JWSS - Journal of Water and Soil Science

The aim of this study was to investigate the climate change impacts on some factors affecting rainfed wheat growth such as effective rainfall, planting date and length of growing season in four stations located in Chaharmahal and Bakhtiari province. Firstly, it is necessary to predict future (2046-2065) climatic conditions. For this purpose, the output of HADCM3 general circulation model was used under three scenarios of A1B, A2 and B1. The data were downscaled by LARS-WG model. After simulating the climatic parameters in mention period, the effective rainfall during the wheat growing season was calculated by Food and Agriculture Organization method. Also, the optimum planting date was defined according to the date of the first rain (at least 10 mm in case of continuing for next days). The wheat's growth stages were determined by Growing Degree Days method. The results indicated a rise in temperature for four stations. On average, it is expected that the annual temperature increase by 1.8°C compared with the baseline period (2010-1990). Total annual precipitation in Shahrekord, Koohrang and Borujen will decrease 2.2, 7.8 and 3.6 per cent respectively. About Lordegan it will increase by 2.7 per cent. Also, the results showed that in three stations of Shahrekord, Koohrang and Borujen, the amount of effective rainfall in November will increase compared to baseline, but in Lordegan it will reduce. So, in the first three stations, in most years, planting date was obtained earlier than baseline, but in Lordegan it was later than baseline. The Length of growing season will reduce in Shahrekord, Borujen and Lordegan stations, 12 days on average and in Koohrang about 13 days.

In the vast majority parts of the Earth, a prospect now visible is the mostly synthetic thinking and fabrication by the human hand. Collision and impact of humans on the natural environment in the short and long-term courses for obvious geographical features have changed a variety of spaces. One of the consequences of human impact on the natural environment during the current period is the phenomenon of climate change. One of the climatic parameters that plays an important role in agriculture, energy, urban, tourism and road transport is the minimum temperature. In this study, an attempt was made using the minimum temperature data from 5 meteorological stations in the West Mazandaran province, as well as HADCM3 model data, to show how to change this parameter in the future periods based on simulation by the SDSM model. Accordingly, after selection of the suitable climate variables and model calibration, the accuracy of the created model in the base period was evaluated; after ensuring the sufficient accuracy of the model according to A2 and B2 scenario, data minimum temperature in 2100 was simulated. Based on the simulation results showed that the values of minimum temperature in the region over the coming years would increase. This parameter was such that the average seasonal periods 2016 to 2039, 2040 to 2069 and 2070 to 2099, as compared to the baseline period would increase, on average, by 1.8, 3.5 and 6 percent. The largest increases in the minimum temperature in the western and southern parts of the region could occur. It was also found that unlike other months of the year, the minimum temperature in January would be a decreasing trend.

Estimation of soil moisture at various temporal and spatial scales is a key to the strategic management of water resources. Satellite-based microwave observations have coarse spatial resolution despite widespread and continuous of the provision surface soil moisture (SSM). In this study, the SSM data from the Advanced Microwave Scanning Radiometer 2 (AMSR2) 25km resolution were used and these products were downscaled by three parameters retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) to 1km resolution. In the next step, the integration of the SSM downscaling model with SMAR model was used to monitor the root zone soil moisture(RZSM) in the study area (Rafsanjan plain). In order to evaluate the performance of the proposed method, the SSM and the soil profile moisture were measured at 10 points in the Rafsanjan plain. Comparison of AMSR2 25k SSM and downscaled SSM with the field measurement data showed that the mean of total stations for the correlation coefficient(R) was increased from 0.540 to 0.739 and the mean absolute error(MAE) and the root mean square(RMSE) were reduced from 0.039 and 0.040 to 0.018 and 0.020, respectively. Moreover, the results obtained from the validation of the RZSM values showed that the proposed method could estimate the RZSM with high accuracy and indicate the variations.