Application of remote sensing and GIS for sustainable development

Bibliographic data

Monograph

Persistent identifier:: 856472832

Title:: Application of remote sensing and GIS for sustainable development

Sub title:: [Workshop on "Environmental Modelling Using RS & GIS for Sustainable Development" ... on 11th March 1999]

Scope:: 82 Seiten

Year of publication:: 1999

Place of publication:: Coventry

Publisher of the original:: RICS Books

Identifier (digital):: 856472832

Illustration:: Illustrationen, Diagramme, Karten

Language:: English

Usage licence:: Attribution 4.0 International (CC BY 4.0)

Publisher of the digital copy:: Technische Informationsbibliothek Hannover

Place of publication of the digital copy:: Hannover

Year of publication of the original:: 2016

Document type:: Monograph

Collection:: Earth sciences

Chapter

Title:: GROUNDWATER MODELLING FOR SUSTAINABLE DEVELOPMENT USING GIS TECHNIQUES. Novaline Jacob, J. Saibaba and P. V. S. P. Prasada Raju

Document type:: Monograph

Structure type:: Chapter

76 The main factors to be included in the view of groundwater management are climate, soil and geology, relief and vegetation. A landscape-ecological oriented management has to base on these factors. But the course of management action cannot influence the climate and the relief, of course. Also the soil attributes cannot be changed in an economical way. Mainly landuse can be adjusted by the way of planning the kind and intensity of farming and foresting, plant rotation, nutrient supply etc. (Selige et al., 1994). Certain issues that should be handled by a Sustainable Groundwater Management System are listed in the flow chart (Figure 1). Modelling can be done in a Geographic Information System (G1S) by clubing the hydrologic models with the GRID-based environment supported by GIS. 2.0 DATA BASE AND STRUCTURE • The study area can be converted into a grid, with grid cell of suitable resolution. • Since most of the groundwater related data would be available from pumping wells/bore hole logs they would be point information, which could be interpolated to get spatial data (i.e.) each grid cell would have valid data without any gaps. • Point data could be water level, weathered zone thickness, saturated zone thickness, yield in the wells, rainfall at various rain gauge stations, porosity of aquifer material, Transmissivity (T) and Storage co-efficient (S) depending on the type of porous media from the pumping test data etc. • Bore hole and geophysical sounding data can be interpolated to prepare aquifer basement map. • In order to assess the groundwater prospects by qualitative modelling, data on geomorphology, geological structures, lineaments would also be required in addition to weathered zone thickness, saturated zone thickness and yield in the wells. Lineaments being line data have to be converted into a spatial data by finding the lineament density on a coarse grid say, 1 kmx 1 km. • In order to assess the suitability of groundwater quality for irrigation, drinking or industrial purpose, Electrical Conductivity (EC), pH, Sodium Absorption Ratio (SAR) data etc., have to be collected from the monitoring wells and interpolated to get spatial data. 3.0 MODELLING FOR GROUNDWATER QUANTITY 3.1 Qualitative Modelling for Assessing Groundwater Prospects Groundwater prospects can be assessed in GIS, by combining various data layers on geomorphology, lineament density, geological structures, weathered zone thickness, saturated zone thickness, yield in the wells etc., by assigning appropriate weightages for the parameters and for the classes within these parameters (Novaline et al., 1993). Groundwater prospects would be finally categorised into excellent, good, moderate and poor classes. 3.2 Quantitative Modelling for Assessing Groundwater Quantity Long-term rainfall data can be used to find out how much of precipitation reaches groundwater reservoir after losses at various stages like interception, run-off, evaporation, transpiration etc., to compute monthly recharges. One can determine the safe yield (i.e.) the amount of water that can be withdrawn from an aquifer without producing adverse result and can give safe monthly extractions. One way of assessing groundwater extraction potential is by a standard technique in statistical methodology (Sharma, 1987). It is found by analysis of water table data that ôd (yearly fluctuation of depth to ground water table from the ground surface) can be expressed as a linear function of R (mean rainfall) and V (water pumped from tube wells and open wells) by the following relationship : ôd = a + bR + cV a, b, and c are constants If the limiting value of ôd be taken as zero, and assign R the normal value of the annual rainfall, the corresponding values of V may be considered to be the limiting value of pumpage upto which there will not be any depletion of the groundwater table. This analysis can also be done in GIS. 3.3 Supply-Demand Analysis Supply-Demand analysis can be performed in GIS to see if the recharge and consumption are balanced. One can group the grid cells into cells having equal recharge and extraction, cells having over exploitation and cells with no recharge with the help of monthly recharge, extraction and safe yield values.

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