BEPS hourly version (v4.10)

The user guide for BEPS hourly version for site (v4.10)

This model was initially developed for boreal ecosystems and has been adapted for all ecosystems over the globe. BEPS mechanistically includes the impacts of various drivers on gross primary productivity (GPP) (climate, CO2 concentration, and nitrogen deposition) and assimilates vegetation structure (LAI) data. BEPS also simulates the dynamics of carbon pools beyond GPP and uses a spin-up procedure to prescribe soil carbon pools for estimating autotrophic respiration (AR) and heterotrophic respiration (HR).

Bugs fixed

2024-10-13

• LAMBDA function in the photosynthesis module, the unit of lambda_ice is error, 333 J/kg should be 333000 J/kg.
• snowpack_stage1:
  • snowrate_o未被初始化，导致snowrate_o > 0为true.
  • 雪深最大设置为10m，防止不合理的不断累积：*depth_snow=min(*mass_snow_g/(*density_snow), 10.0);
• snowpack_stage3: max(mass_water_frozen,*depth_water*density_water), max should be min

How to run this model?

The BEPS hourly version for site (v4.10) can be used in two ways:

1. Dependency import

Please copy the header file and source file into traditional IDEs (i.e. Code::block, https://www.codeblocks.org/) and directly build and run the model.

2. CMake

Please find the "CMakeLists.txt" file. The BEPS v4.10 model requires minimum 3.17 CMake version and is based on C99 standard. It is recommended to use CLion (https://www.jetbrains.com/clion/) and MingW (https://www.mingw-w64.org/) to compile and run the model.

Make sure the "input" and "output" folders have been created in the current folder of the source codes.

According to users' research interests, the parameters and code structure can be edited. Please remember to make readable comment and git version control after each edition.

Please see "Modules_variables4BEPS.docx" for detailed parameter descriptions.

Usage

The BEPS model requires four input files: 1) Basic information; 2) Carbon pool data; 3) Leaf area index; 4) Meteorological data. Users can find input data examples in the 'input' folder.

1) Basic information (data1 in the input data example)

long, lat, LC, CI, soiltxt, soiltemp, soilwater, snowdp [WITH TAB SPACE]

• long : the longitude of site
• lat : the latitude of site
• LC : land cover type of site; 1-ENF 2-DNF 6-DBF 9-EBF 13-shrub 40-C4 plants default-others
• CI : clumping index
• soiltxt : soil texture; 1-land 2-loamy sand 3-sandy loam 4-loam 5-silty loam 6-sandy clay loam 7-clay loam 8-silty clay loam 9-sandy clay 10-silty clay 11-clay default-others
• soiltemp : soil temperature
• soilwater : soil water content
• snowdp : snow depth

2) Carbon pool data (data2 in the input data example)

LAI_yr, ann_NPP, ccd, cssd, csmd, cfsd, cfmd, csm, cm, cs, cp [WITH TAB SPACE]

3) Leaf area index

Daily float number LAI [WITH TAB SPACE]

4) Meteorological data

DOY, H, SW, TA, VPD/RH, P, WS [WITH TAB SPACE] [LINEBREAK EACH HOUR]

• DOY : day of year (1-365)
• H : hour of day (1-24)
• SW : shortwave radiation
• TA : air temperature
• VPD/RH : vapor pressure deficit OR humidity, code needs to be edited for each input in "bepsmain_pnt.c"
• P : precipitation
• WS : wind speed

Citation

Please cite the following [ARTICLES] for using the BEPS model：

• Liu, J., Chen, J., Cihlar, J., and Park, W. M., A process-based boreal ecosystem productivity simulator using remote sensing inputs, Remote Sensing of Environment, 62, 158-175, 1997.

• Chen, J., Liu, J., Cihlar, J., and Goulden, M. L., Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications, Ecological Modelling, 124, 99-119, 1999.

• Liu, J., Chen, J., and Cihlar, J., Mapping evapotranspiration based on remote sensing: an application to Canada’s landmass, Water Resources Research, 39, 1189, doi:10.1029/2002WR001680, 2003.

• Ju, W., Chen, J. M., Black, T.A., Barr, A., Liu, J. and Chen, B., Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest, Agricultural and Forest Meteorology, 140, 136-151. 2006.

• Chen, J., Mo, G., Pisek, J., Liu, J., Deng, F., Maayar, M. E., Ishizawa, M., and Chan, D., Foliage clumping index as an important vegetation structural parameter for estimating global terrestrial gross primary productivity, Global Biogeochemical Cycles, 26, GB1019, doi:10.1029/2010GB003996, 2012.

References

1. Chen, B. Z., Chen, J. M., & Ju, W. M. (2007). Remote sensing-based ecosystem-atmosphere simulation scheme (EASS) - Model formulation and test with multiple-year data. Ecological Modelling, 209(2-4), 277-300. doi:DOI 10.1016/j.ecolmodel.2007.06.032

2. Chen, B., Liu, J., Chen, J. M., Croft, H., Gonsamo, A., He, L., & Luo, X. (2016). Assessment of foliage clumping effects on evapotranspiration estimates in forested ecosystems. Agricultural and Forest Meteorology, 216, 82-92. doi:http://dx.doi.org/10.1016/j.agrformet.2015.09.017

3. Chen, J. M., Ju, W., Ciais, P. et al. Vegetation structural change since 1981 significantly enhanced the terrestrial carbon sink. Nat Commun 10, 4259 (2019). https://doi.org/10.1038/s41467-019-12257-8 (for daily version)

4. Chen, J. M., Mo, G., Pisek, J., Liu, J., Deng, F., Ishizawa, M., & Chan, D. (2012). Effects of foliage clumping on the estimation of global terrestrial gross primary productivity. Global Biogeochemical Cycles, 26. doi:Artn Gb1019 Doi 10.1029/2010gb003996

5. Chen, J. M., Liu, J., Cihlar, J., & Goulden, M. L. (1999). Daily canopy photosynthesis model through temporal and spatial scaling for remote sensing applications. Ecological Modelling, 124(2-3), 99-119. doi:Doi 10.1016/S0304-3800(99)00156-8

6. Gonsamo, A., Chen, J. M., Kurz, W. A., Price, D. T., Liu, J., Boisvenue, C., Hember, R. A., Wu, C., and Chang, K., New assessment of net primary productivity of Canada's landmass, Journal of Geophysical Research, 118, 1-15, doi:10.1002/2013JG002388, 2013.

7. He, L.; Wang, R.; Mostovoy, G.; Liu, J.; Chen, J.M.; Shang, J.; Liu, J.; McNairn, H.; Powers, J. Crop Biomass Mapping Based on Ecosystem Modeling at Regional Scale Using High Resolution Sentinel-2 Data. Remote Sens. 2021, 13, 806. https://doi.org/10.3390/rs13040806

8. He, L., et al. (2019). "Diverse photosynthetic capacity of global ecosystems mapped by satellite chlorophyll fluorescence measurements." Remote Sensing of Environment 232: 111344.

9. He, L.; Mostovoy, G. Cotton Yield Estimate Using Sentinel-2 Data and an Ecosystem Model over the Southern US. Remote Sens. 2019, 11, 2000.

10. He, L. M., Chen, J. M., Gonsamo, A., Luo, X. Z., Wang, R., Liu, Y., & Liu, R. G. (2018). Changes in the Shadow: The Shifting Role of Shaded Leaves in Global Carbon and Water Cycles Under Climate Change. Geophysical Research Letters, 45(10), 5052-5061.

11. He, L. M., Chen, J. M., Croft, H., Gonsamo, A., Luo, X. Z., Liu, J. N., . . . Liu, Y. (2017). Nitrogen Availability Dampens the Positive Impacts of CO2 Fertilization on Terrestrial Ecosystem Carbon and Water Cycles. Geophysical Research Letters, 44(22), 11590-11600. doi:10.1002/2017gl075981

12. He, L., Chen, J. M., Liu, J., Bélair, S., & Luo, X. (2017). Assessment of SMAP soil moisture for global simulation of gross primary production. Journal of Geophysical Research: Biogeosciences, 122, doi:10.1002/2016JG003603. doi:10.1002/2016JG003603

13. He, L., Chen, J. M., Liu, J., Mo, G., Bélair, S., Zheng, T., . . . Barr, A. G. (2014). Optimization of water uptake and photosynthetic parameters in an ecosystem model using tower flux data. Ecological Modelling, 294(0), 94-104. doi:http://dx.doi.org/10.1016/j.ecolmodel.2014.09.019

14. Ju, W., Chen, J. M., Black, T. A., Barr, A. G., Liu, J., & Chen, B. (2006). Modelling multi-year coupled carbon and water fluxes in a boreal aspen forest. Agricultural and Forest Meteorology, 140(1-4), 136-151. doi:10.1016/j.agrformet.2006.08.008

15. Liu, J., Chen, J. M., Cihlar, J., & Park, W. M. (1997). A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sensing of Environment, 62(2), 158-175.

16. Liu, J., Chen, J., Cihlar, J., and Chen, W., Net primary productivity distribution in the BOREAS region from a process model using satellite and surface data, Journal of Geophysical Research, 104, 27,735-27-754, 1999.

17. Luo, X. Z., Chen, J. M., Liu, J. E., Black, T. A., Croft, H., Staebler, R., . . . McCaughey, H. (2018). Comparison of Big-Leaf, Two-Big-Leaf, and Two-Leaf Upscaling Schemes for Evapotranspiration Estimation Using Coupled Carbon-Water Modeling. Journal of Geophysical Research-Biogeosciences, 123(1), 207-225.

18. Luo, X, Croft, H, Chen, JM, He, L, Keenan, TF. Improved estimates of global terrestrial photosynthesis using information on leaf chlorophyll content. Glob Change Biol. 2019; 25: 2499– 2514. https://doi.org/10.1111/gcb.14624

19. Luo, X., Keenan, T.F. Global evidence for the acclimation of ecosystem photosynthesis to light. Nat Ecol Evol (2020). https://doi.org/10.1038/s41559-020-1258-7