Articles | Volume 26, issue 24
https://doi.org/10.5194/hess-26-6379-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-6379-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Does non-stationarity induced by multiyear drought invalidate the paired-catchment method?
Yunfan Zhang
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
Lu Zhang
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
CSIRO Land and Water, Black Mountain, Canberra ACT 2601, Australia
Shujing Qin
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
Yanghe Liu
State Key Laboratory of Water Resources and Hydropower Engineering
Science, Wuhan University, Wuhan 430072, China
Hubei Provincial Collaborative Innovation Center for Water Resources Security, Wuhan 430072, China
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Cited articles
Allen, P. M., Harmel, R. D., Dunbar, J. A., and Arnold, J. G.: Upland
contribution of sediment and runoff during extreme drought: A study of the
1947–1956 drought in the Blackland Prairie, Texas, J. Hydrol., 407, 1–11,
https://doi.org/10.1016/j.jhydrol.2011.04.039, 2011.
Avanzi, F., Rungee, J., Maurer, T., Bales, R., Ma, Q., Glaser, S., and Conklin, M.: Climate elasticity of evapotranspiration shifts the water
balance of Mediterranean climates during multi-year droughts, Hydrol. Earth
Syst. Sci., 24, 4317–4337, https://doi.org/10.5194/hess-24-4317-2020, 2020.
Bosch, J. M. and Hewlett, J. D.: A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration, J. Hydrol., 55, 3–23, https://doi.org/10.1016/0022-1694(82)90117-2, 1982.
Bren, L., Lane, P., and McGuire, D.: An empirical, comparative model of
changes in annual water yield associated with pine plantations in southern
Australia, Aust. Forest., 69, 275–284, https://doi.org/10.1080/00049158.2006.10676248, 2006.
Bren, L. J. and Lane, P. N. J.: Optimal development of calibration equations for paired catchment projects, J. Hydrol., 519, 720–731,
https://doi.org/10.1016/j.jhydrol.2014.07.059, 2014.
Brodribb, T. J., Powers, J., Cochard, H., and Choat, B.: Hanging by a thread? Forests and drought, Science, 368, 261–266, https://doi.org/10.1126/science.aat7631, 2020.
Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W., and Vertessy, R. A.: A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation, J. Hydrol., 310, 28–61,
https://doi.org/10.1016/j.jhydrol.2004.12.010, 2005.
Bruijnzeel, L. A.: Forestaion and dry season flow in the tropics: a closer
look, J. Trop. Forest. Sci., 1, 229–243, 1989.
Brutsaert, W.: Long-term groundwater storage trends estimated from streamflow records: Climatic perspective, Water Resour. Res., 44, 129–135, https://doi.org/10.1029/2007WR006518, 2008.
Budyko, M. I.: Climate and Life, Academic Press, Inc., New York, 508 pp.,
ISBN 9780080954530, 1974.
Cavalcante, R. B. L., Pontes, P. R. M., Souza Filho, P. W. M., and Souza, E.
B.: Opposite Effects of Climate and Land Use Changes on the Annual Water
Balance in the Amazon Arc of Deforestation, Water Resour. Res., 55, 3092–3106, https://doi.org/10.1029/2019WR025083, 2019.
Cheng, L., Zhang, L., Chiew, F. H. S., Canadell, J. G., Zhao, F., Wang, Y.,
Hu, X., and Lin, K.: Quantifying the impacts of vegetation changes on catchment storage-discharge dynamics using paired-catchment data, Water
Resour. Res., 53, 5963–5979, https://doi.org/10.1002/2017WR020600, 2017.
Chiew, F. H. S., Potter, N. J., Vaze, J., Petheram, C., Zhang, L., Teng, J.,
and Post, D. A.: Observed hydrologic non-stationarity in far south-eastern
Australia: Implications for modelling and prediction, Stoch. Env. Res. Risk A., 28, 3–15, https://doi.org/10.1007/s00477-013-0755-5, 2014.
Clark, M. P., Wilby, R. L., Gutmann, E. D., Vano, J. A., Gangopadhyay, S.,
Wood, A. W., Fowler, H. J., Prudhomme, C., Arnold, J. R., and Brekke, L. D.:
Characterizing Uncertainty of the Hydrologic Impacts of Climate Change, Curr. Clim. Change Rep., 2, 55–64, https://doi.org/10.1007/s40641-016-0034-x, 2016.
Descroix, L., Mahé, G., Lebel, T., Favreau, G., Galle, S., Gautier, E.,
Olivry, J., Albergel, J., Amogu, O., Cappelaere, B., Dessouassi, R.,
Diedhiou, A., Le Breton, E., Mamadou, I., and Sighomnou, D.: Spatio-temporal
variability of hydrological regimes around the boundaries between Sahelian
and Sudanian areas of West Africa: A synthesis, J. Hydrol., 375, 90–102,
https://doi.org/10.1016/j.jhydrol.2008.12.012, 2009.
Dey, P. and Mishra, A.: Separating the impacts of climate change and human
activities on streamflow: A review of methodologies and critical assumptions, J. Hydrol., 548, 278–290, https://doi.org/10.1016/j.jhydrol.2017.03.014, 2017.
Farley, K. A., Jobbágy, E., and Jackson, R. B.: Effects of afforestation
on water yield: A global synthesis with implications for policy, Global Change Biol., 11, 1565–1576, https://doi.org/10.1111/j.1365-2486.2005.01011.x, 2005.
Filoso, S., Bezerra, M. O., Weiss, K. C. B., and Palmer, M. A.: Impacts of
forest restoration on water yield: A systematic review, PLoS One, 12, e0183210, https://doi.org/10.1371/journal.pone.0183210, 2017.
Griffin, D. and Anchukaitis, K. J.: How unusual is the 2012–2014 California drought?, Geophys. Res. Lett., 41, 9017–9023, https://doi.org/10.1002/2014GL062433, 2014.
Hallema, D. W., Sun, G., Caldwell, P. V., Norman, S. P., Cohen, E. C., Liu,
Y., Bladon, K. D., and McNulty, S. G.: Burned forests impact water supplies,
Nat. Commun., 9, 1307, https://doi.org/10.1038/s41467-018-03735-6, 2018.
Han, F., Cook, K. H., and Vizy, E. K.: Changes in intense rainfall events and dry periods across Africa in the twenty-first century, Clim. Dynam., 53,
2757–2777, https://doi.org/10.1007/s00382-019-04653-z, 2019.
Han, J., Yang, Y., Roderick, M. L., McVicar, T. R., Yang, D., Zhang, S., and
Beck, H. E.: Assessing the Steady-State Assumption in Water Balance Calculation Across Global Catchments, Water Resour. Res., 56, e2020WR027392, https://doi.org/10.1029/2020WR027392, 2020.
Hoek Van Dijke, A. J., Herold, M., Mallick, K., Benedict, I., Machwitz, M.,
Schlerf, M., Pranindita, A., Theeuwen, J. J. E., Bastin, J., and Teuling, A.
J.: Shifts in regional water availability due to global tree restoration,
Nat. Geosci., 15, 363–368, https://doi.org/10.1038/s41561-022-00935-0, 2022.
Jiao, T., Williams, C. A., Rogan, J., De Kauwe, M. G., and Medlyn, B. E.:
Drought Impacts on Australian Vegetation During the Millennium Drought Measured With Multisource Spaceborne Remote Sensing, J. Geophys. Res.-Biogeo., 125, e2019JG005145, https://doi.org/10.1029/2019JG005145, 2020.
Jones, R. N., Chiew, F. H. S., Boughton, W. C., and Zhang, L.: Estimating
the sensitivity of mean annual runoff to climate change using selected
hydrological models, Adv. Water Resour., 29, 1419–1429,
https://doi.org/10.1016/j.advwatres.2005.11.001, 2006.
Kendall, M. G.: Rank-Correlation Measures, Charles Griffin, London, 202 pp.,
ISBN 10:0195208374, 1975.
Kim, H. S., Croke, B. F. W., Jakeman, A. J., and Chiew, F. H. S.: An
assessment of modelling capacity to identify the impacts of climate variability on catchment hydrology, Math. Comput. Simulat., 81, 1419–1429,
https://doi.org/10.1016/j.matcom.2010.05.007, 2011.
Kinal, J. and Stoneman, G. L.: Disconnection of groundwater from surface
water causes a fundamental change in hydrology in a forested catchment in
south-western Australia, J. Hydrol., 472–473, 14–24,
https://doi.org/10.1016/j.jhydrol.2012.09.013, 2012.
King, A. D., Pitman, A. J., Henley, B. J., Ukkola, A. M., and Brown, J. R.:
The role of climate variability in Australian drought, Nat. Clim. Change, 10, 177–179, https://doi.org/10.1038/s41558-020-0718-z, 2020.
Koster, R. D. and Suarez, M. J.: A simple framework for examining the interannual variability of land surface moisture fluxes, J. Climate, 12,
1911–1917, https://doi.org/10.1175/1520-0442(1999)012<1911:ASFFET>2.0.CO;2, 1999.
Lane, P. N. J., Best, A. E., Hickel, K., and Zhang, L.: The response of flow
duration curves to afforestation, J. Hydrol., 310, 253–265,
https://doi.org/10.1016/j.jhydrol.2005.01.006, 2005.
Lee, R.: Forest hydrology, Columbia University Press, New York, 349 pp.,
ISBN 10:0231047185, 1980.
Lewis, S. L., Brando, P. M., Phillips, O. L., van der Heijden, G. M. F., and
Nepstad, D.: The 2010 Amazon drought, Science, 331, 554, https://doi.org/10.1126/science.1200807, 2011.
Li, H., Zhang, Y., Vaze, J., and Wang, B.: Separating effects of vegetation
change and climate variability using hydrological modelling and
sensitivity-based approaches, J. Hydrol., 420–421, 403–418,
https://doi.org/10.1016/j.jhydrol.2011.12.033, 2012.
Li, L. J., Zhang, L., Wang, H., Wang, J., Yang, J. W., Jiang, D., Li, J. Y.,
and Qin, D. Y.: Assessing the impact of climate variability and human activities on streamflow from the Wuding River basin in China, Hydrol. Process., 21, 3485–3491, https://doi.org/10.1002/hyp.6485, 2007.
Li, Q., Wei, X., Zhang, M., Liu, W., Giles-Hansen, K., and Wang, Y.: The
cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed, J. Hydrol., 557, 448–459, https://doi.org/10.1016/j.jhydrol.2017.12.056, 2018.
Liu, Y., Liu, S., Wan, S., Wang, J., Luan, J., and Wang, H.: Differential
responses of soil respiration to soil warming and experimental throughfall
reduction in a transitional oak forest in central China, Agr. Forest
Meteorol., 226–227, 186–198, https://doi.org/10.1016/j.agrformet.2016.06.003, 2016.
Liu, Y., Liu, P., Zhang, L., Zhang, X., Zhang, Y., and Cheng, L.: Detecting
and attributing drought-induced changes in catchment hydrological behaviours
in a southeastern Australia catchment using a data assimilation method,
Hydrol. Process., 35, e14289, https://doi.org/10.1002/hyp.14289, 2021.
Major, E. J., Cornish, P. M., and Whiting, J. K.: Red Hill hydrology project
establishment report including a preliminary water yield analysis, Forest
Research and Development Division, State Forests of New South Wales, Sydney,
24 pp., https://www.dpi.nsw.gov.au/__data/assets/pdf_file/0008/389663 (last access: 17 December 2022), 1998.
Mann, H. B.: Nonparametric tests against trend, Econometrica, 13, 245–259,
https://doi.org/10.2307/1907187, 1945.
Milly, P. C. D. and Dunne, K. A.: Macroscale water fluxes 2. Water and energy supply control of their interannual variability, Water Resour. Res., 38, 24-1–24-9, https://doi.org/10.1029/2001WR000760, 2002.
Murakami, H., Delworth, T. L., Cooke, W. F., Zhao, M., Xiang, B., and Hsu, P.: Detected climatic change in global distribution of tropical cyclones, P. Natl. Acad. Sci. USA, 117, 10706–10714, https://doi.org/10.1073/pnas.1922500117, 2020.
Newman, B. D., Wilcox, B. P., Archer, S. R., Breshears, D. D., Dahm, C. N.,
Duffy, C. J., McDowell, N. G., Phillips, F. M., Scanlon, B. R., and Vivoni, E. R.: Ecohydrology of water-limited environments: A scientific vision, Water Resour. Res., 42, W06302, https://doi.org/10.1029/2005WR004141, 2006.
Peng, T., Tian, H., Singh, V. P., Chen, M., Liu, J., Ma, H., and Wang, J.: Quantitative assessment of drivers of sediment load reduction in the Yangtze River basin, China, J. Hydrol., 580, 124242, https://doi.org/10.1016/j.jhydrol.2019.124242, 2020.
Peters, E., Torfs, P. J. J. F., van Lanen, H. A. J., and Bier, G.: Propagation of drought through groundwater-A new approach using linear reservoir theory, Hydrol. Process., 17, 3023–3040, https://doi.org/10.1002/hyp.1274, 2003.
Peterson, T. J., Saft, M., Peel, M. C., and John, A.: Watersheds may not
recover from drought, Science, 372, 745–749, https://doi.org/10.1126/science.abd5085, 2021.
Petrone, K. C., Hughes, J. D., Van Niel, T. G., and Silberstein, R. P.:
Streamflow decline in southwestern Australia, 1950–2008, Geophys. Res. Lett., 37, L11401, https://doi.org/10.1029/2010GL043102, 2010.
Pettitt, A. N.: A non-parametric approach to the change-point problem, J. Roy. Stat. Soc. Ser. C, 28, 126–135, https://doi.org/10.2307/2346729, 1979.
Pumo, D., Noto, L. V., and Viola, F.: Ecohydrological modelling of flow
duration curve in Mediterranean river basins, Adv. Water Resour., 52, 314–327, https://doi.org/10.1016/j.advwatres.2012.05.010, 2013.
Queensland Government: SILO – Australian climate data from 1889 to yesterday, Queensland Government [data set], https://www.longpaddock.qld.gov.au/silo/point-data/, last access: 5 May 2020.
Roderick, M. L. and Farquhar, G. D.: A simple framework for relating
variations in runoff to variations in climatic conditions and catchment
properties, Water Resour. Res., 47, W00G07, https://doi.org/10.1029/2010WR009826, 2011.
R Project: The R Project for Statistical Computing, https://www.r-project.org/, last access: 15 October 2022.
Ryberg, K. R., Lin, W., and Vecchia, A. V.: Impact of climate variability on
runoff in the North-Central United States, J. Hydrol. Eng., 19, 148–158,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0000775, 2012.
Saft, M., Western, A. W., Zhang, L., Peel, M. C., and Potter, N. J.: The
influence of multiyear drought on the annual rainfall–runoff relationship:
An Australian perspective, Water Resour. Res., 51, 2444–2463,
https://doi.org/10.1002/2014WR015348, 2015.
Saft, M., Peel, M. C., Western, A. W., and Zhang, L.: Predicting shifts in
rainfall–runoff partitioning during multiyear drought: Roles of dry period
and catchment characteristics, Water Resour. Res., 52, 9290–9305,
https://doi.org/10.1002/2016WR019525, 2016.
Searcy, J. K. and Hardison, C. H.: Double-mass Curves, United states government printing office, Washington, 65 pp., https://doi.org/10.3133/wsp1541B, 1960.
Sen, P. K.: Estimates of the Regression Coefficient Based on Kendall's Tau,
J. Am. Stat. Assoc., 63, 1379–1389, https://doi.org/10.1080/01621459.1968.10480934, 1968.
Stoneman, G. L.: Hydrological response to thinning a small jarrah (Eucalyptus marginata) forest catchment, J. Hydrol., 150, 393–407,
https://doi.org/10.1016/0022-1694(93)90118-S, 1993.
Stoof, C. R., Vervoort, R. W., Iwema, J., van den Elsen, E., Ferreira, A. J.
D., and Ritsema, C. J.: Hydrological response of a small catchment burned by
experimental fire, Hydrol. Earth Syst. Sci., 16, 267–285,
https://doi.org/10.5194/hess-16-267-2012, 2012.
Stuart-Haëntjens, E., De Boeck, H. J., Lemoine, N. P., Mänd, P.,
Kröel-Dulay, G., Schmidt, I. K., Jentsch, A., Stampfli, A., Anderegg, W.
R. L., Bahn, M., Kreyling, J., Wohlgemuth, T., Lloret, F., Classen, A. T.,
Gough, C. M., and Smith, M. D.: Mean annual precipitation predicts primary
production resistance and resilience to extreme drought, Sci. Total Environ., 636, 360–366, https://doi.org/10.1016/j.scitotenv.2018.04.290, 2018.
Sun, Y., Tian, F., Yang, L., and Hu, H.: Exploring the spatial variability
of contributions from climate variation and change in catchment properties
to streamflow decrease in a mesoscale basin by three different methods, J.
Hydrol., 508, 170–180, https://doi.org/10.1016/j.jhydrol.2013.11.004, 2014.
Tian, W., Liu, X., Liu, C., and Bai, P.: Investigation and simulations of
changes in the relationship of precipitation-runoff in drought years, J.
Hydrol., 565, 95–105, https://doi.org/10.1016/j.jhydrol.2018.08.015, 2018.
van Dijk, A. I. J. M., Beck, H. E., Crosbie, R. S., de Jeu, R. A. M., Liu, Y. Y., Podger, G. M., Timbal, B., and Viney, N. R.: The Millennium Drought in southeast Australia (2001–2009): Natural and human causes and implications for water resources, ecosystems, economy, and society, Water Resour. Res., 49, 1040–1057, https://doi.org/10.1002/wrcr.20123, 2013.
Van Loon, A. F., Rangecroft, S., Coxon, G., Breña Naranjo, J. A., Van Ogtrop, F., and Van Lanen, H. A. J.: Using paired catchments to quantify the human influence on hydrological droughts, Hydrol. Earth Syst. Sci., 23,
1725–1739, https://doi.org/10.5194/hess-23-1725-2019, 2019.
Wang, Q., Cheng, L., Zhang, L., Liu, P., Qin, S., Liu, L., and Jing, Z.:
Quantifying the impacts of land-cover changes on global evapotranspiration
based on the continuous remote sensing observations during 1982–2016, J.
Hydrol., 598, 126231, https://doi.org/10.1016/j.jhydrol.2021.126231, 2021.
Wang, W., Shao, Q., Yang, T., Peng, S., Xing, W., Sun, F., and Luo, Y.:
Quantitative assessment of the impact of climate variability and human
activities on runoff changes: A case study in four catchments of the Haihe
River basin, China, Hydrol. Process., 27, 1158–1174, https://doi.org/10.1002/hyp.9299, 2013.
Webb, A. A. and Kathuria, A.: Response of streamflow to afforestation and
thinning at Red Hill, Murray Darling Basin, Australia, J. Hydrol., 412–413,
133–140, https://doi.org/10.1016/j.jhydrol.2011.05.033, 2012.
Wei, X., Li, Q., Zhang, M., Giles-Hansen, K., Liu, W., Fan, H., Wang, Y., Zhou, G., Piao, S., and Liu, S.: Vegetation cover – another dominant factor
in determining global water resources in forested regions, Global Change
Biol., 24, 786–795, https://doi.org/10.1111/gcb.13983, 2018.
Williamson, D. R., Stokes, R. A., and Ruprecht, J. K.: Response of input and
output of water and chloride to clearing for agriculture, J. Hydrol., 94,
1–28, https://doi.org/10.1016/0022-1694(87)90030-8, 1987.
Xiao, Y., Xiao, Q., and Sun, X.: Ecological Risks Arising from the Impact of
Large-scale Afforestation on the Regional Water Supply Balance in Southwest
China, Sci. Rep.-UK, 10, 4150, https://doi.org/10.1038/s41598-020-61108-w, 2020.
Yang, Y., Guan, H., Batelaan, O., McVicar, T. R., Long, D., Piao, S., Liang,
W., Liu, B., Jin, Z., and Simmons, C. T.: Contrasting responses of water use
efficiency to drought across global terrestrial ecosystems, Sci. Rep.-UK, 6,
23284, https://doi.org/10.1038/srep23284, 2016.
Zhang, J., Zhang, Y., Sun, G., Song, C., Dannenberg, M. P., Li, J., Liu, N.,
Zhang, K., Zhang, Q., and Hao, L.: Vegetation greening weakened the capacity
of water supply to China's South-to-North Water Diversion Project, Hydrol.
Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, 2021.
Zhang, L., Dawes, W. R., and Walker, G. R.: Response of mean annual evapotranspiration to vegetation changes at catchment scale, Water Resour.
Res., 37, 701–708, https://doi.org/10.1029/2000WR900325, 2001.
Zhang, L., Zhao, F., Chen, Y., and Dixon, R. N. M.: Estimating effects of
plantation expansion and climate variability on streamflow for catchments in
Australia, Water Resour. Res., 47, W12539, https://doi.org/10.1029/2011WR010711, 2011.
Zhang, L., Nan, Z., Wang, W., Ren, D., Zhao, Y., and Wu, X.: Separating climate change and human contributions to variations in streamflow and its
components using eight time-trend methods, Hydrol. Process., 33, 383–394,
https://doi.org/10.1002/hyp.13331, 2019.
Zhang, S., Yang, H., Yang, D., and Jayawardena, A. W.: Quantifying the effect of vegetation change on the regional water balance within the Budyko framework, Geophys. Res. Lett., 43, 1140–1148, https://doi.org/10.1002/2015GL066952, 2016.
Zhao, F., Zhang, L., Xu, Z., and Scott, D. F.: Evaluation of methods for
estimating the effects of vegetation change and climate variability on
streamflow, Water Resour. Res., 46, W03505, https://doi.org/10.1029/2009WR007702, 2010.
Short summary
Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether changes can invalidate the most fundamental method (i.e., paired-catchment method (PCM)) for separating vegetation change impacts is still unknown. Using paired-catchment data with 10-year drought, PCM is shown to still be reliable even in catchments with non-stationarity. A new framework is further proposed to separate impacts of two non-stationary drivers, using paired-catchment data.
Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship....