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 Improved SMA-based SCS-CN method incorporating storm duration for runoff prediction on the Loess Plateau, China

2020 ◽  
Vol 51 (3) ◽  
pp. 443-455
Author(s):  
Wenhai Shi ◽  
Ni Wang
Keyword(s):  
Loess Plateau ◽  
Curve Number ◽  
The Loess Plateau ◽  
Moisture Condition ◽  
Soil Moisture Accounting ◽  
Antecedent Moisture ◽  
Storm Duration ◽  
Service Curve ◽  
Scs Cn ◽  
Runoff Events

Abstract In the Soil Conservation Service Curve Number (SCS-CN) method for estimating runoff, three antecedent moisture condition (AMC) levels produce a discrete relation between the curve number (CN) and soil water content, which results in corresponding sudden jumps in estimated runoff. An improved soil moisture accounting (SMA)-based SCS-CN method that incorporates a continuous function for the AMC was developed to obviate sudden jumps in estimated runoff. However, this method ignores the effect of storm duration on surface runoff, yet this is an important component of rainfall-runoff processes. In this study, the SMA-based method for runoff estimation was modified by incorporating storm duration and a revised SMA procedure. Then, the performance of the proposed method was compared to both the original SCS-CN and SMA-based methods by applying them in three experimental watersheds located on the Loess Plateau, China. The results indicate that the SCS-CN method underestimates large runoff events and overestimates small runoff events, yielding an efficiency of 0.626 in calibration and 0.051 in validation; the SMA-based method has improved runoff estimation in both calibration (efficiency = 0.702) and validation (efficiency = 0.481). However, the proposed method performed significantly better than both, yielding model efficiencies of 0.810 and 0.779 in calibration and validation, respectively.

scholarly journals Formulation of Parsimonious Urban Flash Flood Predictive Model with Inferential Statistics

Mathematics ◽  
2022 ◽  
Vol 10 (2) ◽  
pp. 175
Author(s):  
Lloyd Ling ◽  
Sai Hin Lai ◽  
Zulkifli Yusop ◽  
Ren Jie Chin ◽  
Joan Lucille Ling
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Flash Flood ◽  
Curve Number ◽  
Runoff Coefficient ◽  
Rainfall Runoff ◽  
Inferential Statistics ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Runoff Model

The curve number (CN) rainfall–runoff model is widely adopted. However, it had been reported to repeatedly fail in consistently predicting runoff results worldwide. Unlike the existing antecedent moisture condition concept, this study preserved its parsimonious model structure for calibration according to different ground saturation conditions under guidance from inferential statistics. The existing CN model was not statistically significant without calibration. The calibrated model did not rely on the return period data and included rainfall depths less than 25.4 mm to formulate statistically significant urban runoff predictive models, and it derived CN directly. Contrarily, the linear regression runoff model and the asymptotic fitting method failed to model hydrological conditions when runoff coefficient was greater than 50%. Although the land-use and land cover remained the same throughout this study, the calculated CN value of this urban watershed increased from 93.35 to 96.50 as the watershed became more saturated. On average, a 3.4% increase in CN value would affect runoff by 44% (178,000 m3). This proves that the CN value cannot be selected according to the land-use and land cover of the watershed only. Urban flash flood modelling should be formulated with rainfall–runoff data pairs with a runoff coefficient > 50%.

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 A Historical Review of Slope Based SCS Method and its Effect on CN and Runoff Potential Globally

2020 ◽  
Author(s):  
Tauseef Ahmad Ansari ◽  
Yashwant B Katpatal ◽  
C Rishma
Keyword(s):  
Soil Conservation ◽  
Historical Review ◽  
Curve Number ◽  
Soil Conservation Service ◽  
Moisture Condition ◽  
Antecedent Moisture ◽  
Runoff Potential ◽  
Service Curve ◽  
Scs Cn ◽  
Large Catchment

The Soil Conservation Service - Curve Number (SCS-CN) method is extensively used to calculate the runoff from rainfall over a large catchment over the world. Slope is an important criterion for runoff but a very few attempts have been made to evaluate the effect of slope on the CN with runoff potential. The objective of this paper is to summarise the historical review on the effects of slope on CN and runoff potential in various regions by the hydrologists. This paper also depicts that how the various researchers proved the importance of consideration of slope for CN and runoff estimation. In addition, paper highlights the key features of research in future like to classify the watersheds on slope based CN, accurate Antecedent Moisture Condition (AMC) and proper initial abstraction in the various regions etc. Considering these parameters an accurate runoff estimation can be predicted and managed properly in the urban watersheds.

Estimation of Rainfall Runoff using SCS-CN Method with RS and GIS Techniques for Mandavi Basin in YSR Kadapa District of Andhra Pradesh, India

2018 ◽  
Vol 2 (1) ◽  
pp. 1-15 ◽  
Author(s):  
Siddi Raju R. ◽  
Sudarsana Raju G. ◽  
Rajasekhar M.
Keyword(s):  
Curve Number ◽  
Crystalline Rock ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Moisture Condition ◽  
Gis Techniques ◽  
Antecedent Moisture ◽  
Rs And Gis ◽  
Wet Condition

The study aims to estimate the surface runoff in the semi-arid crystalline rock terrain of Mandavi basin using Remote Sensing (RS) and Geographical Information System (GIS) techniques. The rainfall is the only source of water in this basin drains off and little amount percolates into the ground. The study area experiences rigorous groundwater scarcity despite having high rainfall -runoff. Consequently, integrated RS and GIS techniques are used for estimation of the runoff. The weighted curve number (CN) is resolute based on AMC-II (Antecedent Moisture Condition) with the combination of HSGs (hydrologic soil groups) and LU/LC (land use and land cover) categories. The outcomes of study showed 52.292 (CNII) of normal condition, 31.506(CNI) of dry condition and 71.583 (CNIII) of wet condition. The ungauged watershed exhibits an annual average of rainfall, runoff, runoff volume and runoff coefficients for 20 years are 688.82 mm, 478.06 mm, 699.75 m3 and 0.69, respectively. The annual rainfall-runoff relationship during 1995 to 2014 is indicating the overall increase in runoff with the rainfall in the study area.

scholarly journals Assessment of the Impacts of Land Use/Cover Change and Rainfall Change on Surface Runoff in China

2019 ◽  
Vol 11 (13) ◽  
pp. 3535 ◽  
Author(s):  
Fazhi Li ◽  
Jingqiu Chen ◽  
Yaoze Liu ◽  
Peng Xu ◽  
Hua Sun ◽  
...  
Keyword(s):  
Land Use ◽  
Surface Runoff ◽  
Texture Classification ◽  
Curve Number ◽  
Annual Runoff ◽  
Urban Land Use ◽  
Rainfall Change ◽  
Average Annual Runoff ◽  
Runoff Depth ◽  
Hydrologic Impact

Assessment of the impacts of land use/cover change (LUCC) and rainfall change on surface runoff depth can help provide an understanding of the temporal trend of variation of surface runoff and assist in urban construction planning. This study evaluated the impacts of LUCC and rainfall change on surface runoff depth by adopting the well-known Soil Conservation Service-Curve Number (SCS-CN) method and the widely used Long-Term Hydrologic Impact Assessment (L-THIA) model. National hydrologic soil group map of China was generated based on a conversion from soil texture classification system. The CN values were adjusted based on the land use/cover types and soil properties in China. The L-THIA model was configured by using the adjusted CN values and then applied nationally in China. Results show that nationwide rainfall changes and LUCC from 2005 to 2010 had little impact on the distribution of surface runoff, and the high values of runoff depth were mainly located in the middle and lower reaches of the Yangtze River. Nationally, the average annual runoff depths in 2005, 2010 and 2015 were 78 mm, 83 mm and 90 mm, respectively. For the 2015 land use data, rainfall change caused the variation of surface runoff depth ranging from −203 mm to 476 mm in different regions. LUCC from 2005 to 2015 did not cause obvious change of surface runoff depth, but expansion of developed land led to runoff depth increases ranging from 0 mm to 570 mm and 0 mm to 742 mm from 2005 to 2010 and 2010 to 2015, respectively. Potential solutions to urban land use change and surface runoff control were also analyzed.

Climate and land use change impacts on water resources in Sardinia (Italy)

2021 ◽  
Author(s):  
Dario Ruggiu ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Land Use Change ◽  
Hydrological Cycle ◽  
Potential Evapotranspiration ◽  
Regional Scale ◽  
Annual Runoff ◽  
Annual Rainfall ◽  
Land Use Scenarios ◽  
Near Future

&lt;p&gt;The assessment of climate change and land use modifications effects on hydrological cycle is challenging. We propose an approach based on Budyko theory to investigate the relative importance of natural and anthropogenic drivers on water resources availability. As an example of application, the proposed approach is implemented in the island of Sardinia (Italy), which is affected by important processes of both climate and land use modifications. In details, the proposed methodology assumes the Fu&amp;#8217;s equation to describe the mechanisms of water partitioning at regional scale and uses the probability distributions of annual runoff (Q) in a closed form. The latter is parametrized by considering simple long-term climatic info (namely first orders statistics of annual rainfall and potential evapotranspiration) and land use properties of basins.&lt;/p&gt;&lt;p&gt;In order to investigate the possible near future water availability of Sardinia, several climate and land use scenarios have been considered, referring to 2006-2050 and 2051-2100 periods. Climate scenarios have been generated considering fourteen bias corrected outputs of climatic models from EUROCORDEX&amp;#8217;s project (RCP 8.5), while three land use scenarios have been created following the last century tendencies.&lt;/p&gt;&lt;p&gt;Results show that the distribution of annual runoff in Sardinia could be significantly affected by both climate and land use change. The near future distribution of Q generally displayed a decrease in mean and variance compared to the baseline. &amp;#160;&amp;#160;&lt;/p&gt;&lt;p&gt;The reduction of&amp;#160; Q is more critical moving from 2006-2050 to 2051-2100 period, according with climatic trends, namely due to the reduction of annual rainfall and the increase of potential evapotranspiration. The effect of LU change on Q distribution is weaker than the climatic one, but not negligible.&lt;/p&gt;

scholarly journals Rainfall-Runoff Modeling Using NRCS-CN method and GIS approach

2020 ◽  
Author(s):  
Rekha Verma ◽  
Azhar Husain ◽  
Mohammed Sharif
Keyword(s):  
Hydrological Modeling ◽  
Curve Number ◽  
Geographical Information ◽  
Rainfall Runoff ◽  
Moisture Condition ◽  
Natural Resource Conservation ◽  
Antecedent Moisture ◽  
Natural Resource Conservation Service ◽  
Runoff Modeling ◽  
Runoff Depth

Rainfall-Runoff modeling is a hydrological modeling which is extremely important for water resources planning, development, and management. In this paper, Natural Resource Conservation Service-Curve Number (NRCS-CN) method along with Geographical Information System (GIS) approach was used to evaluate the runoff resulting from the rainfall of four stations, namely, Bilodra, Kathlal, Navavas and Rellawada of Sabarmati River basin. The rainfall data were taken for 10 years (2005-2014). The curve number which is the function of land use, soil and antecedent moisture condition (AMC) was generated in GIS platform. The CN value generated for AMC- I, II and III were 57.29, 75.39 and 87.77 respectively. Using NRCS-CN method, runoff depth was calculated for all the four stations. The runoff depth calculated with respect to the rainfall for Bilodra, Kathlal, Navavas and Rellawada shows a good correlation of 0.96. The computed runoff was compared with the observed runoff which depicted a good correlation of 0.73, 0.70, 0.76 and 0.65 for the four stations. This method results in speedy and precise estimation of runoff from a watershed.

scholarly journals LOW COST POTENTIAL INFILTRATION ESTIMATION FOR WET TROPICAL WATERSHEDS FOR TERRITORIAL PLANNING SUPPORT

2017 ◽  
Vol 10 (2) ◽  
pp. 233-241
Author(s):  
Franciane Mendonça Dos Santos ◽  
José Augusto Lollo
Keyword(s):  
Land Use ◽  
Soil Conservation ◽  
Low Cost ◽  
Land Use Changes ◽  
Mass Movement ◽  
Curve Number ◽  
Annual Rainfall ◽  
Soil Conservation Service ◽  
Local Conditions ◽  
Territorial Planning

This study was developed at Caçula stream watershed of Ilha Solteira (Brazil) for potential infiltration estimation based on digital cartography. These methods aim at low-cost and quick analysis processes in order to support the territorial planning. The preliminary potential infiltration chart was produced using ArcHydro and pedological information of the study area. The curve-number method (Soil Conservation Service) was used to determine the potential infiltration combining information related to land-use and soil types in the watershed. We also used a methodology that assumes being possible to evaluate potential infiltration of a watershed combining average annual rainfall, land-use and watershed natural attributes (geomorphology, geology and pedology). Results show that ArcHydro is efficient for a preliminary characterization because it shows flow accumulation areas, allowing higher potential of degradation areas in terms of floods, mass movement and erosion. As land-use classes have significant weight in Soil Conservation Service method assessing potential infiltration, this method allow us to evaluate how land-use changes affect water dynamic in the watershed. The propose based on natural environment attributes enables to determine the homologous infiltration areas based on a higher number of natural characteristics of the area, and thereby obtain a result that is closer to the local conditions and, consequently for degradation surface processes identification.

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.

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