摘要：Recent studies show that dissolved iron is a factor essential to the biological productivity of the Sea of Okhotsk. It is also highly probable that wetlands in the Amur River basin play an important role in providing dissolved iron to the Sea of Okhotsk. During the last century, large areas of wetlands within the Amur River catchment have been cultivated, which, in turn, may have had a great impact on the production of dissolved iron. To assess the impact of this conversion of land cover on the production of dissolved iron – and thereby primary production in the Sea of Okhotsk – we have been constructed a numerical model to simulate dissolved iron production and transport in the Amur River. Though the accuracy of hydrological models heavily depends upon the precipitation input, there has been no observation-based gridded precipitation dataset covering a continental-scale region with high spatio-temporal resolution. Recently, however, datasets such as APHRODITE have been released. Thus, in this article we evaluate how hydrological simulation results may be improved by these datasets. By compar- ing the results from the APHRODITE precipitation dataset with those from the NCEP2 precipitation dataset, we show that the precipitation amount from NCEP2 around the Amur River basin is overestimated. Moreover, the closeness of the fit evaluated by the Nash-Sutcliffe criteria indicates that the results from APHRODITE are significantly better than those from NCEP2. The results indicate that the precipitation of the APHRODITE dataset for the Amur River basin has good accuracy.
