Decision Support System For Desertification Control Through Floodwater Spreading In Islamic Republic Of Iran

• Main Author: Nejabat, Masoud
• Format: Thesis
• Language: English; English
• Published: 2009
• Online Access: http://psasir.upm.edu.my/id/eprint/5798/1/FP_2009_21_AB.pdf; http://psasir.upm.edu.my/id/eprint/5798/

Floods and droughts have resulted accelerated land degradations in Iran. Land degradation in arid, semi-arid, and dry sub-humid areas is desertification and more than 90% of Iran's area is classified as arid or semi-arid with 43% being susceptible to land degradation. Different forms of floodwater storage have been proposed as solutions that not only reduce flood damages in wet years but also decrease undesirable effects of water shortage during droughts. Floodwater spreading (FWS) is one of the most logical solution for desertification control (DEC) in Iran. FWS increases soil moisture, improves vegetation cover, and diminishes flood-related damages. The FWS requires diligent planning and as such, site selection is expected to be the foremost priority. Decision Support System (DSS) is a new approach capable of facilitating selection and planning of the most appropriate sites for FWS. To identify the optimum diagnostic problems, updated situation and achievements of 37 FWS research stations all over Iran were investigated. Some of the stations (11 of them) with more reliable data that represent the diversity of Iran's climate, morphological zones, and soil types were chosen. From these investigations, 21 new effective factors were defined and the data required for data-base and knowledgebase components of the DSS were gathered. In order to adopt the DSS to FWS conditions, multicriteria decision analysis (MCDA), weighted summation, and expected value methods were selected for ranking, appraising, and weighting, respectively. Validity of DECFWS, a certain DSS developed for Desertification Control through Flood Water Spreading, was tested by 1) comparing results with vegetation results of implemented scenarios at FWS research stations, and 2) comparing with results of land suitability evaluation for controlled alternatives based on USDA 2003 method. The latest version, DECFWS 3.31, was developed under Visual Basic that can help decision makers with presenting the: the most appropriate alternative for a chosen scenario, the most reasonable scenario for each alternative, the alternative with the highest benefit-to-cost ratio, the most appropriate alternative in general (for several scenarios), the irrelevant alternatives, and the uncertainty analysis in ranking. Some advantages of this DSS are: accurate assessment, targeted evaluation and ranking, rapid appraisal, low cost, ease of application, flexible to variations, helpful in presenting irrelevant alternatives, executable despite data scarcity, editable in report presenting, assessing effects score uncertainty, precision in ranking, exact in converting qualitative to quantitative data. Results of this dissertation demonstrate the ability of DSS to solve unstructured problems and yield a variety of alternatives in dry regions. It prompts soil scientists interested in land and environmental managements to become familiar with DSS and its application for sustainable managements, especially under fragile circumstances. However, more comprehensive researches on DEC and new emerging technologies (such as the one used in this thesis) are needed to help conserve the degrading land.