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
The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this ...The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this study, the simulation of soil erosion and its quantitative attribution analysis have been conducted in different geomorphological types in a typical karst basin based on the RUSLE model and the geodetector method. The influencing factors, such as land use type, slope, rainfall, elevation, lithology and vegetation cover, have been taken into consideration. Results show that the strength of association between the six influencing factors and soil erosion was notably different in diverse geomorphological types. Land use type and slope were the dominant factors of soil erosion in the Sancha River Basin, especially for land use type whose power of determinant(q value) for soil erosion was much higher than other factors. The q value of slope declined with the increase of relief in mountainous areas, namely it was ranked as follows: middle elevation hill> small relief mountain> middle relief mountain. Multi-factors interactions were proven to significantly strengthen soil erosion, particularly for the combination of land use type with slope, which can explain 70% of soil erosion distribution. It can be found that soil erosion in the same land use type with different slopes(such as dry land with slopes of 5° and above 25°) or in the diverse land use types with the same slope(such as dry land and forest with a slope of 5°), varied much. These indicate that prohibiting steep slope cultivation and Grain for Green Project are reasonable measures to control soil erosion in karst areas. Based on statistics of soil erosion difference between diverse stratifications of each influencing factor, results of risk detector suggest that the amount of stratification combinations with significant difference accounted for 55% at least in small relief mountain and middle relief mountainous areas. Therefore, the spatial heterogeneity of soil erosion and its influencing factors in different geomorphological types should be investigated to control karst soil loss more effectively.展开更多
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
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National Basic Research Program of China,No.2015CB452702National Natural Science Foundation of China,No.41671098,No.41530749
文摘The formation mechanism and influencing factors identification of soil erosion are the core and frontier issues of current research. However, studies on the multi-factor synthesis are still relatively lacked. In this study, the simulation of soil erosion and its quantitative attribution analysis have been conducted in different geomorphological types in a typical karst basin based on the RUSLE model and the geodetector method. The influencing factors, such as land use type, slope, rainfall, elevation, lithology and vegetation cover, have been taken into consideration. Results show that the strength of association between the six influencing factors and soil erosion was notably different in diverse geomorphological types. Land use type and slope were the dominant factors of soil erosion in the Sancha River Basin, especially for land use type whose power of determinant(q value) for soil erosion was much higher than other factors. The q value of slope declined with the increase of relief in mountainous areas, namely it was ranked as follows: middle elevation hill> small relief mountain> middle relief mountain. Multi-factors interactions were proven to significantly strengthen soil erosion, particularly for the combination of land use type with slope, which can explain 70% of soil erosion distribution. It can be found that soil erosion in the same land use type with different slopes(such as dry land with slopes of 5° and above 25°) or in the diverse land use types with the same slope(such as dry land and forest with a slope of 5°), varied much. These indicate that prohibiting steep slope cultivation and Grain for Green Project are reasonable measures to control soil erosion in karst areas. Based on statistics of soil erosion difference between diverse stratifications of each influencing factor, results of risk detector suggest that the amount of stratification combinations with significant difference accounted for 55% at least in small relief mountain and middle relief mountainous areas. Therefore, the spatial heterogeneity of soil erosion and its influencing factors in different geomorphological types should be investigated to control karst soil loss more effectively.
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.
