Seasonal Water Quality Upstream of Dahuofang Reservoir, China – the Effects of Land Use Type at Various Spatial Scales

Abstract

Inappropriate land use is considered a main factor in the deterioration of water quality. The relationship between land use and water quality (RLW) is complex, so the exploration of how seasonal water quality is affected by land use at various spatial scales can benefit our understanding of the RLW. We examined data for 110 sampling sites upstream of Dahuofang Reservoir in China. RLWs in three seasons and at three spatial scales were analyzed via Spearman's rank correlation coefficient. After excluding unreliable data attributed to point source pollution and spatial autocorrelation, we found that land use in the riparian zone within 100 m of the river was correlated with water quality during the rainy season. Taking into account the influences of spatial pattern of the land use on water quality, breakpoint regression analysis indicated that when fragmented forest land covers more than 37% of the local riparian zone, the deterioration of water quality will be mitigated, in contrast water pollution would be exacerbated when un-fragmented dry farmland exceeds 54%. Therefore, when analyzing RLW, selection of the appropriate spatial scale and season as well as improvement of land use patterns can facilitate rational and effective basin management.

Effect of land use types on stream water quality under seasonal variation and topographic characteristics in the Wei River basin, China

“…Dominant factors of the temporal scale, such as precipitation, temperature and agricultural activities, vary among seasons, and given their role on flow convergence process and contaminant inputs into water bodies, researchers have suggested that it is imperative to consider seasonal variation when studying the impact of land use on river water quality . Ye (2014) indicated that while non-point source pollution was predominant in rainy seasons, agricultural and forested land showed stronger association with water chemistry. Bu (2014) employed statistical and spatial analyses to investigate the relationship between land use patterns and river water quality in the Taizi River basin, China, during both dry and rainy seasons, and found that during dry seasons, point source pollution was predominant, but in the rainy season water quality showed mixed pollution from both point and non-point sources.…”

“…Although the significant impact of land use on stream water quality has been well documented (Johnson and Gage, 1997;Allen, 2004;Hurley and Mazumder, 2013;Bu et al, 2014;Ye et al, 2014), further study on the complex association should be considered as much as possible, particularly on how the association varies temporally and with different topographical characteristics of land use.…”

Community–environment relationships of riverine invertebrate communities in central Chinese streams

“…as rubbish being deposited at the river banks, either deliberately or due to previous floods. Nitrogen compounds as the NH 3 -N here have been often associated to stress responses with benthic invertebrates (Caschetto et al 2014;Ye et al 2014). Important reach-scale variables also reflected human land use at these scales, including the fraction of agricultural terraces (in this region always constructed for agricultural use), reduced channel width and proportion of grass/bushland.…”

Characterization of the nonpoint source pollution into river at different spatial scales

“…The relationship between water quality and the underlying surface conditions also depends on the spatial scale (Morley & Karr ; Ye et al . ; Ding et al . ).…”

“…The information method, such as the Shannon information entropy, the mean information gain, the effective measure complexity and the fluctuation complexity are useful to measure information characteristics and complexity of the flow and NPS pollution loads (Pachepsky et al 2006;Wang et al 2009). The relationship between water quality and the underlying surface conditions also depends on the spatial scale (Morley & Karr 2002;Ye et al 2014;Ding et al 2016). Therefore, it is essential to investigate the uncertainty and predictability in NPS pollution loads at different spatial scales under the mutual influence of the driving forces (rainfall and pollution sources) and the underlying surfaces.…”