Modifications to SCS-CN Method for Long-Term Hydrologic Simulation

Geetha, K.; Mishra, Surendra Kumar; Eldho, T. I.; Rastogi, A. K.; Pandey, Rajendra

doi:10.1061/(asce)0733-9437(2007)133:5(475)

Cited by 60 publications

(29 citation statements)

References 20 publications

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“…Available literatures on site selection procedures for WHS consider slope, runoff, watershed area, drainage order and socio-economic aspects (Padmavathy et al 1993;IMSD 1995;Geetha et al 2007;De Winnaar et al 2007) as the main parameters. These simplified site selection criteria often result in failure/underperformance of the structures in terms of storage and structural stability.…”

Section: Discussionmentioning

confidence: 99%

“…As the soil moisture increases due to rainfall in the early spell, the runoff during storm event increases. In the present case, depending on the total rainfall in 5-day period, the AMC condition is classified as AMC I (< 35 mm), AMC II (35-53 mm) and AMC III (> 53 mm) (Geetha et al 2007). Since the rainfall data used in this work are from a single meteorological station, the curve numbers are evaluated for AMC-II condition only.…”

Section: Runoff Coefficientmentioning

confidence: 99%

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SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India

2009

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The Kali sub-watershed is situated in the semi-arid region of Gujarat, India and forms a part of the Mahi River Watershed. This watershed receives an average annual rainfall of 900 mm mainly between July and September. Due to high runoff potential, evapo-transpiration and poor infiltration, drought like situation prevails in this area from December to June almost every year. In this paper, augmentation of water resource is proposed by construction of runoff harvesting structures like check dam, percolation pond, farm pond, well and subsurface dyke. The site suitability for different water harvesting structures is determined by considering spatially varying parameters like runoff potential, slope, fracture pattern and micro-watershed area. GIS is utilised as a tool to store, analyse and integrate spatial and attribute information pertaining to runoff, slope, drainage and fracture. The runoff derived by SCS-CN method is a function of runoff potential which can be expressed in terms of runoff coefficient (ratio between the runoff and rainfall) which can be classified into three classes, viz., high (> 40%), moderate (20-40%) and low (< 20%). In addition to IMSD, FAO specifications for water harvesting/recharging structures, parameters such as effective storage, rock mass permeability are herein considered to augment effective storage. Using the overlay and decision tree concepts in GIS, potential water harvesting sites are identified. The derived sites are field investigated for suitability and implementation. In all, the accuracy of the site selection at implementation level varies from 80-100%.

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Section: Discussionmentioning

confidence: 99%

Section: Runoff Coefficientmentioning

confidence: 99%

SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India

2009

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“…Although recently the CN variant has been re-adapted for such simulations (Geetha et al, 2007), it may require a larger number of parameters and surveyed variables in the optimization process leading to higher computational time, beside the fact that most of the typical meteorological data (e.g. evapotranspiration) were not sufficiently available in the study area.…”

Section: Iv31 Vinces Upper Subcatchmentmentioning

confidence: 99%

A Decision Framework for Integrated Wetland-River Basin Management in a Tropical and Data Scarce Environment

Hidalgo¹

2013

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All rights reserved. No part of this publication or the information contained herein may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, by photocopying, recording or otherwise, without written prior permission from the publishers. Although all care is taken to ensure integrity and the quality of this publication and the information herein, no responsibility is assumed by the publishers nor the author for any damage to the property or persons as a result of operation or use of this publication and/or the information contained herein.Published by: CRC Press/Balkema PO Box 447, 2300 AK Leiden, the Netherlands e-mail: Pub.NL@taylorandfrancis.com www.crcpress.com -www.taylorandfrancis.co.uk -www.ba.balkema.nl Guillermo. I miss them, but hélas! C'est la vie and we must go on. List of TablesLast but not least, my greatest feelings go to my dear wife, Nina. She has been an endless source of love, inspiration, patience and support, especially when I was far away from home. Along with our beloved daughter, Valeria Alexandra, both make every day a living dream. Мои любви, я вас люблю всем сердцем: сильно, сильно, крепко, крепко! Я вернусь и сейчас мы будем вместе и навсегда! Delft, the Netherlands, 17 December 2012 SummaryWetlands are probably one of the most astonishing ecosystems across the Earth. They are present in almost every latitude zone, from the arctic tundra's to the tropical wetlands near the equator. Being important parts of watershed ecosystems, wetlands often play a key role in fauna-flora conservation, habitat preservation and attracting recreation. But they also provide important ecosystem services related to water buffering, flood flow regulation water pollution control and water quality improvement.Although traditionally wetlands were often considered separately from riverine systems, nowadays an integrated approach is becoming common practice in wetland-riverine watershed analysis and management. Such overall environmental approach implies not only an adequate representation of relevant bio-physical parameters, but also of socio-political and economic indicators. This is where computer-based modeling and decision support becomes extremely helpful. Currently, there are several complex simulation tools available that try to represent the different processes taking place in river catchments including wetland systems. However, more complexity may also lead to more uncertainty and can become too much for a particular need, in particular in multi-criteria evaluation. Therefore, a balance has to be established between simplicity and sophistication before building any model for decision support.Based on these considerations, the primary goal of this research is to elaborate a simple but useful integrated framework or methodology for a coupled wetlandcatchment environment, containing (i) both quantitative and qualitative approaches; (ii) incorporating stakeholders' feedback; (iii) taking into consideration the pressures on the system; and (iv) ...

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“…As data on infiltration are meagre, estimation of R D is difficult. Hence, as in Geetha et al (2007), we used equations (2d) and (2e) to define R D . Since baseflow is small in the Mandovi basin, we assumed that all the water that infiltrates contributes to R D , i.e.…”

Section: Runoff Partitioningmentioning

confidence: 99%

Simulating the daily discharge of the Mandovi River, west coast of India

Suprit

Shankar

Venugopal

et al. 2012

Hydrological Sciences Journal

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A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June-September), with a peak during July-August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse raingauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system. Key words hydrological modelling; SCS Curve Number; Sahyadris; river discharge; Mandovi River Simulation du débit journalier du fleuve Mandovi, côte occidentale de l'Inde Résumé Un cadre de modélisation hydrologique a été mis en place pour simuler le débit journalier du fleuve Mandovi situé sur la côte occidentale de l'Inde. Sur cette côte occidentale, environ 90% de la pluie, et donc de l'écoulement, se produit durant la mousson d'été (de juin à septembre), avec un maximum pendant les mois de juillet et août. Le cadre de modélisation comprend un modèle numérique de terrain (MNT) appelé GLOBE, un algorithme de routage hydrologique appelé THMB (Terrestrial Hydrological Model with Biogeochemistry), un algorithme pour cartographier la pluie enregistrée par quelques pluviomètres sur le maillage du modèle, et une méthode modifiée du « Soil Conservation Service Curve Number » (SCS-CN). Une série de simulations de débits (avec et sans la méthode SCS) a été réalisée. La meilleure simulation a été obtenue en prenant en compte la variabilité spatio-temporelle dans les paramètres du SCS, obtenue par une division objective de la...

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Modifications to SCS-CN Method for Long-Term Hydrologic Simulation

Cited by 60 publications

References 20 publications

SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India

SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India

A Decision Framework for Integrated Wetland-River Basin Management in a Tropical and Data Scarce Environment

Simulating the daily discharge of the Mandovi River, west coast of India

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