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. 2019 Jun 18;16(12):2149.
doi: 10.3390/ijerph16122149.

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Xinqi Hu  1 , Hongqi Wang  2 , Yi Zhu  3 , Gang Xie  4 , Huijian Shi  5
Affiliations

Landscape Characteristics Affecting Spatial Patterns of Water Quality Variation in a Highly Disturbed Region

Xinqi Hu et al. Int J Environ Res Public Health. .

Abstract

Spatial patterns of water quality trends for 45 stations in control units of the Shandong Province, China during 2009-2017 were examined by a non-parametric seasonal Mann-Kendall's test (SMK) for dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), permanganate index (CODMn), total phosphorus (TP) and ammonia nitrogen (NH3-N). The DO concentration showed significant upward trends at approximately half of the stations, while other parameters showed significant downward trends at more than 40% of stations. The stations with downward trends presented significant spatial autocorrelation, and were mainly concentrated in the northwest and southwest regions. The relationship between the landscape characteristics and water quality was explored using stepwise multiple regression models, which indicated the water quality was better explained using landscape pattern metrics compared to the percentage of land use types. Decreased mean patch area and connectedness of farmland will promote the control of BOD, COD and CODMn, whereas the increased landscape percentage of urban areas were not conducive to the water quality improvement, which suggested the sprawling of farmland and urban land was not beneficial to pollution control. Increasing the grassland area was conducive to the reduction of pollutants, while the effect of grassland fragmentation was reversed.

Keywords: landscape patterns; spatial analysis; water quality management; water quality trends.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Location of water quality monitoring stations and control units.
Figure 2
Figure 2
Land use classification of the Shandong province in 2010, 2015, 2018.
Figure 3
Figure 3
Temporal trends observed upon seasonal Mann-Kendall’s (SMK) testing for water quality parameters at 45 monitoring stations during 2009–2017.
Figure 4
Figure 4
Spatial distribution of Local Moran’s I for water quality trends at 45 monitoring stations.
Figure 5
Figure 5
Spatial variations in water quality current status at 45 control units in wet and dry season from 2015 to 2017 (A: the variation of DO in Dry Season; B: the variation of DO in Wet Season; C: the variation of BOD in Dry Season; D: the variation of BOD in Wet Season; E: the variation of COD in Dry Season; F: the variation of COD in Wet Season; G: the variation of CODMn in Dry Season; H: the variation of CODMn in Wet Season; I: the variation of NH3-N in Dry Season; J: the variation of NH3-N in Wet Season; K: the variation of TP in Dry Season; L: the variation of TP in Wet Season).
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