Designing Monitoring Network for Rain Gauge Stations Using IrregularityTheory (Case Study: Urmia Lake Basin)

Designing of water quantity and quality monitoring system has been raised as one of the most complex issues in the field of water resources and the environment. Designing of these systems used to achieve qualitative and quantitative information, while their design process requires basic information. The study area in this research is Urmia Lake basin that located in the North West of Iran. Entropy literally means disorder. In this study used entropy theory to rain gaging monitoring in period of 1984-2011. Also The modified Mann - Kendal test was used to study the trend of the studied parameters The results of the study of the trend of precipitation values of Urmia Lake basin at annual scale showed that rainfall changes in this basin have been decreasing in the annual scale. In order to study and monitoring the rain gauge network using Entropy theory, two methods of support vector regression and kriging were used to estimate precipitation values. Results indicated that the accuracy of the regression model was higher than the Kriging model. The results of the evaluation of the entropy index at the aquifer showed that only 1.4% of the studied basin had a severe shortage of information that required the construction of a new station in the area. However, since more than 90 percent of the basin area is in terms of data transmission in excess and relatively excessive condition, the study area is relatively good at its monitoring. In general, the results indicated that the accuracy of the optimized method of support vector regression was used to estimate the annual rainfall in the Urmia Lake basin. The results of the stations' ranking in the study area showed that the stations of Jharabad, Badamlou and Orban received ratings ranging from 1 to 3, which indicates the transfer and reception of more information than other stations.