Abstract

Environmental flow is the quantity, timing, and quality of water flows required to sustain freshwater and estuarine ecosystems and the human livelihoods and well-being that depend on these ecosystems. Environmental flows (e-flows) are crucial parameters for ecosystem restoration. Understanding the effects of spatial variation in the hydrological and water quality factors on e-flows aids the determination of recovery prior areas and helps to improve the success rate of ecosystem restoration projects. However, few studies have investigated the effects, which severely hinder the restoration of aquatic ecosystems and the sustainable use of water resources in inland waters. This paper therefore presents a framework for studying such effects. Spatial autocorrelation, a geostatistical method, is used to analyze the spatial variation in the hydrological and water quality factors and to further analyze the effects of various factors on the spatial heterogeneity of e-flows. Four different methods including the Tennant method, wetted perimeter method, AEHRA, and integrated water quality method are integrated to comprehensively evaluate e-flows. The former three methods consider the demands of biota on the streamflow, whereas the latter considers the demands on both the streamflow and the water quality. The results show that the Tennant and wetted perimeter methods, which focus on the statistics of only streamflow, result in similar spatial distribution of e-flows; the AEHRA and integrated water quality method, which consider the effects of water quality and other hydrological factors such as flow velocity and water depth on fish, also result in a similar spatial variation. Consideration of both demands on the hydrological factors and the water quality environmental factors makes the integrated water quality method more practical, particularly in developing regions with excessive pollutant discharge into rivers. In addition, spatial variation in the hydrological and water quality factors influenced the presence of principal fish species and consequently affected the e-flows. Of the 37 water quality factors identified, water transparency had a negative impact on e-flow because the increase in transparency could reduce the number of principal fish species. Of the four hydrological factors, flow velocity and river width had positive impacts on fish because the increase in flow velocity can provide breeding sites and habitats for more fish, respectively, both of which result in increases in the numbers of principal fish species. We found that spatial variation in the hydrology and water quality factors had a profound impact on the living environments of aquatic organisms; negative changes in these factors lowered the survival probability of principal species, which changed the hierarchy and structure of the ecosystems and thus led to variation in e-flows. The results can provide priori knowledge for e-flow methods selection and a reference for ecosystem restoration helping improve the success rate of project elsewhere in the world.

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