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Data Details

Dataset on Drought Trends and Carbon Flux in the Lancang-Mekong River Adjacent Region (2000-2019)


CHEN Shiliang1 CHEN Shiliang2 LI Xia3 QIAN Zhaohui3 WANG Shaoqiang*1,2,4,5 WANG Miaomiao6 LIU Zhenhai5
1 Hubei Key Laboratory of Regional Ecology and Environmental Change，School of Geography and Information Engineering，China University of Geosciences，Wuhan 430074，China2 Engineering Technology Innovation Center for Intelligent Monitoring and Spatial Regulation of Land Carbon Sinks，Ministry of Natural Resources，Wuhan 430074，China3 Foreign Environmental Cooperation Center，Ministry of Ecology and Environment，Beijing 100035，China4 State Key Laboratory of Biogeology and Environmental Geology，China University of Geosciences，Wuhan 430074，China5 Key Laboratory of Ecosystem Network Observation and Modeling，Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China6 Institute of Digital Agriculture，Fujian Academy of Agricultural Sciences，Fuzhou 350000，China

DOI:10.3974/geodb.2024.04.10.V1

Published:Apr. 2024

Visitors：226       Data Files Downloaded：9      
Data Downloaded：872.19 MB      Citations：

Key Words：

the Lancang-Mekong River Adjacent Region,drought,standardized evapotranspiration index of precipitation,geographically weighted

Abstract：

The Lancang-Mekong River Adjacent Region (LMRR) is increasingly vulnerable to drought due to rising temperatures and decreasing precipitation. The authors utilized Terra Climate monthly meteorological data to calculate the standardized precipitation-evapotranspiration index (SPEI) from 2000 to 2019, assessing the current drought trend in the LMRR. The impact of drought on the net ecosystem productivity (NEP) of the LMRR was quantified using standardized anomaly index (SAI), geographically weighted regression (GWR), correlation analysis, and Sen Mann-Kendall trend test. The dataset includes: (1) boundary data of the LMRR; (2) monthly SPEI; (3) drought frequency (DF), drought duration (DD), and drought severity (DS) data for different drought types; (4) carbon flux and trends; (5) correlation between NEP and aridity indices; (6) GWR model results data; (7) lag effects of drought on NEP data. The spatial resolution of the raster data is 0.0727° (about 8 km). The dataset is archived in .shp and .tif formats, and consists of 333 data files with data size of 103 MB (compressed into one file with 96.9 MB). The analysis paper based on the dataset was published in the Acta Geographica Sinica, Vol. 79, No. 3, 2024.

Foundation Item：

China University of Geosciences (Wuhan) (2019004)

Data Citation：

CHEN Shiliang, CHEN Shiliang, LI Xia, QIAN Zhaohui, WANG Shaoqiang*, WANG Miaomiao, LIU Zhenhai. Dataset on Drought Trends and Carbon Flux in the Lancang-Mekong River Adjacent Region (2000-2019)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2024. https://doi.org/10.3974/geodb.2024.04.10.V1.

References：


     [1] Abatzoglou, J. T., Dobrowski, S. Z., Parks, S. A., et al. Data descriptor: TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958-2015 [J]. Scientific Data, 2018, 5: 170191. DOI:10.1038/sdata.2017.191.
     [2] Willmott, C. J., Rowe, C. M., Mintz, Y. Climatology of the terrestrial seasonal water cycle [J]. Journal of Climatology, 1985, 5(6): 589-606.
     [3] Chen, J. M., Liu, J., Cihlar, J., et al. Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications [J]. Ecological Modelling, 1999, 124(2-3): 99-119.
     [4] Shen, G. Q., Zheng, H. F., Lei, Z. F. Applicability analysis of SPEI for drought research in Northeast China [J]. Acta Ecologica Sinica, 2017, 37(11): 3787-3795.
     [5] Ding, Y. X., Peng, S. Z. Spatiotemporal trends and attribution of drought across China from 1901-2100 [J]. Sustainability, 2020, 12(2): 477. DOI: 10.3390/su12020477.
     [6] Pei, F. S., Li, X., Liu, X. P., et al. Assessing the impacts of droughts on net primary productivity in China [J]. Journal of Environmental Management, 2013, 114: 362-371.
     [7] Liu, C. X., Wu, X. L., Wang, L. Analysis on land ecological security change and affect factors using RS and GWR in the Danjiangkou Reservoir area, China [J]. Applied Geography, 2019, 105: 1-14.
     [8] Zhang, T. P., Bao, W. K., Lei, Q. L., et al. Characteristics of spatio-temporal changes in soil temperature in China from 1951 to 2010 and its influencing factors [J]. Acta Geographica Sinica, 2022, 77(3): 589-602.
     [9] Wang, Y. X., Chen, T. T., Wang, Q., et al. Time-lagged and cumulative effects of drought and anthropogenic activities on China's vegetation greening from 1990 to 2018 [J]. International Journal of Digital Earth, 2023, 16(1): 2233-2258.
     [10] Fuller, D. O., Wang, Y. Recent trends in satellite vegetation index observations indicate decreasing vegetation biomass in the southeastern saline everglades wetlands [J]. Wetlands, 2014, 34(1): 67-77.
     [11] Li, H., Zhu, T. T., Liu, Z. H., et al. Stability differences of coastal and inland vegetation to flood events in Southeast Asia [J]. Acta Ecologica Sinica, 2022, 42(16): 6745-6757.
     [12] Chen, B., Li, Y., Wang, S., et al. Integrating leaf functional traits improves modelled estimates of carbon and water fluxes at a subtropical evergreen conifer forest [J]. Ecological Modelling, 2024, 488, 110593. DOI: 10.1016/j.ecolmodel.2023.110593.
     [13] Chen, B., Wang, P., Wang, S., et al. Evaluation of leaf‐to‐canopy upscaling approaches for simulating canopy carbonyl sulfide uptake and gross primary productivity [J]. Journal of Geophysical Research: Biogeosciences, 2024, 129(3), e2023JG007521. DOI: 10.1029/2023JG007521.
     

Data Product:

ID Data Name Data Size Operation
1 Drought&CarbonFluxLMRR.rar 99235.55KB
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