Using remotely sensed imagery to estimate potential annual pollutant loads in river basins

摘要

Land cover changes around river basins have caused serious environmental degradation in globalnsurface water areas, in which the direct monitoring and numerical modeling is inherently difficult.nPrediction of pollutant loads is therefore crucial to river environmental management under thenimpact of climate change and intensified human activities. This research analyzed the relationshipnbetween land cover types estimated from NOAA Advanced Very High Resolution Radiometern(AVHRR) imagery and the potential annual pollutant loads of river basins in Japan. Then annempirical approach, which estimates annual pollutant loads directly from satellite imagery andnhydrological data, was investigated. Six water quality indicators were examined, including totalnnitrogen (TN), total phosphorus (TP), suspended sediment (SS), Biochemical Oxygen Demandn(BOD), Chemical Oxygen Demand (COD), and Dissolved Oxygen (DO). The pollutant loads of TN,nTP, SS, BOD, COD, and DO were then estimated for 30 river basins in Japan. Results show thatnthe proposed simulation technique can be used to predict the pollutant loads of river basinsnin Japan. These results may be useful in establishing total maximum annual pollutant loadsnand developing best management strategies for surface water pollution at river basin scale.