scholarly journals Using Budyko-Type Equations for Separating the Impacts of Climate and Vegetation Change on Runoff in the Source Area of the Yellow River

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3418
Author(s):  
Dan Yan ◽  
Zhizhu Lai ◽  
Guangxing Ji

Assessing the contribution rates of climate change and human activities to the runoff change in the source area of the Yellow River can provide support for water management in the Yellow River Basin. This paper firstly uses a multiple linear regression method to evaluate the contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River. Next, the paper uses the Budyko hypothesis method to calculate the contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change of the Tangnaihai Hydrometric Station. The results showed that: (1) the annual runoff and precipitation in the source area of the Yellow River have a downward trend, while the annual potential evaporation and NDVI (Normalized Difference Vegetation Index) show an increasing trend; (2) The contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River is 62.79% and 37.21%, respectively; (3) The runoff change became more and more sensitive to changes in climate and underlying surface characteristic parameters; (4) The contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change at Tangnaihai Hydrological Station are 75.33% and 24.67%, respectively; (5) The impact of precipitation on runoff reduction is more substantial than that of potential evaporation.

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 612
Author(s):  
Guangxing Ji ◽  
Huiyun Song ◽  
Hejie Wei ◽  
Leying Wu

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.


Author(s):  
Deng Wang ◽  
Shengqi Jian ◽  
Zening Wu ◽  
Zhaoxi Zhang ◽  
Caihong Hu

Abstract. The runoff of the Fenhe River flowed into the Yellow River (RRY) is reducing significantly due to the influence of climate change and human activities. It is generating bad situation of shortage of water resources and led to the deterioration of ecological environment of Shanxi Province. At the same time, the reduction in RRY causes the runoff reduction in Yellow River and exacerbated the water resources shortage of the middle area of the Yellow River. Therefore, it is important to alleviate water shortage and develop the soil and water conservation measurements and regional water policy by analyzing the influence of human activities and climate change on the RRY. The existing study quantified the reduction in amount of RRY which caused by human activities and climate change using statistical methods and watershed hydrological model. The main results of the study were as follow: Using hydrological variation diagnosis system, the variation characteristics of long time series of measured annual runoff were analyzed in Hejin station that is the Fenhe River control station. The results showed that the runoff of Fenhe River run into Yellow River declined year by year, in 1971, fell the most obviously. The impact of LUCC on runoff was calculated using the method of area ratio in the Fenhe River basin. Human activities were major factor in the reduction of RRY than the climate change, contributed 83.09 % of the total reduction in RRY, Groundwater exploitation gave the greatest contribution to the decrease in RRY in the scope of several kinds of human activity (30.09 %), followed by coal mining (26.03 %), climate changed contributed 19.17 % of the total reduction of RRY, and the decrease of precipitation contributed 20.81 %. But the variation of air temperature and wind speed would result in the increase of the amount of RRY.


Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1237 ◽  
Author(s):  
Caihong Hu ◽  
Li Zhang ◽  
Qiang Wu ◽  
Shan-e-hyder Soomro ◽  
Shengqi Jian

Runoff reduction in most river basins in China has become a hotpot in recent years. The Gushanchuan river, a primary tributary of the middle Yellow river, Northern China, showed a significant downward trend in the last century. Little is known regarding the relative contributions of changing environment to the observed hydrological trends and response on the runoff generation process in its watershed. On the basis of observed hydrological and meteorological data from 1965–2010, the Mann-Kendall trend test and climate elasticity method were used to distinguish the effects of climate change and human activities on runoff in the Gushanchuan basin. The results indicate that the runoff in the Gushanchuan Basin has experienced significant declines as large as 77% from 1965 to 2010, and a mutation point occurred around 1997; the contribution rate of climate change to runoff change is 12.9–15.1%, and the contribution rate of human activities to runoff change is 84.9–87.1%. Then we divided long-term data sequence into two stages around the mutation point, and analyzed runoff generation mechanisms based on land use and cover changes (LUCC). We found that the floods in the Gushanchuan Basin were still dominated by Excess-infiltration runoff, but the proportion in 1965–1997 and 1998–2010 decreased gradually (68.46% and 45.83% in turn). The proportion of Excess-storage runoff and Mixed runoff has increased, which means that the runoff is made up of more runoff components. The variation law of the LUCC indicates that the forest area increased by 49.61%, the confluence time increased by 50.42%, and the water storage capacity of the watershed increased by 30.35%.


2014 ◽  
Author(s):  
Peng Li ◽  
Jianhua Xu ◽  
Zhongsheng Chen ◽  
Benfu Zhao

Based on the hydrological and meteorological data of the upper reaches of Shiyang River basin in Northwest China from 1960 to 2009, this paper analyzed the change in runoff and its related climatic factors, and estimated the contribution of climate change and human activity to runoff change by using the moving T test, cumulative analysis of anomalies and multiple regression analysis. The results showed that temperature revealed a significant increasing trend, and potential evaporation capacity decreased significantly, while precipitation increased insignificantly in the past recent 50 years. Although there were three mutations in 1975, 1990 and 2002 respectively, runoff presented a slight decreasing trend in the whole period. The contributions of climate change and human activity to runoff change during the period of 1976-2009 were 45% and 55% respectively.


2008 ◽  
Vol 21 (8) ◽  
pp. 1790-1806 ◽  
Author(s):  
Qiuhong Tang ◽  
Taikan Oki ◽  
Shinjiro Kanae ◽  
Heping Hu

Abstract A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow is more significantly affected by irrigation withdrawals than by climate change. Reservoirs induce more diversions for irrigation, while at the same time the results demonstrate that the reservoirs may help to maintain environmental flows and counter what otherwise would be more serious reductions in low flows.


2020 ◽  
Vol 9 (4) ◽  
pp. 282 ◽  
Author(s):  
Mingyue Wang ◽  
Jun’e Fu ◽  
Zhitao Wu ◽  
Zhiguo Pang

Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area.


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