Abstract. Soil erosion and sediment transport play important roles in terrestrial landscape evolution and biogeochemical cycles of nutrients and contaminants. Although discharge is considered to be a controlling factor in sediment transport, its correlation with sediment concentration varies across the Yellow River basin (YRB) and is not fully understood. This paper provides analysis from gauges across the YRB covering a range of climates, topographic characteristics, and degrees of human intervention. Our results show that discharge control on sediment transport is dampened at gauges with large mean annual discharge, where sediment concentration becomes more and more stable. This emergent stationarity can be attributed to vegetation resistance. Our analysis shows that sediment concentration follows a bell shape with vegetation index (normalized difference vegetation index, NDVI) at an annual scale despite heterogeneity in climate and landscape. We obtain the counterintuitive result that, as mean annual discharge increases, the dominant control on sediment transport shifts from streamflow erosion to vegetation retardation in the YRB.
In this study, a model was proposed based on the sustainable boundary approach, to provide decision support for reservoir ecological operation with the dynamic Bayesian network. The proposed model was developed in four steps: (1) calculating and verifying the sustainable boundaries in combination with the ecological objectives of the study area, (2) generating the learning samples by establishing an optimal operation model and a Monte Carlo simulation model, (3) establishing and training a dynamic Bayesian network by learning the examples and (4) calculating the probability of the economic and ecological targets exceeding the set threshold from time to time with the trained dynamic Bayesian network model. Using the proposed model, the water drawing of the reservoir can be adjusted dynamically according to the probability of the economic and ecological targets exceeding the set threshold during reservoir operation. In this study, the proposed model was applied to the middle reaches of Heihe River, the effect of water supply proportion on the probability of the economic target exceeding the set threshold was analyzed, and the response of the reservoir water storage in each period to the probability of the target exceeding the set threshold was calculated. The results show that the risks can be analyzed with the proposed model. Compared with the existing studies, the proposed model provides guidance for the ecological operation of the reservoir from time to time and technical support for the formulation of reservoir operation chart. Compared with the operation model based on the designed guaranteed rate, the reservoir operation model based on uncertainty reduces the variation range of ecological flow shortage or the overflow rate and the economic loss rate by 5% and 6%, respectively. Thus, it can be seen that the decision support model based on the dynamic Bayesian network can effectively reduce the influence of water inflow and rainfall uncertainties on reservoir operation.
An accelerating trend of global urbanization accompanying various environmental and urban issues makes frequently urban mapping. Nighttime light data (NTL) has shown great advantages in urban mapping at regional and global scales over long time series because of its appropriate spatial and temporal resolution, free access, and global coverage. However, the existing urban extent extraction methods based on nighttime light data rely on auxiliary data and training samples, which require labor and time for data preparation, leading to the difficulty to extract urban extent at a large scale. This study seeks to develop an unsupervised method to extract urban extent from nighttime light data rapidly and accurately without ancillary data. The clustering algorithm is applied to segment urban areas from the background and multi-scale spatial context constraints are utilized to reduce errors arising from the low brightness areas and increase detail information in urban edge district. Firstly, the urban edge district is detected using spatial context constrained clustering, and the NTL image is divided into urban interior district, urban edge district and non-urban interior district. Secondly, the urban edge pixels are classified by an adaptive direction filtering clustering. Finally, the full urban extent is obtained by merging the urban inner pixels and the urban pixels in urban edge district. The proposed method was validated using the urban extents of 25 Chinese cities, obtained by Landsat8 images and compared with two common methods, the local-optimized threshold method (LOT) and the integrated night light, normalized vegetation index, and surface temperature support vector machine classification method (INNL-SVM). The Kappa coefficient ranged from 0.687 to 0.829 with an average of 0.7686 (1.80% higher than LOT and 4.88% higher than INNL-SVM). The results in this study show that the proposed method is a reliable and efficient method for extracting urban extent with high accuracy and simple operation. These imply the significant potential for urban mapping and urban expansion research at regional and global scales automatically and accurately.
Soil water movement is an important component in water cycle, which is also closely correlated with the transport of nutrients and contaminants in the catchment. Although there have been many studies in quantifying the water residence in soil, the understanding of the controlling factors is limited and could be controversial. Here, stable isotopes of water to explore the water age distribution in a mountainous catchment in the southwest China are used. The results are consistent with the regional climate pattern that the water vapor of the study catchment is brought by monsoons from Pacific Ocean in summer and prevailing westerly winds in winter. The estimated young water fraction is found to be strongly correlated with topographic gradient but presents no significant correlation with drainage area or vegetation coverage. Comparison between the difference in young water fraction of two adjacent sub‐catchments suggests that soil water in the steeper sub‐catchment tends to favor deep vertical infiltration, resulting in longer flow path, longer mean residence time, and smaller young water fraction. This difference between the soil water movement and the hydrological response revealed in this study has impacts on the biogeochemical cycles in the catchment.
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