Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/456591
Title: Optimal Allocation Of Land And Water Resources For Maximum Net Return From A Canal Command Area
Researcher: Khandelwal,Suresh Suvalal
Guide(s): Dhiman,Sanjay D.
Keywords: Canal Command
Deterministic And Stochastic RegimesĀ 
Engineering
Engineering and Technology
Engineering Civil
Ground Water Recharge
Limbasi Branch
Optimal Allocation
University: Dharmsinh Desai University
Completed Date: 2017
Abstract: Increase in irrigated agriculture is essential to satisfy the food requirements of newlinecontinuously rising population. However, without proper planning and management of newlineland and water resources, this increase in irrigated agriculture may lead to the problem of waterlogging in irrigated areas resulting in crop yield reduction and abandonment of newlineagricultural land. This condition demands the optimal and planned allocation of land and newlinewater resources, which can be achieved by the use of optimization models. newlinePresent study aims at the formulation of suitable mathematical models in the deterministic and stochastic regimes to optimally allocate available land and water resources so as to maximize the net return while simultaneously mitigating water logging problem of a canal command area. The developed models are applied to the Limbasi branch canal command area of Mahi Right Bank Canal Command (MRBC), Gujarat State, India, which is found to be suffering from water logging conditions. Salinity problem of the study area is also addressed by designing trapezoidal and circular types of evaporation ponds. Annual volume of water to be disposed through evaporation ponds was worked out as 4.0825 MCM which was approx. 9% of total ground water pumped annually and 25% of net annual recharge. newlineThe study was started by analyzing the rainfall and temperature data of the study area. Net Irrigation Requirements (NIR) of different crops of the study area in the deterministic regime was estimated from rainfall and temperature data. In the stochastic regime, NIR was estimated at 2 to 40% risk levels. Goodness of fit was tested by Kolmogorov Smirnov test and normal distribution was found as best fit. Trend analysis of groundwater depth for different wells located in the command area indicated rise in groundwater table with time. Groundwater recharge in the study area was estimated by developing a suitable hydrological budget model and applied to the study area. newline
Pagination: 238
URI: http://hdl.handle.net/10603/456591
Appears in Departments:Engineering

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02_prelim_pages.pdf328.78 kBAdobe PDFView/Open
03_content.pdf56.52 kBAdobe PDFView/Open
04_abstract.pdf68.74 kBAdobe PDFView/Open
05_chapter1.pdf267.6 kBAdobe PDFView/Open
06_chapter2.pdf1.14 MBAdobe PDFView/Open
07_chapter3.pdf574.51 kBAdobe PDFView/Open
08_chapter4.pdf1.02 MBAdobe PDFView/Open
09_annexures.pdf382.02 kBAdobe PDFView/Open
80_recommendation.pdf99.05 kBAdobe PDFView/Open
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