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Spatial evaluation of phosphorus retention in riparian zones using remote sensing data
Authors:Guotao Dong  Shengtian Yang  Yunfei Gao  Juan Bai  Xuelei Wang  Donghai Zheng
Institution:1. State Key Laboratory of Remote Sensing Science, Jointly Sponsored by Beijing Normal University and the Institute of Remote Sensing Applications of Chinese Academy of Sciences, Research Center for Remote Sensing and GIS, Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, School of Geography, Beijing Normal University, Beijing, 100875, People’s Republic of China
2. Yellow River Institute of Hydraulic Research, Yellow River Conservancy Commission, Zhengzhou, 450003, People’s Republic of China
3. Upper and Middle Yellow River Bureau, Yellow River Conservancy Commission, Xi’an, 710021, People’s Republic of China
4. Satellite Environment Center, Ministry of Environmental Protection, Beijing, 100094, People’s Republic of China
5. Department of Civil Engineering, Faculty of Engineering Technology, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands
Abstract:Riparian zones act as important buffer zones for non-point source pollution, thus improving the health of aquatic ecosystems. Previous research has shown that riparian zones play an important role, and that land use has an important effect, on phosphorus (P) retention. A spatial basin-scale approach for analyzing P retention and land use effects could be important in preventing pollution in riparian zones. In this study, a riparian phosphorus cycle model based on EcoHAT was generated with algorithms from soil moisture and heat models, simplified soil and plant phosphorus models, plant growth models, and universal soil loss equations. Based on remote sensing data, model performance was enhanced for spatial and temporal prediction of P retention in the riparian zone. A modified soil and plant P model was used to simulate the soil P cycle of a riparian zone in a temperate continental monsoon climate in northern China. A laboratory experiment and a field experiment were conducted to validate the P cycle model. High coefficients of determination (R 2) between simulated and observed values indicate that the model provides reliable results. P uptake variations were the same as the net primary productivity (NPP) trends, which were affected by soil temperature and moisture in the temperate continental monsoon climate. Beginning in June, the monthly content increased, with the maximum appearing in August, when the most precipitation and the highest temperatures occur. The spatial distribution of P uptake rates from March to September showed that areas near water frequently had relatively high values from May to August, which is contrary to results obtained in March, April, and September. The P uptake amounts for different land uses changed according to expectation. The average monthly P uptake rates for farmlands and grasslands were more than those for orchards and lowlands, which had moderate P uptake rates, followed by shrubs and forests. The spatial distribution of soil erosion demonstrated that the soil erosion came primarily from high-intensity agricultural land in the western and central areas, while the northern and eastern study regions, which were less affected by human activity, experienced relatively slight soil erosion. From the point of view of P pollution prevention, the spatial structure of riparian zones and the spatial distribution of land use around the Guanting reservoir are thus not favorable.
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