scholarly journals Attribution of climate change and human activities to streamflow variations with a posterior distribution of hydrological simulations

2021 ◽  
Author(s):  
Xiongpeng Tang ◽  
Guobin Fu ◽  
Silong Zhang ◽  
Chao Gao ◽  
Guoqing Wang ◽  
...  

Abstract. Hydrological simulations are a main method of quantifying the contribution rate (CR) of climate change (CC) and human activities (HAs) to watershed streamflow changes. However, the uncertainty of hydrological simulations is rarely considered in current research. To fill this research gap, based on the Soil and Water Assessment Tool (SWAT) model, in this study, we propose a new framework to quantify the contribution rate of climate change and human activities based on the posterior histogram distribution of hydrological simulations. In our new quantitative framework, the uncertainty of hydrological simulations is first considered to avoid the phenomenon of "equifinality for different parameters", which is common in hydrological simulations. The Lancang River (LR) Basin in China, which has been greatly affected by human activities in the past two decades, is then selected as the study area. The global gridded monthly sectoral water use data set (GMSWU), coupled with the dead capacity data of the large reservoirs within the LR basin and the Budyko hypothesis framework, are used to compare the calculation result of the novel framework. The results show that (1) the annual streamflow at Yunjinghong station in the Lancang River Basin changed abruptly in 2005, which was mainly due to the construction of the Xiaowan hydropower station that started in October 2004. The annual streamflow and annual mean temperature time series from 1961 to 2015 in the LR Basin showed a significant decreasing and increasing trend at the α = 0.01 significance level, respectively. The annual precipitation showed an insignificant decreasing trend. (2) The results of quantitative analysis using the new framework showed that the reason for the decrease in the streamflow at Yunjinghong station was 42.6 % due to climate change, and the remaining 57.4 % was due to human activities, such as the construction of hydropower stations within the study area. (3) The comparison with the other two methods showed that the contribution rate of climate change calculated by the Budyko framework and the GMSWU data were 37.2 % and 42.5 %, respectively, and the errors of the calculations of the new framework proposed in this study were within 5 %. Therefore, the newly proposed framework, which considers the uncertainty of hydrological simulations, can accurately quantify the contribution rate of climate change and human activities to streamflow changes. (4) The quantitative results calculated by using the simulation results with the largest Nash-Sutcliffe efficiency coefficient (NSE) indicated that climate change was the dominant factor for streamflow reduction, which was in opposition to the calculation results of our new framework. In other words, our novel framework could effectively solve the calculation errors caused by the “equifinality for different parameters” of hydrological simulations. (5) The results of this case study also showed that the reduction in the streamflow in June and November was mainly caused by decreased precipitation and increased evapotranspiration, while the changes in the streamflow in other months were mainly due to human activities such as the regulation of the constructed reservoirs. In general, the novel quantitative framework that considers the uncertainty of hydrological simulations presented in this study has validated an efficient alternative for quantifying the contribution rate of climate change and human activities to streamflow changes.

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Hendri Irwandi ◽  
Mohammad Syamsu Rosid ◽  
Terry Mart

AbstractThis research quantitatively and qualitatively analyzes the factors responsible for the water level variations in Lake Toba, North Sumatra Province, Indonesia. According to several studies carried out from 1993 to 2020, changes in the water level were associated with climate variability, climate change, and human activities. Furthermore, these studies stated that reduced rainfall during the rainy season due to the El Niño Southern Oscillation (ENSO) and the continuous increase in the maximum and average temperatures were some of the effects of climate change in the Lake Toba catchment area. Additionally, human interventions such as industrial activities, population growth, and damage to the surrounding environment of the Lake Toba watershed had significant impacts in terms of decreasing the water level. However, these studies were unable to determine the factor that had the most significant effect, although studies on other lakes worldwide have shown these factors are the main causes of fluctuations or decreases in water levels. A simulation study of Lake Toba's water balance showed the possibility of having a water surplus until the mid-twenty-first century. The input discharge was predicted to be greater than the output; therefore, Lake Toba could be optimized without affecting the future water level. However, the climate projections depicted a different situation, with scenarios predicting the possibility of extreme climate anomalies, demonstrating drier climatic conditions in the future. This review concludes that it is necessary to conduct an in-depth, comprehensive, and systematic study to identify the most dominant factor among the three that is causing the decrease in the Lake Toba water level and to describe the future projected water level.


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%.


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 ◽  
Author(s):  
Yanwen Wang

Net primary productivity (NPP) is an essential indicator of ecosystem function and sustainability and plays a vital role in the carbon cycle, especially in arid and semi-arid grassland ecosystems. Quantifying trends in NPP and identifying the contributing factors are important for understanding the relative impacts of climate change and human activities on grassland degradation. We quantified spatial and temporal patterns in potential NPP (NPPP) and actual NPP (NPPA) in Kyrgyzstan from 2000 to 2014 based on the Zhou Guangsheng model and MOD17A3 NPP data, respectively. By calculating the difference between NPPP and NPPA, we inferred human-induced NPP (NPPH) and thereby characterised changes in grassland NPP attributable to anthropogenic activities. We found that over the past two decades, both climatic variation and anthropogenic activities have significantly affected Kyrgyzstan’s grasslands. Grassland NPP decreased overall but patterns varied between provinces. Climate change, in particular changes in precipitation was the dominant factor driving grassland degradation in the north but human pressures also contributed. In the south however, human activities were associated with extensive areas of grassland recovery. The results provide important contextual understanding for supporting policy for grassland maintenance and restoration under climate change and intensifying human pressures.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2001 ◽  
Author(s):  
Lee ◽  
Yeh

In recent years, the influence of climate change and human activity on the global environment have become a concern. It is essential to better understand the hydrologic environment to evaluate water availability and related issues. In this study, we perform a trend and breakpoint analysis on streamflow time series in the Lanyang, Keelung, Dahan, Fengshan, Youluo and Shangping River Basins in northern Taiwan. Furthermore, we apply the Budyko–Fu equation and the Budyko–Mezentsev–Choudhury–Yang equation to evaluate the elasticity of streamflow with respect to climate factors and the catchment characteristics parameter. We discuss the sensitivity of streamflow to climate factors (precipitation and potential evapotranspiration), as well as sensitivity to human activities such as land use changes. We detected breakpoints in the streamflow time series for the Lanyang and Keelung rivers in in 1993 and 1990, respectively. The streamflow of Lanyang River increased by 32.50% during the variation period (1993–2017), with 109.00% of the variation caused by non-climate factors. The Keelung River’s streamflow was reduced by 18.11% during the variation period (1990–2017), and the dominant factor was climate change, accounting for 71.53% of the reduction. Sensitivity analysis showed that precipitation changes were the most sensitive factor of streamflow variation. For every 1% increase in precipitation, the streamflow would increase by 1.05% to 1.37%. These results could serve as a reference for the sustainable development of water resources and territorial policies in northern Taiwan.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 622 ◽  
Author(s):  
Xing Mu ◽  
Hao Wang ◽  
Yong Zhao ◽  
Huan Liu ◽  
Guohua He ◽  
...  

Streamflow is likely affected by climate change and human activities. In this study, hydro-meteorological data from six rivers upstream of Beijing, namely, the Yongdinghe, Baihe, Heihe, Chaohe, Juhe, and Jumahe Rivers, were analyzed to quantify the spatial and temporal variability of streamflow and their responses to climate change and human activities over the period of 1956–2016. The Mann–Kendall test and moving t-test were used to detect trends and changing points of the annual streamflow. Results showed that the streamflow into Beijing experienced a statistically significant downward trend (p < 0.05), abruptly changing after the early 1980s, owing to climate and human effects. The climate elasticities of the streamflow showed that a 10% decrease in precipitation would result in a 24.5% decrease in total streamflow, whereas a 10% decrease in potential evapotranspiration would induce a 37.7% increase in total streamflow. Human activities accounted for 87% of the reduction in total streamflow, whereas 13% was attributed to climate change. Lastly, recommendations are provided for adaptive management of water resources at different spatial scales.


Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2892
Author(s):  
Zhibo Xie ◽  
Xingmin Mu ◽  
Peng Gao ◽  
Changxue Wu ◽  
Dexun Qiu

Quantitatively assessing the characteristics of river streamflow variation and conducting research on attribution identification are the basis for formulating climate-change response strategies and rational use of water resources. Based on the daily streamflow data of the Zhuangtou Hydrological Station in 1970–2018, this paper analyzes the streamflow changes in the Beiluo River Basin and studies the impact of climate change and anthropogenic activities on the streamflow in this basin. A non-parametric Mann–Kendall test and Pettitt’s test were used to determine the trend and detect abrupt changes of streamflow and baseflow. The method based on precipitation and potential evapotranspiration, as well as the double-mass curve of precipitation–streamflow, was established to evaluate the impact of climate change and non-climate factors on annual streamflow. The results reveal a statistically significant downward trend (p = 0.01) in both annual streamflow and baseflow, with the abrupt point year in 1994 and 1988, respectively. When comparing to a modest declining trend in annual average precipitation, we see that the temperature showed a significant upward trend (p = 0.01), whose abrupt point year was 1996. Under the policy of returning farmland to forest, land-use analysis shows that the area of farmland had decreased by 222.4 km2, of which 31.4% was mainly converted into the forestland. By the end of 2015, the area of forestland had increased by 123.4 km2, which has largely caused streamflow decrease. For the method based on precipitation and potential evapotranspiration, climate change contributed 43.7% of the annual streamflow change, and human activities (mainly refers to LUCC) contributed 56.3%. For the DMC of precipitation–streamflow, the precipitation contributed 9.4%, and non-precipitation factors (mainly refers to human activities) contributed 90.6%, and human activities played a more vital part in driving streamflow reduction in different decades, with a contribution rate of more than 70%. This study is of great practical significance to the planning, management, development and utilization of water resources in basins.


2020 ◽  
Vol 12 (3) ◽  
pp. 912
Author(s):  
Yongcai Dang ◽  
Hongshi He ◽  
Dandan Zhao ◽  
Michael Sunde ◽  
Haibo Du

Climate change and human activities are important factors driving changes in wetland ecosystems. It is therefore crucial to quantitatively characterize the relative importance of these stressors in wetlands. Previous such analyses have generally not distinguished between wetland types, or have focused on individual wetland types. In this study, three representative wetland areas of the upper, middle and lower reaches of the Heilongjiang River Basin (HRB) were selected as the study area. An object-based classification was used with Landsat TM data to extract the spatial distribution of wetland in 1990, 2000 and 2010. We then quantified the relative importance of climate change and human activities on the wetlands by using the R package “relaimpo” package. The results indicated that: (1) the effects of human activities on wetland changes were greater (contribution rate of 63.57%) than climate change in the HRB. Specifically, there were differences in the relative importance of climate change and human activities for wetlands in different regions. Wetlands of the upper reaches were more affected by climate change, while wetlands in the middle and lower reaches were more affected by human activities; (2) climate change had a greater impact (contribution rate of 65.72%) on low intensity wetland loss, while human activities had a greater impact on moderate and severe intensity wetland loss, with respective contribution rates of 57.22% and 70.35%; (3) climate change had a larger effect on the shrub and forested wetland changes, with respective contribution rates of 58.33% and 52.58%. However, human activities had a larger effect on herbaceous wetland changes, with a contribution rate of 72.28%. Our study provides a useful framework for wetland assessment and management, and could be a useful tool for developing wetland utilization and protection approaches, particularly in sensitive environments in mid- and high-latitude areas.


Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3501
Author(s):  
Hao Liu ◽  
Zheng Wang ◽  
Guangxing Ji ◽  
Yanlin Yue

Based on the Lancang River Basin (LRB) hydro–meteorological data from 1961 to 2015, this study uses the Mann–Kendall trend test and mutation test to analyze the trend of hydro–meteorological variables, as well as which year the runoff series changes, respectively. We applied the Choudhury–Yang equation to calculate the climate and catchment landscape elasticity of runoff. Then we quantified the impact of climate change and human activities on runoff change. The results show that: (1) the mean annual precipitation (P) in LRB showed an insignificant decline, the annual potential evapotranspiration (E0) showed a significant increase, and the runoff depth (R) showed a significant decrease; (2) the abrupt change of the R occurred in 2005. Both the climate and catchment landscape elasticity of runoff increased, which means that the hydrological process of LRB became more sensitive to climate changes and human activities; (3) compared with the base period (1961–2004), the reduction of P was the leading cause of runoff reduction, with a contribution of 45.64%. The contribution of E0 and human activities to runoff changes are 13.91% and 40.45%, respectively.


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