جستجوی مقالات مرتبط با کلیدواژه "hadcm3 model" در نشریات گروه "آب و خاک"

Given the extensive cultivation of maize in Iran, any initiative aimed at increasing water use efficiency contributes to reducing water consumption and enhancing food security in the country. One of the most influential factors affecting the growth and performance of crops is the impact of climate change. The present study aims to assess the impact of climate change and altering planting dates on the water productivity of maize in Gorgan County. Additionally, water productivity of maize under different irrigation treatments and planting dates is simulated using the WOFOST model for future conditions. The irrigation treatments include 100% (T1), 75% (T2), and 50% (T3) of the plant's water requirements. Hence, statistical SDSM and HadCM3 General Circulation Model were employed to downscale all scenarios of the fifth report for two thirty-year periods, 2020-2050 and 2050-2080. The results showed with increasing of irrigation water stress, the simulation error of irrigation water productivity increased, but no consistent trend was observed. In the period of 2050-2020, the highest irrigation water productivity was predicted in treatment T3 on 23 June, amounting to 4 kilograms per cubic meter, which represents a 1.9% reduction compared to the baseline period. During this period, the lowest irrigation water productivity was projected in treatment T1 on 2 June, amounting to 2.7 kilograms per cubic meter, indicating a 57.3% reduction compared to the baseline. Based on the simulated results, the optimal planting time for corn in Gorgan is on 23 June. With appropriate validation of the planting date, effective management can be implemented to adapt to the negative effects of climate change on corn water productivity. Choosing the best planting time, along with proper management, is an efficient solution in Gorgan to prevent reduced performance due to an inappropriate choice of planting date.

Rainfall properties is impacted by climate change that includes change in number of wet days, duration, intensity and amount of precipitation. This article shows impact of climate change on intensity and rainfall amount in south coast of Caspian Sea. In this research, rainfall is estimated by the aid of HadCM3, A1B and LARS-WG for triple periods 2011-2030, 2045-2065 and 2080-2099. According to estimation results, average precipitation will increase but there is not any evident pattern for monthly scale in study stations. Additionally, according to results, seasonal rainfall changes will increase in winter and in contrary, it will decrease in summer. Intensity simulation results by IDF curves determine that maximum 30-minute intensity will increase in future periods in compares with observational periods except Babol station. In addition, the maximum and minimum 30-minutes intensities in studied return periods, 2, 5, 10, 20, 50, and 100 years are belonged to Anzali and Sangdeh, respectively. Furthermore, maximum 30-minutes intensities in studied return period of 100 years will be %38 will occur in Gorgan in 2080-2099 and minimum will be %0.88 that will occurred in Behshahr in 2030-2011 Finally, this research shows that precipitation events will exacerbate in future periods, which will have consequence in runoff, percolation, sediment and soil erosion in south coast of Caspian Sea that it needs to proper planning for more adaption to climate change in Iran northern region.

Climate change is one of the most important challenges that have significant effects on human life. In the recent decades, the climate situation resulted in changes in the volume, duration and time of runoff, which might have many considerable effects on the management of water resources. In this study, the main purpose is to obtain fluctuation of runoff over the coming decades (2030-2011) using the IHACRES model. For this purpose, the maximum temperature, minimum temperature and precipitation parameters over the coming decades (2030-2011) were investigated using the LARS-WG program and the HadCM3 model. The obtained data of HadCM3 have entered the IHACRES model at 8 hydrometric stations, located in Ardabil province south and southwest. So, the runoff rate was achieved in the coming decades (2030-2011). The result shows that the precipitation rate has fluctuated in the coming decades, and for the period of 2011-2030, precipitation has decreased till 3.68% and the maximum temperature and minimum temperature increased, 16.48 and 5.39 percent, respectively. Also, the results of the runoff amount during the next decades at the hydrometric stations showed that the average discharge has decreased total 0.16 percent, and on the other hand, peak discharge has increased. The highest increase in the floods evens was observed in the Yamchi hydrometric station with 2.09 m3.s-1average and 16 days with discharge higher than 6 cubic meters per second.

In the present paper, fluctuations of inflow into the Karun-4 Dam under different scenarios of the climate change for the future period of 2021-2050 were investigated. For this purpose, the outputs of the HadCM3 model under the scenarios of B1 (optimistic) and A2 (pessimistic) were utilized for the fourth report; additionally, the outputs of the ensemble model under RCP 2.6 (optimistic) and RCP 8.5 (pessimistic) scenarios were used for the fifth report. Moreover, in order to estimate runoff in the future period, the artificial neural network was considered as a rainfall-runoff model. The results indicated that the average annual precipitation in the five study stations under B1 and RCP 2.6 scenarios was increased by 15 and 5%, respectively, while it showed a decrease equal to 8 and 6%, respectively under the scenarios A2 and RCP 8.5. Furthermore, the average annual temperature in all scenarios showed increase, which was at least 1.06 ⁰C under the scenario B1 and 1.89 ⁰C under scenario RCP 8.5. Examining the input inflow into the Karun-4 dam showed that under both B1 and RCP 2.6 scenarios, the annual inflow will be increased by 1.8 and 1.5%, respectively; under the two scenarios A2 and RCP of 8.5, the annual inflow will be decreased to 10.4 and 9.8%, respectively.

In this study downscaling of temperature was down in Tajan Plain located in the province of Mazandaran. The result of atmospheric general circulation models was obtained with HadCM3 climate model under scenario A2. Since the output of atmospheric general circulation models has a low locative resolution, should be downscaled in the area or Basin level that it was conducted with statistical method. The statistical methods used included of downscaling SDSM5.5. And artificial neural network model. In this study, by using the average daily temperature data of Kordkheil Station during the30-year statistic Period (1971-2001) and the large-scale variables NCEP, as inputs to the neural network and SDSM model, simulation and downscaling was down respectively of the maximum and minimum temperature in the last period to determine models error. To this end were used of the features and functions available in the programming software MATLAB. Then To evaluate the performance of the models, were used the statistical criteria including of correlation coefficient, coefficient of declaration and root mean square error between observed and predicted values ​​of temperature. The obtained results show the appropriate performance of SDSM model for downscaling temperature Than the ANN model. So that the error percentage of SDSM model is lower and the correlation coefficient is more than the ANN model. The best Structure of neural network to simulate of maximum temperature is perceptron model with four hidden layer with the 5-5-6-6 architecture and for the minimum temperature Variable is perceptron model with three hidden layer with 5.3.1 architecture.

In this research, the long-term effect of climate change on the spatial and temporal distribution of precipitation in Iran was investigated under A1B, A2 and B1 scenarios up to 2100. The LARS-WG model calibrated by daily precipitation data from 52 synoptic stations for the reference period (1980-2100) was used for downscaling the HADCM3 atmospheric general circulation model data under the mentioned scenarios up to 2100. The spatial distribution maps of precipitation changes were prepared in GIS environment. Low root mean square error (RMSE) and high efficiency factor (EF) values for comparing the observed and simulated precipitation, demonstrates the ability of LARS-WG for precipitation simulation. Simulation results showed that climate change causes a non-uniform precipitation increase for both spatial and temporal scales in a major part of the country. The precipitation increase over the Caspian Sea, Oman Sea and Persian Gulf coasts, western hillsides of the Zagros Mountains and northern hillsides of the Alborz Mountains was higher than that in the central, eastern and north-eastern parts. Despite a positive significant increasing trend in rainfall during 1980-2100, a decreasing trend was observed in rainfall during 2010-2100 so average rainfall during 2041-2070 and 2071-2100 was lower than one for 2011-2040. These results emphasize on the need for planning to optimally use of green water in the country.

This research work was aimed to investigate agricultural water demand and water requirement using HadCM3 model that occur due to climate change in Aidoghmoush irrigation network at time period 2026-2039. At first، monthly temperature and precipitation data of HadCM3 model were provided and downscaled in the baseline period (1987-2000) and the future period (2026-2039) under the SRES emission scenario، namely A2. Results showed that the temperature increased (Between 1. 0 to 1. 8) and precipitation varied (-28 to 33 percent) in 2026-2039 compared with baseline period (1987-2000). In order to estimate the water requirements، crop evapotranspiration and effective rainfall were calculated. The potential evapotranspiration and the crop evapotranspiration were calculated to FAO Penman-Monteith and FAO-24 method، respectively. Calculation the potential evapotranspiration in future periods (due to lack of information) through the relationship of temperature and potential evapotranspiration in the base period was conducted. Then، for risk analysis، downscaled temperature and precipitation for 2026-2039 were introduced to water requirement model and monthly net water requirement was simulated in the future and in the sequel، water demand and the risk increase of its changing considered. The study also revealed risk increase in agriculture water demand، as these increase is of 10 to 13 (for the risk of 50% and 25%). Considering the present areas of the selected crops (wheat، barley، alfalfa، soya، feed corn، forage maize، potato and walnut) and their augmented requirements، volume of 6 to 9 MCM/y for 2026-2039 period (for the probability of 50% and 25%) will be required to meet the demands. Finally، it is found that responses of the crops were different where wheat and barley more variability to this phenomenon.