Future river basin health assessment through reliability-resilience-vulnerability: Thresholds of multiple dryness conditions

Zeng, Peng; Sun, Fengyun; Liu, Yaoyi; Che, Yue

doi:10.1016/j.scitotenv.2020.140395

Cited by 33 publications

(17 citation statements)

References 75 publications

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“…GCMs are essential tools for environmental applications, including landscape analysis (Guan et al ., 2020; Lu et al ., 2020; Guan et al ., 2021), environmental monitoring (Huang et al ., 2014; Sun et al ., 2019; Zeng et al ., 2020), and climate change adaptation (Kawamiya et al ., 2020; Bai et al ., 2021; Heidari et al ., 2021). The direct use of climate variables such as temperature and precipitation can be suboptimal for many environmental studies.…”

Section: Discussionmentioning

confidence: 99%

Towards better characterization of global warming impacts in the environment through climate classifications with improved global models

Navarro

Merino

Sánchez

et al. 2022

Intl Journal of Climatology

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Climate classifications are useful to synthesize the physical state of the climate with a proxy that can be directly related to biota. However, they present a potential drawback, namely a strong sensitivity because of the use of hard thresholds (step functions). Thus, minor discrepancies in the base data produce large differences in the type of climate. However, such an a priori limitation is also a strength because such sensitivity can be used to better gauge model performance. Although previous attempts of classifying climates of the world using global climate model outputs were encouraging, the applicability of their classifications to impact studies has been limited by past model issues. Notwithstanding the persistence of certain imperfections and limitations in current models, the high‐quality physical simulations from phase six of the Coupled Intercomparison Project (CMIP6) has opened new possibilities in the field, thanks to their improved representation of atmospheric and oceanic physics. The purpose of this paper is twofold: to show that climate classifications from CMIP6 are sufficiently robust for use in impact studies, and to use those classifications for identifying error sources and potential issues that deserve further attention in models. Thus, 52 CMIP6 climate models were evaluated by using three climate classifications schemes, classical Köppen, extended‐Köppen, and modified Thornthwaite. We first assessed model ability to reproduce present climate types by comparing their outputs with observational data. Models performed best for the Köppen and extended‐Köppen classification methods (Cohen's kappa κ = 0.7), and had moderate scores for the Thornthwaite climate classification (κ = 0.4). By tracing back the observed biases, we were able to pinpoint the misrepresentation of dry climates as a major source of error. Another finding was that most models still had some difficulties in representing the seasonal variability of precipitation over several monsoonal regions, thereby yielding the wrong climate type there. Models were also evaluated for future climate. Substantial changes in climate types are projected in the SSP5‐8.5 scenario. These changes include a shrinkage of polar/frigid climates (22%) and an increase of dry climates (7%).

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Section: Discussionmentioning

confidence: 99%

Towards better characterization of global warming impacts in the environment through climate classifications with improved global models

Navarro

Merino

Sánchez

et al. 2022

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…These metrics were introduced by [8] and complement each other, as each criterion evaluates different aspects of water resource systems [7]. That said, climate change, extreme events, and the impacts on the performance of reservoirs using the RRV have been the subject of several studies [9][10][11].…”

Section: Of 25mentioning

confidence: 99%

“…Among these studies, the work of [9] combine the 3-and 12-month standard precipitation evapotranspiration index (SPEI) and framework RRV to map future river basin health based on the responses of basins across China to different dryness conditions from 2021 to 2050.…”

Section: Of 25mentioning

confidence: 99%

Impact of Climate Change and Consumptive Demands on the Performance of São Francisco River Reservoirs, Brazil

Silva¹,

Lima²,

Silveira³

2023

Preprint

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Climate change in the coming decades could intensify extreme events such as severe droughts. Combined with the possible increase of water demands, these changes exert a large pressure on the water systems. In order to confirm this assumption, a set of scenarios was proposed in this study to consider the combined impact of climate changes and the increase in water demand on the main multiple-use reservoirs of São Francisco River, Brazil. For this purpose, five CMIP6 climate models were used considering two greenhouse gas emissions scenarios: the SSP2-4.5 and SSP5-8.5. The naturalized and withdraw streamflows were estimated to the adopted reser-voirs considering all existing, new and projected demands. The conjunction of scenarios indicat-ed an increase in Potential Evapotranspiration, a possible significant reduction in water availa-bility, a growth in water demand mainly for irrigation and a substantial reduction in the perfor-mance of the evaluated reservoirs.

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“…Van Loon (2015) used the threshold level method to define a drought event, and either a fixed or a variable threshold can be used. As standard in many drought impact assessments (AghaKouchak, 2014;Burke & Brown, 2008;Zeng et al, 2020), we use thresholds corresponding to the 20th percentile of the observed SPI or SPEI time series. The 20th percentile of the standardized index belongs to the "mild drought" classification according to McKee et al (1993), Paulo et al (2012), andWorld Meteorological Organization (2012).…”

Section: Evaluation Metrics Of Drought To Assess Model Performancementioning

confidence: 99%

Do Derived Drought Indices Better Characterize Future Drought Change?

2023

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Droughts, the costliest natural disaster known to humanity, have a substantial impact on the economy, society, and environment. A recent example was the drought-induced megafires in 2019-2020 across Australia, which destroyed around 5.8 million hectares of forests, millions of wild animals and 33 human deaths (Boer et al., 2020). It is well acknowledged that rising temperatures intensify the global hydrological cycle (Milly et al., 2002). With projected increases in global temperatures, it is now generally agreed that these extremes events are likely to become more frequent and intense (IPCC, 2014). Many other factors, including a growing population, contamination of surface water and groundwater resources, and an increasing water demand resulting from agricultural activities leading to increased evapotranspiration (Zou et al., 2017), have led to rising water scarcity around the world (Boretti & Rosa, 2019).Understanding the vulnerability of these systems to climate variability has traditionally been achieved by assuming that past hydrological extremes will occur again in the future, an assumption that is no longer tenable due to anthropogenic climate change. Assessing the risks of future sustained hydrological anomalies (e.g., droughts) is generally based on general circulation model (GCM) simulations of precipitation, temperature, and soil moisture. However, climate model simulations of these variables exhibit significant biases at a range of time scales and thus have varying abilities to represent sustained climate anomalies (Johnson et al., 2011). Droughts are caused by the interplay of several climatic factors, such as sustained low precipitation, high temperature, strong winds,

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Future river basin health assessment through reliability-resilience-vulnerability: Thresholds of multiple dryness conditions

Cited by 33 publications

References 75 publications

Towards better characterization of global warming impacts in the environment through climate classifications with improved global models

Towards better characterization of global warming impacts in the environment through climate classifications with improved global models

Impact of Climate Change and Consumptive Demands on the Performance of São Francisco River Reservoirs, Brazil

Do Derived Drought Indices Better Characterize Future Drought Change?

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