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

Water Resources Management (Impact Factor: 2.6). 06/2009; 23(8):1581-1602. DOI: 10.1007/s11269-008-9342-9


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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    • "The GIS is a computer program that can manage a large amount of physical spatial data (but also social data) in an effective way (Moody and Ast, 2012). In the literature, use of GIS for water management is increasing, especially when evaluating the sustainability of water management options (Chowdary et al., 2009), because sustainable water management considers a wide number of variables. When working with spatially distributed climate, soils and land-use variables, the amount of data can be high (Satti and Jacobs, 2004). "
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    ABSTRACT: Large-scale water assessment models can be valid decision support systems for water management institutions. We developed a spatially distributed model in order to evaluate efficiencies of irrigation scenarios. Model development required four stages: questionnaire data collection from farmers, integration of questionnaire data with water supply and physical soil characteristics data, cluster analysis with Management Zone Analyst, and GIS for spatial distribution. Four irrigation scenarios in the north-east of Italy were compared: (i) the current condition (three turns of 24 h of supplied water per month), (ii) scenario 2 (three turns of 16 h of supplied water per month), (iii) scenario 3 (four turns of 12 h per month); and (iv) scenario 4 (4 turns of 10 h per month). In the current irrigation scheme, results show high potential water excess in every month of the irrigation season. Shifting from three to four irrigation turns per month increased the probability of water excess, because water losses decreased and water availability for plants increased. For the same reason, potential water excess increased when the duration of each turn decreased, even when the total water supply was reduced. The irrigation efficiency index, therefore, was lowest in scenario 1 compared to the other scenarios. Scenario 4, in contrast, was the most efficient.
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    • "Remote sensing is identified as an important tool supporting the management of natural resources and agricultural practices for wider spatial coverage. Thus, daily evapotranspiration models derived from remote sensing techniques are better suited the estimation of crop water use at a regional agriculture scale (Allen et al. 2007; Chowdary et al. 2009; Muthuwatta et al. 2010). "
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    ABSTRACT: Daily evapotranspiration is a major component in crops water consumption management plans. Consequently, forecasting of daily evapotranspiration is the keystone of any effective water resources management plans in fragile environment similar to the Nile Delta region. The estimation of daily evapotranspiration was carried out using Surface Energy Balance System (SEBS), while the forecasting of the daily evapotranspiration was carried out using Auto Regressive Integrated Moving Average (ARIMA) and its derivative Seasonal ARIMA. Remote sensing data were downloaded from European Space Agency (ESA) and used to estimate daily evapotranspiration values. Remote sensing data collected from August 2005 till December 2009 on a monthly basis for daily evapotranspiration estimation. The application of the most adequate ARIMA (2,1,2) to the evapotranspiration data set failed to sustain the forecasting accuracy over a long period of time. Although, time series analysis of daily evapotranspiration data set showed a seasonality behavior and thus, using seasonal ARIMA [(2,1,2) (1,1,2)6] was the optimum to forecast the daily evapotranspiration over the study area and sustain the forecasting accuracy. A linear regression model was established to test the correlation between the forecasted daily evapotranspiration values using S-ARIMA model and the actual values. The forecasting model indicates an increase of the daily evapotranspiration values with about 1.3 mm per day.
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    • "Conventionally the delineation of groundwater potential zones were done by ground surveys however with the advent of technologies such as remote sensing and GIS such tasks has become easier. Remote sensing and GIS have been applied in several groundwater potential zonation studies (Panigrahi et al. 1995; Krishnamurthy and Srinivas 1995; Krishnamurthy et al. 1996; Sander et al. 1996; Edet et al. 1998; Jain 1998; Saraf and Choudhury 1998; Murthy 2000; Shahid et al. 2000; Jaiswal et al. 2003; Saraf et al. 2004; Sener et al. 2005; Solomon and Quiel 2006; Jha et al. 2007; Chowdary et al. 2009; Chenini et al. 2010; Machiwal et al. 2011; Singh et al. 2011b). Gustafsson (1993) used GIS for the analysis of lineament data derived from SPOT imagery for groundwater potential mapping. "
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    ABSTRACT: The present research is an attempt to find out the groundwater potential zones within an arid region of India supported by the scientific investigation of lithology, geomorphology, geohydrological characterization of geological formations and their interrelationship. Thematic layers of drainage, lithology, geomorphology, lineaments, slope, soil, digital elevation model, rainfall, landuse/land cover and well inventory have been generated by using ancillary data, digital satellite image, water level data of 90 observation wells for last 11 years (2000–2010), litholog data along with ground truthing. The groundwater potential zones have been classified into five categories like very poor, poor, moderate, good and excellent. The potential zones were obtained by weighted overlay combination using the spatial analyst tool in ArcGIS 9.2. During weighted overlay analysis, the ranking was given for each individual parameter of each thematic map and weights were assigned according to their influence such as lithology (20 %), geomorphology (15 %), lineament density (15 %), drainage density (15 %), soil (10 %), slope (10 %), rainfall (5 %), land use and land cover (5 %) and digital elevation model (DEM) (5 %) and it was found that the potential zones in terms of very poor, poor, moderate, good and excellent zones covered 13.7 %, 42.8 %, 27.3 %, 10.8% and 5.4% respectively of the total area. The result also has been validated by yield data collected from existing sources and it confirms that the higher yield categories are falling within excellent groundwater potential zones where yield ranges from 23 to 40.3 l/s and lower values ranging from 8.1 to 10.6 l/s are falling within poor groundwater potential zones.
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