scholarly journals Influence of Check Dams on Flood and Erosion Dynamic Processes of a Small Watershed in the Loss Plateau

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 834 ◽  
Author(s):  
Shuilong Yuan ◽  
Zhanbin Li ◽  
Peng Li ◽  
Guoce Xu ◽  
Haidong Gao ◽  
...  

As an important soil and water conservation engineering measure, check dams have been constructed on a large scale in the Loess Plateau of China. However, their effects on runoff and sediment processes in the basin are still unclear. In this study, the hydrodynamic processes of the Wangmaogou watershed located in the Loess Plateau were simulated, and the influence of check dams on the flood and erosion dynamic processes in this watershed were also evaluated. The results showed that the check dams obviously reduced the flood peak and flood volume and mitigated the flood process. After the dam system was completed, the flood peak and flood volume were reduced by 65.34% and 58.67%, respectively. The erosion dynamic distribution of the main channel in the small watershed was changed to different extents by the different dam type combinations, and the erosion dynamic parameters of the channel decreased most after the dam system was completed, when the velocity and runoff shear stress of the outlet section were reduced by 10.69% and 31.08%, respectively. Additionally, the benefits of sediment reduction were most obvious after the check dam system was completed, with the sediment discharge in the watershed being reduced by 83.92%. The results of this study would provide specific implications for construction and management of check dams in the Loess plateau.

2020 ◽  
Author(s):  
Shuilong Yuan ◽  
Guoce Xu ◽  
Peng Shi ◽  
Kexin Lu

<p>As an important soil and water conservation engineering measure, check dams have been constructed on a large scale in the Loess Plateau of China. However, their effects on runoff and sediment processes in the basin are still unclear. In this study, the hydrodynamic processes of the Wangmaogou watershed located in the Loess Plateau were simulated, and the influence of check dams on the flood and erosion dynamic processes in this watershed were also evaluated. The results showed that the check dams obviously reduced the flood peak and flood volume and mitigated the flood process. After the dam system was completed, the flood peak and flood volume were reduced by 65.34% and 58.67%, respectively. The erosion dynamic distribution of the main channel in the small watershed was changed to different extents by the different dam type combinations, and the erosion dynamic parameters of the channel decreased most after the dam system was completed, when the velocity and runoff shear stress of the outlet section were reduced by 10.69% and 31.08%, respectively. Additionally, the benefits of sediment reduction were most obvious after the check dam system was completed, with the sediment discharge in the watershed being reduced by 83.92%. The results of this study would provide specific implications for construction and management of check dams in the Loess plateau.</p>


Author(s):  
Hui Wei ◽  
Wenwu Zhao ◽  
Han Wang

Large-scale vegetation restoration greatly changed the soil erosion environment in the Loess Plateau since the implementation of the “Grain for Green Project” (GGP) in 1999. Evaluating the effects of vegetation restoration on soil erosion is significant to local soil and water conservation and vegetation construction. Taking the Ansai Watershed as the case area, this study calculated the soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration, using the Chinese Soil Loess Equation (CSLE), based on rainfall and soil data, remote sensing images and socio-economic data. The effect of vegetation restoration on soil erosion was evaluated by comparing the average annual soil erosion modulus under two scenarios among 16 years. The results showed: (1) vegetation restoration significantly changed the local land use, characterized by the conversion of farmland to grassland, arboreal land, and shrub land. From 2000 to 2015, the area of arboreal land, shrub land, and grassland increased from 19.46 km2, 19.43 km2, and 719.49 km2 to 99.26 km2, 75.97 km2, and 1084.24 km2; while the farmland area decreased from 547.90 km2 to 34.35 km2; (2) the average annual soil erosion modulus from 2000 to 2015 under the initial and current scenarios of vegetation restoration was 114.44 t/(hm²·a) and 78.42 t/(hm²·a), respectively, with an average annual reduction of 4.81 × 106 t of soil erosion amount thanks to the vegetation restoration; (3) the dominant soil erosion intensity changed from “severe and light erosion” to “moderate and light erosion”, vegetation restoration greatly improved the soil erosion environment in the study area; (4) areas with increased erosion and decreased erosion were alternately distributed, accounting for 48% and 52% of the total land area, and mainly distributed in the northwest and southeast of the watershed, respectively. Irrational land use changes in local areas (such as the conversion of farmland and grassland into construction land, etc.) and the ineffective implementation of vegetation restoration are the main reasons leading to the existence of areas with increased erosion.


Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1264
Author(s):  
Fabing Xie ◽  
Guangju Zhao ◽  
Xingmin Mu ◽  
Peng Tian ◽  
Peng Gao ◽  
...  

Soil erosion has become the dominant environmental issue endangering sustainable development in agriculture and the ecosystem on the Loess Plateau. Determination of watershed soil erosion rates and sediment yields is essential for reasonable utilization of water resources and soil loss control. In this study, we employed unmanned aerial vehicles (UAVs) and structure-from-motion (SfM) photogrammetry to determine the sediment yields in 24 dam-controlled watersheds in the Pisha sandstone region of the northern Loess Plateau. High differences in total sediment were trapped before the check dams due to their running periods and sediment yields. The estimated specific sediment yield ranged from 34.32 t/(ha∙a) to 123.80 t/(ha∙a) with an average of 63.55 t/(ha∙a), which indicated that the Pisha sandstone region had an intense soil erosion rate. Furthermore, the modified Sediment Distributed Delivery (SEDD) model was applied to identify the erosion-prone areas in the watersheds, and the sediment retained in the check dams were used for model calibration. The performance of the model was acceptable, and the modeling results indicated that the steep Pisha sandstone was the major sediment source for the watersheds, accounting for approximately 87.37% of the sediment yield. Catchment area, erosive precipitation, and badland proportion were the key factors for sediment yield in the dam-controlled watersheds of the Pisha sandstone region, according to multiple regression analyses. These findings indicated that the modified SEDD model is very efficient in identifying spatial heterogeneities of sediment yield in the watershed but requires comprehensive calibration and validation with long-term observations. The Pisha sandstone region is still the key area of soil erosion control in the Loess Plateau, which needs more attention for soil and water conservation due to high sediment yield.


2021 ◽  
Vol 13 (5) ◽  
pp. 1021
Author(s):  
Hu Ding ◽  
Jiaming Na ◽  
Shangjing Jiang ◽  
Jie Zhu ◽  
Kai Liu ◽  
...  

Artificial terraces are of great importance for agricultural production and soil and water conservation. Automatic high-accuracy mapping of artificial terraces is the basis of monitoring and related studies. Previous research achieved artificial terrace mapping based on high-resolution digital elevation models (DEMs) or imagery. As a result of the importance of the contextual information for terrace mapping, object-based image analysis (OBIA) combined with machine learning (ML) technologies are widely used. However, the selection of an appropriate classifier is of great importance for the terrace mapping task. In this study, the performance of an integrated framework using OBIA and ML for terrace mapping was tested. A catchment, Zhifanggou, in the Loess Plateau, China, was used as the study area. First, optimized image segmentation was conducted. Then, features from the DEMs and imagery were extracted, and the correlations between the features were analyzed and ranked for classification. Finally, three different commonly-used ML classifiers, namely, extreme gradient boosting (XGBoost), random forest (RF), and k-nearest neighbor (KNN), were used for terrace mapping. The comparison with the ground truth, as delineated by field survey, indicated that random forest performed best, with a 95.60% overall accuracy (followed by 94.16% and 92.33% for XGBoost and KNN, respectively). The influence of class imbalance and feature selection is discussed. This work provides a credible framework for mapping artificial terraces.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1755
Author(s):  
Shuo Wang ◽  
Chenfeng Cui ◽  
Qin Dai

Since the early 2000s, the vegetation cover of the Loess Plateau (LP) has increased significantly, which has been fully recorded. However, the effects on relevant eco-hydrological processes are still unclear. Here, we made an investigation on the changes of actual evapotranspiration (ETa) during 2000–2018 and connected them with vegetation greening and climate change in the LP, based on the remote sensing data with correlation and attribution analysis. Results identified that the average annual ETa on the LP exhibited an obvious increasing trend with the value of 9.11 mm yr−1, and the annual ETa trend was dominated by the changes of ETa in the third quarter (July, August, and September). The future trend of ETa was predicted by the Hurst exponent. Partial correlation analysis indicated that annual ETa variations in 87.8% regions of the LP were controlled by vegetation greening. Multiple regression analysis suggested that the relative contributions of potential evapotranspiration (ETp), precipitation, and normalized difference vegetation index (NDVI), to the trend of ETa were 5.7%, −26.3%, and 61.4%, separately. Vegetation greening has a close relationship with the Grain for Green (GFG) project and acts as an essential driver for the long-term development trend of water consumption on the LP. In this research, the potential conflicts of water demanding between the natural ecosystem and social-economic system in the LP were highlighted, which were caused by the fast vegetation expansion.


2021 ◽  
Vol 10 (12) ◽  
pp. 805
Author(s):  
Xuan Fang ◽  
Jincheng Li ◽  
Ying Zhu ◽  
Jianjun Cao ◽  
Jiaming Na ◽  
...  

Terraces, which are typical artificial landforms found around world, are of great importance for agricultural production and soil and water conservation. However, due to the lack of maintenance, terrace damages often occur and affect the local flow process, which will influence soil erosion. Automatic high-accuracy mapping of terrace damages is the basis of monitoring and related studies. Researchers have achieved artificial terrace damage mapping mainly via manual field investigation, but an automatic method is still lacking. In this study, given the success of high-resolution unmanned aerial vehicle (UAV) photogrammetry and object-based image analysis (OBIA) for image processing tasks, an integrated framework based on OBIA and UAV photogrammetry is proposed for terrace damage mapping. The Pujiawa terrace in the Loess Plateau of China was selected as the study area. Firstly, the segmentation process was optimised by considering the spectral features and the terrains and corresponding textures obtained from high-resolution images and digital surface models. The feature selection was implemented via correlation analysis, and the optimised segmentation parameter was achieved using the estimation of scale parameter algorithm. Then, a supervised k-nearest neighbourhood classifier was used to identify the terrace damages in the segmented objects, and additional geometric features at the object level were considered for classification. The comparison with the ground truth, as delineated by the image and field survey, showed that proposed classification can be adequately performed. The F-measures of extraction on three terrace damages were 92.07% (terrace sinkhole), 81.95% (ridge sinkhole), and 85.17% (collapse), and the Kappa coefficient was 85.34%. Finally, the potential application and spatial distribution of the terrace damages in this study were determined. We believe that this work can provide a credible framework for mapping terrace damages in the Loess Plateau of China.


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