Evaluation and Optimization of Rain Gauge Network Based on the Geostatistic Methods and Firefly Algorithm. (Case study: Eastern Basin of Urmia Lake)

Rainfall is the main motivator in the hydrologic cycle of the basin and it is an element of meteorological phenomena undergoing severe changes in time and place. The suitability of density and distribution of rain gauges in the rain gauge networks of each area is an effective step in the success of the water plans, regional projecting and effective use of the information (Karamouz et al., 2010). Many researchers have shown that the geostatistical prediction method provides better estimates of the regional rainfall than the traditional methods. Tanaka and Putthividhya (2013) used the geostatistical method to assess the quality of the rainfall estimation in the Basin of Chao Phraya. They tried to calculate the difference between the rainfall data and the results obtained from the above methods by plotting Thiessen Network and the co-ordinate lines by nverse Distance Weighting and Ordinary Kriging methods. They also examined the correlation between the height, humidity and temperature with the recorded rainfall values. The findings showed that height had a significant correlation with Monsoon rainfall, while humidity and temperature correlated with the monthly rainfalls. Yang and He (2013), using the super innovative firefly algorithm concluded that this algorithm is more  suitable than the optimal search strategy. Considering the problems of Urmia Lake located in the northwest of Iran, comprehensive studies with an inclusive approach to the problems in this basin are considered necessary. Indeed, it is necessary to concentrate more on the process used in the design of the rain gauge networks and begin to redesign the existing networks in order to refine and complete them.