Spatiotemporal variation in reference evapotranspiration and its contributing climatic factors in China under future scenarios

Zhao, Jincai; Xia, Haibin; Yue, Qiulin; Wang, Zheng

doi:10.1002/joc.6429

Cited by 27 publications

(19 citation statements)

References 61 publications

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“…(6) The climate data in the future period are derived from the five global climate models (https://esgf-node.llnl.gov/search/cmip5/, accessed on 1 January 2021), including MIROC-ESM-CHEM, NorES1-M, IPSL-CM5A-LR, GFDL-ESM2M, and HadGEM2-ES (Table 1). These five models are widely used to assess China's future climate change [20,21]. Each global climate model includes daily mean temperature data, daily maximum temperature data, daily minimum temperature data and daily precipitation data under four RCP scenarios.…”

Section: Data Sourcesmentioning

confidence: 99%

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Lai

Xia

et al. 2021

Land

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The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

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Section: Data Sourcesmentioning

confidence: 99%

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Lai

Xia

et al. 2021

Land

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“…The Penman-Monteith (P-M) method is a fairly reliable method to estimate ET 0 , which considers radiative and aerodynamic terms [7]. It focuses on the meteorological factors controlling evaporation process and is widely used in numerous research [8,9]. Understanding the spatial-temporal changes in ET 0 and the main causes can provide considerable understanding into the impact of climatic variation on water resources and hydrological cycles [10].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Variation of Reference Evapotranspiration and Its Climatic Drivers over the Tibetan Plateau during 1970–2018

Gao

Zuyi

et al. 2021

Applied Sciences

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Reference evapotranspiration (ET0) is a key component of hydrologic cycle and it is important for water resources management. Analysis of ET0 changes is particularly critical for understanding the impacts of climatic change on hydrology in ecologically fragile regions. In this study, using the Penman–Monteith method and the Mann–Kendall test, the variation characteristics of ET0 on the Tibetan Plateau (TP) from 1970 to 2018 was analyzed, and the dominant climatic factors controlling the change of ET0 was also explored. The result shows that in TP region: (1) there was an abrupt change in the trend of ET0 around 1997, and the ET0 declined at a rate of −25.9 mm/decade during 1970–1996 but increased by 31.1 mm/decade during 1997–2018; (2) ET0 is most sensitive to solar radiation, then relative humidity, wind speed and mean temperature; (3) the decrease of ET0 before 1997 was mainly due to the decline of wind speed and the increase of relative humidity, while the increase of ET0 after 1997 was mainly due to the decrease of relative humidity. The results of this study can provide data reference for the research of water balance on the TP.

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“…And the largest increase of PET is expected to appear in summer, especially for Northwest and South China. This could be caused by a downward trend of relative humidity and an upward trend of air temperature (Zhao et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Projected Changes in Abrupt Shifts Between Dry and Wet Extremes Over China Through an Ensemble of Regional Climate Model Simulations

et al. 2020

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The dry-wet abrupt alternation (DWAA) event, which is defined as the phenomenon of dry (or wet) spells abruptly following wet (or dry) spells, magnifies the influence of individual wet and dry events. The dynamic evolution of DWAA events has not been studied for different climate zones of China that is particularly susceptible to dry and wet extremes. This study explores the future changes in the abrupt alternations between dry and wet extremes across 10 climate divisions of China, with a thorough assessment of dry and wet conditions using the Standardized Precipitation Evapotranspiration Index (SPEI). We take advantage of an ensemble of regional climate model simulations including the Providing Regional Climate Impacts for Studies (PRECIS) experiment and five CORDEX East Asia experiments to produce high-resolution climate information for a baseline period of 1975-2004 and a future period of 2069-2098. Our findings disclose that a total of 70% of China's land area suffered from the DWAA events at least once during 1975-2004. The wet-dry alternation event is projected to become more frequent in summer, and a prominent increase in the number of dry-wet alternation events is expected to occur in spring over most parts of China. Moreover, an increasing number of DWAA events with intensified magnitude is projected to strike the North China Plain dominated by warm temperature and humid zone, which is the most densely populated region of the country and is also the largest agriculture production area. Our findings also reveal a strong positive correlation between DWAA and heavy rainfall. The 95th percentile rainfall event contributes most to the wet-dry alternation event for most climate divisions of China. Plain Language Summary The emerging disaster of dry-wet abrupt alternation (DWAA) has been receiving increasing attention due to its compound effects on agricultural production and socioeconomic development. Since China is exposed to dry and wet hydrological extremes as well as their interconnections, a first attempt is made in this study to explore the historical evolution and the future change in the abrupt shifts between dry and wet extremes for different climate divisions of China. Our findings reveal that a total of 70% of China's land area suffered from DWAA events at least once from 1975 to 2004. More importantly, the DWAA is expected to occur more frequently and intense by the end of the 21st century, especially for the North China Plain which is the most densely populated region of the country and is also the largest agricultural production area. Moreover, the summertime wet-dry alternation is expected to become more frequent for most climate divisions of China, while the dry-wet alternation event is projected to occur more frequently in spring over East China. These findings provide meaningful insights into the development of adaptation strategies for enhancing society's resilience to compound extremes in a changing climate.

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Spatiotemporal variation in reference evapotranspiration and its contributing climatic factors in China under future scenarios

Cited by 27 publications

References 61 publications

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Future Runoff Variation and Flood Disaster Prediction of the Yellow River Basin Based on CA-Markov and SWAT

Spatio-Temporal Variation of Reference Evapotranspiration and Its Climatic Drivers over the Tibetan Plateau during 1970–2018

Projected Changes in Abrupt Shifts Between Dry and Wet Extremes Over China Through an Ensemble of Regional Climate Model Simulations

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