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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...

Qinghai Lake is the largest saline lake in China. The change in the lake volume is an indicator of the variation in water resources and their response to climate change on the Qinghai-Tibetan Plateau (QTP) in China. The present study quantitatively evaluated the effects of climate change and land use/cover change (LUCC) on the lake volume of the Qinghai Lake in China from 1958 to 2018, which is crucial for water resources management in the Qinghai Lake Basin. To explore the effects of climate change and LUCC on the Qinghai Lake volume, we analyzed the lake level observation data and multi-period land use/land cover (LULC) data by using an improved lake volume estimation method and Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. Our results showed that the lake level decreased at the rate of 0.08 m/a from 1958 to 2004 and increased at the rate of 0.16 m/a from 2004 to 2018. The lake volume decreased by 105.40×10 8 m 3 from 1958 to 2004, with the rate of 2.24×10 8 m 3 /a, whereas it increased by 74.02×10 8 m 3 from 2004 to 2018, with the rate of 4.66×10 8 m 3 /a. Further, the climate of the Qinghai Lake Basin changed from warm-dry to warm-humid. From 1958 to 2018, the increase in precipitation and the decrease in evaporation controlled the change of the lake volume, which were the main climatic factors affecting the lake volume change. From 1977 to 2018, the measured water yield showed an "increase-decrease-increase" fluctuation in the Qinghai Lake Basin. The effects of climate change and LUCC on the measured water yield were obviously different. From 1977 to 2018, the contribution rate of LUCC was -0.76% and that of climate change was 100.76%; the corresponding rates were 8. 57% and 91.43% from 1977 to 2004, respectively, and -4.25% and 104.25% from 2004 to 2018, respectively. Quantitative analysis of the effects and contribution rates of climate change and LUCC on the Qinghai Lake volume revealed the scientific significance of climate change and LUCC, as well as their individual and combined effects in the Qinghai Lake Basin and on the QTP. This study can contribute to the water resources management and regional sustainable development of the Qinghai Lake Basin.