Articles | Volume 26, issue 5
https://doi.org/10.5194/hess-26-1507-2022
© 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-26-1507-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Mar 2022
Research article |
| 18 Mar 2022
| 18 Mar 2022
Theoretical and empirical evidence against the Budyko catchment trajectory conjecture
Water Institute, University of Florida, Gainesville, Florida, USA
Engineering School of Sustainable Infrastructure and Environment
(ESSIE), University of Florida, Gainesville, Florida, USA
David A. Kaplan
Engineering School of Sustainable Infrastructure and Environment
(ESSIE), University of Florida, Gainesville, Florida, USA
Harald Klammler
Department of Geosciences, Federal University of Bahia, Salvador,
Bahia, Brazil
James W. Jawitz
Soil and Water Sciences Department, University of Florida, Gainesville,
Florida, USA
Related authors
Rob De Rooij, Nathan Reaver, Dogil Lee, David Kaplan, and Wendy Graham
EGUsphere, https://doi.org/10.5194/egusphere-2026-2828, https://doi.org/10.5194/egusphere-2026-2828, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Groundwater pollution is a major concern in many watersheds. To better understand where pollution comes from and how long it takes to reach rivers and springs, we developed a new modeling approach. This method combines an existing watershed model (SWAT-MODFLOW) with a particle-tracking tool (MODPATH). The model works by tracing water backward from springs and river reaches to places where it entered the groundwater system.
Rob De Rooij, Nathan Reaver, Dogil Lee, David Kaplan, and Wendy Graham
EGUsphere, https://doi.org/10.5194/egusphere-2026-2828, https://doi.org/10.5194/egusphere-2026-2828, 2026
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Short summary
Groundwater pollution is a major concern in many watersheds. To better understand where pollution comes from and how long it takes to reach rivers and springs, we developed a new modeling approach. This method combines an existing watershed model (SWAT-MODFLOW) with a particle-tracking tool (MODPATH). The model works by tracing water backward from springs and river reaches to places where it entered the groundwater system.
Alexander Wachholz, James W. Jawitz, and Dietrich Borchardt
Biogeosciences, 21, 3537–3550, https://doi.org/10.5194/bg-21-3537-2024, https://doi.org/10.5194/bg-21-3537-2024, 2024
Short summary
Short summary
Human activities are rivers' main source of nitrogen, causing eutrophication and other hazards. However, rivers can serve as a natural defense mechanism against this by retaining nitrogen. We show that the Elbe River retains more nitrogen during times of high pollution. With improvements in water quality, less nitrogen is retained. We explain this with changed algal and bacterial activities, which correspond to pollution and have many implications for the river and adjacent ecosystems.
Kathryn L. McCurley Pisarello and James W. Jawitz
Hydrol. Earth Syst. Sci., 25, 6173–6183, https://doi.org/10.5194/hess-25-6173-2021, https://doi.org/10.5194/hess-25-6173-2021, 2021
Short summary
Short summary
Climate classification systems divide the Earth into zones of similar climates. We compared the within-zone hydroclimate similarity and zone shape complexity of a suite of climate classification systems, including new ones formed in this study. The most frequently used system had high similarity but high complexity. We propose the Water-Energy Clustering framework, which also had high similarity but lower complexity. This new system is therefore proposed for future hydroclimate assessments.
Cited articles
Abatzoglou, J. T. and Ficklin, D. L.: Climatic and physiographic controls
of spatial variability in surface water balance over the contiguous United
States using the Budyko relationship, Water Resour. Res., 53,
7630–7643, 2017.
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop
evapotranspiration-Guidelines for computing crop water requirements-FAO
Irrigation and drainage paper 56, Fao, Rome, 300, D05109, ISBN 92-5-104219-5, 1998.
Andréassian, V. and Sari, T.: Technical Note: On the puzzling similarity of two water balance formulas – Turc–Mezentsev vs. Tixeront–Fu, Hydrol. Earth Syst. Sci., 23, 2339–2350, https://doi.org/10.5194/hess-23-2339-2019, 2019.
Bagrov, N.: O srednem mnogoletnem isparenii s poverchnosti susi (Über
den vieljährigen Durchschnittswert der Verdunstung von der
Oberfläche des Festlands), Meteorog. i Gridrolog, 10, 20–25, 1953.
Bai, P., Liu, X., Zhang, D., and Liu, C.: Estimation of the Budyko model
parameter for small basins in China, Hydrol. Process., 34, 125–138,
https://doi.org/10.1002/hyp.13577, 2019.
Berghuijs, W. R. and Woods, R. A.: Correspondence: Space-time asymmetry
undermines water yield assessment, Nat. Commun., 7, 11603,
https://doi.org/10.1038/ncomms11603, 2016.
Berghuijs, W. R., Gnann, S. J., and Woods, R. A.: Unanswered questions on
the Budyko framework, Hydrol. Process., 34, 5699–5703,
https://doi.org/10.1002/hyp.13958, 2020.
Berkaloff, E. and Tixeront, J.: Notice de la carte du ruissellement annuel moyen en Tunisie, Etudes Hydraulique et Hydrologie, Série I, Fascicule, vol. 7, p. 11, 1958.
Budyko, M. and Zubenok, L.: The determination of evaporation from the land
surface, Izv. Akad. Nauk SSSR Ser. Geogr, 6, 3–17, 1961.
Chen, H., Huo, Z., Zhang, L., and White, I.: New perspective about
application of extended Budyko formula in arid irrigation district with
shallow groundwater, J. Hydrol., 582, 124496,
https://doi.org/10.1016/j.jhydrol.2019.124496, 2020.
Choudhury, B.: Evaluation of an empirical equation for annual evaporation
using field observations and results from a biophysical model, J. Hydrol., 216, 99–110, 1999.
Cong, Z., Zhang, X., Li, D., Yang, H., and Yang, D.: Understanding
hydrological trends by combining the Budyko hypothesis and a stochastic soil
moisture model, Hydrol. Sci. J., 60, 145–155,
https://doi.org/10.1080/02626667.2013.866710, 2015.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, 2020.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M. Robinson, E. L., Wagener, T., and Woods, R.: Catchment attributes and hydro-meteorological timeseries for 671 catchments across Great Britain (CAMELS-GB), NERC Environmental Information Data Centre, [data set], https://doi.org/10.5285/8344e4f3-d2ea-44f5-8afa-86d2987543a9, 2020b.
Daly, E. and Porporato, A.: Impact of hydroclimatic fluctuations on the
soil water balance, Water Resour. Res., 42, W06401, https://doi.org/10.1029/2005wr004606,
2006.
Daly, E., Calabrese, S., Yin, J., and Porporato, A.: Linking parametric and
water-balance models of the Budyko and Turc spaces, Adv. Water
Res., 134, 103435, https://doi.org/10.1016/j.advwatres.2019.103435, 2019a.
Daly, E., Calabrese, S., Yin, J., and Porporato, A.: Hydrological Spaces of
Long-Term Catchment Water Balance, Water Resour. Res., 55,
10747–10764, https://doi.org/10.1029/2019wr025952, 2019b.
Deng, W., Song, J., Sun, H., Cheng, D., Zhang, X., Liu, J., Kong, F., Wang,
H., and Khan, A. J.: Isolating of climate and land surface contribution to
basin runoff variability: A case study from the Weihe River Basin, China,
Ecol. Eng., 153, 105904, https://doi.org/10.1016/j.ecoleng.2020.105904, 2020.
Donohue, R. J., Roderick, M. L., and McVicar, T. R.: Roots, storms and soil
pores: Incorporating key ecohydrological processes into Budyko's
hydrological model, J. Hydrol., 436, 35–50,
https://doi.org/10.1016/j.jhydrol.2012.02.033, 2012.
Doulatyari, B., Betterle, A., Basso, S., Biswal, B., Schirmer, M., and
Botter, G.: Predicting streamflow distributions and flow duration curves
from landscape and climate, Adv. Water Res., 83, 285–298,
https://doi.org/10.1016/j.advwatres.2015.06.013, 2015.
Eagleson, P.: Climate, soil and vegetation. 1 Introduction to water balance
dynamics, Water Resour. Res., 14, 705–712, 1978.
Feng, X., Porporato, A., and Rodriguez-Iturbe, I.: Stochastic soil water
balance under seasonal climates, Proc. Math. Phys. Eng. Sci., 471, 20140623,
https://doi.org/10.1098/rspa.2014.0623, 2015.
Fischer, E. M., Sedláček, J., Hawkins, E., and Knutti, R.: Models
agree on forced response pattern of precipitation and temperature extremes,
Geophys. Res. Lett., 41, 8554–8562, 10.1002/2014gl062018, 2014.
Fu, B.: On the calculation of the evaporation from land surface, Sci. Atmos.
Sin., 5, 23–31, 1981.
Gao, F., Wang, H., and Liu, C.: Long-term assessment of groundwater
resources carrying capacity using GRACE data and Budyko model, J. Hydrol., 588, 125042, https://doi.org/10.1016/j.jhydrol.2020.125042, 2020.
Gentine, P., D'Odorico, P., Lintner, B. R., Sivandran, G., and Salvucci, G.:
Interdependence of climate, soil, and vegetation as constrained by the
Budyko curve, Geophys. Res. Lett., 39, L19404,
https://doi.org/10.1029/2012gl053492, 2012.
Greve, P., Gudmundsson, L., Orlowsky, B., and Seneviratne, S. I.:
Introducing a probabilistic Budyko framework, Geophys. Res. Lett.,
42, 2261-2269, https://doi.org/10.1002/2015gl063449, 2015.
Greve, P., Burek, P., and Wada, Y.: Using the Budyko Framework for
Calibrating a Global Hydrological Model, Water Resour. Res., 56,
e2019WR026280, https://doi.org/10.1029/2019wr026280, 2020.
Gudmundsson, L., Greve, P., and Seneviratne, S. I.: The sensitivity of water
availability to changes in the aridity index and other factors – a
probabilistic analysis in the Budyko-space, Geophys. Res. Lett., 43, 6985–6994,
https://doi.org/10.1002/2016gl069763, 2016.
Guo, A., Chang, J., Wang, Y., Huang, Q., Guo, Z., and Li, Y.: Uncertainty
analysis of water availability assessment through the Budyko framework,
J. Hydrol., 576, 396–407, https://doi.org/10.1016/j.jhydrol.2019.06.033, 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.
Hargreaves, G. H. and Allen, R. G.: History and evaluation of Hargreaves
evapotranspiration equation, J. Irrig. Drain. E.,
129, 53–63, 2003.
Harman, C. and Troch, P. A.: What makes Darwinian hydrology “Darwinian”? Asking a different kind of question about landscapes, Hydrol. Earth Syst. Sci., 18, 417–433, https://doi.org/10.5194/hess-18-417-2014, 2014.
Harman, C. J., Rao, P. S. C., Basu, N. B., McGrath, G. S., Kumar, P., and
Sivapalan, M.: Climate, soil, and vegetation controls on the temporal
variability of vadose zone transport, Water Resour. Res., 47, W00J13,
https://doi.org/10.1029/2010wr010194, 2011.
Harrigan, S., Hannaford, J., Muchan, K., and Marsh, T. J.: Designation and
trend analysis of the updated UK Benchmark Network of river flow stations:
the UKBN2 dataset, Hydrol. Res., 49, 552–567, https://doi.org/10.2166/nh.2017.058,
2018 (data available at: https://nrfa.ceh.ac.uk/benchmark-network, http://nrfa.ceh.ac.uk/sites/default/files/UKBN_Station_List_vUKBN2.0_1.xlsx, last access: 28 September 2020).
He, G., Zhao, Y., Wang, J., Gao, X., He, F., Li, H., Zhai, J., Wang, Q., and
Zhu, Y.: Attribution analysis based on Budyko hypothesis for land
evapotranspiration change in the Loess Plateau, China, J. Arid Land,
11, 939–953, https://doi.org/10.1007/s40333-019-0107-5, 2019.
He, Y., Jiang, X., Wang, N., Zhang, S., Ning, T., Zhao, Y., and Hu, Y.:
Changes in mountainous runoff in three inland river basins in the arid Hexi
Corridor, China, and its influencing factors, Sustain. Cities Soc., 50, 101703, https://doi.org/10.1016/j.scs.2019.101703, 2019a.
He, Y., Qiu, H., Song, J., Zhao, Y., Zhang, L., Hu, S., and Hu, Y.:
Quantitative contribution of climate change and human activities to runoff
changes in the Bahe River watershed of the Qinling Mountains, China,
Sustain. Cities Soc., 51, 101729, https://doi.org/10.1016/j.scs.2019.101729, 2019b.
Holander, M. and Wolfe, D. A.: Nonparametric statistical methods, New York,
John Wiley and Sons, Inc., 503 pp., 1973.
Huang, S., Chang, J., Huang, Q., Chen, Y., and Leng, G.: Quantifying the
Relative Contribution of Climate and Human Impacts on Runoff Change Based on
the Budyko Hypothesis and SVM Model, Water Resour. Manage., 30,
2377–2390, https://doi.org/10.1007/s11269-016-1286-x, 2016.
Hulme, M., Marsh, R., and Jones, P. D.: Global changes in a humidity index
between 1931-60 and 1961-90, Clim. Res., 2, 1–22, https://doi.org/10.3354/cr002001,
1992.
Jaramillo, F., Cory, N., Arheimer, B., Laudon, H., van der Velde, Y., Hasper, T. B., Teutschbein, C., and Uddling, J.: Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space, Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, 2018.
Jiang, C., Xiong, L., Wang, D., Liu, P., Guo, S., and Xu, C.-Y.: Separating
the impacts of climate change and human activities on runoff using the
Budyko-type equations with time-varying parameters, J. Hydrol.,
522, 326–338, https://doi.org/10.1016/j.jhydrol.2014.12.060, 2015.
Kazemi, H., Sarukkalige, R., and Badrzadeh, H.: Evaluation of streamflow
changes due to climate variation and human activities using the Budyko
approach, Environ. Earth Sci., 78, 713, https://doi.org/10.1007/s12665-019-8735-9, 2019.
Knighton, J., Singh, K., and Evaristo, J.: Understanding Catchment-Scale
Forest Root Water Uptake Strategies Across the Continental United States
Through Inverse Ecohydrological Modeling, Geophys. Res. Lett., 47, e2019GL085937,
https://doi.org/10.1029/2019gl085937, 2020.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of
the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Lee, C.-H. and Yeh, H.-F.: Impact of Climate Change and Human Activities on Streamflow
Variations Based on the Budyko Framework, Water, 11, 2001, https://doi.org/10.3390/w11102001,
2019.
Li, C., Wang, L., Wanrui, W., Qi, J., Linshan, Y., Zhang, Y., Lei, W., Cui,
X., and Wang, P.: An analytical approach to separate climate and human
contributions to basin streamflow variability, J. Hydrol., 559,
30–42, https://doi.org/10.1016/j.jhydrol.2018.02.019, 2018.
Li, D., Pan, M., Cong, Z., Zhang, L., and Wood, E.: Vegetation control on
water and energy balance within the Budyko framework, Water Resour. Res., 49, 969–976, https://doi.org/10.1002/wrcr.20107, 2013.
Li, H., Shi, C., Zhang, Y., Ning, T., Sun, P., Liu, X., Ma, X., Liu, W., and
Collins, A. L.: Using the Budyko hypothesis for detecting and attributing
changes in runoff to climate and vegetation change in the soft sandstone
area of the middle Yellow River basin, China, Sci. Total Environ., 703,
135588, https://doi.org/10.1016/j.scitotenv.2019.135588, 2020.
Li, S., Zhang, L., Du, Y., Zhuang, Y., and Yan, C.: Anthropogenic impacts on
streamflow-compensated climate change effect in the Hanjiang River basin,
China, J. Hydrol. Eng., 25, p.04019058,
https://doi.org/10.1061/(asce)he.1943-5584.0001876, 2020.
Li, T., Xia, J., She, D., Cheng, L., Zou, L., and Liu, B.: Quantifying the
Impacts of Climate Change and Vegetation Variation on Actual
Evapotranspiration Based on the Budyko Hypothesis in North and South
Panjiang Basin, China, Water, 12, 508, https://doi.org/10.3390/w12020508, 2020.
Li, Y., Liu, C., Yu, W., Tian, D., and Bai, P.: Response of streamflow to
environmental changes: A Budyko-type analysis based on 144 river basins over
China, Sci. Total Environ., 664, 824–833, https://doi.org/10.1016/j.scitotenv.2019.02.011,
2019.
Li, Z., Huang, S., Liu, D., Leng, G., Zhou, S., and Huang, Q.: Assessing the
effects of climate change and human activities on runoff variations from a
seasonal perspective, Stoch. Env. Res. Risk A.,
34, 575–592, https://doi.org/10.1007/s00477-020-01785-1, 2020a.
Li, Z., Li, Q., Wang, J., Feng, Y., and Shao, Q.: Impacts of projected
climate change on runoff in upper reach of Heihe River basin using climate
elasticity method and GCMs, Sci. Total Environ., 716, 137072,
https://doi.org/10.1016/j.scitotenv.2020.137072, 2020b.
Liang, W., Bai, D., Wang, F., Fu, B., Yan, J., Wang, S., Yang, Y., Long, D.,
and Feng, M.: Quantifying the impacts of climate change and ecological
restoration on streamflow changes based on a Budyko hydrological model in
China's Loess Plateau, Water Resour. Res., 51, 6500–6519, 2015.
Liu, J., Chen, J., Xu, J., Lin, Y., Yuan, Z., and Zhou, M.: Attribution of
Runoff Variation in the Headwaters of the Yangtze River Based on the Budyko
Hypothesis, Int. J. Environ. Res. Public Health, 16, https://doi.org/10.3390/ijerph16142506,
2019a.
Liu, J., Xu, S., Han, X., Chen, X., and He, R.: A Multi-Dimensional
Hydro-Climatic Similarity and Classification Framework Based on Budyko
Theory for Continental-Scale Applications in China, Water, 11, 319,
https://doi.org/10.3390/w11020319, 2019b.
Liu, N., Harper, R. J., Smettem, K. R. J., Dell, B., and Liu, S.: Responses
of streamflow to vegetation and climate change in southwestern Australia,
J. Hydrol., 572, 761–770, https://doi.org/10.1016/j.jhydrol.2019.03.005, 2019.
Liu, Z., Cheng, L., Zhou, G., Chen, X., Lin, K., Zhang, W., Chen, X., and
Zhou, P.: Global Response of Evapotranspiration Ratio to Climate Conditions
and Watershed Characteristics in a Changing Environment, J. Geophys. Res.-Atmos., 125, e2020JD032371, https://doi.org/10.1029/2020jd032371, 2020.
Lu, J., Sun, G., McNulty, S. G., and Amatya, D. M.: A comparison of six
potential evapotranspiration methods for regional use in the southeastern
United States, J. Am. Water Resour. Assoc.,
41, 621–633, 2005.
Lv, X., Zuo, Z., Ni, Y., Sun, J., and Wang, H.: The effects of climate and
catchment characteristic change on streamflow in a typical tributary of the
Yellow River, Sci. Rep., 9, 14535, https://doi.org/10.1038/s41598-019-51115-x, 2019.
McCurley Pisarello, K. L. and Jawitz, J. W.: Coherence of global hydroclimate classification systems, Hydrol. Earth Syst. Sci., 25, 6173–6183, https://doi.org/10.5194/hess-25-6173-2021, 2021.
Mezentsev, V.: More on the calculation of average total evaporation,
Meteorol. Gidrol, 5, 24–26, 1955.
Mianabadi, A., Davary, K., Pourreza-Bilondi, M., and Coenders-Gerrits, A. M.
J.: Budyko framework; towards non-steady state conditions, J. Hydrol., 588, 125089, https://doi.org/10.1016/j.jhydrol.2020.125089, 2020.
Milly, P.: Climate, soil water storage, and the average annual water
balance, Water Resour. Res., 30, 2143–2156, 1994.
Milly, P. C. D.: An analytic solution of the stochastic storage problem
applicable to soil water, Water Resour. Res., 29, 3755–3758,
https://doi.org/10.1029/93WR01934, 1993.
Milly, P. C. D., Kam, J., and Dunne, K. A.: On the Sensitivity of Annual
Streamflow to Air Temperature, Water Resour. Res., 54, 2624–2641,
https://doi.org/10.1002/2017WR021970, 2018.
Mo, S., Li, Z., Gou, K., Qin, L., and Shen, B.: Quantifying the Effects of
Climate Variability and Direct Human Activities on the Change in Mean Annual
Runoff for the Bahe River (Northwest China), J. Coast. Res.,
341, 81–89, https://doi.org/10.2112/jcoastres-d-16-00159.1, 2018.
Newman, A. J., Clark, M. P., Sampson, K., Wood, A., Hay, L. E., Bock, A., Viger, R. J., Blodgett, D., Brekke, L., Arnold, J. R., Hopson, T., and Duan, Q.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, 2015.
Newman, A., Sampson, K., Clark, M. P., Bock, A., Viger, R. J., Blodgett, D.: A large-sample watershed-scale hydrometeorological dataset for the contiguous USA, Boulder, CO, UCAR/NCAR [data set], https://doi.org/10.5065/D6MW2F4D, 2014.
Ning, T., Li, Z., and Liu, W.: Vegetation dynamics and climate seasonality jointly control the interannual catchment water balance in the Loess Plateau under the Budyko framework, Hydrol. Earth Syst. Sci., 21, 1515–1526, https://doi.org/10.5194/hess-21-1515-2017, 2017.
Ning, T., Zhou, S., Chang, F., Shen, H., Li, Z., and Liu, W.: Interaction of
vegetation, climate and topography on evapotranspiration modelling at
different time scales within the Budyko framework, Agr. Forest
Meteorol., 275, 59–68, https://doi.org/10.1016/j.agrformet.2019.05.001, 2019.
Ning, T., Li, Z., Feng, Q., Chen, W., and Li, Z.: Effects of forest cover
change on catchment evapotranspiration variation in China, Hydrol. Process., 34, 2219-2228, 10.1002/hyp.13719, 2020a.
Ning, T., Liu, W., Li, Z., and Feng, Q.: Modelling and attributing
evapotranspiration changes on China's Loess Plateau with Budyko framework
considering vegetation dynamics and climate seasonality, Stoch. Env. Res. Risk A., 34, 1217–1230, https://doi.org/10.1007/s00477-020-01813-0
2020b.
Ol'Dekop, E.:Evaporation from the surface of river basins (Bcgapeyie c]
godepxyocnb pexysx], acceqyod]), Collection of the Works of Students of the
Meteorological Observatory. University of Tartu-Jurjew-Dorpat, Tartu, Estonia,, 4, p. 209., 1911.
Padrón, R. S., Gudmundsson, L., Greve, P., and Seneviratne, S. I.:
Large-Scale Controls of the Surface Water Balance Over Land: Insights From a
Systematic Review and Meta-Analysis, Water Resour. Res., 53,
9659-9678, 10.1002/2017wr021215, 2017.
Porporato, A., Daly, E., and Rodriguez-Iturbe, I.: Soil water balance and
ecosystem response to climate change, Am. Nat., 164, 625–632,
2004.
Qiu, H., Niu, J., and Phanikumar, M. S.: Quantifying the space – time
variability of water balance components in an agricultural basin using a
process-based hydrologic model and the Budyko framework, Sci. Total Environ.,
676, 176–189, https://doi.org/10.1016/j.scitotenv.2019.04.147, 2019.
Reaver, N. G. F., Kaplan, D. A., Klammler, H., and Jawitz, J. W.: Technical Note: Analytical Inversion of the Parametric Budyko Equations, Hydrol. Earth Syst. Sci. Discuss. [preprint], https://doi.org/10.5194/hess-2020-585, 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.
Rodriguez-Iturbe, I., Porporato, A., Ridolfi, L., Isham, V., and Coxi, D.:
Probabilistic modelling of water balance at a point: the role of climate,
soil and vegetation, P. Roy. Soc. A-Math. Phy., 455,
3789–3805, 1999.
Rubel, F., Brugger, K., Haslinger, K., and Auer, I.: The climate of the
European Alps: Shift of very high resolution Köppen-Geiger climate zones
1800–2100, Meteorol. Z., 26, 115–125,
https://doi.org/10.1127/metz/2016/0816, 2017.
Schaake, J., Cong, S., and Duan, Q.: The US MOPEX data set, IAHS
Publ., 307, 9, https://www.osti.gov/servlets/purl/899413, 2006.
Schreiber, P.: Über die Beziehungen zwischen dem Niederschlag und der
Wasserführung der Flüsse in Mitteleuropa, Meteorol. Z., 21, 441–452,
1904.
Shao, Q., Traylen, A., and Zhang, L.: Nonparametric method for estimating
the effects of climatic and catchment characteristics on mean annual
evapotranspiration, Water Resour. Res., 48, W03517, https://doi.org/10.1029/2010wr009610,
2012.
Shen, Q., Cong, Z., and Lei, H.: Evaluating the impact of climate and
underlying surface change on runoff within the Budyko framework: A study
across 224 catchments in China, J. Hydrol., 554, 251–262,
https://doi.org/10.1016/j.jhydrol.2017.09.023, 2017.
Singh, R. and Kumar, R.: Vulnerability of water availability in India due
to climate change: A bottom-up probabilistic Budyko analysis, Geophys. Res. Lett., 42, 9799–9807, 10.1002/2015gl066363, 2015.
Sinha, J., Das, J., Jha, S., and Goyal, M. K.: Analysing model disparity in
diagnosing the climatic and human stresses on runoff variability over India,
J. Hydrol., 581, 124407, https://doi.org/10.1016/j.jhydrol.2019.124407, 2020.
Song, X., Sun, W., Zhang, Y., Song, S., Li, J., and Gao, Y.: Using
hydrological modelling and data-driven approaches to quantify mining
activities impacts on centennial streamflow, J. Hydrol., 585, 124764,
https://doi.org/10.1016/j.jhydrol.2020.124764, 2020.
Sposito, G.: Incorporating the Vadose Zone into the Budyko Framework, Water,
9, 698, https://doi.org/10.3390/w9090698, 2017a.
Sposito, G.: Understanding the Budyko Equation, Water, 9, 236,
https://doi.org/10.3390/w9040236, 2017b.
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.
Thornthwaite, C. W.: An approach toward a rational classification of
climate, Geogr. Rev., 38, 55–94, 1948.
Tixeront, J.: Prévision des apports des cours d'eau, Symposium sur les
Eau de surface, Assemblée générale de l'IUGG, Berkeley, 118–126, 1964.
Trenberth, K. E.: Changes in precipitation with climate change, Clim. Res., 47, 123–138, https://doi.org/10.3354/cr00953, 2011.
Turc, L.: Le bilan d'eau des sols: relations entre les précipitations,
l'évaporation et l'écoulement, 491–595,
1953.
van der Velde, Y., Vercauteren, N., Jaramillo, F., Dekker, S. C., Destouni,
G., and Lyon, S. W.: Exploring hydroclimatic change disparity via the Budyko
framework, Hydrol. Process., 28, 4110–4118, https://doi.org/10.1002/hyp.9949, 2014.
Wang, C., Wang, S., Fu, B., and Zhang, L.: Advances in hydrological
modelling with the Budyko framework: A review, Prog. Phys. Geogr., 40, 409–430, https://doi.org/10.1177/0309133315620997, 2016.
Wang, D. and Hejazi, M.: Quantifying the relative contribution of the
climate and direct human impacts on mean annual streamflow in the contiguous
United States, Water Resour. Res., 47, W00J12, https://doi.org/10.1029/2010wr010283,
2011.
Wang, D. and Tang, Y.: A one-parameter Budyko model for water balance
captures emergent behavior in darwinian hydrologic models, Geophys. Res. Lett., 41, 4569–4577, https://doi.org/10.1002/2014gl060509, 2014.
Wang, F., Duan, K., Fu, S., Gou, F., Liang, W., Yan, J., and Zhang, W.:
Partitioning climate and human contributions to changes in mean annual
streamflow based on the Budyko complementary relationship in the Loess
Plateau, China, Sci. Total Environ., 665, 579–590,
https://doi.org/10.1016/j.scitotenv.2019.01.386, 2019.
Wang, J.-P., François, B., and Lambert, P.: Equations for hydraulic
conductivity estimation from particle size distribution: A dimensional
analysis, Water Resour. Res., 53, 8127–8134, https://doi.org/10.1002/2017wr020888,
2017.
Wang, T., Yang, H., Yang, D., Qin, Y., and Wang, Y.: Quantifying the
streamflow response to frozen ground degradation in the source region of the
Yellow River within the Budyko framework, J. Hydrol., 558,
301–313, https://doi.org/10.1016/j.jhydrol.2018.01.050, 2018.
Wang, W., Zou, S., Shao, Q., Xing, W., Chen, X., Jiao, X., Luo, Y., Yong,
B., and Yu, Z.: The analytical derivation of multiple elasticities of runoff
to climate change and catchment characteristics alteration, J. Hydrol., 541, 1042–1056, https://doi.org/10.1016/j.jhydrol.2016.08.014, 2016.
Wu, C., Yeh, P. J. F., Wu, H., Hu, B. X., and Huang, G.: Global Analysis of
the Role of Terrestrial Water Storage in the Evapotranspiration Estimated
from the Budyko Framework at Annual to Monthly Time Scales, J. Hydrometeorol., 20, 2003–2021, https://doi.org/10.1175/jhm-d-19-0065.1, 2019.
Xiangyu, Z., Chao, Z., and Jinyan, Y.: Quantitative Analysis of Impact of
Climate Variability and Human Activities on Water Resources Change in Suzhou
City, IOP Conference Series: Earth and Environmental Science, https://doi.org/10.1088/1755-1315/435/1/012015, 012015, 2020.
Xin, Z., Li, Y., Zhang, L., Ding, W., Ye, L., Wu, J., and Zhang, C.:
Quantifying the relative contribution of climate and human impacts on
seasonal streamflow, J. Hydrol., 574, 936–945,
https://doi.org/10.1016/j.jhydrol.2019.04.095, 2019.
Xing, W., Wang, W., Shao, Q., and Yong, B.: Identification of dominant
interactions between climatic seasonality, catchment characteristics and
agricultural activities on Budyko-type equation parameter estimation,
J. Hydrol., 556, 585–599, https://doi.org/10.1016/j.jhydrol.2017.11.048, 2018a.
Xing, W., Wang, W., Zou, S., and Deng, C.: Projection of future runoff
change using climate elasticity method derived from Budyko framework in
major basins across China, Global Planet. Change, 162, 120–135,
https://doi.org/10.1016/j.gloplacha.2018.01.006, 2018b.
Xu, X., Liu, W., Scanlon, B. R., Zhang, L., and Pan, M.: Local and global
factors controlling water-energy balances within the Budyko framework,
Geophys. Res. Lett., 40, 6123–6129, https://doi.org/10.1002/2013gl058324, 2013.
Xu, X., Yang, D., Yang, H., and Lei, H.: Attribution analysis based on the
Budyko hypothesis for detecting the dominant cause of runoff decline in
Haihe basin, J. Hydrol., 510, 530–540,
https://doi.org/10.1016/j.jhydrol.2013.12.052, 2014.
Yang, D., Sun, F., Liu, Z., Cong, Z., Ni, G., and Lei, Z.: Analyzing spatial
and temporal variability of annual water-energy balance in nonhumid regions
of China using the Budyko hypothesis, Water Resour. Res., 43, W04426,
https://doi.org/10.1029/2006wr005224, 2007.
Yang, D., Shao, W., Yeh, P. J. F., Yang, H., Kanae, S., and Oki, T.: Impact
of vegetation coverage on regional water balance in the nonhumid regions of
China, Water Resour. Res., 45, W00A14, https://doi.org/10.1029/2008wr006948, 2009.
Yang, H., Yang, D., Lei, Z., and Sun, F.: New analytical derivation of the
mean annual water-energy balance equation, Water Resour. Res., 44, W03410, https://doi.org/10.1029/2007wr006135, 2008.
Yang, H. and Yang, D.: Derivation of climate elasticity of runoff to assess
the effects of climate change on annual runoff, Water Resour. Res.,
47, W07526, https://doi.org/10.1029/2010wr009287, 2011.
Yang, Y., Donohue, R. J., and McVicar, T. R.: Global estimation of effective
plant rooting depth: Implications for hydrological modeling, Water Resour. Res., 52, 8260–8276, https://doi.org/10.1002/2016wr019392, 2016.
Yang, Y., Zhang, S., McVicar, T. R., Beck, H. E., Zhang, Y., and Liu, B.:
Disconnection between trends of atmospheric drying and continental runoff,
Water Resour. Res., 54, 4700–4713, https://doi.org/10.1029/2018wr022593, 2018.
Yao, A. Y. M.: Agricultural potential estimated from the ratio of actual to
potential evapotranspiration, Agr. Meteorol., 13, 405–417,
https://doi.org/10.1016/0002-1571(74)90081-8, 1974.
Yeh, H.-F. and Tsao, J.: Hydrological Response to Natural and Anthropogenic
Factors in Southern Taiwan, Sustainability, 12, https://doi.org/10.3390/su12051981, 2020.
Young, D., Zegre, N., Edwards, P., and Fernandez, R.: Assessing streamflow
sensitivity of forested headwater catchments to disturbance and climate
change in the central Appalachian Mountains region, USA, Sci. Total Environ.,
694, 133382, https://doi.org/10.1016/j.scitotenv.2019.07.188, 2019.
Zhang, K., Ruben, G. B., Li, X., Li, Z., Yu, Z., Xia, J., and Dong, Z.: A
comprehensive assessment framework for quantifying climatic and
anthropogenic contributions to streamflow changes: A case study in a typical
semi-arid North China basin, Environ. Modell. Softw., 128, 104704,
https://doi.org/10.1016/j.envsoft.2020.104704, 2020.
Zhang, L., Dawes, W., and Walker, G.: Response of mean annual
evapotranspiration to vegetation changes at catchment scale, Water Resour. Res., 37, 701–708, 2001.
Zhang, L., Hickel, K., Dawes, W. R., Chiew, F. H. S., Western, A. W., and
Briggs, P. R.: A rational function approach for estimating mean annual
evapotranspiration, Water Resour. Res., 40, W02502,
https://doi.org/10.1029/2003wr002710, 2004.
Zhang, S., Yang, H., Yang, D., and Jayawardena, A.: Quantifying the effect
of vegetation change on the regional water balance within the Budyko
framework, Geophys. Res. Lett., 43, 1140–1148, 2016.
Zhang, S., Yang, Y., McVicar, T. R., and Yang, D.: An Analytical Solution
for the Impact of Vegetation Changes on Hydrological Partitioning Within the
Budyko Framework, Water Resour. Res., 54, 519–537, https://doi.org/10.1002/2017WR022028,
2018.
Zhang, X., Dong, Q., Cheng, L., and Xia, J.: A Budyko-based framework for
quantifying the impacts of aridity index and other factors on annual runoff,
J. Hydrol., 579, 124224, https://doi.org/10.1016/j.jhydrol.2019.124224, 2019a.
Zhang, X., Dong, Q., Costa, V., and Wang, X.: A hierarchical Bayesian model
for decomposing the impacts of human activities and climate change on water
resources in China, Sci. Total Environ., 665, 836–847,
10.1016/j.scitotenv.2019.02.189, 2019b.
Zhao, J., Huang, S., Huang, Q., Leng, G., Wang, H., and Li, P.: Watershed
water-energy balance dynamics and their association with diverse influencing
factors at multiple time scales, Sci. Total Environ., 711, 135189,
https://doi.org/10.1016/j.scitotenv.2019.135189, 2020.
Zhou, S., Yu, B., Huang, Y., and Wang, G.: The complementary relationship
and generation of the Budyko functions, Geophys. Res. Lett., 42,
1781–1790, https://doi.org/10.1002/2015gl063511, 2015.
Zhou, S., Yu, B., Zhang, L., Huang, Y., Pan, M., and Wang, G.: A new method
to partition climate and catchment effect on the mean annual runoff based on
the Budyko complementary relationship, Water Resour. Res., 52, 7163–7177,
https://doi.org/10.1002/2016wr019046, 2016.
Short summary
The Budyko curve emerges globally from the behavior of multiple catchments. Single-parameter Budyko equations extrapolate the curve concept to individual catchments, interpreting curves and parameters as representing climatic and biophysical impacts on water availability, respectively. We tested these two key components theoretically and empirically, finding that catchments are not required to follow Budyko curves and usually do not, implying the parametric framework lacks predictive ability.
The Budyko curve emerges globally from the behavior of multiple catchments. Single-parameter...
