Sediment discharge from the Yellow River originates mainly from the drainage area between Hekouzhen and Longmen, i.e., the Helong area. Spatial-temporal variations of the vegetation cover in this area during the 1981-...Sediment discharge from the Yellow River originates mainly from the drainage area between Hekouzhen and Longmen, i.e., the Helong area. Spatial-temporal variations of the vegetation cover in this area during the 1981-2007 period have been investigated using GIMMS and SPOT VGT NDVI data. We have also analyzed the interannual variations in vegetation cover and changes in annual runoff and sediment discharge, the consequences from precipitation change and the Grain for Green Project （GGP）. The results show that vegetation cover of the Helong area has increased during the 1981-2007 period. The northwestern part the Helong area, where the flat sandy lands are covered by grass, has experienced the largest increase. The region where the vegetation cover has declined is largely found in the southern and southeastern Helong area, which is a gullied hilly area or forested. Although precipitation was relatively low during the 1999-2007 period, the vegetation cover showed a significant increase in the Helong area, due to the implementation of the GGP. During this period, the most significant improvement in the vegetation cover occurred mainly in the gullied hilly areas of the Loess Plateau, such as the drainage basins of the Kuyehe and Tuweihe rivers and the middle and lower reaches of the Wudinghe and Yanhe rivers. A comparison of the average annual maximum NDVI between the earlier （1998-2002） stage and the next five years （2003-2007） of the GGP indicates that the areas with increases of 10% and 20% in NDVI account for 72.5% and 36.4% of the total area, respectively. Interannual variation of annual runoff and sediment discharge shows a declining trend, especially since the 1980s, when the decrease became very obvious. Compared with the 1950-1969 period, the average runoff during the 1980-2007 period was reduced by 34.8 × 10^8 m3 and the sediment discharge by 6.4 ×10^8 t, accounting for 49.4% and 64.9% of that in the 1950-1969 period, respectively. There is a positive correlation between the annual maximum NDVI and annual runoff and sediment discharge. This correlation was reversed since the implementation of the GGP in 1999 and vegetation cover in the He- long area has increased, associated with the decrease in runoff and sediment discharge. Less precipitation has been an important fac- tor driving the decrease in runoff and sediment discharge during 1999 2007. However, restoration and improvement of the vegetation cover may also have played a significant role in accelerating the decrease in annual runoff and sediment discharge by enhancing evapotranspiration and alleviating soil erosion.展开更多
Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-drive...Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.展开更多
基金supported by Beijing Forestry University for Young Scientist and funded by the National Natural Science Foundation of China (Grant No.40871136)
文摘Sediment discharge from the Yellow River originates mainly from the drainage area between Hekouzhen and Longmen, i.e., the Helong area. Spatial-temporal variations of the vegetation cover in this area during the 1981-2007 period have been investigated using GIMMS and SPOT VGT NDVI data. We have also analyzed the interannual variations in vegetation cover and changes in annual runoff and sediment discharge, the consequences from precipitation change and the Grain for Green Project （GGP）. The results show that vegetation cover of the Helong area has increased during the 1981-2007 period. The northwestern part the Helong area, where the flat sandy lands are covered by grass, has experienced the largest increase. The region where the vegetation cover has declined is largely found in the southern and southeastern Helong area, which is a gullied hilly area or forested. Although precipitation was relatively low during the 1999-2007 period, the vegetation cover showed a significant increase in the Helong area, due to the implementation of the GGP. During this period, the most significant improvement in the vegetation cover occurred mainly in the gullied hilly areas of the Loess Plateau, such as the drainage basins of the Kuyehe and Tuweihe rivers and the middle and lower reaches of the Wudinghe and Yanhe rivers. A comparison of the average annual maximum NDVI between the earlier （1998-2002） stage and the next five years （2003-2007） of the GGP indicates that the areas with increases of 10% and 20% in NDVI account for 72.5% and 36.4% of the total area, respectively. Interannual variation of annual runoff and sediment discharge shows a declining trend, especially since the 1980s, when the decrease became very obvious. Compared with the 1950-1969 period, the average runoff during the 1980-2007 period was reduced by 34.8 × 10^8 m3 and the sediment discharge by 6.4 ×10^8 t, accounting for 49.4% and 64.9% of that in the 1950-1969 period, respectively. There is a positive correlation between the annual maximum NDVI and annual runoff and sediment discharge. This correlation was reversed since the implementation of the GGP in 1999 and vegetation cover in the He- long area has increased, associated with the decrease in runoff and sediment discharge. Less precipitation has been an important fac- tor driving the decrease in runoff and sediment discharge during 1999 2007. However, restoration and improvement of the vegetation cover may also have played a significant role in accelerating the decrease in annual runoff and sediment discharge by enhancing evapotranspiration and alleviating soil erosion.
基金This work was financially supported by National Natural Science Foundation of China(41972262)Hebei Natural Science Foundation for Excellent Young Scholars(D2020504032)+1 种基金Central Plains Science and technology innovation leader Project(214200510030)Key research and development Project of Henan province(221111321500).
文摘Landslide is a serious natural disaster next only to earthquake and flood,which will cause a great threat to people’s lives and property safety.The traditional research of landslide disaster based on experience-driven or statistical model and its assessment results are subjective,difficult to quantify,and no pertinence.As a new research method for landslide susceptibility assessment,machine learning can greatly improve the landslide susceptibility model’s accuracy by constructing statistical models.Taking Western Henan for example,the study selected 16 landslide influencing factors such as topography,geological environment,hydrological conditions,and human activities,and 11 landslide factors with the most significant influence on the landslide were selected by the recursive feature elimination(RFE)method.Five machine learning methods[Support Vector Machines(SVM),Logistic Regression(LR),Random Forest(RF),Extreme Gradient Boosting(XGBoost),and Linear Discriminant Analysis(LDA)]were used to construct the spatial distribution model of landslide susceptibility.The models were evaluated by the receiver operating characteristic curve and statistical index.After analysis and comparison,the XGBoost model(AUC 0.8759)performed the best and was suitable for dealing with regression problems.The model had a high adaptability to landslide data.According to the landslide susceptibility map of the five models,the overall distribution can be observed.The extremely high and high susceptibility areas are distributed in the Funiu Mountain range in the southwest,the Xiaoshan Mountain range in the west,and the Yellow River Basin in the north.These areas have large terrain fluctuations,complicated geological structural environments and frequent human engineering activities.The extremely high and highly prone areas were 12043.3 km^(2)and 3087.45 km^(2),accounting for 47.61%and 12.20%of the total area of the study area,respectively.Our study reflects the distribution of landslide susceptibility in western Henan Province,which provides a scientific basis for regional disaster warning,prediction,and resource protection.The study has important practical significance for subsequent landslide disaster management.
