Modeling suspended sediment sources and transport in the Ishikari River Basin, Japan using SPARROW

Abstract

Abstract. It is important to understand the mechanisms that control suspended sediment (SS) fate and transport in rivers as high suspended sediment loads have significant impacts on riverine hydroecology. In this study, the watershed model SPARROW (SPAtially Referenced Regression on Watershed Attributes) was applied to estimate the sources and transport of SS in surface waters of the Ishikari River Basin (14 330 km2), the largest watershed on Hokkaido Island, Japan. The final developed SPARROW model has four source variables (developing lands, forest lands, agricultural lands, and stream channels), three landscape delivery variables (slope, soil permeability, and precipitation), two in-stream loss coefficients including small stream (streams with drainage area < 200 km2), large stream, and reservoir attenuation. The model was calibrated using measurements of SS from 31 monitoring sites of mixed spatial data on topography, soils and stream hydrography. Calibration results explain approximately 95.96% (R2) of the spatial variability in the natural logarithm mean annual SS flux (kg km−2 yr−1) and display relatively small prediction errors at the 31 monitoring stations. Results show that developing-land is associated with the largest sediment yield at around 1006.27 kg km−2 yr−1, followed by agricultural-land (234.21 kg km−2 yr−1). Estimation of incremental yields shows that 35.11% comes from agricultural lands, 23.42% from forested lands, 22.91% from developing lands, and 18.56% from stream channels. The results of this study improve our understanding of sediments production and transportation in the Ishikari River Basin in general, which will benefit both the scientific and the management community in safeguarding water resources.

Effects of Nonaerated Circulation Water Velocity on Nutrient Release from Aquaculture Pond Sediments

“…Figure 10c shows that this was also true for PO4 − : when the overlying water was still, the concentration was once again almost 3-fold higher than when the overlying water was moving, but unlike NH3-N, when the water was flowing the PO4 − concentrations increased with increasing water velocity. Similar results were reported for earlier studies by Luo et al [38], Duan et al [39], Larned and Atkinson [40], and Zhu et al [41]. For example, Larned and Atkinson found that with increasing water velocity, the rate of NH3-N and PO4 − uptake were positively correlated with velocity by D. cavernosa, which indicates that the NH3-N and PO4 − concentrations when the overlying water maintains a certain velocity are lower than those found in still overlying water.…”

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

“…By using multivariate statistical techniques, Shrestha and Kazama [24] evaluated the temporal/spatial variations in the Fuji river basin, illustrating the usefulness of multivariate statistical techniques for identifying pollution sources/factors and understanding temporal/spatial variation. Duan et al (2015) developed a SPARROW-based (SPAtially Referenced Regression on Watershed Attributes) watershed model to estimate the sources and transport of suspended sediments in surface waters of the Ishikari River basin [25]. Recently, remote sensing was used to evaluating water quality.…”