Groundwater assessment in Salboni Block, West Bengal (India) using remote sensing, geographical information system and multi-criteria decision analysis techniques

An approach is presented for the evaluation of groundwater potential using remote sensing, geographic information system, geoelectrical, and multi-criteria decision analysis techniques. The approach divides the available hydrologic and hydrogeologic data into two groups, exogenous (hydrologic) and endogenous (subsurface). A case study in Salboni Block, West Bengal (India), uses six thematic layers of exogenous parameters and four thematic layers of endogenous parameters. These thematic layers and their features were assigned suitable weights which were normalized by analytic hierarchy process and eigenvector techniques. The layers were then integrated using ArcGIS software to generate two groundwater potential maps. The hydrologic parameters-based groundwater potential zone map indicated that the ‘good’ groundwater potential zone covers 27.14% of the area, the ‘moderate’ zone 45.33%, and the ‘poor’ zone 27.53%. A comparison of this map with the groundwater potential map based on subsurface parameters revealed that the hydrologic parameters-based map accurately delineates groundwater potential zones in about 59% of the area, and hence it is dependable to a certain extent. More than 80% of the study area has moderate-to-poor groundwater potential, which necessitates efficient groundwater management for long-term water security. Overall, the integrated technique is useful for the assessment of groundwater resources at a basin or sub-basin scale.     

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.     

Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models

Climate Dynamics - The present study explored the performance of the current coupled models obtained from the Asia Pacific Economic Cooperation (APEC) Climate Centre (APCC) in representing the...     

Indian summer monsoon rainfall variability during 2014 and 2015 and associated Indo-Pacific upper ocean temperature patterns

Theoretical and Applied Climatology - In this study, factors responsible for the deficit Indian Summer Monsoon (ISM) rainfall in 2014 and 2015 and the ability of Indian Institute of Tropical...     

Landslide Hazard Zonation using Remote Sensing and GIS: a case study of Dikrong river basin, Arunachal Pradesh, India

Landslides are among the most costly and damaging natural hazards in mountainous regions, triggered mainly under the influence of earthquakes and/or rainfall. In the present study, Landslide Hazard Zonation (LHZ) of Dikrong river basin of Arunachal Pradesh was carried out using Remote Sensing and Geographic Information System (GIS). Various thematic layers namely slope, photo-lineament buffer, thrust buffer, relative relief map, geology and land use / land cover map were generated using remote sensing data and GIS. The weighting-rating system based on the relative importance of various causative factors as derived from remotely sensed data and other thematic maps were used for the LHZ. The different classes of thematic layers were assigned the corresponding rating value as attribute information in the GIS and an “attribute map” was generated for each data layer. Each class within a thematic layer was assigned an ordinal rating from 0 to 9. Summation of these attribute maps were then multiplied by the corresponding weights to yield the Landslide Hazard Index (LHI) for each cell. Using trial and error method the weight-rating values have been re-adjusted. The LHI threshold values used were: 142, 165, 189 and 216. A LHZ map was prepared showing the five zones, namely “very low hazard”, “low hazard”, “moderate hazard”, “high hazard” and “very high hazard” by using the “slicing” operation.     

Delineation of groundwater recharge zones and identification of artificial recharge sites in West Medinipur district,West Bengal,using RS,GIS and MCDM techniques

Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. This study proposes a methodology to delineate artificial recharge zones as well as to identify favorable artificial recharge sites using integrated remote sensing (RS), geographical information system (GIS) and multi-criteria decision making (MCDM) techniques for augmenting groundwater resources in the West Medinipur district of West Bengal, India, which has been facing water shortage problems for the past few years. The thematic layers considered in this study are: geomorphology, geology, drainage density, slope and aquifer transmissivity, which were prepared using IRS-1D imagery and conventional data. Different themes and their corresponding features were assigned proper weights based on their relative contribution to groundwater recharge in the area, and normalized weights were computed using the Saaty’s analytic hierarchy process (AHP). These thematic layers were then integrated in the GIS environment to delineate artificial recharge zones in the study area. The artificial recharge map thus obtained divided the study area into three zones, viz., ‘suitable,’ ‘moderately suitable’ and ‘unsuitable’ according to their suitability for artificial groundwater recharge. It was found that about 46% of the study area falls under ‘suitable’ zone, whereas 43% falls under the ‘moderately suitable’ zone. The western portion of the study area was found to be unsuitable for artificial recharge. The artificial recharge zone map of the study area was found to be in agreement with the map of mean groundwater depths over the area. Furthermore, forty possible sites for artificial recharge were also identified using RS and GIS techniques. Based on the available field information, check dams are suggested as promising artificial recharge structures. The results of this study could be used to formulate an efficient groundwater management plan for the study area so as to ensure sustainable utilization of scarce groundwater resources.     

Application of the WEPP model for prioritization and evaluation of best management practices in an Indian watershed

The pre‐calibrated and validated physically based watershed model, water erosion prediction project (WEPP) was used as a modelling tool for the identification of critical watersheds and evaluation of best management practices for a small hilly watershed (Karso) of India. The land use/cover of the study area was generated using IRS‐1C LISS‐III (linear imaging self scanner) satellite data. The watershed and sub‐watershed boundaries, drainage, slope and soil map of the study area were generated using ARC/INFO geographic information system (GIS). The WEPP model was finally applied to the Karso watershed which lies within Damodar Barakar catchment of India to identify the critical sub‐watersheds on the basis of their simulated average annual sediment yields. Priorities were fixed on the basis of ranks assigned to each critical sub‐watershed based on the susceptibility to erosion. The sub‐watershed having the highest sediment yield was assigned a priority number 1, the next highest value was assigned a priority number 2, and so on. Subsequently, the model was used for evaluating the effectiveness of best management practices (crop and tillage) for conservation of soil for all the sub‐watersheds. On the basis of this study, it is realized that cash crops like soyabean should be encouraged in the upland portion of the sub‐watersheds, and the existing tillage practice (country plough/mould board plough) may be replaced by a field cultivation system for conservation of soil and water in the sub‐watersheds. Copyright © 2009 John Wiley & Sons, Ltd.