تغییرات اقلیم

The macro water system flows in nature based on the physiographic condition of watershed and it is not limited to by a political border. In order to achieve water governance and rational use of natural resources, water resources must be managed at the watershed scale and under climate governance. But in most areas where urbanization has grown based on political borders, they mistakenly reduce the water system to the same range of political borders, which causes disruption in a chain of ecosystem relationships and complexity in water resources management. This issue has historical roots and originates from insufficient knowledge and technological limitations in the past era and when Political borders were formed. But in the current era, due to the advancement of technology and the use of Geographic Information Systems (GIS), as well as the increase in human knowledge about the inherent complexity of the water system, it has been possible to link the political boundaries with the boundaries of the watershed by producing and presenting new maps. Research literature shows that water resources and other environmental goods are better protected in countries where political borders and watershed borders are more compatible. Therefore, in the current study, by using the geographic information system, the border construction patterns in the country's watersheds have been analyzed. The results of this research show that matching political borders with watershed borders is a necessary step for the governance of Iran's water resources and sustainable development.

In the wake of the damage that man has Sntgrayyash the ground , place the study of climate change and global warming , due to the industrialization of the earth , the day will be added .The radiative effect of greenhouse gases on global warming is a major factor and the factor in global climate change with unprecedented speed . Every kind of climate change on the terrestrial earth is the beginning a chain of reactions whose direct effect on hydrological processes can be observed.
In this study, SDSM model is used to measure the large -scale data of the atmospheric general circulation model (HadCM3) in two local climate change scenarios, A2 and B2, for the meteorological parameters of temperature and precipitation in the basin of Qara Su. Then, considering the data of rainfall, temperature and flow rate and the fine- scale model outputs exponentially in the an artificial neural network is used to calculate the river’s discharge during the future period. Climate model results indicate an increase in temperature and a decrease in rainfall within the desired course relative to the base period. Consequently, this increase in temperature and decrease in rainfall will lessen the discharge rates of Qara Su River.

Soil organic carbon (SOC) storage estimation with high accuracy is very important due to having such prominent role corresponding to climate change and global warming reduction. Therefore، the current study was carried out in the beech mixed-stands forest of reserved compartment in Glandrood forests، in the northern parts of Iran. Stepwise regression method was used in order to present the SOC pool weight modeling considering the prominent soil physic-chemical properties at 3 different soil depths (0-10، 10-30، and 30-50 cm). The results of ANOVAs showed that exchangeable calcium content، lime and clay percentage (P < 0. 05) and also carbon content، soil organic matter، nitrogen and C/N ratio (P < 0. 01) were significantly different among the three soil depths. Moreover، on average، the total soil carbon stored considered as SOC pool weight in the ecosystem equaled 543. 87 ± 22. 07 t. C ha-1. According to the stepwise regression analysis C/N ratio was the effective content as explanatory variable to predict SOC pool (R2adj = 0. 44; SEE = 4. 8). In the following models، P، N and clay percentage، respectively، were the effective contents which improved significantly SOC pool prediction (R2adj = 0. 64-0. 83; SEE = 3. 8-2. 6). C/N ratio، P، N and clay were included 46. 3، 22. 41، 14. 71 and 9. 44 percent respectively with respect to the variations of SOC pool. Regression analysis indicated that introducing electrical conductivity، pH، and Mg as input variables in the following steps did not ameliorate the precision of SOC pool prediction clearly (R2adj = 0. 85-0. 89; SEE = 2. 5-2. 1). Furthermore، during the modeling and according to the collinearity diagnostic test، the result indicated that the maximum variance inflation factor of the models was less than 10 (VIF < 10)، validating them for application.

In this study the impact of climate change on temperature, rainfall and river flows of the Zayandeh Rud basin under two climate change scenarios for two periods (2010-2039 and 2070-2099) are investigated. For the evaluation of future climate change impact on stream flow to Chadegan reservoir, the global circulation model (GCM) outputs of the HadCM3 model (monthly temperature and precipitation) with two scenarios, A2 and B2, are obtained and downscaled to the local level for the selected time periods. The results indicate that the annual average of precipitation decreases and temperature increases for both periods that are more pronounced for the period 2079-2099. Such that 10% to 16% decrease in precipitation and 3.2 to 4.6ºC increases in temperature can be anticipated for scenarios A2 and B2, respectively. To predict future stream flow changes due to climate change, artificial neural networks (ANNs) have been applied and trained by the several input models and architectures for rainfall-runoff simulation. The results indicate that the maximum of 5.8% decrease in the annual flows. Comparison of the two scenarios indicates the more critical situation in scenario A2 for the basin.