Due to growing demand and reduction of water resources and increasing pollution of water,driven by dramatic population and economic growth, arid and semi-arid land's imminent water problems are nowadays aggravatin...Due to growing demand and reduction of water resources and increasing pollution of water,driven by dramatic population and economic growth, arid and semi-arid land's imminent water problems are nowadays aggravating. This study aims to determine the most appropriate management strategies for balancing the Abhar plain aquifer using the SWOT coupled with AHP technique. The results indicate that weaknesses prevail over strengths as well as threats over opportunities. The placement in the quarter of weaknesses-threats with a defensive strategy indicates the critical condition of the Abhar plain aquifer. The most appropriate solutions to achieve the goal of balancing the groundwater were prioritized by AHP method. According to results, improper management of water consumption with a weight of 72.5% is the most destructive factor in reducing groundwater resources. Among the types of consumption, the effect of an agricultural factor carries a weight of 74.2%. The exploitation of illegal wells, overdraft of exploitation license provisions of wells, reduction of precipitation and traditional irrigation methods were selected as the destructive factors causing the deteriration of groundwater resources. Also, with filling the illegal wells,changing the type of cultivation and greenhouse crops cultivation, installing a smart water meter,observance the provisions of the water exploitation license, implementing integrated pressurized irrigation systems, benefiting from suitable climatic conditions and geographical location for cultivating and developing the low-water use species and industries and on the other hand, with implementing artificial recharge to control the surface water resources and reduce abstraction from groundwater aquifers, the adverse trend of Abhar Plain groundwater resources can be controlled.展开更多
Although the construction of underground dams is one of the best methods to conserve water resources in arid and semi-arid regions,applying efficient methods for the selection of suitable sites for subsurface dam cons...Although the construction of underground dams is one of the best methods to conserve water resources in arid and semi-arid regions,applying efficient methods for the selection of suitable sites for subsurface dam construction remains a challenge.Due to the costly and time-consuming methods of site selection for underground dam construction,this study aimed to present a new method using geographic information systems techniques and decision-making processes.The exclusionary criteria including fault,slope,hypsometry,land use,soil,stream,geology,and chemical properties of groundwater were selected for site selection of dam construction and inappropriate regions were omitted by integration and scoring layers in ArcGIS based on the Boolean logic.Finally,appropriate sites were prioritized using the Multi-Attribute Utility Theory.According to the results of the utility coefficient,seven sites were selected as the region for underground dam construction based on all criteria and experts’opinions.The site of Nazarabad dam was the best location for underground dam construction with a utility coefficient of 0.7137 followed by sites of Akhavan with a utility coefficient of 0.4633 and Mirshamsi with a utility coefficient of 0.4083.This study proposed a new approach for the construction of the subsurface dam at the proper site and help managers and decision-makers achieve sustainable water resources with limited facilities and capital and avoid wasting national capital.展开更多
Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to ident...Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to identify homogeneous hydrological watersheds using remote sensing data in western Iran. To achieve this goal, remote sensing indices including SAVI, LAI, NDMI, NDVI and snow cover, were extracted from MODIS data over the period 2000 to 2015. Then, a fuzzy method was used to clustering the watersheds based on the extracted indices. A fuzzy c-mean(FCM) algorithm enabled to classify 38 watersheds in three homogeneous groups.The optimal number of clusters was determined through evaluation of partition coefficient, partition entropy function and trial and error. The results indicated three homogeneous regions identified by the fuzzy c-mean clustering and remote sensing product which are consistent with the variations of topography and climate of the study area. Inherently,the grouped watersheds have similar hydrological properties and are likely to need similar management considerations and measures.展开更多
Aims The accurate estimation of aboveground biomass in vegetation is critical for global carbon accounting.Regression models provide an easy estimation of aboveground biomass at large spatial and temporal scales.Yet,o...Aims The accurate estimation of aboveground biomass in vegetation is critical for global carbon accounting.Regression models provide an easy estimation of aboveground biomass at large spatial and temporal scales.Yet,only few prediction models are available for aboveground biomass in rangelands,as compared with forests.In addition to the development of prediction models,we tested whether such prediction models vary with plant growth forms and life spans,and with the inclusion of site and/or quadrat-specific factors.Methods We collected dataset of aboveground biomass from destructive harvesting of 8088 individual plants belonging to 79 species in 735 quadrats across 35 sites in semi-steppe rangelands in Iran.A logarithmic transformation of the power-law model was used to develop simple prediction models for the easy estimation of above-ground biomass using plant coverage and vegetation density as predictors for the species-specific model,multispecies and plants of different growth forms and life spans.In addition,additive and multiplicative linear regression models were developed by using plant coverage and one categorical variable from the site and/or quadrat-specific factors.Important Findings The log-transformed power-law model based on plant coverage pre-cisely predicted aboveground biomass across the whole dataset for ei-ther most of the species-specific model,multispecies or plants of the same growth forms(shrubs,forbs or graminoids)and life spans(annuals,biennials or perennials).The addition of vegetation density as a single or in a compound predictor variable had relatively poor performance com-pared with the model having plant coverage only.Although generalizing at the levels of plant group forms and/or life spans did not substantially enhance the model-fit and validation of the plant coverage-based mul-tispecies model,the inclusion of plant growth forms or life spans as a categorical predictor variable had performed well.Generalized models in this study will greatly contribute to the accurate and easy predic-tion of aboveground biomass in the studied rangelands and will be also useful to rangeland practitioners and ecological modellers interested in the global relationship between biodiversity and aboveground biomass productivity across space and time in natural rangelands.展开更多
文摘Due to growing demand and reduction of water resources and increasing pollution of water,driven by dramatic population and economic growth, arid and semi-arid land's imminent water problems are nowadays aggravating. This study aims to determine the most appropriate management strategies for balancing the Abhar plain aquifer using the SWOT coupled with AHP technique. The results indicate that weaknesses prevail over strengths as well as threats over opportunities. The placement in the quarter of weaknesses-threats with a defensive strategy indicates the critical condition of the Abhar plain aquifer. The most appropriate solutions to achieve the goal of balancing the groundwater were prioritized by AHP method. According to results, improper management of water consumption with a weight of 72.5% is the most destructive factor in reducing groundwater resources. Among the types of consumption, the effect of an agricultural factor carries a weight of 74.2%. The exploitation of illegal wells, overdraft of exploitation license provisions of wells, reduction of precipitation and traditional irrigation methods were selected as the destructive factors causing the deteriration of groundwater resources. Also, with filling the illegal wells,changing the type of cultivation and greenhouse crops cultivation, installing a smart water meter,observance the provisions of the water exploitation license, implementing integrated pressurized irrigation systems, benefiting from suitable climatic conditions and geographical location for cultivating and developing the low-water use species and industries and on the other hand, with implementing artificial recharge to control the surface water resources and reduce abstraction from groundwater aquifers, the adverse trend of Abhar Plain groundwater resources can be controlled.
文摘Although the construction of underground dams is one of the best methods to conserve water resources in arid and semi-arid regions,applying efficient methods for the selection of suitable sites for subsurface dam construction remains a challenge.Due to the costly and time-consuming methods of site selection for underground dam construction,this study aimed to present a new method using geographic information systems techniques and decision-making processes.The exclusionary criteria including fault,slope,hypsometry,land use,soil,stream,geology,and chemical properties of groundwater were selected for site selection of dam construction and inappropriate regions were omitted by integration and scoring layers in ArcGIS based on the Boolean logic.Finally,appropriate sites were prioritized using the Multi-Attribute Utility Theory.According to the results of the utility coefficient,seven sites were selected as the region for underground dam construction based on all criteria and experts’opinions.The site of Nazarabad dam was the best location for underground dam construction with a utility coefficient of 0.7137 followed by sites of Akhavan with a utility coefficient of 0.4633 and Mirshamsi with a utility coefficient of 0.4083.This study proposed a new approach for the construction of the subsurface dam at the proper site and help managers and decision-makers achieve sustainable water resources with limited facilities and capital and avoid wasting national capital.
文摘Determining the relatively similar hydrological properties of the watersheds is very crucial in order to readily classify them for management practices such as flood and soil erosion control. This study aimed to identify homogeneous hydrological watersheds using remote sensing data in western Iran. To achieve this goal, remote sensing indices including SAVI, LAI, NDMI, NDVI and snow cover, were extracted from MODIS data over the period 2000 to 2015. Then, a fuzzy method was used to clustering the watersheds based on the extracted indices. A fuzzy c-mean(FCM) algorithm enabled to classify 38 watersheds in three homogeneous groups.The optimal number of clusters was determined through evaluation of partition coefficient, partition entropy function and trial and error. The results indicated three homogeneous regions identified by the fuzzy c-mean clustering and remote sensing product which are consistent with the variations of topography and climate of the study area. Inherently,the grouped watersheds have similar hydrological properties and are likely to need similar management considerations and measures.
基金This work was supported by the University of Tehran,Iran(grant No.3870306)We would like to thank Mr.Mohsen Hosseini,Drs.Esmaeil Alizadeh and Azad Rastegar for their contributions to this work.A.A.is financially supported by Guangdong Provincial Government(grant No.205588)for conducting ecological research at South China Normal University.
文摘Aims The accurate estimation of aboveground biomass in vegetation is critical for global carbon accounting.Regression models provide an easy estimation of aboveground biomass at large spatial and temporal scales.Yet,only few prediction models are available for aboveground biomass in rangelands,as compared with forests.In addition to the development of prediction models,we tested whether such prediction models vary with plant growth forms and life spans,and with the inclusion of site and/or quadrat-specific factors.Methods We collected dataset of aboveground biomass from destructive harvesting of 8088 individual plants belonging to 79 species in 735 quadrats across 35 sites in semi-steppe rangelands in Iran.A logarithmic transformation of the power-law model was used to develop simple prediction models for the easy estimation of above-ground biomass using plant coverage and vegetation density as predictors for the species-specific model,multispecies and plants of different growth forms and life spans.In addition,additive and multiplicative linear regression models were developed by using plant coverage and one categorical variable from the site and/or quadrat-specific factors.Important Findings The log-transformed power-law model based on plant coverage pre-cisely predicted aboveground biomass across the whole dataset for ei-ther most of the species-specific model,multispecies or plants of the same growth forms(shrubs,forbs or graminoids)and life spans(annuals,biennials or perennials).The addition of vegetation density as a single or in a compound predictor variable had relatively poor performance com-pared with the model having plant coverage only.Although generalizing at the levels of plant group forms and/or life spans did not substantially enhance the model-fit and validation of the plant coverage-based mul-tispecies model,the inclusion of plant growth forms or life spans as a categorical predictor variable had performed well.Generalized models in this study will greatly contribute to the accurate and easy predic-tion of aboveground biomass in the studied rangelands and will be also useful to rangeland practitioners and ecological modellers interested in the global relationship between biodiversity and aboveground biomass productivity across space and time in natural rangelands.
