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|Title: ||Spatial optimal allocation of land and water resources using GIS and genetic algorithm|
|Authors: ||Galgale, Harshal|
|Issue Date: ||2006|
|Publisher: ||© Harshal Galgale|
|Abstract: ||This research focuses on spatial optimal allocation of land and water resources for
crop production in agricultural watersheds. The process of optimal allocation is complex
due to spatial and temporal variation in supply and demand parameters. In this
study methodology that integrates the system simulation models (hydrological and crop
growth), economic analysis model, and resource allocation model (using genetic algorithm
evolutionary optimisation technique) within GIS is developed to build a spatial
decision support system (SDSS) for spatial and optimal allocation of resources.
This study investigated different ways of integrating simulation models with GIS
(loose coupling, tight coupling and full coupling). The study revealed that the full
coupling method is superior to other two methods of integration. The full coupling
(integrated) approach is used to develop the SDSS.
The hydrological processes such as rainfall, interception, infiltration, runoff, channel
routing, deep percolation, evaporation, crop evapotranspiration, irrigation and crop
growth are considered for the development of distributed hydrological simulation model
in this study. The outputs of this model are runoff, net benefits, crop yields and water
use pattern for the specified landuse plan.
The resource allocation (optimisation) model developed for optimal spatial allocation
of land and water resources in the watershed uses the hydrological simulation
model as external evaluation function for GA optimisation technique. The optimisation
model is designed to handle various objective functions (to maximise cropped area, crop
yields and net benefit; to minimise runoff). The GA generates initial population (landuse
plans). These landuse plans are evaluated by the hydrological simulation model
and are then ranked according to their fitness. The best performing landuse plans are
used to reproduce new landuse plans using crossover and mutation operators of GA.
The newly generated landuse plans are evaluated and are competed with the initial
set of population to get included in the next generation. The next generation is reranked
according to their fitness and the process is repeated till the optimal solution is
obtained. The optimal set of population contains land and water resources allocation
plans performing on par.
The developed SDSS was applied to the Pimpalgaon Ujjaini watershed, a case study
watershed from Ahmednagar District, Maharashtra, India. The satellite remote sensing
images of the study area were used to develop the landuse and other thematic maps.
These maps were used to generate the initial population. The application of the model
resulted in spatial optimal land and water resource allocation plans. These plans enable
the decision makers to investigate on what has to be changed and where the changes
have to be made for sustainable development. The SDSS gives the decision maker a
powerful tool to study the effect of changes in watershed.|
|Description: ||A Doctoral Thesis. Submitted in partial fulfillment of the requirements for the award of Doctor of Philosophy of Loughborough University.|
|Appears in Collections:||PhD Theses (Architecture, Building and Civil Engineering)|
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