AI Summary & Key Takeaways
AI InsightTherefore, different methods should be used as much as possible, not just only one method,for filling missing values and comparison of the results from different methods would lead to bestmissing data filling method.
📌 3 Key Takeaways
Abstract
For the planning of water resources based on the demands through the basin, water potential of thebasin must be analyzed carefully. For these analyses to be accurate and dependable, completemeteorological and flow data must be obtained which covers a long period of previous years. Because,especially missing flow monitoring data used at the planning stage of water structures have beenreported to induce serious hazards at the operating stage. In this paper, filling of the missing data obtained from the flow gauging stations (FGS) wasperformed using regression analyses related to the correlations and drainage area-ratio methods. ZabRiver basin has been used for studying area.In order to fill the missing data, linear and non-linear regression equations have been used foridentifying the missing values without disturbing the statistical structure of the original (long) data sets.The same approach was followed for drainage area-ratio method. The size of missing part of the data,however, is one of the most important points to consider in filling the missing values. Especially in caseof large amount of missing values, both filling methods resulted in large deviation when compared withoriginal data. Therefore, different methods should be used as much as possible, not just only one method,for filling missing values and comparison of the results from different methods would lead to bestmissing data filling method.