Assessing the effect of climate natural variability in water resources evaluation impacted by climate change

Liu, Yanli; Zhang, Jianyun; Wang, Guoqing; Liu, Jiufu; He, Ronghai; Wang, Hongjie; Liu, Cuishan; Jin, Jian

doi:10.1002/hyp.9251

Cited by 13 publications

(7 citation statements)

References 37 publications

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“…Liu et al (2012) make the salient point that many climate change impact assessment studies start from the position that impacts are attributable to GHG-induced climate change only, and do not properly account for natural climatic variability. Using seven future climate projections derived from three GCMs and three emission scenarios, the impact of future climate change on water resources was estimated in terms of separating its contribution from natural climatic variability.…”

Section: Evidence For Climate Change Impacts On the Hydrological Cyclmentioning

confidence: 99%

Towards Adaptation of Water Resource Systems to Climatic and Socio-Economic Change

O’Connell

2017

Water Resour Manage

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Climate change is viewed as the major threat to the security of water supplies in most parts of the world in the coming decades, and the water resources literature continues to be dominated by impact and risk assessments based on the latest climate projections from General Circulation Models (GCMs). However, the evidence for anthropogenic changes in precipitation and streamflow records continues to be elusive which, together with the known high uncertainty in GCM ensemble projections, has led to the development of risk assessment methods which are not driven exclusively by GCMs. It is argued that a baseline risk assessment should retain the assumption of climatic stationarity, and be based on the modelling of observed interannual variability as a dominant process in determining water resource system reliability, augmented where justifiable by reliable information from GCMs. However, irrespective of what the climate does in the future, globalization and socio-economic changes are the major drivers for increases in water demand and threats to water security, as exemplified by the burgeoning economies of the BRIC and MINT countries, and the large population increases and economic growth seen in many developing countries. It is suggested that more attention needs to be paid to adaptation to socio-economic change which is arguably more predictable than climatic change, based on what is already known about population and economic growth, lifestyle changes and human choices. More focus is needed on economic analyses that can inform the major investments in water use efficiency measures which can deliver the water savings needed to avert widespread water scarcity. The effectiveness of water use efficiency measures is largely determined by (a) the potential of modern information technology to achieve more efficient water resources management and water use and (b) human responses and choices in the uptake of measures. To assess the potential efficiency gains, it is argued that water resource systems modelling needs to evolve to incorporate the human dimension more explicitly, through Coupled Human and Natural Systems (CHANS) modelling. A CHANS modelling framework is outlined which incorporates agent-based Water Resour Manage

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Section: Evidence For Climate Change Impacts On the Hydrological Cyclmentioning

confidence: 99%

Towards Adaptation of Water Resource Systems to Climatic and Socio-Economic Change

O’Connell

2017

Water Resour Manage

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“…They mainly aim on decomposition the GCMs, emission scenarios, downscaling method, hydrological model structure and parameter for simulation process (Kujawa et al 2020;Shi et al 2020;Keller et al 2019). Moreover, to investigate the role of the internal variability in the overall climate change uncertainty can provide more useful information to uncertainty estimating of simulation process and establish more comprehensive framework of uncertainty analysis (Liu et al 2012;Xue et al 2014;Yen et al 2014;Schindler et al 2015;Steinschneider et al 2015;Nerantzaki et al 2020). (Belcher et al 2005).…”

Section: Introductionmentioning

confidence: 99%

Estimating the role of climate internal variability and source of uncertainties in hydrological climate-impact projections

Cai

Liu

Zhu

et al. 2021

Preprint

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Hydrological climate-impact projections in future are limited by large uncertainties from various sources. Therefore, this study aimed to explore and estimate the sources of uncertainties involved in climate changing impacted assessment in a representative watershed of Northeastern China. Moreover, recent researches indicated that the climate internal variability (CIV) plays an important role in various of hydrological climate-impact projections. Six downscaled Global climate models (GCMs) under two emission scenarios and a calibrate Soil and Water Assessment Tool (SWAT) model were used to obtain hydrological projections in future periods. The CIV and signal-to-noise ratio (SNR) are investigated to analyze the the role of internal variability in hydrological projections. The results shows that the internal variability shows a considerable influence on hydrological projections, which need be partitioned and quantified particularly. Moreover, it worth noting the CIV can propagate from precipitation and ET to runoff projections through the hydrological simulation process. In order to partition the CIV and sources of uncertainties, the uncertainty decomposed frameworks based on analysis of variance (ANOVA) are established. The results demonstrate that the CIV and GCMs are the dominate contributors of runoff in rainy season. In contrast, the CIV and SWAT model parameter sets provided obvious uncertainty to runoff in January to May and October to December. The findings of this study advised that the uncertainty is complex in hydrological simulation process hence, it is meaning and necessary to estimate the uncertainty in climate simulation process, the uncertainty analysis results can provide effectively efforts to reduce uncertainty and then give some positive suggestions to stakeholders for adaption countermeasure under climate change.

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“…Additionally, at present, there are many studies regarding the climate change over major rivers in China (Li et al ., 2008; Zhang et al ., 2009; Bao et al ., 2012; Liu et al ., 2012; Wang, Zhang, et al, 2012; Wang, Sun, et al, 2012; Yin et al ., 2016). Most of them have used global climate models (GCMs), for example, based on five GCMs, Yin et al .…”

Section: Introductionmentioning

confidence: 99%

“…Additionally, at present, there are many studies regarding the climate change over major rivers in China (Li et al, 2008;Zhang et al, 2009;Bao et al, 2012;Liu et al, 2012;Wang, Sun, et al, 2012;Yin et al, 2016). Most of them have used global climate models (GCMs), for example, based on five GCMs, Yin et al (2016) indicated that the extreme precipitation over most of HHH river basin will increase considerable in the future, which will result in larger flood risk.…”

Section: Introductionmentioning

confidence: 99%

Changes of extreme climate events and related risk exposures in Huang‐Huai‐Hai river basin under 1.5–2°C global warming targets based on high resolution combined dynamical and statistical downscaling dataset

Han

et al. 2020

Intl Journal of Climatology

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Extreme climate events and related risk exposures in Huang‐Huai‐Hai (HHH) river basin were projected under global warming of 1.5–2°C using the high‐resolution combined dynamical and statistical downscaling dataset. Firstly, evaluation indicated that the dataset can well reproduce the spatial distribution of all temperature extremes and most of the precipitation extremes, providing a reliable ability for future projections. Then, projections showed that the hot events were projected to increase, while the cold events were projected to decrease substantially in the whole HHH river basin for 1.5°C and 2°C global warming. The additional 0.5°C of warming roughly accelerated the increase of extreme temperatures by 0.6°C, and increased the number of heat days by 2.7 days. In addition, the rainfall events and the precipitation intensity were projected to increase while the drought events were projected to decrease, with the slight changes due to the additional 0.5°C warming. The gross domestic product (GDP) exposures to heat events and heavy rainfall increased more than nine fold for 1.5°C and 2°C global warming, while the growing population (POP) exposures to that increased by more than 100% and 20%, respectively. For the increased exposures to heat events, the changes in GDP (POP) were as important as changes in interaction effect between climate and GDP (POP), while the exposures to heavy rainfall events was mainly dominated by GDP (POP). In addition, the enhanced interaction effect was the most important factor to the increase of exposures due to additional 0.5°C of warming. Notably, the largest increases of heat events and heavy rainfall events were projected in Huaihe river basin due to the additional 0.5°C warming, accompanied by greatest increase of exposures, implying larger risk in the future.

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Assessing the effect of climate natural variability in water resources evaluation impacted by climate change

Cited by 13 publications

References 37 publications

Towards Adaptation of Water Resource Systems to Climatic and Socio-Economic Change

Towards Adaptation of Water Resource Systems to Climatic and Socio-Economic Change

Estimating the role of climate internal variability and source of uncertainties in hydrological climate-impact projections

Changes of extreme climate events and related risk exposures in Huang‐Huai‐Hai river basin under 1.5–2°C global warming targets based on high resolution combined dynamical and statistical downscaling dataset

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