Classification of Rainfall Warnings Based on the TOPSIS Method

Abstract

Abstract:Extreme weather, by definition, is any unexpected, unusual, unpredictable, severe or unseasonal weather condition. A rainfall event that is considered normal in one region may be considered a torrent in a dry region and may cause flash flooding. Therefore, appropriate weather warnings need to be issued with respect to areas with different climates. Additionally, these alerts should be easy to understand-by clear classification-in order to apply reinforcements. Early warning levels not only depend on the intensity and duration of rainfall events, but also on the initial water stress conditions, land cover situations and degree of urbanization. This research has focused on defining different warning levels in northwest Iran using long-term precipitation data from 87 weather stations well distributed across the study area. Here, in order to determine alert levels, TOPSIS (The Order of Preference by Similarity to Ideal Solution), as one of the most common methods in multi-criteria decision making, has been used. Results show that five main levels of alerts can be derived, leading to the provision of spatial maps. Further, it can be deduced that these levels are highly associated to the location of a region at different times: months/seasons. It has been observed that the issuance of a warning for precipitation should correspond with the location and time. At one location during different seasons, different alert levels would be raised corresponding to the rainfall. It was also concluded that using of fixed alert levels and extending them to larger areas without considering the seasons could be grossly misleading.

A Multi Criteria Decision Analysis Approach for Regional Climate Model Selection and Future Climate Assessment in the Mono River Basin, Benin and Togo

“…The best alternative is identified as the closest to the positive ideal solution and the farthest from the negative ideal solution. The TOPSIS method is widely used for ranking alternatives and for decision making in water resources management, early warning systems, participatory flood risk management, social learning, and consensus achievement among stakeholders [32][33][34][35]. It has been increasingly used in the last decade in the field of climatology to select among different datasets [24][25][26][27][28]36].…”

Precipitation variability, trends and regions in Poland: Temporal and spatial distribution in the years 1951–2018

“…Differences in the extent of atmospheric precipitation in Poland are primarily explained by the effect of certain types of atmospheric circulation; high importance is attributed to cloud cover (Degirmendžić, Kożuchowski and Żmudzka 2004;Żmudzka 2009;Twardosz, Niedźwiedź and Łupikasza 2011;Młyński, Cebulska and Wałęgaet 2018). For extreme phenomena it is difficult to prove the significance of a trend and regularities in the development of a given phenomenon (Pfeifer et al 2015;Zeyaeyan et al 2017). The observed differences in temporal distribution of precipitation totals between particular years result in irregular periods of drought and excessive precipitation, whose negative social and economic effects cannot be prevented (Kundzewicz, Radziejewski and Pińskwar 2006;Dumrul and Kilicarslan 2017;Brázdil et al 2019).…”

Reallocation of water resources according to social, economic, and environmental parameters

“…TOPSIS 32 , a multi-criteria decision-making method has been successfully implemented in various studies, and the results have revealed its great potential as an MADM method (e.g., 33,34 ). After simulating the generated scenarios and calculating the values of the five evaluation indicators, TOPSIS was used to rank the scenarios and select the best one.…”