Quantitative analysis of the temporal and spatial distribution characteristics of coastal nutrient substances enables to
adequately estimate the state of coastal marine environment and describe environmental change processes conditioned by
anthropogenic forces. Remote sensing has the potential to provide synoptic information and has been somewhat
successful in monitoring nutrient properties at rivers and estuaries. So taking total inorganic nitrogen (TIN) as typical
nutrient monitoring index, Sheyang River estuary located in middle part of Jiangsu coastline, China was chosen for water
quality simulation and variation trend analysis. Six correlation coefficient matrixes were calculated by using
synchronous TIN concentration and its corresponding normalized water surface reflectance data from 15 field samples.
Results showed that band combination of 804 and 630nm with the form of pseudo-sediment parameter could get the best
correlation capacity and minimized reversion error. Based on this selected parameter, an inverse model was built for TIN
quantitative reversion. R<sup>2</sup> coefficients reached 0.97 and 0.9972 in calibration and validation period respectively. And
then the spatial distribution pattern of TIN in Sheyanghe River estuary was obtained using the inverse model via
Hyperion hyperspectral remote sensing image. A coupled wave-tide-surge model and material transport and diffusion
model were adopted for TIN concentration cross validation of the reversion precision exactly at river outlet. Comparison
results indicated that these two dataset made a good consistency for TIN diffusive characters in Sheyang River estuary
with the R<sup>2</sup> reached 0.6549. The magnitude of TIN concentration was also agreed fairly well.