IRS-1C data application in watershed characterization and management

Saxena, R. K.; Verma, K. S.; Chary, G. Ravindra; Srivastava, Rajeev; Barthwal, A. K.

doi:10.1080/014311600750019822

Cited by 45 publications

(18 citation statements)

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“…Pandey et al (2007) divided Karso Watershed of Hazaribagh, Jharkhand State, India into 200×200 m grid cells and average annual sediment yields were estimated for each cell of the watershed to identify the critically prone areas of watershed. Recent studies (Pandey et al 2007;Yoshino and Ishioka 2005;Chowdary et al 2004;Pandey et al 2004;Sharma et al 2001;Khan et al 2001;Saxena et al 2000;Sidhu et al 1998;Sharda et al 1993;Prasad et al 1992) revealed that RS and GIS techniques are of great use in characterization and prioritization of watershed areas.…”

Section: Introductionmentioning

confidence: 95%

Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing

Dabral

Baithuri

Pandey

2008

Water Resour Manage

316

137

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In the present study, soil erosion assessment of Dikrong river basin of Arunachal Pradesh (India) was carried out. The river basin was divided into 200×200 m grid cells. The Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data and the USLE was used to predict the spatial distribution of the average annual soil loss on grid basis. The average rainfall erositivity factor (R) for Dikrong river basin was found to be 1,894.6 MJ mm ha −1 h −1 year −1 . The soil erodibility factor (K) with a magnitude of 0.055 t ha h ha −1 MJ −1 mm −1 is the highest, with 0.039 t ha h ha −1 MJ −1 mm −1 is the least for the watershed. The highest and lowest value of slope length factor (LS) is 53.5 and 5.39 respectively for the watershed. The highest and lowest values of crop management factor (C) were found out to be 0.004 and 1.0 respectively for the watershed. The highest and lowest value of conservation factor (P) were found to be 1 and 0.28 respectively for the watershed. The average annual soil loss of the Dikrong river basin is 51 t ha −1 year −1 . About 25.61% of the watershed area is found out to be under slight erosion class. Areas covered by moderate, high, very high, severe and very severe erosion potential zones are 26.51%, 17.87%, 13.74%, 2.39% and 13.88% respectively. Therefore, these areas need immediate attention from soil conservation point of view.

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Section: Introductionmentioning

confidence: 95%

Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing

Dabral

Baithuri

Pandey

2008

Water Resour Manage

316

137

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“…(Still and Shih, 1985;Pande and Saha 1994;Sudhakar et al, 1994;Jose et al, 1994;Saxena et al, 2000). Remote sensing data can permit hydrologists to derive the curve number as percentage basis from the SCS table (Ragan and Jackson, 1980;Tiwari et al, 1991).…”

Section: Introductionmentioning

confidence: 97%

Prioritization of watersheds using morphometric parameters and assessment of surface water potential using remote sensing

Suresh

Sudhakar

Tiwari

et al. 2004

J Indian Soc Remote Sens

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In the present study, prioritization of sub-watersheds was carried out on the basis of sediment production rate. Further, basic hydrologic information such as peak rate of runoff and annual surface water potential were also assessed for the study watersheds and these are essential requisites for effective watershed management. The 10 sub watersheds of Tarai development project area are selected for the present study. Morphometric parameters pertaining to study area are used in the estimation of sediment production rate. The sediment production rate in the study area varies between 2.45 to 11.0 ha-m/100 km2/year. The remote sensing data has been utilized for generating land use/land cover data which is an essential prerequisite for land and water resource planning and development. The remote sensing data can especially play significant role in collection of real time information from remote areas of river basins for generation of parameters required for hydrologic modeling.

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“…Further, Decision Support Systems' (DSS) show greater promise in the strategic planning of soil conservation efforts and can aid in the selection of appropriate soil conservation practices for agricultural watersheds (Montas and Madramootoo 1992;Saxena et al 2000;Yoshino and Ishioka 2005). Thus, the potential of satellite remote sensing in various applications related to water resources is well established: hence, it is necessary to use this technology not only for targeting of groundwater potential zones, but also for identifying location specific activities such as percolation tanks, check dams, farm ponds etc.…”

Section: Introductionmentioning

confidence: 99%

Integrated Water Resource Development Plan for Sustainable Management of Mayurakshi Watershed, India using Remote Sensing and GIS

Chowdary

Ramakrishnan

Srivastava

et al. 2008

Water Resour Manage

138

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Integrated watershed management requires a host of inter-related information to be generated and studied in relation to each other. Remote sensing technique provides valuable and up-to-date spatial information on natural resources and physical terrain parameters. Geographical Information System (GIS) with its capability of integration and analysis of spatial, aspatial, multi-layered information obtained in a wide variety of formats both from remote sensing and other conventional sources has proved to be an effective tool in planning for watershed development. In this study, area and locale specific watershed development plans were generated for Mayurakshi watershed, India using remote sensing and GIS techniques. Adopting Integrated Mission for Sustainable Development (IMSD) guidelines, decision rules were framed. Using the overlay and decision tree concepts water resource development plan was generated. Indian Remote Sensing Satellite (IRS-1C), Linear Imaging Self Scanner (LISS-III) satellite data along with other field and collateral data on lithology, soil, slope, well inventory, fracture have been utilized for generating land use/land cover and hydro geomorphology of the study area, which are an essential prerequisites for water resources planning and development. Spatial data integration and analyses are carried out in GIS environment.

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IRS-1C data application in watershed characterization and management

Cited by 45 publications

References 0 publications

Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing

Soil Erosion Assessment in a Hilly Catchment of North Eastern India Using USLE, GIS and Remote Sensing

Prioritization of watersheds using morphometric parameters and assessment of surface water potential using remote sensing

Integrated Water Resource Development Plan for Sustainable Management of Mayurakshi Watershed, India using Remote Sensing and GIS

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