JWSS - Journal of Water and Soil Science

The estimation of reference crop evapotranspiration (ETo) is one the important factors in hydrological studies, irrigation planning, and water resources management. This study attempts to explore the possibility of predicting this key component using three different methods in the Sistan plain: Generalized Linear Models (GLM), Random Forest (RF) and Gradient Boosting Trees (GBT). The maximum and minimum temperature, mean temperature, maximum and minimum humidity, mean humidity, rainfall, sunshine hours, wind speed, and pan evaporation data were applied for years between 2009 to 2018. Using various networks, the ETo as output parameter was estimated for different scenarios including the combination of daily scale meteorological parameters. In order to evaluate the capabilities of different models, results were compared with the ETo calculated by FAO Penman-Monteith as the standard method. Among studied scenarios, M1 covering the maximum number of input parameters (10 parameters) showed the highest accuracy for GBT model, with the lowest RMSE (0.633) and MAE (0.451) and the maximum coefficient of regression (R = 0.993). Air temperature was found as the most sensitive parameters during sensitivity analysis of studied models. It indicated that accuracy and precision of temperature data can improve the results. Application of the GBT model could decrease the time consumed to run the model by 70%. Therefore, the GBT model is recommended for estimation of ETo in the Sistan plain.

In order to plan and manage the land and its changes, it is necessary to identify and evaluate the factors affecting it. Land use / cover changes are one of the main factors in global environmental change that is defined as a change in the type of land use; it is one of the major factors changing hydrologic flow, land erosion and destruction of biodiversity. The main purpose of this study was to assess the trends of land use changes in Beheshtabad Watershed of Chaharmahal and Bakhtiari Province with an area about 3847 square kilometers by using remote sensing and GIS during a 25-year period. In this research, first, analyzing and pre-processing the satellite images of Landsat 5 TM sensors from 1991 and 2008 were done, and Landsat 8 of OLI sensor of 2016 was applied. Then, by using the hybrid classification method, 5 land use classes including pasture lands, urban-building lands, agricultural lands, garden lands and bare lands, land use maps for the three time periods were prepared. The overall accuracy of the obtained land use maps for 1991, 2008 and 2016, was 92.17%, 94.29% and 93.41%, respectively, indicating the acceptable accuracy of the maps. Then, the process of land use change and the contribution of each land use classes and the percentage of changes in each land use class were determined in two study periods. The results of this study showed some changes occurred in the studied watershed. The total area of pasture lands during two periods indicated the decreasing trend, but urban-building and garden lands during two periods represented the increasing one. Agricultural lands during the first period indicated the decreasing trend and during the second period showed the increasing trend, while bare lands during the first period showed the increasing trend and during the second period, reflected the decreasing trend. In general, it should be noted that in the Beheshtabad watershed, we could see an increase in the replacement of pastures by urban-building class, rainfed agriculture, gardens, and bare lands, the incidence of destruction in the region.

In this study, spatial-temporal variation of dust deposition rate in the western and eastern half of Tehran and its climatic parameters affecting were studied. At 34 points in the city, dust samples were collected by glass traps from the roof, for twelve months, and the climatic data were obtained and analyzed from relevant organizations. The highest deposition rate is in the western half of the city and its total amount has varied from 54.52 to 121.21 g/m²/y. In both halves of the city, summer has the highest dust deposition rate and its central areas have the highest amount. There were significant positive correlations between dust deposition rate with temperature and medium wind speed, and there were significant negative correlations between dust deposition rate with rainfall and relative humidity in all months, which justifies the high dust deposition rate in the dry seasons of the year. The results of stepwise regression showed that rainfall was the most important factor affecting the dust deposition rate in both halves of the city. The city of Tehran has a special geographical location the presence of mountains like a barrier has prevented dust from leaving the city and the air inlet corridor of Tehran has faced problems due to the expansion of building construction and high-rise building. Other factors affecting the rate of dust deposition in this city, in addition to the distance from the main source of dust production, atmospheric parameters can be mentioned the existence of barren lands around the city, vegetation cover, construction operations, and traffic.