The analytical derivation of multiple elasticities of runoff to climate change and catchment characteristics alteration

Wang, Weiguang; Zou, Songbing; Shao, Quanxi; Chen, Xi; Jiao, Xiyun; Luo, Yufeng; Yong, Bin; Yu, Zhongbo

doi:10.1016/j.jhydrol.2016.08.014

Cited by 90 publications

(72 citation statements)

References 56 publications

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“…In Figure a, Budyko curves with different values of parameter n describe the relations between long‐term evaporation ratio ( E / P ) and dryness index ( E 0 / P ) with reasonable accuracy. The elasticities of streamflow to precipitation and temperature (equations to ) in the northern China are generally greater than those in the southern China (Figure b), which is consistent with previous studies (Wang et al, ; Yang & Yang, ; Yang et al, ), indicating that streamflow change in dry regions is more sensitive to the changing climate than that in wet regions. In the northern China, including SHR, LR, HR, YR, and HuR, the elasticity coefficient of streamflow change to precipitation and temperature change for most catchments range between 2–5 and −5 to −1, respectively.…”

Section: Resultssupporting

confidence: 90%

“…This study deduced a four‐parameter climatic elasticity method (PnT) using the Budyko framework and simplified Makkink equation. The PnT method performs well for assessing the impacts of climate change to streamflow change and is similar to the three‐parameter climatic elasticity method (PnE) (Yang et al, , ) and the seven‐parameter climatic elasticity method (Pn5) (Wang et al, ). The PnT method generally was found to be more accurate than Pn5 but less accurate than PnE.…”

Section: Discussionmentioning

confidence: 99%

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Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

Liu

Zhang

et al. 2017

JGR Atmospheres

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Climatic elasticity has been widely applied to assess streamflow responses to climate changes. To fully assess impacts of climate under global warming on streamflow and reduce the error and uncertainty from various control variables, we develop a four‐parameter (precipitation, catchment characteristics n, and maximum and minimum temperatures) climatic elasticity method named PnT, based on the widely used Budyko framework and simplified Makkink equation. We use this method to carry out the first comprehensive evaluation of the streamflow response to potential climate change for 372 widely spread catchments in China. The PnT climatic elasticity was first evaluated for a period 1980–2000, and then used to evaluate streamflow change response to climate change based on 12 global climate models under Representative Concentration Pathway 2.6 (RCP2.6) and RCP 8.5 emission scenarios. The results show that (1) the PnT climatic elasticity method is reliable; (2) projected increasing streamflow takes place in more than 60% of the selected catchments, with mean increments of 9% and 15.4% under RCP2.6 and RCP8.5 respectively; and (3) uncertainties in the projected streamflow are considerable in several regions, such as the Pearl River and Yellow River, with more than 40% of the selected catchments showing inconsistent change directions. Our results can help Chinese policy makers to manage and plan water resources more effectively, and the PnT climatic elasticity should be applied to other parts of the world.

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Section: Resultssupporting

confidence: 90%

Section: Discussionmentioning

confidence: 99%

Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

Liu

Zhang

et al. 2017

JGR Atmospheres

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“…In the TP, climate change is considered as an important role in the degradation of the grassland and influences hydrological processes by altering the typical precipitation distribution and temperature fluctuation (J. Gao, Zhang, Liu, & Wang, ; Peng & Xu, ; W. G. Wang et al, ). The positive increment of precipitation projected in the future over the TP would benefit the recovery and conversation of the local grasslands (Y. G. Zhang et al, ).…”

Section: Discussionmentioning

confidence: 99%

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Lü

Wang

Shao

et al. 2018

Hydrological Processes

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Understanding climate change impacts on hydrological regime and assessing future water supplies are essential to effective water resources management and planning, which is particularly true for the Tibetan Plateau (TP), one of the most vulnerable areas to climate change. In this study, future climate change in the TP was projected for 2041–2060 by a high‐resolution regional climate model, RegCM4, under 3 representative concentration pathways (RCPs): 2.6, 4.5, and 8.5. Response of all key hydrological elements, that is, evapotranspiration, surface run‐off, baseflow, and snowmelt, to future climate in 2 typical catchments, the source regions of Yellow and Yangtze rivers, was further investigated by the variable infiltration capacity microscale hydrological model incorporated with a 2‐layer energy balance snow model and a frozen soil/permafrost algorithm at a 0.25°×0.25° spatial scale. The results reveal that (a) spatial patterns of precipitation and temperature from RegCM4 agree fairly well with the data from China Meteorological Forcing Dataset, indicating that RegCM4 well reproduces historical climatic information and thus is reliable to support future projection; (b) precipitation increase by 0–70% and temperature rise by 1–4 °C would occur in the TP under 3 RCPs. A clear south‐eastern–north‐western spatial increasing gradient in precipitation would be seen. Besides, under RCP8.5, the peak increase in temperature would approach to 4 °C in spring and autumn in the east of the TP; (c) evapotranspiration would increase by 10–60% in 2 source regions due to the temperature rise, surface run‐off and baseflow in higher elevation region would experience larger increase dominantly due to the precipitation increase, and streamflow would display general increases by more than 3% and 5% in the source regions of Yellow and Yangtze rivers, respectively; (d) snowmelt contributes 11.1% and 16.2% to total run‐off in the source regions of Yellow and Yangtze rivers, respectively, during the baseline period. In the source region of Yangtze River, snowmelt run‐off would become more important with increase of 17.5% and 18.3%, respectively, under RCP2.6 and RCP4.5 but decrease of 15.0% under RCP8.5.

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“…Physically based methods (e.g., Penman–Monteith equation) have been widely used to estimate PET around the world (Wang et al, ; H. Yang & Yang, ). However, these methods are constrained by dependence on numerous parameters (i.e., temperature, relative humidity, wind speed, and solar radiation), especially for mountainous regions (Córdova, Carrillo‐Rojas, Crespo, Wilcox, & Célleri, ; Moeletsi, Walker, & Hamandawana, ).…”

Section: Methodsmentioning

confidence: 99%

Quantifying the impacts of climate change and land use/cover change on runoff in the lowerConnecticut River Basin

Wang

Stephenson

2018

Hydrological Processes

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Climate change and land use and cover change (LUCC) have had great impacts on watershed hydrological processes. Although previous studies have focused on quantitative assessment of the impacts of climate change and human activities on decreasing run‐off change, few studies have examined regions that have significant increasing run‐off due to both climate variability and land cover change. We show that annual run‐off had a significant increasing trend from 1956 to 2014 in the U.S. lower Connecticut River Basin. Abrupt change point years of annual run‐off for four subbasins are detected by nonparametric Mann–Kendall–Sneyers test and reconfirmed by the double mass curve. We then divide the study period into 2 subperiods at the abrupt change point year in the early 1970s for each subbasin. The Choudhury–Yang equation based on Budyko hypothesis was used to calculate precipitation and potential evapotranspiration, and landscape elasticities of run‐off. The results show that the difference in mean annual run‐off between 2 subperiods for each subbasin ranged from 102 to 165.6 mm. Climate variations were the primary drivers of increasing run‐off in this region. Quantitative contributions of precipitation and potential evapotranspiration in all subbasins are 106.5% and −3.6% on average, respectively. However, LUCC contributed both positively and negatively to run‐off: −18.6%, −13.3%, and 10.1% and 9.9% for 4 subbasins. This may be attributed to historical LUCC occurring after the abrupt change point in each subbasin. Our results provide critical insight on the hydrological dynamics of north‐east tidal river systems to communities and policymakers engaged in water resources management in this region.

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The analytical derivation of multiple elasticities of runoff to climate change and catchment characteristics alteration

Cited by 90 publications

References 56 publications

Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

Deducing Climatic Elasticity to Assess Projected Climate Change Impacts on Streamflow Change across China

Hydrological projections of future climate change over the source region of Yellow River and Yangtze River in the Tibetan Plateau: A comprehensive assessment by coupling RegCM4 and VIC model

Quantifying the impacts of climate change and land use/cover change on runoff in the lowerConnecticut River Basin

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