Spatio-temporal analysis of trend the hydro-climatic time series and identify factors affecting Flood Hazard

Floods have consistently been regarded as a significant threat in natural environments, making the identification and analysis of factors influencing flood trends crucial for effective flood Hazard management and mitigation in watersheds. So, this study looked into how spatial-temporal trends relate to hydro-climatic time series. It also found factors that affect flood risks and the role of hydro-climatic factors in the Doab Veysiyan watershed. We used powerful tests like the classic Mann-Kendall test to examine and analyze the data's trend, and the modified Mann-Kendall (TFPW) test to eliminate serial correlation from the hydro-climatic time series. Furthermore, we employed the weighted linear combination (WLC) method, the most widely used decision rule in GIS, to perform spatial zoning of flood hazards. This method is based on the Analytical Hierarchy Process (AHP) and weights derived from pairwise comparisons of relevant criteria and sub-criteria.These criteria included precipitation intensity and quantity, runoff coefficient, slope, geology, land use, soil hydrological group, vegetation cover percentage, flooding coefficient, and drainage density. Trend analysis of monthly precipitation data using the Mann-Kendall test revealed that the highest statistics with a significant upward trend belong to the Kakareza station with values of 2.64 and 3.06 for the months of November and March, respectively. Furthermore, according to this test, the precipitation at Khorramabad station exhibits a significant downward trend among the existing stations, with a statistic of -2.64 in March. The upward trend of maximum precipitation during different continuity periods at Kakareza and Dehnoo stations is consistent with the upward trend of maximum instantaneous discharge at Bahramju and Karganeh stations, with a statistic of 1.86. A statistical analysis of the relationship between the highest instantaneous discharge of the Doab Veysiyan and Cham Anjir rivers and upstream precipitation stations shows a strong link with rainfall over a two-day period at the Kakareza station, with coefficients of 0.89 and 0.91 for each. In fact, by comparing the maximum rainfall data with daily continuity and instantaneous maximum discharge, it is possible to clearly identify the effective regional storms and determine the most effective upstream rainfall gauge stations in the event of flooding. The WLC model's results for spatial zoning of flood hazard potential show that the most important factors and criteria affecting this event are the amount of rain and the runoff coefficient weights, with a value of 0.146. This method is also very good at modeling flood risks, as shown by the area under the curve (AUC) of 0.76 for the probability of the 2019 flood happening or not happening based on the ROC curve, which is significant at the 5% level. Therefore, we recommend trend analysis of hydro-climatic data and zoning flood hazard potential, prioritizing rainfall intensity and runoff coefficient, for optimal flood management in various global regions.