Prioritization of watersheds using multi-criteria evaluation through fuzzy analytical hierarchy process

Conservation of available natural resources through demarcation of potential zones at micro level are primary necessitate for sustainable development, particularly in the fragile semi-arid tropics.  Delineation of potential zones for implementation of conservation measures above the entire watershed at similar occurrence is inaccessible as well as uneconomical; consequently it is a prerequisite to apply viable technique for prioritization of sub-watersheds (SWDs).  Keeping this in view, the present research attempted to study various morphological characteristics and to implement Geographical Information System (GIS) and Multi Criteria Decision Making (MCDM) through Fuzzy Analytical Hierarchy Process (FAHP) techniques for identification of critical sub-watersheds situated in transaction zone between mountainous and water scarcity region of Western Part of India.  The morphometric characterization was obtained through the measurement of three distinct linear, areal and relief aspects over the eight sub-watersheds.  The morphometric characterization showed imperative role in distinguishing the topographical and hydrological behavior of the watershed.  Each hydrological unit was ranked with respect to the value and weightages obtained by deriving the relationships between the morphometric parameters obtained through classification of the SWDs by associating the robustness of fuzzy logic and the Analytical Hierarchy Processes (AHP).  Based on FAHP approach, sub-watersheds were evaluated as vulnerability assessment zones and alienated into five prioritization levels: very less, less, medium, high and very high classes.  The evaluated results illustrated that 60.85% of sub-watersheds (five sub-watersheds) were in the medium to high susceptible zones, which depicted potential areas for necessity of establishment of conservation interventions for the sustainable watershed management planning.  The FAHP based technique is a viable approach in illustrating the dilemma particularly over data hungry and complex conventional soil and water risk assessment methods and will be useful to various stakeholders (rural extension community, agriculturists and water resources managers) for better decision making with an obliging rule based system for implementing various assessment measures.   Keywords: fuzzy analytical hierarchy process, geographic information system, multiple criteria decision making, watershed prioritizatio

Optimum Design of a Watershed-Based Tank System for the Semiarid and Subhumid Tropics

This article was published in the serial, Journal of Irrigation and Drainage Engineering [© American Society of Civil Engineers ]. The definitive version is available at: http://ascelibrary.org/iro/resource/1/jidedh/v137/i10/p651_s1?isAuthorized=noSmall reservoirs known as tanks are constructed in the watersheds of arid, semiarid, and subhumid regions of India to provide supplementary or protective irrigation to crops during dry spells of the monsoon season or full irrigation during the postmonsoon season. The stored water in tanks or recharged groundwater is used for this irrigation. Several models have previously been developed to design the capacity of individual tanks. However, for optimum utilization of water generated in a watershed to meet the demands for irrigation and for downstream release, it is necessary to design the tanks together in terms of their number, locations, and capacities. A comprehensive methodology for this is presented using stream points, i.e., possible tank locations on the main stream(s) in the watershed. Tank strategies (combinations of numbers of tanks, their locations at stream points, and tank types) are then generated for the identified stream points. Subsequently, fields in the watershed are assigned to the catchment and the command of different tanks of a specified tank strategy. Simulation of field, tank, and groundwater balance is then carried out on a daily basis, from which optimum tank dimensions are obtained for a specified tank strategy. The optimum tank strategy and corresponding optimum tank dimensions are obtained by investigating all the possible tank strategies

Spectral reflectance characteristics, vegetation and leaf area indices for sorghum (Sorghum bicolor L.)

A growing number of studies have focused on evaluating the spectral indices in terms of their sensitivity to vegetation biophysical parameters like leaf area index. In this context, different hyperspectral ratios and normalized difference vegetation indices were computed for sorghum based on groundbased spectral data obtained in 350-2500 nm wave length region over the crop growth period of sorghum. The analysis of the hyperspectral data was carried out to compare the performance of vegetation indices (Normalized Difference Vegetation Index [NDVI], Renormalized Difference Vegetation Index [RDVI], Modified Simple Ratio [MSR], Soil-Adjusted Vegetation Index [SAVI], Modified Soil-Adjusted Vegetation Index [MSAVI], and Modified Chlorophyll Absorption Ratio Index [MCARI]) by linearly relating to LAI separately for growth and decline phases. The regression coefficient values were found in the range of 0.79 to 0.87 for growth phase and 0.89 to 0.98 for decline phase. The most significant relationship of LAI was found with MSAVI when growth (R2 of 0.87) and decline (R2 of 0.98) phases were analyzed separatel

Seasonal ARIMA model for generation and forecasting evapotranspirtion of Solapur district of Maharashtra

This paper deals with the stochastic modeling of weekly reference crop evapotranspiration in semi-arid climatic condition by using seasonal Auto Regressive Moving Average (ARIMA) model. The weekly values of reference crop evapotranspiration (ETr) estimated by Penman Monteith method for 23 years (1984 to 2006) were used to fit the ARIMA models of different orders. ARIMA models up to 1st order were selected based on autocorrelation function (ACF) and partial autocorrelation function (PACF) of the ETr series. The parameters of the selected models were obtained with the help of maximum likelihood method. The ARIMA models that satisfied the adequacy tests were selected for forecasting. One year ahead forecast (i.e. for 2007) of ETr values were obtained with the help of these selected models. The root mean square error (RMSE) was computed between forecast and actual values of ETr of 2007. The lowest RMSE was obtained for ARIMA (1,1,0) (1,0,1)52 and hence is the best stochastic model for generating and forecasting of weekly ETr values