Abstract
Abstract. Ecohydrological sensitivity, defined as the response intensity of streamflow to per unit vegetation change is an integrated indicator for assessing hydrological sensitivity to vegetation change. Understanding ecohydrological sensitivity and its influencing factors is crucial for managing water supply, reducing water-related hazards and ensuring aquatic functions by vegetation management. Yet, there is still a systematic assessment on ecohydrological sensitivity and associated driving factors especially at a seasonal scale lacking. In this study, 14 large watersheds across various environmental gradients in China were selected to quantify their ecohydrological sensitivities at a seasonal scale and to examine the role of associated influencing factors such as climate, vegetation, topography, soil and landscape. Based on the variables identified by correlation analysis and factor analysis, prediction models of seasonal ecohydrological sensitivity were constructed to test their utilities for the design of watershed management and protection strategies. Our key findings were the following: (1) ecohydrological sensitivities were more sensitive under dry conditions than wet conditions – for example, 1 % LAI (leaf area index) change, on average, induced 5.05 % and 1.96 % change in the dry and wet season streamflow, respectively; (2) seasonal ecohydrological sensitivities were highly variable across the study watersheds with different climate conditions, dominant soil types and hydrological regimes; and (3) the dry season ecohydrological sensitivity was mostly determined by topography (slope, slope length, valley depth and downslope distance gradient), soil (topsoil organic carbon and topsoil bulk density) and vegetation (LAI), while the wet season ecohydrological sensitivity was mainly controlled by soil (topsoil-available water-holding capacity), landscape (edge density) and vegetation (leaf area index). Our study provided a useful and practical framework to assess and predict ecohydrological sensitivities at the seasonal scale. The established ecohydrological sensitivity prediction models can be applied to ungauged watersheds or watersheds with limited hydrological data to help decision makers and watershed managers effectively manage hydrological impacts through vegetation restoration programs. We conclude that ecohydrological sensitivities at the seasonal scale are varied by climate, vegetation and watershed property, and their understanding can greatly support the management of hydrological risks and protection of aquatic functions.
Highlights
Natural rivers often have a distinctive seasonal pattern of flow, where flow is highly related to precipitation and shows large variations over dry and wet seasons
The dry season ecohydrological sensitivity significantly increased with a rising dryness index, while the wet season ecohydrological sensitivity significantly decreased with increasing effective precipitation (Table 6)
Our findings clearly showed that seasonal ecohydrological sensitivity was highly associated with climate and vegetation change and significantly related to watershed properties like topography, soil and landscape
Summary
Natural rivers often have a distinctive seasonal pattern of flow, where flow is highly related to precipitation and shows large variations over dry and wet seasons. Seasonal flows determine ecosystem functions (Toledo-Aceves et al, 2011; Bruijnzeel et al, 2011; Salve et al, 2011), and their responses to vegetation change are highly variable and, affect watershed ecosystem equilibrium (Maeda et al, 2015). Research has shown that vegetation change can influence water retention time (Moore and Wondzell, 2005; Baker and Wiley, 2009; Bisantino et al, 2015), alter snow accumulation and snowmelt processes (Lin and Wei, 2008; Zhang and Wei, 2012; Calder, 2005) and route river flow quickly downstream (Winkler et al, 2010; Chang, 2012) and, increase the frequency and size of floods in wet season. Understanding seasonal hydrological variations in vegetation change is critical for maintaining the sustainable water supply, preventing large floods and droughts and developing the best watershed management plans
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