a. najafi nejad

Editorial and Short Notes

Frequency analysis of daily rainfall or return period of rainfall and flooding events is very important considering the behavioral complexity in water resources management; because ignoring it can lead to urban destructive floods. In the present research, three distribution functions of Pearson, Beta, and Gamma were compared to investigate and select the most appropriate distribution function for the precipitation data acquired from meteorology stations and CHIRPS satellite in seven stations in the watershed of Bustan Dam. Statistical analyses showed that satellite data were ineffective to estimate daily precipitation due to high errors in RMSE, MAD, and NASH. Meteorological data were used to spot the best distribution. Google Earth Engine and Python programming language were used. Then, the selected distribution function was used to determine the maximum daily rainfall, frequency probability, and return period of 2, 10, 50, 100, and 200 years. The results of the goodness of fit test, Error Sum of Squares, Bayesian Information Criterion, Akaike Information Criteria well as Kullback-Leibler Divergence showed that in five stations of Kalaleh, Qarnaq, Golestan National Park, Golestan Dam, and Glidagh, the Pearson function is the most suitable distribution function. Also, in the other two stations (Gonbad and Tamar), the Beta function was recognized as a suitable function. However, Gamma distribution in the study area is not efficient. So, it can be concluded that heavy and irregular rainfall can be effective in choosing the best distribution function at each station. Therefore, it is recommended to consider the maximum possible rainfall and as a result of the possible occurrence of floods with principled and accurate management to prevent human and financial losses in susceptible areas, especially in the study area.

Study of soil erosion process and assessment of the control factors are the most important prerequisite for proper management of soil and water resources. This research was carried out to investigate effects of slope and soil properties on runoff and soil loss using rainfall simulator in Chehel-chai watershed, Golestan province. Also, considering the land unit map of the area, three land units were selected in the farm lands. In each land unit, three slope classes of 0-10%, 10-30% and highes than 30% were determined. Then four 10×10 m plots were selected in each slope class. Runoff and erosion were measured in each plot randomly using rainfall simulator with 2 mm/min intensity and 15 min duration in 4 replicates. Soil samples were taken in each plot as well. Results showed that there was a weak correlation between runoff and slope and there was no significant relationship at 0.05 confidence level but there was a significant and positive correlation between soil loss and slope at 0.01 confidence level. Based on the results of the Pearson correlation matrix, the contents of the fine sand in 1% confidence level and lime and silt at 5% confidence level had positive correlation with runoff and soil moisture content had positive correlation and soil surface resistance had negative correlation with soil loss. However, runoff volume and soil loss increased 8% and 100%, respectively in slope class of more than 30% in comparison with 0-10% slope class. With increasing slope, soil resistance decreased and soil loss increased.