Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water,persistent insufficient precipitation,lack of moisture,and high evapotranspira...Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water,persistent insufficient precipitation,lack of moisture,and high evapotranspiration.Drought caused by insufficient precipitation is a temporary and recurring meteorological event.Precipitation in semi-arid regions is different from that in other regions,ranging from 50 to 750 mm.In general,the semi-arid regions in the west and north of Iran received more precipitation than those in the east and south.The Terrestrial Climate(TerraClimate)data,including monthly precipitation,minimum temperature,maximum temperature,potential evapotranspiration,and the Palmer Drought Severity Index(PDSI)developed by the University of Idaho,were used in this study.The PDSI data was directly obtained from the Google Earth Engine platform.The Standardized Precipitation Index(SPI)and the Standardized Precipitation Evapotranspiration Index(SPEI)on two different scales were calculated in time series and also both SPI and SPEI were shown in spatial distribution maps.The result showed that normal conditions were a common occurrence in the semi-arid regions of Iran over the majority of years from 2000 to 2020,according to a spatiotemporal study of the SPI at 3-month and 12-month time scales as well as the SPEI at 3-month and 12-month time scales.Moreover,the PDSI detected extreme dry years during 2000-2003 and in 2007,2014,and 2018.In many semi-arid regions of Iran,the SPI at 3-month time scale is higher than the SPEI at 3-month time scale in 2000,2008,2014,2015,and 2018.In general,this study concluded that the semi-arid regions underwent normal weather conditions from 2000 to 2020.In a way,moderate,severe,and extreme dry occurred with a lesser percentage,gradually decreasing.According to the PDSI,during 2000-2003 and 2007-2014,extreme dry struck practically all hot semi-arid regions of Iran.Several parts of the cold semi-arid regions,on the other hand,only experienced moderate to severe dry from 2000 to 2003,except for the eastern areas and wetter regions.The significance of this study is the determination of the spatiotemporal distribution of meteorological drought in semi-arid regions of Iran using strongly validated data from TerraClimate.展开更多
Changes in land use/land cover(LULC)are a substantial environmental subject with considerable consequences for human well-being,climate,and ecosystems.Innovative investigations for predicting LULC changes are essentia...Changes in land use/land cover(LULC)are a substantial environmental subject with considerable consequences for human well-being,climate,and ecosystems.Innovative investigations for predicting LULC changes are essential for effective land management and sustainable development.This study used Landsat images and supplementary spatial factors to evaluate spatiotemporal LULC changes in Erbil Province,Kurdistan Region-Iraq.It predicts future changes in 2040 using four climates scenario-based Shared Socioeconomic Pathways(SSPs).The Random Forest(RF)model was used to classify and forecast LULC changes,which are crucial for effective land management and sustainable development.The RF model was assessed using performance metrics,such as the overall accuracy,F1-score,and kappa coefficient.The simulated LULC outcomes demonstrated the efficiency of the selected model,achieving an overall accuracy of 94.34%,a perfect agreement in the kappa statistic of 0.92,and a high F1-score between 0.71 and 0.93.The study revealed that agricultural land declines under SSP126 but increases under other scenarios,with SSP585 showing the highest gain(+209.98 sq.km,23.32%).Barren land increased across all scenarios,whereas built-up areas consistently increased.Forest gains in SSP126 but declined in all other scenarios,with the most significant loss in SSP585(−101.20 sq.km,−5.31%).The riparian zone gains in SSP126 but declines in all the other scenarios.Snow remained stable,but minor losses were observed in SSP245,SSP370,and SSP585.Water showed a slight increase in SSP126 but declined in all other scenarios.SSP126 showed minor changes,whereas SSP scenarios 370 and 585 show severe land transformations,forest loss,rangeland degradation,and urban expansion,indicating increased deforestation and degradation.This study highlights the importance of integrating a scenario-based RFmodel with hyperparameter tuning in remote sensing applications to improve LULCdynamics predictions,benefiting land-use planning,environmental management,and rational decision-making.展开更多
文摘Drought occurs in almost all climate zones and is characterized by prolonged water deficiency due to unbalanced demand and supply of water,persistent insufficient precipitation,lack of moisture,and high evapotranspiration.Drought caused by insufficient precipitation is a temporary and recurring meteorological event.Precipitation in semi-arid regions is different from that in other regions,ranging from 50 to 750 mm.In general,the semi-arid regions in the west and north of Iran received more precipitation than those in the east and south.The Terrestrial Climate(TerraClimate)data,including monthly precipitation,minimum temperature,maximum temperature,potential evapotranspiration,and the Palmer Drought Severity Index(PDSI)developed by the University of Idaho,were used in this study.The PDSI data was directly obtained from the Google Earth Engine platform.The Standardized Precipitation Index(SPI)and the Standardized Precipitation Evapotranspiration Index(SPEI)on two different scales were calculated in time series and also both SPI and SPEI were shown in spatial distribution maps.The result showed that normal conditions were a common occurrence in the semi-arid regions of Iran over the majority of years from 2000 to 2020,according to a spatiotemporal study of the SPI at 3-month and 12-month time scales as well as the SPEI at 3-month and 12-month time scales.Moreover,the PDSI detected extreme dry years during 2000-2003 and in 2007,2014,and 2018.In many semi-arid regions of Iran,the SPI at 3-month time scale is higher than the SPEI at 3-month time scale in 2000,2008,2014,2015,and 2018.In general,this study concluded that the semi-arid regions underwent normal weather conditions from 2000 to 2020.In a way,moderate,severe,and extreme dry occurred with a lesser percentage,gradually decreasing.According to the PDSI,during 2000-2003 and 2007-2014,extreme dry struck practically all hot semi-arid regions of Iran.Several parts of the cold semi-arid regions,on the other hand,only experienced moderate to severe dry from 2000 to 2003,except for the eastern areas and wetter regions.The significance of this study is the determination of the spatiotemporal distribution of meteorological drought in semi-arid regions of Iran using strongly validated data from TerraClimate.
文摘Changes in land use/land cover(LULC)are a substantial environmental subject with considerable consequences for human well-being,climate,and ecosystems.Innovative investigations for predicting LULC changes are essential for effective land management and sustainable development.This study used Landsat images and supplementary spatial factors to evaluate spatiotemporal LULC changes in Erbil Province,Kurdistan Region-Iraq.It predicts future changes in 2040 using four climates scenario-based Shared Socioeconomic Pathways(SSPs).The Random Forest(RF)model was used to classify and forecast LULC changes,which are crucial for effective land management and sustainable development.The RF model was assessed using performance metrics,such as the overall accuracy,F1-score,and kappa coefficient.The simulated LULC outcomes demonstrated the efficiency of the selected model,achieving an overall accuracy of 94.34%,a perfect agreement in the kappa statistic of 0.92,and a high F1-score between 0.71 and 0.93.The study revealed that agricultural land declines under SSP126 but increases under other scenarios,with SSP585 showing the highest gain(+209.98 sq.km,23.32%).Barren land increased across all scenarios,whereas built-up areas consistently increased.Forest gains in SSP126 but declined in all other scenarios,with the most significant loss in SSP585(−101.20 sq.km,−5.31%).The riparian zone gains in SSP126 but declines in all the other scenarios.Snow remained stable,but minor losses were observed in SSP245,SSP370,and SSP585.Water showed a slight increase in SSP126 but declined in all other scenarios.SSP126 showed minor changes,whereas SSP scenarios 370 and 585 show severe land transformations,forest loss,rangeland degradation,and urban expansion,indicating increased deforestation and degradation.This study highlights the importance of integrating a scenario-based RFmodel with hyperparameter tuning in remote sensing applications to improve LULCdynamics predictions,benefiting land-use planning,environmental management,and rational decision-making.
