Comparison of Changing Population Exposure to Droughts in River Basins of the Tarim and the Indus

Wang, Anqian; Wang, Yanjun; Su, Buda; Kundzewicz, Zbigniew W.; Tao, Hui; Wen, Shanshan; Qin, Jiancheng; Gong, Yu; Jiang, Tong

doi:10.1029/2019ef001448

Cited by 31 publications

(26 citation statements)

References 32 publications

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“…The population distribution in the year 2000 and the future projections for 2061–2100 under scenarios SSP1, SSP2, SSP3, and SSP5 were used to estimate the future population exposure to different types of HWs in SA (https://www.cgd.ucar.edu/iam/modeling/spatial-population-scenarios.html) (Jones & O’Neill, 2016). The population datasets were resampled into 0.5° × 0.5° resolution to match the GCMs (A. Wang et al., 2020; Liu et al., 2020). The 2000 population distribution data were combined with the historical period’s data to estimate the historical exposure (Chen et al., 2020; Li et al., 2018).…”

Section: Methodsmentioning

confidence: 99%

Future Population Exposure to Daytime and Nighttime Heat Waves in South Asia

et al. 2022

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Climate change is expected to result in more frequent and intense heat waves (HWs) in South Asia (SA). The simultaneous increases in temperature and population will exacerbate the population exposure to future HWs. Here we estimate the future population exposure to daytime and nighttime HWs in SA using the Coupled Model Intercomparison Project 6 (CMIP6) models under four Shared Socioeconomic Pathways (SSPs) during 2061–2100, relative to 1975–2014. The results show that the projected frequency and spatial extent of the daytime (nighttime) HWs will be higher under scenario SSP5‐8.5, followed by SSP2‐4.5, SSP3‐7.0, and SSP1‐2.6 (SSP5‐8.5, followed by SSP3‐7.0, SSP2‐4.5, and SSP1‐2.6), relative to the historical period. The approach presented here allows decomposing the effects of climate change and future population on the overall exposure. The results reveal that the compounding effects of projected trends in population and HWs will significantly escalate the population exposure to HWs. Under the selected SSPs, the total population exposure to daytime and nighttime HWs ranges from 185 to 492 and 204–555 million people‐event, respectively, with the maximum exposure occurring in the Indo‐Gigantic Plain. The wide range of exposed populations highlights the sensitivity of the overall exposure to our future socioeconomic pathway decisions, emphasizing the importance of curbing anthropogenic greenhouse gas emissions and adopting sustainable urban planning solutions to minimize the potential socioeconomic and health impacts of HWs.

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Section: Methodsmentioning

confidence: 99%

Future Population Exposure to Daytime and Nighttime Heat Waves in South Asia

et al. 2022

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“…This formulation incorporates the effects of thermal and dynamic factors such as temperature, solar and infrared radiation, humidity, and wind speed variations on evapotranspiration [4,37]. Referring to the most recent IPCC report in 2021 and Wang conducted in the Tarim River Basin (arid regions) [8,41], SPEI values on a 12-month time scale are used to characterize drought in the present study and are calculated as below. In this case, the PET is calculated using the FAO Penman-Monteith (PM) formula [42], which is given by:…”

Section: Cmip6 Datamentioning

confidence: 99%

Projected Meteorological Drought over Asian Drylands under Different CMIP6 Scenarios

Chen

et al. 2021

Remote Sensing

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Asia currently has the world’s largest arid and semi-arid zones, so a timely assessment of future droughts in the Asian drylands is prudent, particularly in the context of recent frequent sandstorms. This paper assesses the duration, frequency, and intensity of drought events in the Asian drylands based on nine climate models of the Coupled Model Intercomparison Project Phase 6 (CMIP6). The results show that a high percentage of land area is experiencing significant drought intensification of 65.1%, 89.9%, and 99.8% under Shared Socioeconomic Pathways (SSP)126, SSP245, and SSP585 scenarios, respectively. Furthermore, the data indicate that future droughts will become less frequent but longer in duration and more intense, with even more severe future droughts predicted for northwest China and western parts of Uzbekistan and Kazakhstan. Drought durations of 10.8 months and 13.4 months are anticipated for the future periods of 2021–2060 and 2061–2100, respectively, compared to the duration of 6.6 months for the historical period (1960–2000). Meanwhile, drought intensity is expected to reach 1.37 and 1.66, respectively, for future events compared to 0.97 for the historical period. However, drought severity under SSP245 will be weaker than that under SSP126 due to the mitigating effect of precipitation. The results of this study can provide a basis for the development of adaptation measures in Asian dryland nations.

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“…Therefore, this BN trained from the yearly data may be more suitable for modelling variables that are sensitive to the annual hy-drological variation, because each hydrological year is considered to be independent in this BN. The evaluation of some long-term variables may require a further integration of the process models, such as the long-term trend of soil salinization below the root zone and the long-term melting trend of the upstream glaciers with its impacts on components and spatiotemporal processes of the runoff in these river basins (Liu et al, 2011;Wang et al, 2016). The lack of a more detailed description of causality may cause some detailed but important causality to be ignored, making it difficult for us to discover the differences between river basins.…”

Section: Discussionmentioning

confidence: 99%

A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins

Shi

Luo

Zheng

et al. 2021

Hydrol. Earth Syst. Sci.

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Abstract. The previous comparative studies on watersheds were mostly based on the comparison of dispersive characteristics, which lacked systemicity and causality. We proposed a causal structure-based framework for basin comparison based on the Bayesian network (BN) and focus on the basin-scale water–energy–food–ecology (WEFE) nexus. We applied it to the Syr Darya River basin (SDB) and the Amu Darya River basin (ADB), of which poor water management caused the Aral Sea disaster. The causality of the nexus was effectively compared and universality of this framework was discussed. In terms of changes in the nexus, the sensitive factor for the water supplied to the Aral Sea changed from the agricultural development during the Soviet Union period to the disputes in the WEFE nexus after the disintegration. The water–energy contradiction of the SDB is more severe than that of the ADB, partly due to the higher upstream reservoir interception capacity. It further made management of the winter surplus water downstream of the SDB more controversial. Due to this, the water–food–ecology conflict between downstream countries may escalate and turn into a long-term chronic problem. Reducing water inflow to depressions and improving the planting structure prove beneficial to the Aral Sea ecology, and this effect of the SDB is more significant. The construction of reservoirs on the Panj River of the upstream ADB should be cautious to avoid an intense water–energy conflict such as the SDB's. It is also necessary to promote the water-saving drip irrigation and to strengthen the cooperation.

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Comparison of Changing Population Exposure to Droughts in River Basins of the Tarim and the Indus

Cited by 31 publications

References 32 publications

Future Population Exposure to Daytime and Nighttime Heat Waves in South Asia

Future Population Exposure to Daytime and Nighttime Heat Waves in South Asia

Projected Meteorological Drought over Asian Drylands under Different CMIP6 Scenarios

A novel causal structure-based framework for comparing a basin-wide water–energy–food–ecology nexus applied to the data-limited Amu Darya and Syr Darya river basins

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