlay analysis-based related thematic map layers were further reclassified, and weights were assigned according to the technical guidelines of suggested international standards and under consideration of the study area’s topographic, hydrological, and climatic factors. As a result, about 20% of the area was found suitable, 52% less suitable, and 29% as not suitable. Furthermore, relative suitability was assigned to the results of suitable sites as an input for the identification of potential sites for different rainwater harvesting storage structures. These results show that 10% of the area was suitable for farm ponds, 5.74% for check dams, 21.5% for Nigarims, and 8.9% was found to be suitable for gully plugs. The comparison of our GIS-derived and field-based results spatially affirms that the analyzed results were agreeably overlaid in the context of spatial results for check dams, gully plugs, and Nigarims.

The changes that occur in various forms of land classes are known as land-use and land-cover changes (LULC). Such changes have a substantial impact on the contours of an urban basin and consequently have an effect on the surface runoff of the rainfall that occurs in the area. The runoff features obviously deteriorate because of the decrease in initial abstraction, and an increase in imperviousness causes enhanced runoff. The particular challenges in the urban basin are specificity calculation and quantification of surface runoff. Geospatial techniques are adopted along with the Soil Conservation Service-curve number (SCS-CN) technique to reliably predict and accurately measure runoff. The GIS is used to prepare the transformed layers of land classes from remotely sensed data. In this explorative study, LULC change and its impact on the urban Koraiyar basin, Tiruchirappalli city, South India, is studied by using SCS-CN with the aid of GIS techniques. As the basin that passes is located in a developing city, rapid changes in LULC are observed in and around the periphery of the basin. The LULC changes and their impact on surface runoff are analyzed using GIS with multi-dated Landsat satellite images for the years 1986–2016 at intervals of every 10 years. The supervised classification algorithm is used to develop LULC maps. From the study, it is observed that there is a continuous increase in settlement area of 1.04% from 1986 to 2016, especially in the northern part of the basin. A Markov model analysis is done from the historically developed LULC maps to predict the anticipated future LULC changes for the years 2026 and 2036 along with an estimation of the surface runoff. The predicted maps show that there is likely to be an increase in settlement area of 1.04% and decrease in 12.29% of agricultural land. The various thematic layers like slope, soil and curve number (CN) maps are also prepared using GIS. The composite CNs are generated for various land classes in the basin from 1986 to 2036. The increase in CN from 72 to 74.76 and their influence on runoff are studied. Finally, the study attempts to reliably estimate the present and future LULC status and its effect on surface runoff in the Koraiyar river basin. [ABSTRACT FROM AUTHOR]

The accessibility of water resources is depleting everyday on a spatial and temporal scale, while water demand is expanding reliably. With this view, the investigation is an endeavour to identify the best locations appropriate for water conservation measures in West Midnapur, Purulia, and Bankura regions of West Bengal, India, using Geoinformatics approach. In this study, administrative boundaries have been considered to get the best locations for all water conservation measures. Then, these locations are shown district wise by considering administrative boundaries. In India, most of the funds are allocated based on administrative boundaries so it is necessary to suggest water conservation measures based on administrative boundaries. The Digital Elevation Model (DEM), Landsat 7 satellite imagery, and daily precipitation data of the year 2011 were used to get ready layers of the slope, and land use land cover. The runoff and runoff potential zones were determined using the Soil Conservation Service Curve Number (SCS-CN) method in the Geographic Information System (GIS) environment. The weights were assigned to thematic layers (slope and runoff coefficient) and ranks were given to these features; then, score was calculated to find out the Water Conservation Potential Index (WCPI). Thematic layers were integrated using ArcGIS software to generate water conservation potential maps for both surface water harvesting structures and groundwater recharge measures. Based on the values of WCPI, zones suitable for surface water harvesting structures and groundwater recharge measures were identified using slope, soil, drainage order, and rainfall as suitability criteria. The outcomes demonstrated that 479, 1884, 1400, 808, and 140 locations in all the three regions were suitable for percolation ponds, farm ponds, check dams, contour bunds, and contour trenching respectively. This research will be useful for policymakers to allocate government funds based on administrative boundaries. [ABSTRACT FROM AUTHOR]

Urbanization has evolved as one of the key factors responsible for the environmental health not only for the urban centres, but also for the suburban regions. In the recent years, most of the suburban regions in India are experiencing flash floods during the high intensity low duration rainfall condition. Such situations of flash floods in the urban and suburban areas are referred to as storm runoff. This paper deals with the computation of storm runoff in the suburban catchments of the Pune City. Five catchments, known for flash floods in the recent years, are identified for the present work. Storm runoff estimations in these catchments have been done using LandsatTM data of 1989 and 2011. Population-calibrated impervious surfaces (IS) were extracted for these catchments, and runoff has been calculated using the Soil Conservation Service-Curve Number method. Major changes in the land use land cover pattern in these 22 years have been detected, with a net growth in built-up area of almost 10 times from 1989 to 2011, leading to the increase in IS in the catchment. The impact of increase in built-up area and IS has augmented storm runoff in the catchment. Estimated runoff values increased from 461.8 m3 to 1068.52 m3 (Baner), 2026.4 m3 to 3638.73 m3 (Kharadi), 2947.5 m3 to 4736.46 m3 (Kondhwa Ghorpadi), 1021.1 m3 to 2039.57 m3 (Wadgaon Sheri) and 1176.89 m3 to 3691.18 m3 (Wadgaon Budruk) from 1989 to 2011. Thus, it is quite evident that the growth in built-up area and impervious surfaces has enhanced the capacity of suburban basins to generate more runoff. [ABSTRACT FROM AUTHOR]