Modeling the Linkage Between River Water Quality and Landscape Metrics in the Chugoku District of Japan

Amiri, Bahman Jabbarian; Nakane, Kaneyuki

doi:10.1007/s11269-008-9307-z

Cited by 130 publications

(59 citation statements)

References 34 publications

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“…In addition, spatial information on land use practices could be further integrated into the analysis to enrich the interpretation. LULC effects can also be studied in more detail by taking into account spatial heterogeneity through landscape metrics studies, as some authors did [18,47,48], or, e.g., focusing on specific locations or types of forest such as riparian forests. Study of residuals and outliers could bring to light how catchment management can mitigate effects on water quality, as there are sub-catchments where water quality is unexpectedly high or low based on its LULC profile.…”

Section: Discussionmentioning

confidence: 99%

Linking Forest Cover to Water Quality: A Multivariate Analysis of Large Monitoring Datasets

Brogna

Michez

Jacobs

et al. 2017

Water

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Forested catchments are generally assumed to provide higher quality water. However, this hypothesis must be validated in various contexts as interactions between multiple land use and land cover (LULC) types, ecological variables and water quality variables render this relationship highly complex. This paper applies a straightforward multivariate approach on a typical large monitoring dataset of a highly managed and densely populated area (Wallonia, Belgium; 10-year dataset), quantifying forest cover effects on nine physico-chemical water quality variables. Results show that forest cover explains about one third of the variability of water quality and is positively correlated with higher quality water. When controlling for spatial autocorrelation, forest cover still explains 9% of water quality. Unlike needle-leaved forest cover, broad-leaved forest cover presents an independent effect from ecological variables and explains independently 4.8% of water quality variability while it shares 5.8% with cropland cover. This study demonstrates clear independent effects of forest cover on water quality, and presents a method to tease out independent LULC effects from typical large multivariate monitoring datasets. Further research on explanatory variables, spatial distribution effects and water quality datasets could lead to effective strategies to mitigate pollution and reach legal targets.

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Section: Discussionmentioning

confidence: 99%

Linking Forest Cover to Water Quality: A Multivariate Analysis of Large Monitoring Datasets

Brogna

Michez

Jacobs

et al. 2017

Water

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“…Research has studied the impact of land use on water quality by spatial analysis, statistical analysis, and hydrologic modeling (Mattikalli and Richards 1996;Hanratty and Stefan 1998;Rai and Sharma 1998;Tsihrintzis and Hamid 1998;Brezonik and Stadelmann 2002;Chang 2008;Amiri and Nakane 2009). A strong relationship between land use and water quality within catchments or watersheds has been suggested by previous studies (Gburek and Folmar 1999;Brezonik and Stadelmann 2002;Ha and Stenstrom 2003;Donohue et al 2006;Moreno et al 2006).…”

Section: Introductionmentioning

confidence: 99%

Testing a Dynamic Complex Hypothesis in the Analysis of Land Use Impact on Lake Water Quality

Guo

Liu

et al. 2009

Water Resour Manage

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In this study, we proposed a dynamic complex hypothesis that the impact of land use on water quality could vary along the expansion of the buffer size, and there should be an effective buffer zone where the strongest linkage occurs between land use and water quality. The hypothesis was tested and supported by a case study carried out in four watersheds in Hanyang District, China. More specific, buffer analysis and regression model were applied for studying the impacts of land use type, area proportion of land use type, and spatial pattern of land use on water quality. We conclude that not only the proportion of land use but also the spatial pattern moderates the impact of land use on water quality. Our study indicates that the identification of the effective buffer zones can provide new information and ideas for planning and management. Moreover, this study could also partially help to explain the conflicting results on the impact of land use on water quality in buffer versus in catchments in the literatures.

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“…The land use types of the river basin have been gradually transformed to agricultural or urban land from natural vegetation due to human activities, which caused the degradation of water environmental quality finally (Amiri and Nakane, 2009;Gao et al, 2004;Johnson et al, 1997;Mou et al, 2004;Uuemaa et al, 2007). Under the condition of point-source pollution has been effectively controlled, non-point source pollution from agricultural land use and private rural land has become one of the most important issues for the management of freshwater worldwide because of its extensive and uncertainty (Duncan, 2014;Short, 2013;Zhang et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Land use transitions and their effects on water environment in Huang-Huai-Hai Plain, China

et al. 2015

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a b s t r a c tThis paper analyzes the spatio-temporal dynamic patterns of land use in Huang-Huai-Hai Plain, one of the China's most important grain production bases experiencing rapid urban-rural transformation development, using high-resolution Landsat TM (Thematic Mapper) data and series data of water environmental quality monitoring in 2000 and 2010, and related socio-economic data from government departments. After assessing the change of water environmental quality of Huang-Huai-Hai Plain during 2000-2010, three spatial econometric regression models including Spatial Lag Model (SLM), Spatial Error Model (SEM) and ordinary least squares (OLS) are used to explore the correlationships between land use transitions and water environmental changes. The outcomes indicated that, during the research period, land use pattern changes in the study area were characterized by the loss of large quantities of farmland and the increase of construction land and water body. On the whole, the water environment in the study area was obviously improved, but there also existed partial deterioration as evidenced by the increase of monitoring sections with water environmental quality below Class V. In general, the increases of grassland, forested land and water body have positive effects on water environmental quality while farmland and construction land have negative effects on that. The authors argue that construction land use and farmland use have almost equal negative effects on water environmental quality, and managing agricultural non-point source pollution is pivotal to improve local water environmental quality. Finally, some of the major implications for managing the land and water resources in the plain areas of China as well as other developing countries undergoing rapid urban-rural transformation development are discussed in the aspects of ecological farming practices, rural construction land management, land use planning and urban planning.

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Modeling the Linkage Between River Water Quality and Landscape Metrics in the Chugoku District of Japan

Cited by 130 publications

References 34 publications

Linking Forest Cover to Water Quality: A Multivariate Analysis of Large Monitoring Datasets

Linking Forest Cover to Water Quality: A Multivariate Analysis of Large Monitoring Datasets

Testing a Dynamic Complex Hypothesis in the Analysis of Land Use Impact on Lake Water Quality

Land use transitions and their effects on water environment in Huang-Huai-Hai Plain, China

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