h. asakereh

Identifying the behavior of precipitation is one of the most important planning principles related to water resources. In this research, an attempt was made to analyze the trend of time changes in extreme rainfall profiles of the country by using the daily rainfall data of 3423 synoptic, climatology, and rain gauge stations for the period from 1970 to 2016 and by performing interpolation using the kriging method. Then, using percentile profiles (percentile less than 10, less than 25, 25 to 75, 75 to 90, and above 90) and regression analysis, changes in the frequency of member days of each of the percentile methods over time were calculated and mapped. The results showed that during the studied period, 86.6% of cells associated with days with the tenth percentile or less in the country had an increasing trend. On the other hand, the pixels associated with days with the 90th percentile and more have shown an increasing trend. Considering that the pixels with the 25th, 25th-75th percentiles (normal), and 75th percentile have shown a decreasing trend in terms of the number of days in their group, it can be concluded that the country's rainfall conditions and the days with rainfall are towards the limit values has moved and the possibility of drought or destructive floods has increased in the country.

Precipitation is one of the main elements of the Earth's hydro-climatic cycle and its variability depends on the complex and non-linear relationships between the climate system and environmental factors. Understanding these relationships and doing environmental planning based on them is difficult. Therefore, classifying data and dividing information into homogeneous and small categories can be helpful in this regard. In the present study, an attempt was made to prepare precipitation, altitude, slope, slope direction, and station density data for 3423 synoptic, climatological, and gauge stations in Iran in the 1961-2015 years’ period. These data were entered into fuzzy (FCM), self-organizing map neural network (SOM-ANN) models and precipitation-spatial zoning. The outputs of the two models were compared in terms of accuracy and efficiency. The results obtained from the output of the models have divided the rainfall conditions of Iran into four zones concerning environmental factors. Evaluations also showed that both models had high accuracy in classifying precipitation parameters; However, the fuzzy model has a relative advantage over the neural network model in the accuracy of results.

Precipitation is one of the most significant climatic parameters; its distribution and values in different areas is the result of complex linear and nonlinear relationships between atmospheric elements-climatic processes and the spatial structure of the earth's surface environment. Classification of data and placing them in small and homogeneous zones can be effective in improving the understanding of these complex relationships and their results. In the present study, zoning and analyzing the distribution of rainfall in Iran concerning environmental factors was performed using the annual precipitation data of 3423 synoptic, climatological, and gauge stations in the country during the period from 1961 to 2015 and the altitude, slope, aspect, and station density data. After standardization and preparation of the data matrix, the optimal number of clusters was determined and the data set was entered into the neural-fuzzy network model (ANFIS-FCM). The results showed that the values of R2  and MAE  indices were 0.76 and 0.23, respectively which indicate the appropriate accuracy of the model. It was also found that in the four output zones of the model, environmental factors have a high impact on the spatial distribution of precipitation. In the first and third zones, the combination of high altitude and slope factors along with geographical proximity to precipitation systems has caused the average annual rainfall in these zones to be 318 and 181 mm, respectively. The mean annual rainfall has decreased to about 100 mm by the weakening of the role of environmental factors in the second and fourth clusters.

Precipitation is one of the most important climatic variables playing a decisive role for different purposes. Temporal changes in precipitation affect many climatic and environmental phenomena (such as runoff, floods, air temperature, and humidity) as well as many human activities (such as agriculture and housing). The precipitation regime includes all characteristics and statistics of precipitation in relation to its distribution throughout the year, and the temporal distribution of precipitation according to the months or seasons of the year is called the "Precipitation Regime".

The daily data of 385 stations were obtained from Iran Meteorological Organization and the Ministry of Energy for the period of 2016-1966 (51 years). The hidden aspects of precipitation and precipitation regime of the Iranian coast of Caspian Sea were studied. At first, these stations were used in order to create maps with a spatial resolution of 3 × 3 km, and the general specifications of the monthly and annual precipitation were presented. Sinusoidal behaviors of monthly precipitation in each pixels were then investigated. Accordingly, first to sixth harmonics were extracted. Finally, the cluster analysis method was used based on the Euclidean distance and the "Ward" method of linkage to identify the spatial patterns of precipitation based on the contribution of different periodic and its zoning. Then, the homogeneity and seasonal index of precipitation was estimated.

The results show that the mean annual precipitation is higher on the coastline, especially in the southwest of the Caspian Sea, and decreases as it passes from the coast. In the southwest parts of the Caspian Sea, maximum precipitation occurs in the autumn. At the Alborz highlands, the maximum and minimum precipitation fall during winter and summer, respectively. The monthly precipitation coefficient of variation indicates that with seasonal changes from winter to spring, precipitation changes in the Caspian region are declining, and with changes in seasonal precipitation from summer to autumn, precipitation changes are in the ascendant. The largest variability coefficient of the month to month of the precipitation (60 to 70 percent) was calculated at the coastline of the Caspian Sea. This shows notable month to month precipitation changes and seasonal instability in these areas. The coefficient of variation is gradually reduced by distance from the coastline. The lowest coefficient of variation was obtained in the southern parts of the Caspian Sea (the Alborz altitudes) between 15% and 30%. This suggests a small difference in rainfall over the course of the months. In other words, they indicate the activity of various rainy systems, or at least the continuity of rainy systems in these areas, and the stability of the precipitation season. The homogeneity index indicates that the precipitation distribution is more concentrated in the coastal areas of the Caspian Sea, and it becomes more uniform with the advance towards the southern parts of the area (part of the Alborz heights). The seasonal precipitation index of the Caspian Sea region indicates three types of precipitation regime. The lowest spatial extent (6.28%) is related to the uniform precipitation regime, found in small parts of the Alborz heights. The most abundant regime has a wetter season. This precipitation regime, which includes 76.13% of the Iranian coast of Caspian Sea, is observed in the eastern and western regions of the Caspian Sea. The third regime (13.25% of the study area), which is mainly seasonal with a short dry season, covers the Caspian Sea coastline, parts of the Talesh heights, and a small part of the eastern region.

The results revealed that the precipitation classes obtained based on the seasonal index were closer to the reality due to the similarity of these classes with the average monthly and annual precipitation. Therefore, this index seems to be the most optimal tool for determining precipitation regimes in the Caspian region. According to this precipitation regime classification, there are three classes of precipitation regime in the Caspian region. The existence of these three classes indicates the presence and activity of different synoptic and local systems in the Caspian region.