Water yield, nitrogen and sediment retentions in Northern Japan (Teshio river watershed): land use change scenario analysis

Min Fan () and Hideaki Shibata

Mitigation and Adaptation Strategies for Global Change, 2016, vol. 21, issue 1, 119-133

Abstract: We investigated the effects of changing land use on water yield, and nitrogen (N) and sediment retentions in the Teshio river watershed in northern Japan. The Land Use and it’s Effects (CLUE) model was used to predict land use change and multilevel Bayesian analysis was used to quantify relationships between water quality components and topographical slope. The Soil and Water Assessment Tool (SWAT) hydrology model was used to simulate water yield, N and sediment retentions under land use change scenarios. Most of the study area was covered by forest in 1976, 2006 and 2036, with rice fields totally converted to farmland by 2036. There were positive correlations between water yield, inorganic-N yield, sediment yield and organic-N yield and topographical slope, but there was negative correlation between nitrate nitrogen (NO 3 -N) in the bottom of soil profile and topographical slope. Sediment and organic-N yields of forest were less than those of other land uses. Water yield, organic-N and sediment retentions were largest in the southeast of the study watershed, while the inorganic-N retention was highest along the riverine area. In comparison with the 1976 land use pattern, water yield sediment retention and organic-N retention decreased under 2006 and 2036 land use patterns while inorganic-N retention increased. We conclude that planning a comprehensive adaptation and mitigation program (e.g. establishing riparian zones, planning nutrient management practices and integrating systematic conservation planning into agricultural expansion) is necessary to avoid negative impacts of land use change on water yield, N and sediment retentions in the watershed. Copyright Springer Science+Business Media Dordrecht 2016

Keywords: Water yield; N retention; Sediment retention; Hydrology model; Land use change; Multilevel Bayesian analysis (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11027-014-9574-3

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