Dongdong Kong, CUG
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以NorthChina为输入,测试PMLV2的核心代码;
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植被驱动数据,等待GEE跑完Albedo,然后进行线性插值、历史平均插值处理;
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气象驱动数据,从GEE截取,tiff转nc;
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模型参数率定,截取通量站驱动数据,重新率定模型参数(ERA5L, GLDASv2.1, GLDASv2.2, CFSV2, MERRA2);
You can install the development version of PMLV2
like so:
remotes::install_github("gee-hydro/PMLV2")
pak::pkg_install(c("phenofit"))
pak::pkg_install(c("rpkgs/rfluxnet", "rpkgs/nctools"))
See the following instruction:
https://gee-hydro.github.io/PML.R/articles/model_forcing.html
https://gee-hydro.github.io/PML.R/articles/run_model.html
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Eddy covariance flux
https://fluxnet.org/data/fluxnet2015-dataset/fullset-data-product
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Basin-scale water balance
$$E_{wb} = P - R - \Delta S + RES_s$$ $$E_{wb} ≈ P - R - \Delta S$$ -
Atmosphere moisture balance
$$E_{atm} = P + Div + \Delta W - RES_w$$ $$E_{atm} ≈ P + Div$$
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Zhang, Y., Kong, D., Gan, R., Chiew, F. H. S., McVicar, T. R., Zhang, Q., & Yang, Y. (2019). Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017. Remote Sensing of Environment, 222, 165–182. https://doi.org/10.1016/j.rse.2018.12.031
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Kong, D., Zhang, Y., Gu, X., & Wang, D. (2019). A robust method for reconstructing global MODIS EVI time series on the Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing, 155, 13–24. https://doi.org/10.1016/j.isprsjprs.2019.06.014