Exploring the Influence of Seasonal Cropland Abandonment on Evapotranspiration and Water Resources in the Humid Lowland Region, Southern China

Yan, Rong; Li, Lingling; Gao, Junfeng

doi:10.1029/2021wr031888

Cited by 10 publications

(4 citation statements)

References 71 publications

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“…In comparison, the regression relation between AET and T was the best, followed by Rs and the lowest of P, with an adjusted R 2 of 0.95, 0.88, and 0.61, respectively. It showed that AET in the TGRA was mainly affected by the temperature and radiation term, which is consistent with the conclusion of Yan et al [53].…”

Section: Correlation Analysissupporting

confidence: 91%

Spatiotemporal Variations in Actual Evapotranspiration Based on LPJ Model and Its Driving Mechanism in the Three Gorges Reservoir Area

Zhang,

Wang,

Wang

2023

Water

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Under the influence of climate change and human activities, the ecohydrological processes in the Three Gorges Reservoir Area (TGRA) present new evolution characteristics at different temporal and spatial scales. Research on the evolution and driving mechanism of key ecohydrological element in the TGRA under the changing environment has important theoretical and practical values for correctly understanding the ecohydrological situation in the reservoir area and guiding the coordinated development of water and soil resources. In this study, the LPJ (Lund–Potsdam–Jena) model was used to simulate and analyze the spatiotemporal variations in evapotranspiration (AET) from 1981 to 2020. Sen’s slope and sensitivity analysis methods were used to quantify individual contributions of climate and human factors to changes in AET in different periods. The results indicate the following: (1) The simulation accuracy of the LPJ model for AET in the TGRA was high, with a certainty coefficient (R2), Nash efficiency coefficient (NSE), and mean relative error (MRE) of 0.89, 0.76, and 4.32%, respectively. (2) The multiyear average AET was 650.71 mm and increased at a rate of 21.63 mm/10a from 1981 to 2020. The annual distribution of AET showed a unimodal seasonal variation trend. The peak value occurred in July, reaching 113.02 mm, and the valley value occurred in January and December, less than 13 mm. (3) AET increased by 5.60% and 6.28% before and after impoundment, respectively. The contribution rate of human activities increased significantly from −3.75% before impoundment to 26.95% after impoundment, and the contribution ratios of climate change were 89.39% and 73.09%, respectively, during these two periods. From 1981 to 2020, AET increased by 5.28%, in which the contribution ratios of climate and human factors were 89.39% and 10.61%, respectively.

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Section: Correlation Analysissupporting

confidence: 91%

Spatiotemporal Variations in Actual Evapotranspiration Based on LPJ Model and Its Driving Mechanism in the Three Gorges Reservoir Area

Zhang,

Wang,

Wang

2023

Water

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“…For investigating how the variation of CDHW events can be attributed to variations of its influencing factors, we employ path analysis to explore the response of CDHW events to the temperature and the WDI (i.e., difference between precipitation and PET), of which the selected two drivers are the most critical factors influencing CDHW events (Tomas‐Burguera et al., 2020; Y. Zhang, Hao, et al., 2022). Path analysis is an extension of multiple regression method that accounts for the covariance among variables, which has been widely applied to estimating the magnitude and significance of hypothesized causal connections between dependent and independent variables, when the effects of the variables are confounded (Saito et al., 2009; Smith et al., 1997; Yan et al., 2022). It has the superior advantage of decomposing the correlation coefficient into direct and indirect interaction coefficients, that is, direct path coefficient and indirect path coefficient relative to the commonly used regression method (Cheng et al., 2021; B. Zhang et al., 2016).…”

Section: Methodsmentioning

confidence: 99%

“…Zhang, Hao, et al, 2022). Path analysis is an extension of multiple regression method that accounts for the covariance among variables, which has been widely applied to estimating the magnitude and significance of hypothesized causal connections between dependent and independent variables, when the effects of the variables are confounded (Saito et al, 2009;Smith et al, 1997;Yan et al, 2022). It has the superior advantage of decomposing the correlation coefficient into direct and indirect interaction coefficients, that is, direct path coefficient and indirect path coefficient relative to the commonly used regression method (Cheng et al, 2021;B.…”

Section: Statistical Analysis Methodsmentioning

confidence: 99%

High Sensitivity of Compound Drought and Heatwave Events to Global Warming in the Future

et al. 2022

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Compound drought and heatwave (CDHW) events have received considerable attention in recent years due to their devastating effects on human society and ecosystem. In this study, we systematically investigated the changes of CDHW events in multi‐spatiotemporal scales for historical period (1951–2014) and four future scenarios (2020–2100) (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5) over global land by using Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The responses of the CDHW events to the changes of maximum air temperature and the climatic water balance variable are also examined. The results show that the multi‐model ensembles project a significant increasing trend in CDHW characteristics over almost all global lands under SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5, especially across northern North‐America, Caribbean, Mediterranean and Russian‐Arctic, there is a stronger increasing trend. A significantly increasing CDHW risk will occur across most global land for the medium to long term future without aggressive adaptation and mitigation strategies. The results of path analysis suggest that temperature is the dominant factor influencing CDHW events. Additionally, higher sensitivity of CDHW events to global warming will occur in the future. Particularly, each 1°C global warming increases the duration of the CDHW events by 3 days in the historical period, but by about 10 days in the future period. Overall, this study improves our understanding in the projection of CDHW events and the impacts of climate drivers to the CDHW events under various future scenarios, which could provide supports about the risk assessment, adaptation and mitigation strategies under climate change.

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“…Traditional field survey and measurement methods are time-consuming, laborious, costly, and easily affected by the natural environment, making it difficult to obtain data [21]. Simultaneously, the accuracy and representativeness of field-collected data also face challenges including subjectivity and spatial limitations [22]. In contrast, using remote sensing technology to obtain cropland monitoring data shows advantages.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Spatiotemporal Changes in Cropland Quantity and Quality with Multi-Source Remote Sensing

Liu,

Wang,

Sang

et al. 2023

Land

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Timely cropland information is crucial for ensuring food security and promoting sustainable development. Traditional field survey methods are time-consuming and costly, making it difficult to support rapid monitoring of large-scale cropland changes. Furthermore, most existing studies focus on cropland evaluation from a single aspect such as quantity or quality, and thus cannot comprehensively reveal spatiotemporal characteristics of cropland. In this study, a method for evaluating the quantity and quality of cropland using multi-source remote sensing-derived data was proposed and effectively applied in the black soil region in Northeast China. Evaluation results showed that the area of cropland increased significantly in the study area between 2010 and 2018, and the proportion of cropland increased by 1.17%. Simultaneously, cropland patches became larger and landscape connectivity improved. Most of the gained cropland was concentrated in the northeast and west, resulting in a shift in the gravity center of cropland to the northeast direction. Among land converted into cropland, unused land, grassland, and forest were the main sources, accounting for 36.38%, 31.47%, and 16.94% respectively. The quality of cropland in the study area generally improved. The proportion of low-quality cropland decreased by 7.17%, while the proportions of high-quality and medium-quality cropland increased by 5.65% and 5.17%, respectively. Specifically, the quality of cropland improved strongly in the east, improved slightly in the southwest, and declined in the north. Production capacity and soil fertility were key factors impacting cropland quality with obstacle degrees of 36.22% and 15.64%, respectively. Overall, the obtained results were helpful for a comprehensive understanding of spatiotemporal changes in cropland and driving factors and can provide guidance for cropland protection and management. The proposed method demonstrated promising reliability and application potential, which can provide a reference for other cropland evaluation studies.

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Exploring the Influence of Seasonal Cropland Abandonment on Evapotranspiration and Water Resources in the Humid Lowland Region, Southern China

Cited by 10 publications

References 71 publications

Spatiotemporal Variations in Actual Evapotranspiration Based on LPJ Model and Its Driving Mechanism in the Three Gorges Reservoir Area

Spatiotemporal Variations in Actual Evapotranspiration Based on LPJ Model and Its Driving Mechanism in the Three Gorges Reservoir Area

High Sensitivity of Compound Drought and Heatwave Events to Global Warming in the Future

Evaluation of Spatiotemporal Changes in Cropland Quantity and Quality with Multi-Source Remote Sensing

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