Assessing Changes of Water Yield in Qinghai Lake Watershed of China

Abstract

Water yield is an important ecosystem service, which is directly related to human welfare and affects the sustainable development. Using the integrated valuation of environmental services and tradeoffs model (InVEST model), we simulated the dynamic change of water yield in Qinghai lake watershed, Qinghai, China, and verified the simulation results. This paper emphatically explored how precipitation change and land use/land cover change (LUCC) affected the change of water yield on the spatial and temporal scales. Before 2004, the areas of cultivated land and unused land showed a dramatic increasing tendency, while forestland and water area presented a decreasing trend. After 2004 cultivated land changed slowly, unused land decreased. Grassland revealed a general trend of decline during 1977-2018, while built-up land basically presented a linear increase. The results show that water yield fluctuated and increased during 1977 . From 1977 to 2000, the mean water yield in each sub-watershed showed an increasing trend and afterward a decreasing one. After 2000, the sub-watersheds basically showed an increasing tendency. There was a strong correlation, with a correlation coefficient of 0.954 ** (** correlation is significant at the 0.01 level), between precipitation and water yield. Land use/land cover change can change the hydrological state of infiltration, evapotranspiration, and water retention. Meanwhile, the correlation between built-up land and water yield was the highest, with a correlation coefficient of 0.932, followed by forestland, with a correlation coefficient of 0.897. Through the analysis of different scenarios, we found that compared with land use/land cover change, precipitation played a more dominant role in affecting water yield.Water 2020, 12, 11 2 of 18 accuracy of the model output and the validation and evaluation of the performance of models in different circumstances and locations [11,12]. The input parameters have a great influence on the output results of the model. Many studies use sensitivity analysis methods to analyze the dependence between model output and variables [13,14], and in turn adjust model input parameters to find a set of optimal parameters. In fact, the input parameters of water yield module need to be calculated by physical equation or empirical equation [15,16]. So, we should make the input parameters more reasonable and accurate by standardizing the input data and taking full account of the regional characteristics and differences. In addition, the output results of the model are compared and verified through the observation data to evaluate the performance of the model without sensitive analysis methods and parameter adjustment, so as to provide a supporting evidence for us to use the model in the similar areas without measured data or insufficient data.Since the 1970s, many distributed hydrological models, including soil and water assessment tool (SWAT) [17], artificial intelligence for ecosystem services (ARIES) [18], integrated valuation of ecosystem services and trade...

Using InVEST to evaluate water yield services in Shangri-La, Northwestern Yunnan, China

“…In addition, within each slope grade, water yield initially increased and then gradually decreased over time, with a peak in 1989. In general, topographical factors indirectly affect the water yield ecosystem service function by affecting precipitation and vegetation types, as also reported by Lian et al (2020) .…”

“…The water yield of Shangri-La City generally showed significant changes corresponding to changes in precipitation and evapotranspiration, with the effect of precipitation on water yield far exceeding that of PET. Many past studies have similarly shown that a decrease in precipitation results in corresponding decreases in water yield ( Lian et al, 2020 ) and that precipitation is considered to be an important factor affecting changes in water yield ( Li et al, 2021b ; Yang et al, 2021 ). Evapotranspiration is a key component of the terrestrial water cycle connecting the atmosphere, vegetation, and soil, and represents the sum of vegetation and soil evaporation ( Yin et al, 2021 ).…”

“…Water yield is an important parameter describing regional water resources ( Li et al, 2021a ) and also plays an indispensable role in other ecological functions, such as the carbon cycle and sediment transport ( Ajaz Ahmed et al, 2017 ; Wang et al, 2020 ). Therefore, the study of water yield is helpful for understanding the evolution of the water yield ecosystem service function and for exploring the relationship between human beings and water resources, which has great significance for the scientific management and rational utilization of water resources ( Dennedy-Frank et al, 2016 ; Lian et al, 2020 ).…”

“…The InVEST mode was developed in 2007 through a collaboration between Stanford University, the World Wildlife Fund, the Nature Conservation Society, and other related institutions on the basic of the Budyko curve and annual precipitation ( Yang et al, 2019a ). The model is relatively simple, suited for applications to catchments lacking observed datasets ( Lian et al, 2020 ; Wei et al, 2021 ) and provides a reliable method for estimating water yield under different spatiotemporal scales ( Yang et al, 2019a ; Yin et al, 2020 ). Furthermore, the InVEST model calculates water yield based on the water balance to fully consider the spatial differences in soil permeability under different LULC and the influencing factors, such as topography and runoff.…”

The Effects of Land-Use Change/Conversion on Trade-Offs of Ecosystem Services in Three Precipitation Zones

“…Land use influences carbon sequestration [56] and soil conservation directly [57], and it also influences water yield by hydrologic processes [58]. Similarly, precipitation is the key factor for carbon sequestration [59], soil conservation [60], and water yield [61]. Soil properties affect plant growth [62], soil erosion [63], and hydrologic processes [64], and they are also important factors for these three ESs.…”