Quantifying the relative contribution of climate and human impacts on seasonal streamflow

Xin, Zhuohang; Yu, Li; Zhang, Lu; Ding, Wei; Ye, Lei; Wu, Jian; Zhang, Chi

doi:10.1016/j.jhydrol.2019.04.095

Cited by 59 publications

(29 citation statements)

References 68 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The study indicated that climate variability had more of an impact on streamflow than changes in land use. Xin et al [8] quantified the intra-annual changes that occurred in the streamflow of a basin that was suffering from significant anthropogenic influence on a seasonal scale. The results demonstrated that the decline in streamflow that is directly attributable to human activity is more pronounced during the irrigation season.…”

Section: Introductionmentioning

confidence: 99%

Hydrological Response to Natural and Anthropogenic Factors in Southern Taiwan

Yeh

Tsao

2020

Sustainability

View full text Add to dashboard Cite

Global climate change and rapid industrial development have led to changes in streamflow worldwide, and determining the relative contributions from climate variability and human activity is important for water management. However, studies using attribution analysis to investigate the streamflow in Taiwan are scarce. In this study, statistical methods are used to evaluate the changes in streamflow in order to assess the variation in the hydrological environment of Taiwan. Four river basins in Southern Taiwan were selected as the study area. The impact of climate variability and human activities on the changes in the streamflow from 1980 to 2017 was quantified via the hydrological sensitivity-based method and the decomposition method, which is based on the Budyko hypothesis. The results from these two methods were consistent and demonstrated that the increase in the streamflow of the four river basins was mainly attributable to climate variability. Streamflow change was more responsive to precipitation because of the relatively larger value of the sensitivity coefficients. This study provides a basic insight into the hydrological dynamics of river basins in Southern Taiwan and may serve as a reference for related research in the future.

show abstract

Section: Introductionmentioning

confidence: 99%

Hydrological Response to Natural and Anthropogenic Factors in Southern Taiwan

Yeh

Tsao

2020

Sustainability

View full text Add to dashboard Cite

show abstract

“…CC BY 4.0 License. Xiangyu et al, 2020;Song et al, 2020;Sinha et al, 2020;Li et al, 2020d;Li et al, 2020a;Deng et al, 2020;Zhang et al, 2019a;Young et al, 2019;Xin et al, 2019;Wang et al, 2019;Lv et al, 2019;Liu et al, 2019c;Lee and Yeh, 2019;Kazemi et al, 2019;He et al, 2019c;He et al, 2019b;He et al, 2019a;Wang et al, 2018;Xu et al, 2014). We argue and demonstrate herein that the two widely accepted parametric Budyko equations are non-unique, meaning they are only two of many possible single-parameter Budyko equations.…”

Section: Introductionmentioning

confidence: 59%

“…et al, 2018b; Li et al, 2018;Xiangyu et al, 2020) and multiple methods for decomposing anthropogenic and climatic impacts on rainfall partitioning (Wang and Hejazi, 2011;Xing et al, 2018b;Jaramillo et al, 2018;Mo et al, 2018;Sun et al, 2014;Jiang et al, 2015;Liang et al, 2015;Huang et al, 2016;Zhang et al, 2020;Yeh and Tsao, 2020;Xiangyu et al, 2020;Song et al, 2020;Sinha et al, 2020;Li et al, 2020d;Li et al, 2020a;Deng et al, 2020;Zhang et al, 2019a;Young et al, 2019;Xin et al, 2019;Wang et al, 2019;Lv et al, 2019;Liu et al, 2019c;Lee and Yeh, 2019;Kazemi et al, 2019;He et al, 2019c;He et al, 2019b;He et al, 2019a;Wang et al, 2018;Xu et al, 2014). Additionally, these interpretations have led numerous studies to pursue predictive relationships for the catchment-specific parameter based on various biophysical features ( Table S1 in the Supplemental Information) (Yang et al, 2007;Donohue et al, 2012;Yang et al, 2009;Shao et al, 2012;Li et al, 2013;Xu et al, 2013;Cong et al, 2015;Yang et al, 2016;…”

Section: Current Interpretations Of Explicit Budyko Curves and The Pamentioning

confidence: 99%

“…This interpretation has motivated profound efforts to understand the relationship between biophysical features and catchment-specific parameters (Yang et al, 2007;Donohue et al, 2012;Yang et al, 2009;Shao et al, 2012;Li et al, 2013;Xu et al, 2013;Cong et al, 2015;Yang et al, 2016;Zhang et al, 2018;Abatzoglou and Ficklin, 2017;Xing et al, 2018a;Zhao et al, 2020;Ning et al, 2020b;Li et al, 2020c;Li et al, 2020b;Zhang et al, 2019b;Ning et al, 2019;Bai et al, 2019). Numerous studies have also focused on determining the sensitivity of rainfall partitioning to climatic and/or land use changes (Roderick and Farquhar, 2011;Wang and Hejazi, 2011;Yang and Yang, 2011;Wang et al, 2016b;Zhou et al, 2016;Shen et al, 2017;Zhang et al, 2016;Yeh and Tsao, 2020;Zhang et al, 2020;Sinha et al, 2020;Ning et al, 2020b;Liu et al, 2020;Li et al, 2020e;Li et al, 2020a;Liu et al, 2019a;Li et al, 2019;Yang et al, 2018;Xing et al, 2018b;Li et al, 2018;Xiangyu et al, 2020), as well as on deriving causal attribution to changes in this partitioning (Wang and Hejazi, 2011;Xing et al, 2018b;…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reinterpreting the Budyko Framework

Reaver¹,

Kaplan²,

Klammler³

et al. 2020

Preprint

View full text Add to dashboard Cite

Abstract. The Budyko framework posits that a catchment's long-term mean evapotranspiration (E) is primarily governed by the availabilities of water and energy, represented by long-term mean precipitation (P) and potential evapotranspiration (E0), respectively. This assertion is supported by the distinctive clustering pattern that catchments take in Budyko space. Several semi-empirical, non-parametric curves have been shown to generally represent this clustering pattern but cannot explain deviations from the central tendency. Parametric Budyko equations attempt to generalize the non-parametric framework, through the introduction of a catchment-specific parameter (n or w). Prevailing interpretations of Budyko curves suggest that the explicit functional forms represent trajectories through Budyko space for individual catchments undergoing changes in aridity index, (E0/P), while n and w values represent catchment biophysical features; however, neither of these interpretations arise from the derivation of the Budyko equations. In this study, we re-examine, reinterpret, and test these two key components of the current Budyko framework both theoretically and empirically. In our theoretical test, we use a biophysical model for E to demonstrate that n and w values can change without invoking changes in landscape biophysical features and that catchments are not required to follow Budyko curve trajectories. Our empirical test uses data from 728 reference catchments in the United Kingdom and United States to illustrate that catchments rarely follow Budyko curve trajectories and that n and w are not transferable between catchments or across time for individual catchments. This non-transferability implies n and w are proxy variables for E/P, rendering the parametric Budyko equations under-determined and lacking of predictive ability. Finally, we show that the parametric Budyko equations are non-unique, suggesting their physical interpretations are unfounded. Overall, we conclude that, while the shape of Budyko curves generally captures the global behavior of multiple catchments, their specific functional forms are arbitrary and not reflective of the dynamic behavior of individual catchments.

show abstract

“…Previous research has indicated that anthropogenic activities and climate change have changed the water cycle in many catchments globally [16,17]. A number of approaches have been applied to evaluate the impacts of climate change and human interactions on runoff changes [14,18,19]. To analyze the individual impact of the two drivers in runoff, it is most important to identify the abrupt change point (time) of these influences.…”

Section: Introductionmentioning

confidence: 99%

Impacts of Climate Change and Human Activities on Runoff Variation of the Intensive Phosphate Mined Huangbaihe River Basin, China

Dong

Li³

et al. 2019

Water

View full text Add to dashboard Cite

Natural hydrological processes have been changed under the combined influences of climate change and intensive human activities in the Huangbaihe River Basin, where large-scale phosphate mining has been taking place. Therefore, evaluating the impact of climate change and intensive human activities on runoff variation and detecting the main driving factor leading to the variation are important for more efficient water resource management and more sustainable development of the regional economy. Despite numerous studies having been performed on this topic, little research focused on the impact of mining on runoff variation. The non-parametric Mann-Kendall (MK) trend test and accumulative anomaly methods were applied to identifying basic trends and change points of the hydro-meteorological elements over the period from 1978 to 2016. Then, the Soil Water and Assessment Tool (SWAT) and the Slope Changing Ratio of Accumulative Quantity (SCRAQ) were both used to quantify the contributions of climate change and anthropogenic activities on runoff variation. In this step, the runoff data were restored to their natural state before the construction of Xuanmiaoguan (XMG) dam. Due to the lack of locally observed evapotranspiration data, Global Land Evaporation Amsterdam Model and an empirical equation applied to obtain the evapotranspiration data. The results revealed that the change points are in 1985 and 2006. Therefore, the total period was divided into three periods, that is, the baseline period Ta (1978–1984), change period Tb (1985–2005) and change period Tc (2006–2016). Compared with the baseline period Ta, climate change dominates the runoff variation in the period Tb and is responsible for 60.5 and 74.4% of runoff variation, while human activities contribute the most to runoff variation for the period Tc (79.3 and 86.1%). Furthermore, an analysis of the underlying mechanism of underground phosphate mining indicates that mining can affect overland flow and baseflow simultaneously. This study can provide some information in determining the contributions of climate change and human activities in intensive phosphate mined basins and areas lack of evapotranspiration data.

show abstract

Quantifying the relative contribution of climate and human impacts on seasonal streamflow

Cited by 59 publications

References 68 publications

Hydrological Response to Natural and Anthropogenic Factors in Southern Taiwan

Hydrological Response to Natural and Anthropogenic Factors in Southern Taiwan

Reinterpreting the Budyko Framework

Impacts of Climate Change and Human Activities on Runoff Variation of the Intensive Phosphate Mined Huangbaihe River Basin, China

Contact Info

Product

Resources

About