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Water shortage and pollution have become prominent in the arid regions of northwest China, seriously affecting human survival and sustainable development. The Bosten Lake basin has been considered as an example of an arid region in northwest China, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model has been used to quantitatively evaluate the future water yield and water purification services for four representative concentration pathways (RCP) scenarios. The results show that for the four RCP scenarios, the annual average precipitation in 2020–2050 decreases compared to that in 1985–2015; the area of cultivated land and unused land decreases, and the area of other land-use types increases from 2015 to 2050. The water yield service reduces, while the water purification service increases from 2015 to 2050 in the Bosten Lake basin. In 2050, the water yield and water purification services are the best for the RCP6.0 scenario, and are the worse for the RCP4.5 scenario and RCP8.5 scenario, respectively. The distribution of the water yield and water purification services show a gradual decline from northwest to southeast.
Xu Yang; Ruishan Chen; Guangxing Ji; Chao Wang; Yuanda Yang; Jianhua Xu. Assessment of Future Water Yield and Water Purification Services in Data Scarce Region of Northwest China. International Journal of Environmental Research and Public Health 2021, 18, 8960 .
AMA StyleXu Yang, Ruishan Chen, Guangxing Ji, Chao Wang, Yuanda Yang, Jianhua Xu. Assessment of Future Water Yield and Water Purification Services in Data Scarce Region of Northwest China. International Journal of Environmental Research and Public Health. 2021; 18 (17):8960.
Chicago/Turabian StyleXu Yang; Ruishan Chen; Guangxing Ji; Chao Wang; Yuanda Yang; Jianhua Xu. 2021. "Assessment of Future Water Yield and Water Purification Services in Data Scarce Region of Northwest China." International Journal of Environmental Research and Public Health 18, no. 17: 8960.
Analyzing the temporal variation of runoff and vegetation and quantifying the impact of anthropic factors and climate change on vegetation and runoff variation in the source area of the Yangtze River (SAYR), is of great significance for the scientific response to the ecological protection of the region. Therefore, the Budyko hypothesis method and multiple linear regression method were used to quantitatively calculate the contribution rates of climate change and anthropic factors to runoff and vegetation change in the SAYR. It was found that: (1) The runoff, NDVI, precipitation, and potential evaporation in the SAYR from 1982 to 2016 all showed an increasing trend. (2) The mutation year of runoff data from 1982 to 2016 in the SAYR is 2004, and the mutation year of NDVI data from 1982 to 2016 in the SAYR is 1998. (3) The contribution rates of precipitation, potential evaporation and anthropic factors to runoff change of the SAYR are 75.98%, −9.35%, and 33.37%, respectively. (4) The contribution rates of climatic factors and anthropic factors to vegetation change of the SAYR are 38.56% and 61.44%, respectively.
Guangxing Ji; Huiyun Song; Hejie Wei; Leying Wu. Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016. Land 2021, 10, 612 .
AMA StyleGuangxing Ji, Huiyun Song, Hejie Wei, Leying Wu. Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016. Land. 2021; 10 (6):612.
Chicago/Turabian StyleGuangxing Ji; Huiyun Song; Hejie Wei; Leying Wu. 2021. "Attribution Analysis of Climate and Anthropic Factors on Runoff and Vegetation Changes in the Source Area of the Yangtze River from 1982 to 2016." Land 10, no. 6: 612.
Previous studies mainly focused on quantifying the contribution rate of different factors on annual runoff variation in the source region of the Yellow River (SRYR), while there are few studies on the seasonal runoff variation. In this study, the monthly water storage and monthly actual evaporation of SRYR were calculated by the monthly ABCD model, and then a seasonal Budyko frame was constructed. Finally, the contribution rate of climatic and anthropic factors on the seasonal runoff variation in Tangnaihai hydrological station were quantitatively calculated. It turned out that: (1) The changing point of runoff data at Tangnaihai hydrological station is 1989. (2) The ABCD monthly hydrological model could well simulate the monthly runoff variation of Tangnaihai hydrological station. (3) Anthropic factors play a major role in runoff change in spring, summer, and winter, while climatic factors play a major role in runoff change in autumn.
Guangxing Ji; Leying Wu; Liangdong Wang; Dan Yan; Zhizhu Lai. Attribution Analysis of Seasonal Runoff in the Source Region of the Yellow River Using Seasonal Budyko Hypothesis. Land 2021, 10, 542 .
AMA StyleGuangxing Ji, Leying Wu, Liangdong Wang, Dan Yan, Zhizhu Lai. Attribution Analysis of Seasonal Runoff in the Source Region of the Yellow River Using Seasonal Budyko Hypothesis. Land. 2021; 10 (5):542.
Chicago/Turabian StyleGuangxing Ji; Leying Wu; Liangdong Wang; Dan Yan; Zhizhu Lai. 2021. "Attribution Analysis of Seasonal Runoff in the Source Region of the Yellow River Using Seasonal Budyko Hypothesis." Land 10, no. 5: 542.
The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.
Guangxing Ji; Zhizhu Lai; Haibin Xia; Hao Liu; Zheng Wang. Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT. Land 2021, 10, 421 .
AMA StyleGuangxing Ji, Zhizhu Lai, Haibin Xia, Hao Liu, Zheng Wang. Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT. Land. 2021; 10 (4):421.
Chicago/Turabian StyleGuangxing Ji; Zhizhu Lai; Haibin Xia; Hao Liu; Zheng Wang. 2021. "Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT." Land 10, no. 4: 421.