Landscape scale patterns in the character of natural organic matter in a Swedish boreal stream network

Temnerud, Johan; Düker, Anders; Karlsson, Sune; Allard, Bert; Köhler, Stephan Jürgen; Bishop, Kevin

doi:10.5194/hess-13-1567-2009

Cited by 9 publications

(6 citation statements)

References 64 publications

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“…The independent variables in a PLSR model were the selected watershed descriptors and the dependent variable was the specific water contaminant, which were both aggregated to wet/dry season for each year. All variables were centred by mean normalization and weighted by dividing the variables with the standard deviation prior to PLSR modeling (Temnerud et al, 2009). The logarithmic-transformation was applied to normalize the distribution of each variable.…”

Section: Partial Least Squares Regressionmentioning

confidence: 99%

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Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics

Shi

Yin

et al. 2015

Journal of Hydrology

120

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Section: Partial Least Squares Regressionmentioning

confidence: 99%

“…where IQR is interquartile range, and normalized IQR is IQR multiplied by 0.7413 (Temnerud et al, 2009). Interrelationships among landscape metrics, watershed characteristics and water contaminants were investigated using the PLSR (details in Section 3.4).…”

Section: Water Contaminant Maps and Statistical Analysesmentioning

confidence: 99%

Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics

Shi

Yin

et al. 2015

Journal of Hydrology

120

View full text Add to dashboard Cite

“…Water quality depends on landscape structure, and the nature of relationship between the two is affected by seasonal changes, as depicted in Figures 1-3. Seasonal variation of precipitation and runoff have great effects on stream water contamination concentration [15,38,51]. The concentration of DO is higher during the dry season, while the COD Mn and BOD 5 contaminant concentrations are higher during the wet season.…”

Section: Seasonal Effects Of Water Qualitymentioning

confidence: 99%

Influence of Landscape Structures on Water Quality at Multiple Temporal and Spatial Scales: A Case Study of Wujiang River Watershed in Guizhou

Ren

Zhen-hua

et al. 2019

Water

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Water quality is highly influenced by the composition and configuration of landscape structure, and regulated by various spatiotemporal factors. Using the Wujiang river watershed as a case study, this research assesses the influence of landscape metrics-including composition and spatial configuration-on river water quality. An understanding of the relationship between landscape metrics and water quality can be used to improve water contamination predictability and provide restoration and management strategies. For this study, eight water quality variables were collected from 32 sampling sites from 2014 through 2017. Water quality variables included nutrient pollutant indicators ammoniacal nitrogen (NH 3 -N), nitrogen (NO 3 − ), and total phosphate (TP), as well as oxygen-consuming organic matter indicators COD (chemical oxygen demand), biochemical oxygen demand (BOD 5 ), dissolved oxygen (DO), and potassium permanganate index (COD Mn ). Partial least squares (PLS) regression was used to quantitatively analyze the influence of landscape metrics on water quality at five buffer zone scales (extending 3, 6, 9, 12, and 15 km from the sample site) in the Wujiang river watershed. Results revealed that water quality is affected by landscape composition, landscape configuration, and precipitation. During the dry season, landscape metrics at both landscape and class levels predicted organic matter at the five buffer zone scales. During the wet season, only class-level landscape metrics predicted water contaminants, including organic matter and nutrients, at the middle three of five buffer scales. We identified the following important indicators of water quality degradation: percent of landscape, edge density, and aggregation index for built-up land; aggregation index for water; CONTAGION; COHESION; and landscape shape index. These results suggest that pollution can be mitigated by reducing natural landscape composition fragmentation, increasing the connectedness of region rivers, and minimizing human disturbance of landscape structures in the watershed area.

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“…where NIR is interquartile range multiplied by 0.7413 [32]. The PLS regression was used to determine the main watershed land use type that controls baseflow.…”

Section: Statistical Analysesmentioning

confidence: 99%

Influences of Land Use Change on Baseflow in Mountainous Watersheds

Huang

Shi

Fang

et al. 2016

Forests

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Abstract:It is crucial for effective water resource management in a watershed that the relationship between land use changes and baseflow. This study quantifies the influence of land use changes on the baseflow dynamics using a hydrological model and partial least-squares (PLS) regression in the Upper Du Watershed (8961 km 2 ), China. Our study suggests that forest can be a major factor with a negative impact on the baseflow. Additionally, farmland and urban land have second-order negative effects on the baseflow dynamics. Baseflow increases when forest is replaced by farmland because the evapotranspiration (ET), associated with baseflow recession, is weaker and shorter in duration in the farmland than in the forest. The conversion of forest to urban land increases baseflow owing to the presence of non-contributing impervious surfaces in urban areas, which prevents the urban land from intercepting the baseflow discharge. These results indicate that the baseflow dynamics are closely associated with varying land use types within a watershed. Thus, this study is intended to provide a deeper understanding of the baseflow processes and useful quantitative information on land use factors in watersheds, enabling more informed decision-making in forest and watershed management.

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Landscape scale patterns in the character of natural organic matter in a Swedish boreal stream network

Abstract: Abstract. This paper defines landscape-scale patterns in the character of natural organic matter (NOM) and tests for relationships to catchment soil, vegetation and topography. The

Cited by 9 publications

References 64 publications

Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics

Spatial and seasonal patterns in stream water contamination across mountainous watersheds: Linkage with landscape characteristics

Influence of Landscape Structures on Water Quality at Multiple Temporal and Spatial Scales: A Case Study of Wujiang River Watershed in Guizhou

Influences of Land Use Change on Baseflow in Mountainous Watersheds

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