Analysis of Precipitation Trends and characteristics on Agricultural Water Resources in Lorestan Province

The analysis of hydrological events is one of the important components of the management of water resources and consumption. The amount of water consumption directly depends on the climatic phenomena in a region. Rainfall is one of the important indicators of climate change, which has been considered by researchers in the probabilistic analysis of hydrological phenomena. This research has been conducted with the aim of evaluating trend analysis and estimation of rainfall return period in water resources management of Lorestan province using modified Mann-Kendall method and bivariate probabilistic modeling.

The study area is Lorestan province located in the western part of Iran. Based on the conceptual framework of the study, time series of rainfall data were collected for the statistical period of 35 years from 1365 to 1400. In order to analyze the trend of precipitation in the province, the modified Mann-Kendall non-parametric test was used. Furthermore, Archimedean joint functions were used to determine the return period of two variables, duration and height of precipitation.

The results showed that in most parts of Lorestan province, the height of rainfall in the 10-year return period was less than 50 mm per day. This amount of rainfall will provide between 100 and 200 million cubic meters of agricultural water for eight cities. Noorabad and Aleshtar respectively have the highest and lowest predicted amounts of water in the next 10 years. Moreover, the comparison of precipitation trends showed that there was no significant decreasing or increasing trend at the 5% confidence level.

The results showed that although a significant decreasing or increasing trend was not detected using the Man-Kendall method in the cities of Lorestan province, the return period of rainfall indicates a decrease in available water resources for agriculture. Planning based on bivariate distribution functions showed that the duration of rainfall can play a decisive role in calculating the return period.