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This study aims to simulate runoff depth using the Soil Conservation Service-curve number (SCS-CN) method with remote sensing and geographic information system (GIS) techniques. In this study, the SCS-CN technique adapted for Indian conditions has been used for the generation of CNs for an ungauged watershed. The USDA SCS-CN method is used for estimating the runoff depth in the Manimuktha subwatershed. Monthly and annual runoff values have been obtained from the daily runoff values of the watershed. A base map, soil map, and land use map of the study area have been prepared using remote sensing data and Survey of India (SOI) toposheets. The vector layers have been generated in GIS software. The SCS model is then applied to estimate the daily runoff from the watershed and validated, comparing it with the observed runoff of a few selected events of the monsoon periods of 1980-2009. The statistical analysis indicates that the SCS-CN method can be applied to predict runoff depths of an ungauged watershed. The present study reveals that the remote sensing and GIS-based SCS-CN model can be used effectively to estimate the runoff from the ungauged Indian watersheds of similar geohydrological characteristics. [ABSTRACT FROM AUTHOR]

Use of the Soil Conservation Service curve number (SCS-CN) approach is very popular among hydrologists. Despite this, its applications in water quality modeling have been very limited. For the first time, the present work explores the potential of the SCS-CN approach in water quality modeling of the river bank filtration process using a theoretical framework. The approach relates the curve number (CN) with the filtration/kinetic coefficient and the input applied to the system. The approach is tested for its effectiveness using the field data collected at the river bank filtration site at Haridwar, India. The CN is found to be dependent on travel time between source water and the abstraction well in addition to the influent concentration. For very low or very high values of influent concentration, the curve number exhibits an asymptotic variation approaching 100 and 0, respectively. Using the data on source water quality and the travel time, it is possible to compute the curve number and, subsequently, the filtrate quality at an abstraction well. [ABSTRACT FROM AUTHOR]

The Soil Conservation Service curve number (SCS CN) model has been used in the GIS environment to compute run-off at spatio-temporal scales using remote sensing-derived rainfall for 2004 and climatic normal (1951-80) rainfall data. The SCS CN model takes into account land use/land cover, antecedent soil moisture condition and hydrological soil groups. Temporal 10-day composite Normalized Difference Vegetation Index images of SPOT-VGT sensor, and daily remote sensing-derived rainfall data at 10 km resolution from the NOAA Climate Prediction Centre have been used to generate the land cover and antecedent moisture condition (degree of saturation) respectively. Hydrological soil groups were prepared using the soil texture and their infiltration and drainage characteristics. Run-off coefficient maps were generated using the CN-based rainfall excess run-off. Wetland rice-growing areas of West Bengal, India were used to calculate threshold run-off coefficient (0.2) to identify run-off potential areas for major river basins of India during the monsoon season (June to September). There was a large difference in the spatial pattern of run-off estimated for the year 2004 compared to using normal climatic rainfall data. Area estimates for run-off potential were also found to vary significantly for the climatic normal and in-season (2004) data. The spatial variability showed high run-off potential in the western India river basins like Mahi, Luni, rivers of Saurashtra and Sabarmati in 2004. Run-off potential areas over India have been found to increase abruptly from June (158,700 km²) to July (712,300 km²), and decrease from August (633,400 km²) to September (142,000 km²) during 2004. [ABSTRACT FROM AUTHOR]

This paper recognises the need for a revision of watershed development policy in India in relation to the planning of development interventions involving agricultural intensification and rainwater harvesting and the need for new approaches to assist the planning process. Building on, and using as an example, the results of biophysical and societal impact studies carried out on two watershed development projects in Karnataka three new management/dissemination tools, are suggested. These are (1) the web-based geographical information systems exploratory, climate land assessment and impact management tool dissemination tool for disseminating to policymakers and non-specialist stakeholders the downstream impacts of watershed interventions, (2) the ‘quadrant’ approach for ensuring that sustainability criteria are met and (3) Bayesian networks to investigate the biophysical and societal impacts of interventions. [ABSTRACT FROM AUTHOR]

The article presents a study which discussed modifications to Soil Conservation Service-curve number (SCS-CN) method for long-term hydrologic simulation. The antecedent moisture condition (AMC) and the antecedent moisture amount (AMA) models were applied to estimate annual runoff volumes from daily rainfall depth for large basins in India. The predictive capabilities of selected calibrated procedures in determining average conditions for annual series of rainfall and runoff were analyzed.