scholarly journals RUNOFF TREND AND POTENTIALITY IN MELAKA TENGAH CATCHMENT OF MALAYSIA USING SCS-CN AND STATISTICAL TECHNIQUE

2016 ◽  
Vol 24 (4) ◽  
pp. 245-257 ◽  
Author(s):  
Sharif Moniruzzaman SHIRAZI ◽  
MD Ibrahim ADHAM ◽  
Faridah OTHMAN ◽  
Noorul Hasan ZARDARI ◽  
Zubaidah ISMAIL
Keyword(s):  
Land Use ◽  
Surface Water ◽  
Surface Runoff ◽  
Curve Number ◽  
Statistical Technique ◽  
Land Use Pattern ◽  
Surface Water Resources ◽  
Total Runoff ◽  
Use Pattern ◽  
Scs Cn

This study is focused to identify the surface runoff trends and potentiality of the five watersheds transforming the discrete runoff pattern to smooth patterns. Runoff potentiality was analyzed by Soil Conservation Service Curve Number (SCS-CN) technique. Considering Hydrologic Soil Group (HSG) and percentage of particular land use pattern, weighted cns of five watersheds were found between 82 and 85. Monthly surface runoff trends were investigated by statistical autocorrelation, Mann-Kendall, Sen slope and lowess methods. According to the Mann-Kendall method, no statistical significant monotonic trends were found for all the watersheds. Smoothing curve analysis reveals that the monthly mean runoff is 30 mm, 34 mm, 39 mm, 28 mm and 37 mm and the percentage of runoff is 23%, 25%, 31%, 25% and 26% for the watersheds 1, 2, 3, 4 and 5, respectively. Degree of effect of several land use pattern with corresponding soil type was analyzed to assess the total runoff volume for contributing to the surface water resources. Result shows that 26% of the rainwater contributes to the surface runoff of Melaka Tengah catchment and provides the information for planning of surface water management and potentiality of groundwater recharge.

scholarly journals Evaluating the Impacts of Future Urban Expansion on Surface Runoff in an Alpine Basin by Coupling the LUSD-Urban and SCS-CN Models

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3405
Author(s):  
Zihang Fang ◽  
Shixiong Song ◽  
Chunyang He ◽  
Zhifeng Liu ◽  
Tao Qi ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Runoff ◽  
Urban Expansion ◽  
Coupled Model ◽  
Curve Number ◽  
The Tibetan Plateau ◽  
Adaptation Measures ◽  
Land Use Scenario ◽  
The Future ◽  
Scs Cn

Effective evaluations of the future urban expansion impacts (UEI) on surface runoff in alpine basins are full of challenges due to the lack of reliable methods. Our objective was to provide a new approach by coupling the Land Use Scenario Dynamics-urban (LUSD-urban) and Soil Conservation Service-Curve Number (SCS-CN) models to estimate the future UEI on surface runoff. Taking the Qinghaihu-Huangshui basin (QHB) in the Tibetan Plateau, China, as an example, we first applied the SCS-CN model to quantify the surface runoff in 2000 and 2018 and analyzed the changes in surface runoff. Next, we applied the LUSD-urban model to simulate urban expansion under five localized shared socioeconomic pathways (SSPs) from 2018 to 2050. Finally, we assessed the UEI on surface runoff in the QHB from 2018 to 2050. We found that coupling the LUSD-urban and SCS-CN models could effectually evaluate the future UEI on surface runoff. Compared with the combination of the Future Land Use Simulation (FLUS) and SCS-CN models, our method reduced the absolute evaluation errors from 3.40% and 11.78% to 0.18% and 4.23%, respectively. In addition, the results showed that future urban expansion will have severe impacts on surface runoff in the valley region. For example, as a result of urban expansion, the surface runoff in the Huangzhong, Xining, and Datong catchments will increase by 4.90–9.01%, 4.25–7.36%, and 2.33–3.95%, respectively. Therefore, we believe that the coupled model can be utilized to evaluate the future UEI on surface runoff in alpine basins. In addition, the local government should pay attention to flood risk prevention, especially in the valley region, and adopt reasonable urban planning with soft and hard adaptation measures to promote the sustainable development of alpine basins under rapid urban expansion.

scholarly journals Estimation of Surface Water Runoff for a Semi-Arid Area Using RS and GIS-Based SCS-CN Method

Water ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1924 ◽  
Author(s):  
Hussein Al-Ghobari ◽  
Ahmed Dewidar ◽  
Abed Alataway
Keyword(s):  
Land Use ◽  
Saudi Arabia ◽  
Surface Runoff ◽  
Curve Number ◽  
Accurate Estimation ◽  
Water Runoff ◽  
Rainfall Runoff ◽  
Study Region ◽  
Rs And Gis ◽  
Scs Cn

The proper planning of storage structures, waterways, irrigation schemes, water harvesting, erosion control structures, and groundwater development strategies requires accurate estimation of surface runoff. However, hydrologists in Saudi Arabia face serious challenges, specifically due to the rare availability of surface runoff data. In this study, the soil conservation service-curve number (SCS-CN) method integrated with geographic information system (GIS) and remote sensing (RS) was utilized to estimate the surface runoff in Wadi-Uranah basin, in the western region of Saudi Arabia. Different thematic maps such as slope, hydrologic soil group (HSG), land use/land cover (LULC), and daily rainfall have been created in GIS environment and processed to generate the curve number (CN) and surface runoff maps. Based on the soil classification results, the study area was categorized into two HSGs (B and C). The dominant HSG was group C, representing about 98.8% of the total area. The LULC analysis showed four main land use types in the study region: urban, rocks, barren soil, and agricultural areas. Furthermore, the finding results showed that CN values for the normal conditions (CNII) ranged between 74 and 93 in agricultural and both urban and rock areas, respectively. The CNII values were further corrected using slope data to derive slope-adjusted CNII. Moreover, the rainfall-runoff results showed an increase in the daily runoff of the study region with a minimum of 15 mm to a maximum of 74 mm. Another interesting result was rainfall-runoff linear regression analysis that showed a good correlation of 0.98. Additionally, the peak runoff hydrograph flows for 10-, 50-, and 100-year return periods obtained from the SCS-based dimensionless unit hydrograph were 828, 1353, and 1603 m3/s, respectively. Therefore, this study highlights that the SCS-CN method integrated with RS and GIS deserves further attention for estimating runoff of ungauged basins for better basins management and conservation purposes.

scholarly journals Gis Based SCS - CN Method For Estimating Runoff In Kundahpalam Watershed, Nilgries District, Tamilnadu

2015 ◽  
Vol 19 (1) ◽  
pp. 59-64 ◽  
Author(s):  
Viji Raja
Keyword(s):  
Land Use ◽  
Curve Number ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Land Use Pattern ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Average Annual Runoff ◽  
Distributed Hydrological Models ◽  
Scs Cn

<p>Divination and determination of catchment surface runoff are the most important contestable process of hydrology. Soil Conservation Service - Curve Number (SCS – CN) method is employed to estimate the runoff. It is one of the physical based and spatially distributed hydrological models. In this model, the curve number is a primary factor used for runoff calculation. The selection of curve number is based on the land use pattern and HSG (Hydrological Soil Group) present in the study area. Since the spatial distribution of CN estimation by the conventional way is very difficult and time consuming, the GIS (Geographic Information System) based CN method is generated for Kundapallam watershed. With the combination of land use and HSG the estimated composite CN for AMC (Antecedent Moisture Condition) I, AMC II and AMC III for the entire watershed was about 48, 68 and 83 respectively. The average annual runoff depth estimated by SCS-CN method for the average annual rainfall of 173.5 mm was found to be 72.5 mm. The obtained results were comparable to measured runoff in the watershed.</p><p> </p><p><strong>Resumen</strong></p>La predicción y la determinación del caudal de escorrentía de una cuenca son procesos de amplio debate en la hidrología. El método coeficiente de escurrimiento, del Servicio de Conservación de Suelos (SCS-CN, inglés) fue utilizado en este trabajo para estimar la escorrentía. Este es uno de los modelos hidrológicos basados en conceptos físicos y distribución espacial. En este modelo el coeficiente de escurrimiento es un factor de relevancia para el cálculo de la escorrentía. La selección del coeficiente de escurrimiento está basada en los patrones del uso de la tierra y del Grupo de Suelos Hidrológicos (HSG, inglés) relativos a esta área de estudio. Debido a que la estimación del coeficiente de escurrimiento en la distribución espacial es compleja, para la cuenca Kundapallam se implementó un método a partir de un Sistema de Información Geográfica (GIS, inglés), y basado en el coeficiente de escurrimiento. Con la combinación del uso de suelos y el HSG, la estimación compuesta del coeficiente de escurrimiento para el Antecedente de Condición de Humedad AMCI, AMCII y AMCIII para toda la cuenca fue de 48, 68 y 83. El promedio anual de escorrentía profunda estimada por el método SCS-CN con una media anual de lluvia de 173,5 mm fue de 72,5 mm. Los resultados fueron comparados con la escorrentía medida en la cuenca.

scholarly journals Surface Runoff Responses to Suburban Growth: An Integration of Remote Sensing, GIS, and Curve Number

Land ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 452
Author(s):  
Khurshid Jahan ◽  
Soni M. Pradhanang ◽  
Md Abul Ehsan Bhuiyan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Use Change ◽  
Surface Runoff ◽  
Agricultural Land ◽  
Curve Number ◽  
Integrated Approach ◽  
Substantial Impact ◽  
Sensing Applications ◽  
Scs Cn

Suburban growth and its impacts on surface runoff were investigated using the soil conservation service curve number (SCS-CN) model, compared with the integrated advanced remote sensing and geographic information system (GIS)-based integrated approach, over South Kingston, Rhode Island, USA. This study analyzed and employed the supervised classification method on four Landsat images from 1994, 2004, 2014, and 2020 to detect land-use pattern changes through remote sensing applications. Results showed that 68.6% urban land expansion was reported from 1994 to 2020 in this suburban area. After land-use change detection, a GIS-based SCS-CN model was developed to examine suburban growth and surface runoff estimation. The developed model demonstrated the spatial distribution of runoff for each of the studied years. The results showed an increasing spatial pattern of 2% to 10% of runoff from 1994 to 2020. The correlation between runoff co-efficient and rainfall indicated the significant impact of suburban growth in surface runoff over the last 36 years in South Kingstown, RI, USA, showing a slight change of forest (8.2% area of the total area) and agricultural land (4.8% area of the total area). Suburban growth began after 2000, and within 16 years this land-use change started to show its substantial impact on surface runoff. We concluded that the proposed integrated approach could classify land-use and land cover information to understand suburban growth and its potential impact on the area.

scholarly journals Study on Surface Runoff Estimation for Puzhal Lake Using GIS

2018 ◽  
Vol 7 (3.10) ◽  
pp. 135
Author(s):  
T Subramani ◽  
S Sasikala
Keyword(s):  
Land Use ◽  
Surface Runoff ◽  
Soil Degradation ◽  
Curve Number ◽  
Environmental Condition ◽  
Environment Change ◽  
Geographic Data ◽  
Composite Curve ◽  
Scs Cn

To make greater in grow in land use/cover have lead to environment change in Puzhal Lake and flooding in under areas. environmental condition and the utilization of apparatus for cultivating in the zone are causing issues of soil degradation. Runoff is one in every of most vital hydrological factors that are utilized as a part of numerous common works, anticipating ideal utilization of supplies, sorting out waterways and cautioning flood. Appropriate to the spatial and transient fluctuation of the variables associated with surface runoff, the use of a displaying plan in a GIS ecological gives a productive way to deal with decide zones of concern. Three surface runoff models were connected including: the record strategy, SCS bend number technique, a semi physical way to deal with evaluate the dissemination of surface runoff. The customary SCS-CN strategy for computing the composite curve number devours a noteworthy part of the hydrologic displaying time. Hence, geographic data frameworks (GIS) are presently being utilized as a part of mix with the SCS-CN technique.  

scholarly journals (P1-5) How Does Land use Pattern could Effect to Mitigate the Risk Flash Floods” a Success Story on a Model Project Implementing at the Upper Catchments Area of Badullu River in Sri Lanka

2011 ◽  
Vol 26 (S1) ◽  
pp. s100-s100
Author(s):  
K.J. Attanayake
Keyword(s):  
Land Use ◽  
Surface Water ◽  
Sri Lanka ◽  
Soil Conservation ◽  
Flash Floods ◽  
Land Use Management ◽  
Water Drainage ◽  
Land Use Pattern ◽  
Model Project ◽  
Use Pattern

The watersheds are the home for our key natural resources and have been one of the basic elements in land use management systems throughout the hydraulic civilization of our country. “Badulla River” is one of the main watersheds in Sri Lanka extend about 1400sq.km consisting five sub catchments high steep lands. It mainly represents tea estates and agricultural lands with a weak land use pattern due to poor maintenance and unsuitable human involvements. This has contributed to reduce the rain water infiltration in to the soil increasing a huge amount of runoff water drainage. Situation has resulted frequent floods even in a small precipitation causing widespread damages to community. Hence, an initial project was started on surface water management, soil conservation and livelihoods development to control the frequent floods highlighting the urgent actions for an optimal land use management with support of field experts. Improved surface water drainage and soil conservation are the main options that might lead to mitigate the flash floods. Efforts were sharpened by integrating GIS Mapping for such initiation to enhance the effectiveness of the design. Results achieved could address many issues in relation to flood protection, habitat management, water protection and water quality management. Food risk generally related to the specific characters in a particular catchments and this model project proved that such issues can effectively be addressed through a joint program properly designed.

scholarly journals Surface Runoff Estimation Of Sind River Basin Using SCS-CN Method And GIS Technology

2020 ◽  
Author(s):  
Abanish Sharma ◽  
Shruti Kanga
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Water Resources ◽  
River Basin ◽  
Surface Runoff ◽  
Daily Rainfall ◽  
Curve Number ◽  
Land Use Land Cover ◽  
Annual Average ◽  
Scs Cn

Abstract Rainfall and runoff are significant hydrologic component in the water resources assessment. Rainfall is the primary source of recharge into the ground water. Understanding of rainfall and runoff is necessary for assessment of water availability. The runoff generation procedure is extremely complex. Accurate runoff assessment is carried out for useful management and improvement of water resources. Many methods are available to estimate runoff from rainfall; however, the SCS-CN method still remains the most popular, fruitful and frequently used method. Runoff curve number (CN) is a key factor of the SCS-CN method and it is depends on land use/land cover (LULC), soil type, and antecedent soil moisture (AMC). Different parameters, like land use/land cover, hydrological soil characteristics (HSG), rainfall data (P), Potential Maximum Retention (S), Antecedent Moisture Condition (AMC), Weighted Curve Number (CN), that are the mandatory inputs to SCS model, have been either derived from remote sensing data or from conventional data collection systems. The advance application of Remote Sensing and GIS techniques used to estimate surface runoff based on different parameters. The total area of present study is 26207.02 km2 of Sind River Basin, located in the northern part of Madhya Pradesh, India. The daily rainfall data of 23 weather stations (2005-2014) was collected and used to predict the daily runoff from the Sind river basin using SCS-CN method and GIS technique for the duration of 2005-2014, annual average of daily rainfall are 777.07 mm and annual average of daily runoff calculated for Sind river basin are 133.71 mm. The developed rainfall–runoff model has been used to understand the characteristics of the watershed and its runoff.

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