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Water 2016, 8(9), 361; doi:10.3390/w8090361

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

1
State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
2
Key Laboratory of Watershed Geographic Science, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
3
Key Laboratory of Subsurface Hydrology and Ecological Effects in Arid Region (Chang’an University), Ministry of Education, Xi’an 710064, China
4
School of Environmental Science and Engineering, Chang’an University, Xi’an 710064, China
5
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
View Full-Text   |   Download PDF [3605 KB, uploaded 23 August 2016]   |  

Abstract

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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MDPI and ACS Style

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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