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Water 2016, 8(9), 361;

Source Apportionment of Annual Water Pollution Loads in River Basins by Remote-Sensed Land Cover Classification

State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Key Laboratory of Watershed Geographic Science, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region (Chang’an University), Ministry of Education, Xi’an 710064, China
School of Environmental Science and Engineering, Chang’an University, Xi’an 710064, China
Faculty of Agriculture, University of the Ryukyus, Nishihara, Okinawa 903-0213, Japan
Authors to whom correspondence should be addressed.
Academic Editor: Y. Jun Xu
Received: 4 April 2016 / Revised: 8 August 2016 / Accepted: 9 August 2016 / Published: 23 August 2016
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In this study, in order to determine the efficiency of estimating annual water pollution loads from remote-sensed land cover classification and ground-observed hydrological data, an empirical model was investigated. Remote sensing data imagery from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer were applied to an 11 year (1994–2004) water quality dataset for 30 different rivers in Japan. Six water quality indicators—total nitrogen (TN), total phosphorus (TP), biochemical oxygen demand (BOD), chemical oxygen demand (COD), and dissolved oxygen (DO)—were examined by using the observed river water quality data and generated land cover map. The TN, TP, BOD, COD, and DO loads were estimated for the 30 river basins using the empirical model. Calibration (1994–1999) and validation (2000–2004) results showed that the proposed simulation technique was useful for predicting water pollution loads in the river basins. We found that vegetation land cover had a larger impact on TP export into all rivers. Urban areas had a very small impact on DO export into rivers, but a relatively large impact on BOD and TN export. The results indicate that the application of land cover data generated from the remote-sensed imagery could give a useful interpretation about the river water quality. View Full-Text
Keywords: Japan; river; water quality; remote sensing; AVHRR Japan; river; water quality; remote sensing; AVHRR

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Wang, Y.; He, B.; Duan, W.; Li, W.; Luo, P.; Razafindrabe, B.H.N. Source Apportionment of Annual Water Pollution Loads in River Basins by Remote-Sensed Land Cover Classification. Water 2016, 8, 361.

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