lars-wg

The impact of climate change and global warming on Earth's climate and other systems such as water sources, agriculture, environment, industry, health and the economy as a known the threats to sustainable development. So the effects of climate change on different systems and adaptive solutions to deal with the negative consequences of this phenomenon in future periods is essential. So according to importance of the issue, the purpose of this study was to evaluate the effects of climate change on temperature, precipitation, runoff and finally hydrological drought in the “Roude Zard” watershed in the future. For this purpose, data from the years 2000-1971 as a base data to small-scale model of LARS-WG introduction and calibration data for the years 1997-1990 and 1989-1974 years data were used to validate models of rainfall-runoff IHACRES. In order to evaluate hydrologic drought index SDI was used. Results show that increase in mean annual temperature in the study area 1.02 degrees Celsius as well as the expected changes in mean annual precipitation to the study area 11/91 percent and 73/78 millimeters. Results IHACRES model to simulate rainfall-runoff study area show that this model is suitable. The simulation results runoff also indicated an increase in the average runoff affected by climate change in some of the months of January, February and March and a decrease in average monthly runoff out of the area in September, October. Also results of the SDI index show increase in intensity of drought in the future compared to the base period. The results of this study will be to adapt to climate change studies in order to provide suitable management strategies used in the study area.

Today, climate issues threaten the security of the world, security which is considered necessary and vital in all fields and for all people. The phenomenon of climate change can affect the water requirement of crops by changing the amount of evaporation and transpiration of plants and the duration, intensity and time of rainfall. The studies related to climate change that have been conducted in Iran in recent years have focused more on climatic indicators and the effects of these changes on agricultural production have been given less attention. Therefore, assessing the effects of climate change on agriculture is an essential need. Due to the fact that Ardabil province is one of the poles of agriculture and animal husbandry and any change in the climate will endanger the lives of most of the residents of this region and will cause a change in the use of farms, pastures and the loss of agricultural production.kkkT Therefore, assessing the effects of climate

The study area is located on the slopes of Sabalan Mountain in Ardabil and East Azerbaijan provinces. Its geographical location is located at latitudes of 37 degrees and 44 minutes to 38 degrees 25 minutes and longitude 46 degrees and 22 minutes to 48 degrees 41 minutes. The minimum height of the area is 371 meters and its maximum is 4811 meters above sea level (Fig, 1). This study was conducted to influence climate change in wheat cultivation on slopes of Sabalan mountain. The important part of this research is based on statistics and information about meshkinshahr and sarab synoptic stations. In order to investigate the climate change conditions, a basic statistical period and a period as climate change should be determined. Therefore, statistical periods in this study from 1995 to 2015 and climate change period from 2016 to 2045 and 2046 were selected. Statistics about the studied stations were obtained from the Statistics and Information Bank of the National Meteorological Organization. The data taken from these statistics include: maximum and minimum temperature,daily rainfall and sunshine. to work with the LARS-WG model; First, the studied data should be sorted as Julius days. After collecting data in the Excel environment, it should be noted that there is no missing data, in case of missing, it must be encoded with -99. Aggregated data must be stored in a folder in nodpad with st extension.The address of folders stored in the N environment should be provided to the model from the option series, and the output data address should be given to the model. How to choose a scenario. First, in Excel environment, statistical data is placed in a column and in the next step, the generated data for each scenario is placed in the columns in front of each column of observational statistics, after preparing this step, the data is taken to the spss environment and correlation is taken between observational and production data. Production scenarios that are highly correlated with observational statistics are accepted as the studied scenario. CROPWAT software was used to estimate water requirement and effective precipitation. By entering minimum temperature, maximum temperature, relative humidity, wind speed and number of sunshine hours related to the plant, as well as the environment and region and its cultivation time, you can calculate the water requirement of the plant at different growth stages. Figure 2 shows the steps of data analysis in CROPWAT software.

In this study, first, the power of LARS-WG model for the basic statistical period of the years (1995-2015) was measured. The purpose of this assessment is whether the model has the ability to simulate for future periods. To do this, the tst file containing the results of comparing the statistical characteristics of the observed data with the simulated data was plotted as a diagram (Shapes, 2 and 3). The results showed that in Meshkinshahr station, the model has better efficiency for simulating maximum temperature and minimum temperature. The observed temperature and simulated temperature for 1995-2015 are similar and the diagrams are overlapping. Also, the deviation of production criteria is in the range of number one. This model is not effective in simulating the sunshine hour because it simulates the amount of sunshine hours in the first half of the year less than the actual size. In the case of rainfall, the model is better than April and May in other months. In Sarab station, the data were performed based on LARS-WG model by comparing the statistical period data and the produced data. To ensure the ability of computational data model, they were compared by model and observational data in the studied stations. Comparative results show the data of minimum temperature, maximum temperature, precipitation and sunshine in mirage synoptic stations for the base period. The capability of LARS-WG model in modeling minimum temperature, maximum temperature and radiation in these stations is completely in accordance with the observed data. The standard deviation rate is between 0.5 and 1. The results of this study show that in Meshkinshahr station, precipitation and temperature in the period 2016 to 2045 are -3.9 and +1.73, respectively, and these two variables in the period 2046 to 2065 are -6.67 and +1.80, respectively. In Sarab station, precipitation and temperature in the period 2016 to 2045 were +6.17 and -0.69, respectively, and in the statistical period of 2046 to 2065 were -12.91 and +0.37, respectively. As a result, rainfall in the coming periods is associated with a decrease in Sarab and Meshkinshahr stations, respectively. Temperatures are also rising at about 2 °C in Meshkinshahr station and the temperature increase is low in Sarab station. In comparison, Sarab plain has a wonderful state because by the period 2046 to 2065 the rainfall in this plain will decrease about 13% compared to the base period, in the same time period, wheat evapotranspiration will reach from 530 mm in the base period to 887 mm in the period 2046 to 2065. Wheat water requirement also increases from 422 mm in the base period to 810 mm, i.e. about 92%. Also, modeling shows that the average minimum temperature of this region decreases from -3 in the base period to -9.67 °C in January and from -4.3 to -8.23 in February. According to the modeling and with the decrease in rainfall in this region, wheat cultivation in this plain will face limitations in the future. However, the results of the models indicate that meshkinshahr plain is better in future periods than Sarab plain.

Owing to the rise in water demand and looming climate change, recent years have witnessed much focus on global drought scenarios. Drought as a complex natural hazard is best characterized by multiple climatological and hydrological parameters and the assessment of it is important for planning and managing water resources. So understanding the history of drought in the area is essential like investigating the effects of drought. In this study, at first Climate parameters affecting the drought have downscaled by LARS-WG stochastic weather generator over Gilan province in Iran. After choosing a suitable model, outputs of it used for assessing the drought situation in the period of 2011-2030. Assessing the drought was done by TOPSIS method during 2 periods (present and future). After validation of the method, zoning the drought was performed by IDW method in GIS. Results shown that expanse of situations with lower drought index will increase. Also we will expect more droughts in these regions for the future.

In order to investigate the future changes of Karaj microclimate, data collection of Karaj weather station from 1995 to 2015 were applied as baseline period. Daily climate data including minimum and maximum temperatures, precipitation and solar radiation by means of GCM-HadCM3 model under emission scenarios were simulated using LARS-WG software. The negative impacts of climate change induced temperatures increase up to 2°C for the period (2046-2065) under A2 and A1B scenarios and precipitations increase of approximately 13% for the period 2011-2030 under A1B scenario. The annual AI varied from 0.01 to 0.05 across the study area. The mean annual AI for the study area during the period 1995 to 2015 was measured at the rate of 0.40. Based on the linear regression, the aridity index of the given condition measured at the rate of 0.002. Thus, with the climate change trend from arid and semi-arid to arid condition in Karaj region, adaptation strategy is mandatory to improve the economical productivity of water resources to account for stability of Karaj agroclimate ecosystem.

In order to study was to evaluate future climate Fereydunshahr of Isfahan for the next hundred years and its effect on potato production in Fereydunshahr. To forecast future climate conditions in Fereydunshahr were collected daily climate data including maximum and minimum temperature, rainfall and sunshine hours in this region during the period 1982 to 2012. In this study was used to simulate climatic data LARS-WG model and for the simulation of tuber yield of potato cultivars SUBSTOR-Potato model. For this purpose, we employed two types of General Circulation Models ((United Kingdom Met. Office Hadley Center: HadCM3) and (Institute Pierre Simon Laplace: IPCM4)) and three scenarios (A1B, A2 and B1) for three time period as 2015 to 2045, 2046 to 2075 and 2075 to 2105 AD. The SUBSTOR-Potato model was used for simulating the baseline and future yield and growth characteristics of potato. This is one of sixteen models embedded within the DSSAT program. The precision of LARS-WG model was evaluated by root mean-squared error (RMSE) test. In order to validate growth model, a split plot experiment based on complete random block design (CRBD) in three replications for two years (2012-2013 and 2014-2015) was conducted. The treatments included seeding date as main factor in three levels (5, 15 and 30 May) and three potato cultivars (Arinda, Santeh and Agria as early, medium and late maturity variety, respectively) as subplot including. Then, using of LARS-WG model was estimated the climatic data for a sample of Fereydunshahr in three periods 2015 to 2045, 2046 to 2075 and 2076 to 2105 AD, using two general circulation models (HadCM3 and IPCM4) under three scenarios standard A2, B1 and A1B. The results showed that the model LARS-WG had acceptable potential (RMSE <30) in the simulated climate data Fereydunshahr. Data validation results of LARS-WG showed that LARS-WG is more accurately simulate the maximum temperature in comparison whit minimum temperature and rainfall. Maximum and minimum temperature increased in all general circulation models and scenarios assessed in relation to the current situation. In general, the results showed that in the future will see less rainfall and higher temperatures than the current situation for Fereydunshahr and therefore will see reduce the yield of potato in Fereydunshahr. As we observed in HadCM3 and IPCM4 models and three scenarios (A1B, A2 and B1) reduction in potato yield respectively in 2090 compared with 2030. It seems that management of planting dates can be regarded as appropriate approach to reduce adverse effects of climate change on tuber yield of potato. Evaluation of adaption ways to future climate condition clarified that either early or late seeding date of tolerant cultivars such as Arinda might be considered as a solution to face changing climate since under these seeding dates flowering stage won't occur under high temperatures. It seems that management of planting dates can be regarded as appropriate approach to reduce adverse effects of climate change on tuber yield of potato.