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Use of the SSiB4/TRIFFID model coupled with TOPMODEL to investigate the effects of vegetation and climate on evapotranspiration and runoff in a subalpine basin of southwestern China

    Huiping Deng Affiliation
    ; Li Dan Affiliation
    ; Huanguang Deng Affiliation
    ; Yan Xiao Affiliation
    ; Qian Wang Affiliation

Abstract

It is important to understand the response of vegetation dynamics and surface water budget to the changing climate. To investigate the effects of vegetation and climate change on evapotranspiration and runoff on a basin scale, the SSiB4T/TRIFFID (SSiB4/TRIFFID coupled with TOPMODEL) is used to perform long-term dynamic simulations of vegetation succession and the water balance under different climate scenarios for a subalpine basin. The results of all experiments show that fraction of vegetation changes from a dominance of C3 grasses to tundra shrubs and then gradually approaches equilibrium with a dominance of forests. Change to evapotranspiration is very sensitive to temperature changes but is not sensitive to precipitation changes when the temperature remains unchanged. Runoff is very sensitive to changes in both temperature and precipitation. In the increase of temperature, evapotranspiration of forests increases the most among the three vegetation types. From the control run to the [T+5, (1+40%)P] run (A temperature increase of 5 °C, an increase in precipitation of 40%), the role of forests in increasing runoff changes to a reduction in runoff.

Keyword : coupled model SSiB4T/TRIFFID, dynamic simulations, vegetation succession, water balances, impacts of vegetation and climate change, effects of forest vegetation on runoff

How to Cite
Deng, H., Dan, L., Deng, H., Xiao, Y., & Wang, Q. (2022). Use of the SSiB4/TRIFFID model coupled with TOPMODEL to investigate the effects of vegetation and climate on evapotranspiration and runoff in a subalpine basin of southwestern China. Journal of Environmental Engineering and Landscape Management, 30(1), 43-55. https://doi.org/10.3846/jeelm.2022.15227
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References

Arnell, N. W. (2003). Relative effects of multi-decadal climatic variability: Future streamflows in Britain. Journal of Hydrology, 270(3–4), 195–213. https://doi.org/10.1016/S0022-1694(02)00288-3

Beven, K. J., & Kirkby, M. J. (1979). A physical based variable contributing area model of basin hydrology. Hydrological Science Bulletin, 24(1), 43–69. https://doi.org/10.1080/02626667909491834

Beven, K. J. (2000). Rainfall-Runoff modeling. In Encyclopedia of hydrological sciences (Part 11). John Wiley & Sons.

Bonan, G. B., Levis, S., Sitch, S., Vertenstein, M., & Oleson, K. W. (2003). A dynamical global vegetation model for use with climate models: Concepts and description of simulated vegetation dynamics. Global Change Biology, 9(11), 1543–1566. https://doi.org/10.1046/j.1365-2486.2003.00681.x

Bosch, J. M., & Hewlett, J. D. (1982). A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration. Journal of Hydrology, 55(1–4), 3–23. https://doi.org/10.1016/0022-1694(82)90117-2

Chen, J., & Kumar, P. (2001). Topographic influence on the seasonal and interannual variation of water and energy balance of basins in North America. Journal of Climate, 14(9), 1989–2012. https://doi.org/10.1175/1520-0442(2001)014<1989:TIOTSA>2.0.CO;2

Cheng, G. W. (1991). An approach to the relationship between runoff characters and forest in the basin of Sichuan. Journal of Soil and Water Conservation, 5(1), 48–52 (in Chinese).

Cowling, S. A., Jones, C. D., & Cox, P. M. (2009). Greening the terrestrial biosphere: Simulated feedbacks on atmospheric heat and energy circulation. Climate Dynamics, 32, 287–299. https://doi.org/10.1007/s00382-008-0481-8

Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., & Totterdell, L. J. (2000). Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature, 408, 184–187. https://doi.org/10.1038/35041539

Cox, P. M., Betts, R. A., Jones, C. D., Spall, S. A., & Totterdell, I. J. (2001). Modelling vegetation and the carbon cycle as interactive elements of the climate system. In R. Pearce (Ed.), Meteorology at the Millennium (pp. 259–279). Academic Press. https://doi.org/10.1016/S0074-6142(02)80172-3

Dan, L., Ji, J., & He, Y. (2007). Use of ISLSCP II data to intercompare and validate the terrestrial net primary production in a land surface model coupled to a general circulation model. Journal of Geophysical Research: Atmospheres, 112(D2), D02S90. https://doi.org/10.1029/2006JD007721

Dan, L., Ji, J., Xie, Z. H., Chen, F., Wen, G., & Richey, J. E. (2012). Hydrological projections of climate change scenarios over the 3H region of China: A VIC model assessment. Journal of Geophysical Research: Atmospheres, 117(D11), 1–17. https://doi.org/10.1029/2011JD017131

Deng, H. P., & Sun, S. F. (2012). Incorporation of TOPMODEL into land surface model SSiB and numerically testing the effects of the corporation at basin scale. Science China Earth Sciences, 55, 1731–1741. https://doi.org/10.1007/s11430-012-4431-2

Diaz-Nieto, J., & Wilby, R. L. (2005). A comparison of statistical downscaling and climate change factor methods: Impacts on low flows in the River Thames, United Kingdom. Climate Change, 69, 245–268. https://doi.org/10.1007/s10584-005-1157-6

Douville, H. (2003). Assessing the influence of soil moisture on seasonal climate variability with AGCMs. Journal of Hydrometeorology, 4(6), 1044–1066. https://doi.org/10.1175/1525-7541(2003)004<1044:ATIOSM>2.0.CO;2

Dunn, S. M., & Mackay, R. (1995). Spatial variation in evapotranspiration and the influence of land use on catchment hydrology. Journal of Hydrology, 171(1–2), 49–73. https://doi.org/10.1016/0022-1694(95)02733-6

Gedney, N., & Cox, P. M. (2003). The sensitivity of globle climate model simulations to the representation of soil moisture heterogeneity. Journal of Hydrometeorology, 4(6), 1265–1275. https://doi.org/10.1175/1525-7541(2003)004<1265:TSOGCM>2.0.CO;2

Gerten, D., Sibyll, S., Uwe, H., Wolfgang, L., & Stephen, S. (2004). Terrestrial vegetation and water balance – hydrological evaluation of a dynamic global vegetation model. Journal of Hydrology, 286(1–4), 249–270. https://doi.org/10.1016/j.jhydrol.2003.09.029

Koster, R. D., Suarez, M. J., Ducharne, A., Stieglitz, M., & Kumar, P. (2000). A catchment-based approach to modeling land surface processes in a general circulation model, 1. Model structure. Journal of Geophysical Research, 105(D20), 809–822. https://doi.org/10.1029/2000JD900327

Li, W. H., He, Y. T., & Yang, L. Y. (2001). A summary and perspective of forest vegetation impacts on water yield. Journal of Natural Resources, 16(5), 398–406 (in Chinese). http://www.jnr.ac.cn/EN/abstract/abstract26372.shtml

Liu, Y., Xue, Y., MacDonald, G., Cox, P. M., & Zhang, Z. (2019). Global vegetation variability and its response to elevated CO2, global warming, and climate variability – a study using the offline SSiB4/TRIFFID model and satellite data. Earth System Dynamics, 10(1), 9–29. https://doi.org/10.5194/esd-10-9-2019

Ma, X. H. (1987). Preliminary study on hydrological function of fir forest in Miyaluo region of Sichuan. Scientia Silves Sinicae, 23, 253–264 (in Chinese).

Minville, M. F., Brissette, F., & Leconte, R. (2008). Uncertainty of the impact of climate change on the hydrology of a Nordic watershed. Journal of Hydrology, 358(1–2), 70–83. https://doi.org/10.1016/j.jhydrol.2008.05.033

Niu, G.-Y., Yang, Z.-L., Dickinson, R. E., & Gulden, L. E. (2005). A simple TOPMODEL-based runoff parameterization (SIMTOP) for use in global climate models. Journal of Geophysical Research, 110(D21), 1–15. https://doi.org/10.1029/2005JD006111

Peng, J., & Dan, L. (2015). Impacts of CO2 concentration and climate change on the terrestrial carbon flux using six global climate-carbon coupled models. Ecological Modelling, 304, 69–83. https://doi.org/10.1016/j.ecolmodel.2015.02.016

Sellers, P. J., Mintz, Y., Sud, Y. C., & Dalcher, A. (1986). A Simple Biosphere Model (SiB) for use within general circulation models. Journal of the Atmospheric Science, 43(6), 505–531. https://doi.org/10.1175/1520-0469(1986)043<0505:ASBMFU>2.0.CO;2

Sellers, P. J., Randall, D. A., Collatz, G. J., Berry, J. A., Field, C. B., Dazlich, D. A., Zhang, C., Collelo, G. D., & Bounoua, L. (1996). A revised land surface parameterization (SiB2) for atmospheric GCMs. Journal of Climate, 9(4), 676–705. https://doi.org/10.1175/1520-0442(1996)009<0676:ARLSPF>2.0.CO;2

Sellers, P. J., Dickinson, R. E., Randall, D. A., Betts, A. K., Hall, F. G., Berry, J. A., Collatz, G. J., Denning, A. S., Mooney, H. A., Nobre, C. A., Sato, N., Field, C. B., & Henderson-Sellers, A. (1997). Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science, 275(5299), 502–509. https://doi.org/10.1126/science.275.5299.502

Sheffield, J., Goteti, G., & Wood, E. F. (2006). Development of a 50-yr high-resolution global dataset of meteorological forcings for land surface modeling. Journal of Climate, 19(13), 3088–3111. https://doi.org/10.1175/JCLI3790.1

Sivapalan, M., Beven, K. J., & Wood, E. F. (1987). On hydrologic similarity: 2. A scaled model of storm runoff production. Water Resource Research, 23(12), 2266–2278. https://doi.org/10.1029/WR023i012p02266

Stieglitz, M., Rind, D., Famiglieth, J., & Rosenzweig, C. (1996). An efficient approach to modeling the topographic control of surface hydrology for regional and global climate modeling. Journal of Climate, 10(1), 118–137. https://doi.org/10.1175/1520-0442(1997)010<0118:AEATMT>2.0.CO;2

United States Geological Survey. (2003). Shuttle Radar Topography Mission documentation: SRTM Topo [EB/OL]. https://pubs.er.usgs.gov/publication/fs07103

Warrach, K., Stieglitz, M., Mengelkamp, H. T., & Raschke, E. (2002). Advantages of a topographically controlled runoff simulation in a soil-vegetation-atmosphere transfer model. Journal of Hydrometeorology, 3(2), 131–148. https://doi.org/10.1175/1525-7541(2002)003<0131:AOATCR>2.0.CO;2

Woodward, F. I., Lomas, M. R., & Kelly, C. K. (2004). Global climate and the distribution of plant biomes. Philosophical Transactions of the Royal Society B, 359(1450), 1465–1476. https://doi.org/10.1098/rstb.2004.1525

Xue, Y. K., Sellers, P. J., Kinter, J. L., & Shukla, J. (1991). A simplified biosphere model for global climate studies. Journal of Climate, 4(3), 345–364. https://doi.org/10.1175/1520-0442(1991)004<0345:ASBMFG>2.0.CO;2

Xue, Y. K., Deng, H. P., & Cox, P. M. (2006). Testing a coupled biophysical/dynamic vegetation model (SSiB-4/TRIFFID) in different climate zones using satellite-derived and ground-measured data. In 86th AMS Annual Meeting, 18th Conference on Climate Variability and Change. https://ams.confex.com/ams/Annual2006/webprogram/Paper101721.html

Zeng, Z. Z., Piao, S. L., Li, L. Z. X., Wang T., Ciais, P., Lian, X., Yang, Y., Mao, J., Shi, X., & Myneni, R. (2018). Impact of earch greening on the terrestrial water cycle. Journal of Climate, 31(7), 2633–2650. https://doi.org/10.1175/JCLI-D-17-0236.1

Zhan, X. W., Xue, Y. K., & Collatz, G. J. (2003). An analytical approach for estimating CO2 and heat fluxes over the Amazonian region. Ecological Modeling, 162(1–2), 97–117. https://doi.org/10.1016/S0304-3800(02)00405-2

Zhang, F. H., Chen, L. W., Wu, X. X., & Gong, Y. B. (2007). An analysis of influences of forest vegetation changes on the runoff in small watersheds in hilly areas in the upper reaches of the Yangtze River. Journal of Sichuan Forestry Science and Technology, 28(4), 49–53 (in Chinese).

Zhang, M. F., Wei, X. H., Sun, P. S., & Liu, S. R. (2012). The effect of forest harvesting and climatic variability on runoff in a large watershed: The case study in the Upper Minjiang River of Yangtze River basin. Journal of Hydrology, 464–465, 1–11. https://doi.org/10.1016/j.jhydrol.2012.05.050

Zhang, M. F., Liu, N., Harper, R., Li, Q., Liu, K., Wei, X. H., Ning, D. Y., Hou, Y. P., & Liu, S. R. (2017). A global review on hydrological responses to forest change across multiple spatial scales: Importance of scale, climate, forest type and hydrological regime. Journal of Hydrology, 546, 44–59. https://doi.org/10.1016/j.jhydrol.2016.12.040

Zhang, Z. Q., Xue, Y. K., MacDonald, G., Cox, P. M., & Collatz, G. J. (2015). Investigation of North American vegetation variability under recent climate: A study using the SSiB4/TRIFFID biophysical/dynamic vegetation model. Journal of Geophysical Research: Atmospheres, 120(4), 1300–1321. https://doi.org/10.1002/2014JD021963