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Behavior Analysis and Modeling of Stakeholders in Integrated Water Resource Management with a Focus on Irrigated Agriculture

The scarcity of freshwater resources in the Sultanate of Oman, makes it essential that both surface and groundwater resources are carefully managed. Introducing new water demand management tools is important, especially for the coastal agricultural areas (e. g. Al Batinah coastal region) which are affected by sea water intrusion. Based on a social survey performed during this work, the existing situation generates conflicts between different stakeholders (SHs) which have different interests regarding water availability, sustainable aquifer management, and profitable agricultural production. The current aim is to evaluate the implementation potential of several management interventions and their combinations by analysing opinions and responses of the relevant stakeholders in the region. Influencing the behavior and drivers affecting farmers’ decision-making manner, can be a valuable tool to improve water demand management. The work also introduces the use of a participatory process within the frame of an integrated water resources management (IWRM) to support decision makers in taking better informed decisions. Data were collected by questionnaires from different groups of stakeholders. These data were analysed statistically for each group separately as well as relations amongst groups by using the SPSS (Statistical Package for Social Science) software package. Differences were examined between opinions of farmers and decision makers (DM’s) regarding potential interventions. Farmers’ frequency curves showed differences in opinions in some interventions, while differences in opinions were not so high within the group of DM’s. Therefore, Cross Tabulation and Discriminant Analysis (DA) were performed to identify the drivers influencing farmers’ opinions regarding the intervention measures. As an advanced step, a Bayesian Networks (BNs) approach is used for mapping stakeholders’ behaviors and to show the strength of a relationship between dependent and predictor variables. By using BNs it is possible to analyse future scenarios for implementation and acceptance of interventions.

Identiferoai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:33195
Date15 February 2019
CreatorsAl Khatri, Ayisha Mohammed Humaid
ContributorsSchütze, Niels, von der Weth, Rüdiger, Zekri, Slim, Technische Universität Dresden
Source SetsHochschulschriftenserver (HSSS) der SLUB Dresden
LanguageEnglish
Detected LanguageEnglish
Typedoc-type:doctoralThesis, info:eu-repo/semantics/doctoralThesis, doc-type:Text
Rightsinfo:eu-repo/semantics/openAccess

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