Spatiotemporal water yield variations and influencing factors in the Lhasa River Basin, Tibetan Plateau

Huiting Lu,Gang Wu,Lindsay C. Stringer,Guohua Liu,Tiantian Jin,Yan Yan,Martin Dallimer,Jieyuan Zhu

doi:10.5194/egusphere-egu2020-7403

Abstract

&lt;p&gt;Climate and land use/cover changes are widely recognized as two main drivers of variations in ecosystem services including water yield. However, vegetation cover condition, which can also influence the hydrological cycle through evapotranspiration process, is seldom considered. In this study, we used the Seasonal Water Yield Model (SWYM) to assess the spatiotemporal water yield changes of Lhasa River Basin from 1990 to 2015, and analysed its influencing factors by focusing on precipitation change, land cover change, and vegetation cover change (indexed by Normalized Difference Vegetation Index, i.e. NDVI). We first examined the model through Morris Screening sensitivity analysis and validated it with observed flow data. Spatiotemporal variation of three indices of water yield, baseflow, quick flow and local recharge, were then assessed. To analyse the contribution of each factor to water yield change, three scenarios were built in which one factor was altered at a time. Results showed that, the precipitation and vegetation cover change were substantial during the study period, while land cover change was quite small. From 1990 to 2015, the baseflow, local recharge and quick flow decreased by 67.03%, 80.21% and 37.03% respectively, with the change mainly occurring during 2000-2010. The spatial pattern of water yield remained mostly unchanged. The upstream area had relatively high baseflow and local recharge, and was the main contributor of quick flow. The downstream area had relatively low or even zero baseflow, and most of its local recharge was negative due to high evapotranspiration. According to contribution analysis, precipitation and vegetation cover change were the main factors affecting water yield in the Lhasa River Basin. For baseflow, the influence of precipitation change was, on average, 7.98 times as big as vegetation cover change, and the influence of vegetation cover change was, on average, 115.45 times as big as land cover change. However, land cover change began to exert greater influence after 2010. We suggest that besides climate and land use/cover change, vegetation cover change should also be studied in greater depth to fully understand its effect on regional hydrological process and ecosystem service provision.&lt;/p&gt;

Highlights

Among the many ecosystem services that influence human wellbeing, water yield is of great importance as many agricultural, industrial, and domestic activities depend on it [1–3]
Important factors, high σ values the presence of non-linearity and/or and local recharge, theirwith sensitivity factorsindicating were nearly the same: P and Curve number (CN) were the interactions two most with other factors; Rain events (RE), Kc, and were less important factors and have less non-linearity important factors, with high σ values indicating the presence of non-linearity and/or interactions and/or fewer interactions; Threshold flow accumulation (TFA)
The seasonal water yield model (SWYM) has been proven to be an efficient tool for revealing the effects of climate, land cover, and Normalized Difference Vegetation Index (NDVI) change on water yield by delivering the spatial results of baseflow, local recharge, and quick flow, which together depicts the seasonal flow characteristics

Summary

Introduction

Among the many ecosystem services that influence human wellbeing, water yield is of great importance as many agricultural, industrial, and domestic activities depend on it [1–3]. The spatiotemporal variation in water yield is important, and often leads to the challenge of how to allocate water resources between different seasons, and between upstream and downstream areas [2,5]. For arid and semi-arid regions, especially where the climate is highly seasonal, the baseflow that is slowly released by upstream areas due to the interception of vegetation or soil during the rainy season is highly valuable for downstream residents [6,7]. Understanding the spatiotemporal variation in water yield including the baseflow, local recharge, and quick flow as well as their driving factors is critical for developing appropriate water resources management strategies [3,8–10]

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Discussion

Conclusion