4.5 Article

Statistical analysis and estimation of annual suspended sediments of major rivers in Japan

Journal

ENVIRONMENTAL SCIENCE-PROCESSES & IMPACTS
Volume 15, Issue 5, Pages 1052-1061

Publisher

ROYAL SOC CHEMISTRY
DOI: 10.1039/c3em30777h

Keywords

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Funding

  1. Japan Society for the Promotion of Science (JSPS) [P12055]
  2. JSPS KAKENHI [24 02055]
  3. Designing Local Frameworks for Integrated Water Resources Management at the Research Institute for Humanity and Nature (RIHN)
  4. JSPS [24248041]
  5. Kyoto University Global COE program on Sustainability/Survivability Science for a Resilient Society Adaptable to Extreme Weather Conditions
  6. Inter-Graduate School Program for Sustainable Development and Survivable Societies (GSS)
  7. MEXT
  8. Grants-in-Aid for Scientific Research [23760503] Funding Source: KAKEN

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We evaluate the spatiotemporal trendsof recent suspended sediment conditions in Japanese rivers. Statistical and spatiotemporal trend analysis is conducted on the 92 major rivers in Japan based on water quality monitoring data from 1992 to 2005. The Mann-Kendall non-parametric method was used to investigate the spatial and temporal trends for the suspended sediment indicator. Results show that the mean concentration of suspended sediments in Japanese rivers has generally declined in recent years, although there are still water quality problems at some monitoring sites (Kanto, Chubu, Kinki and Kyushu regions). A positive relationship between observed yearly discharge and suspended sediment load was found. Land use maps with 100 meter spatial resolution were used to apply an empirical model and develop a regression model for estimating annual suspended sediment loads directly from land use and hydrologic data. Rivers were assigned to three groups according to statistical cluster analysis of suspended sediment (SS) concentration. The correlation between the simulation result from the empirical model and the observed data had R-2 values of 0.62 and 0.71 for groups 2 and 3, and the correlation between the simulation result from the regression model and the observed data had R-2 values of 0.48 and 0.34 for groups 2 and 3. Results show that the proposed simulation technique can be used to predict the pollutant loads to river basins in Japan. Results also suggest prioritization methods and strategies that policy-makers can use to address suspended sediment pollution in rivers and water quality management in general.

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