Estimation of Surface Runoff Potential Using SCS-CN Method and GIS for Parts of Doddahalla3 Watershed in Krishna River Basin

2020 ◽  
pp. 359-372
Author(s):  
Bhavyata Jethva ◽  
Ashim Ghosh ◽  
Lingaraju Yale
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Runoff Potential ◽  
Scs Cn

Assessment of surface runoff depth changes in Sǎrǎţel River basin, Romania using GIS techniques

2014 ◽  
Vol 6 (3) ◽  
Author(s):  
Costache Romulus ◽  
Fontanine Iulia ◽  
Corodescu Ema
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Curve Number ◽  
Annual Rainfall ◽  
Average Annual Rainfall ◽  
Runoff Depth ◽  
Gis Environment ◽  
Quantitative Changes ◽  
Scs Cn

AbstractSǎrǎţel River basin, which is located in Curvature Subcarpahian area, has been facing an obvious increase in frequency of hydrological risk phenomena, associated with torrential events, during the last years. This trend is highly related to the increase in frequency of the extreme climatic phenomena and to the land use changes. The present study is aimed to highlight the spatial and quantitative changes occurred in surface runoff depth in Sǎrǎţel catchment, between 1990–2006. This purpose was reached by estimating the surface runoff depth assignable to the average annual rainfall, by means of SCS-CN method, which was integrated into the GIS environment through the ArcCN-Runoff extension, for ArcGIS 10.1. In order to compute the surface runoff depth, by CN method, the land cover and the hydrological soil classes were introduced as vector (polygon data), while the curve number and the average annual rainfall were introduced as tables. After spatially modeling the surface runoff depth for the two years, the 1990 raster dataset was subtracted from the 2006 raster dataset, in order to highlight the changes in surface runoff depth.

scholarly journals Estimation of Surface Runoff in an Ungauged Basin Using SCS-CN Method, A Case Study of Manair River Basin in Telangana, India

2020 ◽  
Vol 8 (6) ◽  
pp. 340-350
Author(s):  
Abdul Moid Mohammed ◽  
Vijaya Lakshmi Thatiparthi ◽  
Kesava Rao Pyla ◽  
Abhilash Maryada
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Ungauged Basin ◽  
Scs Cn

scholarly journals Analysis of surface runoff potential in ungauged basin using basin parameters and SCS-CN method

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
K. Nageswara Rao
Keyword(s):  
Surface Runoff ◽  
Research Work ◽  
Curve Number ◽  
Morphometric Parameters ◽  
Rainfall Data ◽  
Eastern Ghats ◽  
Moisture Condition ◽  
Ungauged Basin ◽  
Runoff Potential ◽  
Scs Cn

AbstractThe present research work was carried out to understand the influence of basin morphometric parameters on runoff potential in an ungauged basin using satellite images, topographical maps, and rainfall data combined with geospatial techniques. The upper Gosthani river basin is an ungauged basin which is located in the Eastern Ghats of Visakhapatnam District, Andhra Pradesh State, Southern India. The river Gosthani and its tributaries are draining through the basin area covering about 321.1 km2. The quantitative analysis of basin morphometry reveals that the area is under influenced by steep ground slopes, with moderate to less permeable rocks, leading to high runoff. The basin is elongated in shape resulting to flatter peak of flow for longer duration. The daily rainfall data during 2008–2016 were used in the estimation of runoff potential with the help of the Soil Conservation Service-Curve Number (SCS-CN) model. The weighted curve number was determined by the integration of land use and land cover, antecedent moisture condition, and hydrological soil groups. It was observed from the analysis that the overall increase in runoff corresponding to the rainfall. The area receives a good amount of rainfall, but most of it lost as surface runoff (nearly 40% of total rainfall) due to rapid overland flow and impermeable rocks. Analysis of morphometric parameters combined with SCS-CN-based approaches can be explored as an alternative for simulating the hydrological response of the basins.

scholarly journals Analysis Of Surface Runoff Potential At Medan Industrial Estate Use SCS Method

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Yudha Hanova
Keyword(s):  
Return Period ◽  
Surface Runoff ◽  
Catchment Area ◽  
Flood Mitigation ◽  
Effective Rainfall ◽  
Flood Discharge ◽  
Industrial Estate ◽  
Runoff Potential ◽  
Alternative Solutions ◽  
Scs Cn

<p><em>Flood disaster at the region Medan Industrial Estate resulted the losses in infrastructure, farming, and residence. </em><em></em></p><p><em>Flood discharge at Medan Industrial Estate are influenced by surface runoff from several catchment area in Medan Industrial Estate. Analysis of potential for surface runoff is expected to provide input and information to find alternative solutions appropriate flood mitigation.</em> <em>Discharge of surface runoff were analyzed using SCS method with the return period of 1, 2 and 5 Years. Rainfall data are obtained BMKG Stations of Maritim Belawan</em>. <em>Effective rainfall calculated using SCS-CN method on condition AMC III (wet conditions). The results of the analysis of the potential for surface runoff maximum for 1 year return period on DAS I, II, III, IV, V, and VI was 17.631 m<sup>3</sup>/s</em><em>, 22.183 m<sup>3</sup>/s, 12.621 m<sup>3</sup>/s, 11.338 m<sup>3</sup>/s, 18.224 m<sup>3</sup>/st, dan 15.839 m<sup>3</sup>/s.</em> <em>To return period of 2 years was 31.234 m<sup>3</sup>/sec,</em> <em>39.235 m<sup>3</sup>/s, 22.351 m<sup>3</sup>/det, 20.044 m<sup>3</sup>/det, 32.300 m<sup>3</sup>/det, dan 28.097 m<sup>3</sup>/det. F</em><em>or the return period of 5 years is 45.346 m<sup>3</sup>/s,</em> <em>56.926 m<sup>3</sup>/s, 32.446 m<sup>3</sup>/s, 29.076 m<sup>3</sup>/s, 46.903 m<sup>3</sup>/s, dan 40.816 m<sup>3</sup>/s.</em></p>

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

HydroResearch ◽  
2021 ◽  
Author(s):  
Abanish Kumar ◽  
Shruti Kanga ◽  
Ajay Kumar Taloor ◽  
Suraj Kumar Singh ◽  
Bojan Đurin
Keyword(s):  
River Basin ◽  
Surface Runoff ◽  
Gis Techniques ◽  
Scs Cn

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.

scholarly journals Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 704
Author(s):  
Hussein Al-Ghobari ◽  
Ahmed Z. Dewidar
Keyword(s):  
Water Conservation ◽  
Surface Runoff ◽  
Rainwater Harvesting ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Curve Number ◽  
Drainage Density ◽  
Promising Alternative ◽  
Thematic Layers ◽  
Scs Cn

An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

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