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Formulation of a proper watershed management plan requires reliable and up-to-date information about various factors such as morphologic (size and shape of the watershed, drainage parameters, topography), soil and their characteristics, land use, and land cover, etc. that affect the behavior of a watershed. Satellite based remote sensing technology and GIS meets both the requirements of reliability and speed and are ideal tools for generating spatial information needs. In this study, a locale-specific watershed development plan was generated for the case study area of a small agricultural watershed of Karso, Hazaribagh, India using remote sensing and GIS techniques. Indian Remote Sensing Satellite (IRS-1C), Linear Imaging Self Scanner (LISS-III) satellite data along with other datasets, e.g. existing maps and field observation data have been utilized for generating a land use/land cover map and to extract information on morphological parameters (bifurcation ratio, elongation ratio, drainage density, ruggedness number, relief ratio, and circulatory ratio) and other thematic maps which are an essential prerequisites for watershed development. Morphological parameters of subwatersheds were derived to understand its usefulness for surface water development. The conceptual framework for plan and site suitability mapping for soil and water conservation structures is developed and subsequently, these parameters were integrated with other thematic information viz., land use/cover, drainage, slope, and soil in the GIS environment to arrive at a decision regarding a suitable site for having soil and water conservation structures (, check dam, and percolation tank) in its place adopting a holistic approach. Copyright © 2010 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The article presents a study which evaluates the adoption of the hydrological model water erosion prediction project (WEPP) as a modelling tool for erosion-based watershed prioritization and for identification of best management practices in Karzo watershed of Hazaribagh, India. It notes the use of linear imaging self scanner satellite data and geographic information system (GIS). It also offers insights on the use of cash crops and field cultivation system for watershed conservation.

A systematic planning of groundwater exploitation using modern techniques is essential for the proper utilization and management of this precious but shrinking natural resource. With the advent of powerful and high-speed personal computers, efficient techniques for water management have evolved, of which RS (remote sensing), GIS (geographic information system) and GPS (Global Positioning System) are of great significance. In the present study, an attempt has been made to delineate and classify possible groundwater potential zones in the West Medinipur district of West Bengal, India using integrated remote sensing and GIS techniques. The thematic layers considered in this study are lithology, landform, drainage density, recharge, soil, land slope and surface water body, which were prepared using the IRS-1D imagery and conventional data. All these themes and their individual features were then assigned weights according to their relative importance in groundwater occurrence and the corresponding normalized weights were obtained based on the Saaty's analytical hierarchy process. The thematic layers were finally integrated using ArcInfo GIS software to yield a groundwater potential zone map of the study area. Thus, three different groundwater potential zones were identified, namely 'good', 'moderate' and 'poor'. The area having good groundwater potential is about 1400 km2, which is about 15% of the total study area. The eastern portion and some small patches in the central and northern portions of the study area fall under moderate groundwater potential zone, which encompasses an area of 5400 km2 (55%). However, the groundwater potential in the western, south-western and parts of north-eastern portions of the study area is poor, encompassing an area of about 3000 km2. Moreover, the average annually exploitable groundwater reserve in the good zone was estimated to be 0.29 MCM/km2, whereas it is 0.25 MCM/km2 for the moderate zone and 0.13 MCM/km2 for the poor zone. Finally, it is concluded that the RS and GIS techniques are very efficient and useful for the identification of groundwater potential zones. [ABSTRACT FROM AUTHOR]

Rainfall is one of the fundamental components of the hydrological cycle as its accurate estimation is necessary for planning, designing and operation of water resources development programmes. In the present study, monthly stochastic model was developed using rainfall data for Doimukh (Itanagar), Arunachal Pradesh, India. The rainfall series was assumed to be composed of deterministic and stochastic components. The trend component was found to be non-significant. Fourier series analysis was used to identify the periodic component. Three harmonics were found significant. The stochastic component was modeled by fitting into auto regressive model of order 6. The Mean and standard deviation of the generated series were found to be close to the historical values. The value of absolute error, relative error, correlation coefficient and Nash-Sutcliffe coefficient indicated a high degree of model fitness to the observed data series. [ABSTRACT FROM AUTHOR]

In the present study, Karso watershed of Hazaribagh, Jharkhand State, India was divided into 200 x 200 grid cells and average annual sediment yields were estimated for each grid cell of the watershed to identify the critical erosion prone areas of watershed for prioritization purpose. Average annual sediment yield data on grid basis was estimated using Universal Soil Loss Equation (USLE). In general, a major limitation in the use of hydrological models has been their inability to handle the large amounts of input data that describe the heterogeneity of the natural system. Remote sensing (RS) technology provides the vital spatial and temporal information on some of these parameters. A recent and emerging technology represented by Geographic Information System (GIS) was used as the tool to generate, manipulate and spatially organize disparate data for sediment yield modeling. Thus, the Arc Info 7.2 GIS software and RS (ERDAS IMAGINE 8.4 image processing software) provided spatial input data to the erosion model, while the USLE was used to predict the spatial distribution of the sediment yield on grid basis. The deviation of estimated sediment yield from the observed values in the range of 1.37 to 13.85 percent indicates accurate estimation of sediment yield from the watershed. [ABSTRACT FROM AUTHOR]