The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models.For this,a landslide inventory map was created with 406 historical ...The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models.For this,a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points,which was randomly divided into two datasets for model training(70%)and model testing(30%).22 factors were initially selected to establish a landslide factor database.We applied the GeoDetector and recursive feature elimination method(RFE)to address factor optimization to reduce information redundancy and collinearity in the data.Thereafter,the frequency ratio method,multicollinearity test,and interactive detector were used to analyze and evaluate the optimized factors.Subsequently,the random forest(RF)model was used to create a landslide susceptibility map with original and optimized factors.The resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve(AUC)and accuracy.The accuracy of the two hybrid models(0.868 for GeoDetector-RF and 0.869 for RFE-RF)were higher than that of the RF model(0.860),indicating that the hybrid models with factor optimization have high reliability and predictability.Both RFE-RF GeoDetector-RF had higher AUC values,respectively 0.863 and 0.860,than RF(0.853).These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.展开更多
Changes in natural geographic features and landscape patterns directly influence the hydrology and non-point source pollution processes in the watershed;however,to slow down non-point source pollution,it is necessary ...Changes in natural geographic features and landscape patterns directly influence the hydrology and non-point source pollution processes in the watershed;however,to slow down non-point source pollution,it is necessary to distinguish their effects.But the non-point source pollution process is interactional as a result of multiple factors,and the collinearity between multiple independent variables limits our ability of reason diagnosis.Thus,taking the Burhatong River Basin,Northeast China as an example,the methods of hydrological simulation,geographic detectors,and redundancy analysis have been combined to determine the impact of natural geographic features and landscape patterns on non-point source pollution in the watershed.The Soil&Water Assessment Tool(SWAT)has been adopted to simulate the spatial and temporal distribution characteristics of total nitrogen and total phosphorus in the watershed.The results show that the proportions of agricultural land and forest area and the location-weighted landscape contrast index(LWLI)are the main indicators influencing the rivers total nitrogen and total phosphorus.The interaction of these indicators with natural geographic features and landscape configuration indicators also significantly influences the changes in total nitrogen(TN)and total phosphorus(TP).Natural geographical features and landscape patterns have different comprehensive effects on non-point source pollution in the dry and wet seasons.TN and TP loads are affected mainly by the change in landscape pattern,especially in the wet season.Although the ecological restoration program has improved forest coverage,the purification effect of increased forest coverage on the water quality in the watershed may be offset by the negative impact of increased forest fragmentation.The high concentration and complexity of farmland patches increase the risk of non-point source pollution spread to a certain extent.展开更多
Reference crop evapotranspiration(ET0)is an important parameter in the research of farmland irrigation management,crop water demand estimation and water balance in scarce data areas,therefore,it is very important to s...Reference crop evapotranspiration(ET0)is an important parameter in the research of farmland irrigation management,crop water demand estimation and water balance in scarce data areas,therefore,it is very important to study the factors affecting the spatial variation of ET0.In this paper,the Penman-Monteith formula was used to calculate ET0 which is the dependent variable of elevation(Elev),daily maximum temperature(T_(max)),daily minimum temperature(Tmin),daily average temperature(T_(mean)),wind speed(U_(2)),sunshine duration(SD)and relative humidity(RH).The sensitivity analysis of ET0 was performed using a Geodetector method based on spatial stratified heterogeneity.The applicability of Geodetector in sensitivity analysis of ET0 was verified by comparing it with existing research results.Results show that RH,Tmax,SD,and Tmean are the main factors affecting ET0 in Northwest China,and RH has the best explanatory power for the spatial distribu‐tion of ET0.Geodetector has a unique advantage in sensitivity analysis,because it can analyze the synergistic effect of two factors on the change of ET0.The interactive detector of Geodetector revealed that the synergistic effect of RH and Tmean on ET0 is very significant,and can explain 89%of the spatial variation of ET0.This research provides a new method for sensitivity analysis of ET0 changes.展开更多
The North China Plain is vital hub for agricultural production and urban development.However,decades of excessive groundwater extraction have resulted on significant land subsidence,posing severe threats to the region...The North China Plain is vital hub for agricultural production and urban development.However,decades of excessive groundwater extraction have resulted on significant land subsidence,posing severe threats to the region's socio-economic stability and sustainable development.The relationship between land deformation and groundwater storage Anomalies in this region remains insufficiently understood,and the driving factors behind land subsidence require further exploration.This study employs downscaled GRACE and SBAS InSAR technologies to monitor and analyze land subsidence and groundwater storage Anoma-lies in four representative cities of the North China Plain:Beijing,Tianjin,Cangzhou,and Hengshui.Using geodetector methods,the study investigates the driving factors of land subsidence,incorporating both natu-ral environmental and human activity factors.The results indicate that:(1)Groundwater storage in the North China Plain generally exhibited an overall declining trend from 2002 to 2022,with the rate of decrease weakening from southwest to northeast,showing a clear spatial clustering pattern.(2)While,land subsidence rates in the main urban areas of each city were relatively low,severe subsidence persisted in the surrounding suburban and rural areas.(3)The temporal trends of land subsidence were consistent with changes in groundwater storage across all cities.(4)Groundwater storage Anomalies emerged as the most significant factor influencing the spatial distribution of land subsidence,with a q-value of 0.387,followed by factors such as DEM,evapotranspiration,and rainfall.Seasonal characteristics were evident in land deformation corresponding to groundwater storage Anomalies:During the spring and summer irrigation periods,land subsidence occurred due to groundwater depletion,while in autumn and winter,the surface uplifted with increased groundwater storage.In Cangzhou and Hengshui,excessive deep groundwater extraction caused a lagged response in land subsidence relative to groundwater storage Anomalies.Further-more,interaction among various factors significantly amplified their influence on land subsidence.The interaction between groundwater storage Anomalies and rainfall had the strongest combined effect,under-scoring its critical role in shaping land subsidence in the study area.The findings offer valuable insights for the scientific prevention and management of land subsidence in the North China Plain.展开更多
Due to irrational human activities and extreme climate,the Qinghai-Xizang Plateau,China,faces a serious threat of desertification.Desertification has a detrimental effect on the ecological environment and socioeconomi...Due to irrational human activities and extreme climate,the Qinghai-Xizang Plateau,China,faces a serious threat of desertification.Desertification has a detrimental effect on the ecological environment and socioeconomic development.In this study,the desertification sensitivity index(DSI)model was established by integrating the spatial distance model and environmentally sensitive area index evaluation method,and then the model was used to quantitatively analyze the spatial and temporal characteristics of desertification sensitivity of the Qinghai-Xizang Plateau from 1990 to 2020.The results revealed that:(1)a general increasing tendency from southeast to northwest was identified in the spatial distribution of desertification sensitivity.The low-sensitivity areas were mostly concentrated in the Hengduan and Nyaingqêntanglha mountains and surrounding forest and meadow areas.The high-sensitivity areas were located mainly in the Kunlun and Altun mountains and surrounding decertified areas.The center of gravity of all types of desertification-sensitive areas moved to the northwest,and the desertification sensitivity showed a decreasing trend as a whole;(2)the area of highly sensitive desertification areas decreased by 8.37%,with extreme sensitivity being the largest change among the sensitivity types.The desertification sensitivity transfer was characterized by a greater shift to lower sensitivity levels(24.56%)than to higher levels(2.03%),which demonstrated a declining trend;(3)since 1990,the change in desertification sensitivity has been dominated by the stabilizing type Ⅰ(29.30%),with the area of continuously increasing desertification sensitivity accounting for only 1.10%,indicating that the management of desertification has achieved positive results in recent years;and(4)natural factors have had a more significant impact on desertification sensitivity on the Xizang Plateau,whereas socioeconomic factors affected only localized areas.The main factors influencing desertification sensitivity were vegetation drought tolerance and aridity index.Studying spatiotemporal variations in desertification sensitivity and its influencing factors can provide a scientific foundation for developing strategies to control desertification on the Qinghai-Xizang Plateau.Dividing different desertification-sensitive areas on the basis of these patterns of change can facilitate the formulation of more targeted management and protection measures,contributing to ecological construction and sustainable economic development in the area.展开更多
Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid an...Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas.This study took the Helan Mountain,a typical arid and semi-arid area in China,as the study area.By adopting an Enhanced Remote Sensing Ecological Index(ERSEI)that integrates the habitat quality(HQ)index with the Remote Sensing Ecological Index(RSEI),we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes.Principal Component Analysis(PCA)was used to validate the composite ERSEI,enabling the extraction of key features and the reduction of redundant information.The results showed that the contributions of first principal component(PC1)for ERSEI and RSEI were 80.23%and 78.72%,respectively,indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality.Temporally,the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022,with the average value of ERSEI ranging between 0.298 and 0.346.Spatially,the ERSEI showed a trend of being higher in the southwest and lower in the northeast,with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes.The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022.Temperature and digital elevation model(DEM)emerged as the primary drivers of ERSEI changes.This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies,ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures.The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.展开更多
文摘The present study aims to develop two hybrid models to optimize the factors and enhance the predictive ability of the landslide susceptibility models.For this,a landslide inventory map was created with 406 historical landslides and 2030 non-landslide points,which was randomly divided into two datasets for model training(70%)and model testing(30%).22 factors were initially selected to establish a landslide factor database.We applied the GeoDetector and recursive feature elimination method(RFE)to address factor optimization to reduce information redundancy and collinearity in the data.Thereafter,the frequency ratio method,multicollinearity test,and interactive detector were used to analyze and evaluate the optimized factors.Subsequently,the random forest(RF)model was used to create a landslide susceptibility map with original and optimized factors.The resultant hybrid models GeoDetector-RF and RFE-RF were evaluated and compared by the area under the receiver operating characteristic curve(AUC)and accuracy.The accuracy of the two hybrid models(0.868 for GeoDetector-RF and 0.869 for RFE-RF)were higher than that of the RF model(0.860),indicating that the hybrid models with factor optimization have high reliability and predictability.Both RFE-RF GeoDetector-RF had higher AUC values,respectively 0.863 and 0.860,than RF(0.853).These results confirm the ability of factor optimization methods to improve the performance of landslide susceptibility models.
基金Under the auspices of the National Key R&D Program(No.2019YFC0409104)the National Natural Science Foundation of China(No.41830643)the National Science and Technology Basic Resources Survey Project(No.2019FY101703)。
文摘Changes in natural geographic features and landscape patterns directly influence the hydrology and non-point source pollution processes in the watershed;however,to slow down non-point source pollution,it is necessary to distinguish their effects.But the non-point source pollution process is interactional as a result of multiple factors,and the collinearity between multiple independent variables limits our ability of reason diagnosis.Thus,taking the Burhatong River Basin,Northeast China as an example,the methods of hydrological simulation,geographic detectors,and redundancy analysis have been combined to determine the impact of natural geographic features and landscape patterns on non-point source pollution in the watershed.The Soil&Water Assessment Tool(SWAT)has been adopted to simulate the spatial and temporal distribution characteristics of total nitrogen and total phosphorus in the watershed.The results show that the proportions of agricultural land and forest area and the location-weighted landscape contrast index(LWLI)are the main indicators influencing the rivers total nitrogen and total phosphorus.The interaction of these indicators with natural geographic features and landscape configuration indicators also significantly influences the changes in total nitrogen(TN)and total phosphorus(TP).Natural geographical features and landscape patterns have different comprehensive effects on non-point source pollution in the dry and wet seasons.TN and TP loads are affected mainly by the change in landscape pattern,especially in the wet season.Although the ecological restoration program has improved forest coverage,the purification effect of increased forest coverage on the water quality in the watershed may be offset by the negative impact of increased forest fragmentation.The high concentration and complexity of farmland patches increase the risk of non-point source pollution spread to a certain extent.
基金the Inner Mongolia Key Research and Development program(zdzx2018057)the National Key Research and Development Program(2016YFC0400908).
文摘Reference crop evapotranspiration(ET0)is an important parameter in the research of farmland irrigation management,crop water demand estimation and water balance in scarce data areas,therefore,it is very important to study the factors affecting the spatial variation of ET0.In this paper,the Penman-Monteith formula was used to calculate ET0 which is the dependent variable of elevation(Elev),daily maximum temperature(T_(max)),daily minimum temperature(Tmin),daily average temperature(T_(mean)),wind speed(U_(2)),sunshine duration(SD)and relative humidity(RH).The sensitivity analysis of ET0 was performed using a Geodetector method based on spatial stratified heterogeneity.The applicability of Geodetector in sensitivity analysis of ET0 was verified by comparing it with existing research results.Results show that RH,Tmax,SD,and Tmean are the main factors affecting ET0 in Northwest China,and RH has the best explanatory power for the spatial distribu‐tion of ET0.Geodetector has a unique advantage in sensitivity analysis,because it can analyze the synergistic effect of two factors on the change of ET0.The interactive detector of Geodetector revealed that the synergistic effect of RH and Tmean on ET0 is very significant,and can explain 89%of the spatial variation of ET0.This research provides a new method for sensitivity analysis of ET0 changes.
基金supported by the Fundamental Research Funds for Central Public Welfare Research Institutes,CAGS(Project No.KY202302)China Geological Survey Project(DD20230719)China Geological Survey Project(DD20230427)。
文摘The North China Plain is vital hub for agricultural production and urban development.However,decades of excessive groundwater extraction have resulted on significant land subsidence,posing severe threats to the region's socio-economic stability and sustainable development.The relationship between land deformation and groundwater storage Anomalies in this region remains insufficiently understood,and the driving factors behind land subsidence require further exploration.This study employs downscaled GRACE and SBAS InSAR technologies to monitor and analyze land subsidence and groundwater storage Anoma-lies in four representative cities of the North China Plain:Beijing,Tianjin,Cangzhou,and Hengshui.Using geodetector methods,the study investigates the driving factors of land subsidence,incorporating both natu-ral environmental and human activity factors.The results indicate that:(1)Groundwater storage in the North China Plain generally exhibited an overall declining trend from 2002 to 2022,with the rate of decrease weakening from southwest to northeast,showing a clear spatial clustering pattern.(2)While,land subsidence rates in the main urban areas of each city were relatively low,severe subsidence persisted in the surrounding suburban and rural areas.(3)The temporal trends of land subsidence were consistent with changes in groundwater storage across all cities.(4)Groundwater storage Anomalies emerged as the most significant factor influencing the spatial distribution of land subsidence,with a q-value of 0.387,followed by factors such as DEM,evapotranspiration,and rainfall.Seasonal characteristics were evident in land deformation corresponding to groundwater storage Anomalies:During the spring and summer irrigation periods,land subsidence occurred due to groundwater depletion,while in autumn and winter,the surface uplifted with increased groundwater storage.In Cangzhou and Hengshui,excessive deep groundwater extraction caused a lagged response in land subsidence relative to groundwater storage Anomalies.Further-more,interaction among various factors significantly amplified their influence on land subsidence.The interaction between groundwater storage Anomalies and rainfall had the strongest combined effect,under-scoring its critical role in shaping land subsidence in the study area.The findings offer valuable insights for the scientific prevention and management of land subsidence in the North China Plain.
基金funded by the National Natural Science Foundation of China(42371219)the Key Natural Science Foundation of Gansu Province(24JRRA135)the Oasis Scientific Research Achievements Breakthrough Action Plan Project of Northwest Normal University(NWNU-LZKX-202302).
文摘Due to irrational human activities and extreme climate,the Qinghai-Xizang Plateau,China,faces a serious threat of desertification.Desertification has a detrimental effect on the ecological environment and socioeconomic development.In this study,the desertification sensitivity index(DSI)model was established by integrating the spatial distance model and environmentally sensitive area index evaluation method,and then the model was used to quantitatively analyze the spatial and temporal characteristics of desertification sensitivity of the Qinghai-Xizang Plateau from 1990 to 2020.The results revealed that:(1)a general increasing tendency from southeast to northwest was identified in the spatial distribution of desertification sensitivity.The low-sensitivity areas were mostly concentrated in the Hengduan and Nyaingqêntanglha mountains and surrounding forest and meadow areas.The high-sensitivity areas were located mainly in the Kunlun and Altun mountains and surrounding decertified areas.The center of gravity of all types of desertification-sensitive areas moved to the northwest,and the desertification sensitivity showed a decreasing trend as a whole;(2)the area of highly sensitive desertification areas decreased by 8.37%,with extreme sensitivity being the largest change among the sensitivity types.The desertification sensitivity transfer was characterized by a greater shift to lower sensitivity levels(24.56%)than to higher levels(2.03%),which demonstrated a declining trend;(3)since 1990,the change in desertification sensitivity has been dominated by the stabilizing type Ⅰ(29.30%),with the area of continuously increasing desertification sensitivity accounting for only 1.10%,indicating that the management of desertification has achieved positive results in recent years;and(4)natural factors have had a more significant impact on desertification sensitivity on the Xizang Plateau,whereas socioeconomic factors affected only localized areas.The main factors influencing desertification sensitivity were vegetation drought tolerance and aridity index.Studying spatiotemporal variations in desertification sensitivity and its influencing factors can provide a scientific foundation for developing strategies to control desertification on the Qinghai-Xizang Plateau.Dividing different desertification-sensitive areas on the basis of these patterns of change can facilitate the formulation of more targeted management and protection measures,contributing to ecological construction and sustainable economic development in the area.
基金funded by the Fujian Province's Foreign Cooperation Project in 2023(2023I0047)the Fujian Provincial Natural Science Foundation Project(2023J011432,2024J011195)+3 种基金the Ministry of Education's Supply-demand Docking Employment and Education Project(2024011223947)the Open Project Fund of Hunan Provincial Key Laboratory for Remote Sensing Monitoring of Ecological Environment in Dongting Lake Area(DTH Key Lab.2024-04,2022-04)the Fujian Provincial Natural Science Foundation Guiding Project(2024Y0057)the Fujian Province Social Science Plan Project(FJ2024BF071).
文摘Understanding the ecological evolution is of great significance in addressing the impacts of climate change and human activities.However,the ecological evolution and its drivers remain inadequately explored in arid and semi-arid areas.This study took the Helan Mountain,a typical arid and semi-arid area in China,as the study area.By adopting an Enhanced Remote Sensing Ecological Index(ERSEI)that integrates the habitat quality(HQ)index with the Remote Sensing Ecological Index(RSEI),we quantified the ecological environment quality of the Helan Mountain during 2010-2022 and analyzed the driving factors behind the changes.Principal Component Analysis(PCA)was used to validate the composite ERSEI,enabling the extraction of key features and the reduction of redundant information.The results showed that the contributions of first principal component(PC1)for ERSEI and RSEI were 80.23%and 78.72%,respectively,indicating that the ERSEI can provide higher precision and more details than the RSEI in assessing ecological environment quality.Temporally,the ERSEI in the Helan Mountain exhibited an initial decline followed by an increase from 2010 to 2022,with the average value of ERSEI ranging between 0.298 and 0.346.Spatially,the ERSEI showed a trend of being higher in the southwest and lower in the northeast,with high-quality ecological environments mainly concentrated in the western foothills at higher altitudes.The centroid of ERSEI shifted northeastward toward Helan County from 2010 to 2022.Temperature and digital elevation model(DEM)emerged as the primary drivers of ERSEI changes.This study highlights the necessity of using comprehensive monitoring tools to guide policy-making and conservation strategies,ensuring the resilience of fragile ecosystems in the face of ongoing climatic and anthropogenic pressures.The findings offer valuable insights for the sustainable management and conservation in arid and semi-arid ecosystems.
