Articles | Volume 29, issue 7
https://doi.org/10.5194/hess-29-1919-2025
© Author(s) 2025. 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-29-1919-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Apr 2025
Research article |
| 15 Apr 2025
| 15 Apr 2025
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Mahmut Tudaji
Department of Hydraulic Engineering and State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Department of Hydraulic Engineering and State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
Fuqiang Tian
Department of Hydraulic Engineering and State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China
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Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
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Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
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You Lu, Fuqiang Tian, Liying Guo, Iolanda Borzì, Rupesh Patil, Jing Wei, Dengfeng Liu, Yongping Wei, David J. Yu, and Murugesu Sivapalan
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The upstream countries in the transboundary Lancang–Mekong basin build dams for hydropower, while downstream ones gain irrigation and fishery benefits. Dam operation changes the seasonality of runoff downstream, resulting in their concerns. Upstream countries may cooperate and change their regulations of dams to gain indirect political benefits. The socio-hydrological model couples hydrology, reservoir, economy, and cooperation and reproduces the phenomena, providing a useful model framework.
Jing Wei, Yongping Wei, Fuqiang Tian, Natalie Nott, Claire de Wit, Liying Guo, and You Lu
Hydrol. Earth Syst. Sci., 25, 1603–1615, https://doi.org/10.5194/hess-25-1603-2021, https://doi.org/10.5194/hess-25-1603-2021, 2021
Liming Wang, Songjun Han, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 25, 375–386, https://doi.org/10.5194/hess-25-375-2021, https://doi.org/10.5194/hess-25-375-2021, 2021
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It remains unclear at which timescale the complementary principle performs best in estimating evaporation. In this study, evaporation estimation was assessed over 88 eddy covariance monitoring sites at multiple timescales. The results indicate that the generalized complementary functions perform best in estimating evaporation at the monthly scale. This study provides a reference for choosing a suitable time step for evaporation estimations in relevant studies.
Cited articles
Andréassian, V., Perrin, C., Michel, C., Usart-Sanchez, I., and Lavabre, J.: Impact of imperfect rainfall knowledge on the efficiency and the parameters of watershed models, J. Hydrol., 250, 206–223, https://doi.org/10.1016/s0022-1694(01)00437-1, 2001.
Blöschl, G. and Sivapalan, M.: Scale issues in hydrological modelling: A review, Hydrol. Process., 9, 251–290, https://doi.org/10.1002/hyp.3360090305, 1995.
Creutin, J. and Obled, C.: Modelling spatial and temporal characteristics of rainfall as input to a flood forecasting model, IAHS-AISH Publication (129), 41–49, Oxford, Eng., IAHS, 1980.
Cui, T., Li, Y., Yang, L., Nan, Y., Li, K., Tudaji, M., Hu, H., Long, D., Shahid, M., Mubeen, A., He, Z., Yong, B., Lu, H., Li, C., Ni, G., Hu, C., and Tian, F.: Non-monotonic changes in Asian Water Towers' streamflow at increasing warming levels, Nat. Commun., 14, 1176, https://doi.org/10.1038/s41467-023-36804-6, 2023.
Didan, K.: MODIS/Terra Vegetation Indices 16-Day L3 Global 500m SIN Grid V061 [data set], https://doi.org/10.5067/MODIS/MOD13A1.061, 2021.
Eriksson, D., Bindel, D., and Shoemaker, C. A.: pySOT and POAP: An event-driven asynchronous framework for surrogate optimization, arXiv [preprint], https://doi.org/10.48550/arXiv.1908.00420, 2019.
Ficchì, A., Perrin, C., and Andréassian, V.: Impact of temporal resolution of inputs on hydrological model performance: An analysis based on 2400 flood events, J. Hydrol., 538, 454–470, https://doi.org/10.1016/j.jhydrol.2016.04.016, 2016.
Gabellani, S., Boni, G., Ferraris, L., von Hardenberg, J., and Provenzale, A.: Propagation of uncertainty from rainfall to runoff: A case study with a stochastic rainfall generator, Adv. Water Resour., 30, 2061-2071, https://doi.org/10.1016/j.advwatres.2006.11.015, 2007.
Han, D. and Bray, M.: Automated Thiessen polygon generation, Water Resour. Res., 42, https://doi.org/10.1029/2005WR004365, 2006.
Huang, Y., Bárdossy, A., and Zhang, K.: Sensitivity of hydrological models to temporal and spatial resolutions of rainfall data, Hydrol. Earth Syst. Sci., 23, 2647–2663, https://doi.org/10.5194/hess-23-2647-2019, 2019.
Jeong, J., Kannan, N., Arnold, J. G., Glick, R., Gosselink, L., Srinivasan, R., and Harmel, R. D.: Development of sub-daily erosion and sediment transport algorithms for swat, T. Asabe, 54, 1685–1691, https://doi.org/10.13031/2013.39841, 2011.
Jie, M.-X., Chen, H., Xu, C.-Y., Zeng, Q., Chen, J., Kim, J.-S., Guo, S.-L., and Guo, F.-Q.: Transferability of Conceptual Hydrological Models Across Temporal Resolutions: Approach and Application, Water Resour. Manag., 32, 1367–1381, https://doi.org/10.1007/s11269-017-1874-4, 2018.
Kandel, D. D., Western, A. W., and Grayson, R. B.: Scaling from process timescales to daily time steps: A distribution function approach, Water Resour. Res., 41, W02003, https://doi.org/10.1029/2004wr003380, 2005.
Kandel, D. D., Western, A. W., Grayson, R. B., and Turra, H. N.: Process parameterization and temporal scaling in surface runoff and erosion modelling, Hydrol. Process., 18, 1423–1446, https://doi.org/10.1002/hyp.1421, 2004.
Kannan, N., White, S. M., Worrall, F., and Whelan, M. J.: Sensitivity analysis and identification of the best evapotranspiration and runoff options for hydrological modelling in SWAT-2000, J. Hydrol., 332, 456–466, https://doi.org/10.1016/j.jhydrol.2006.08.001, 2007.
Kavetski, D., Fenicia, F., and Clark, M. P.: Impact of temporal data resolution on parameter inference and model identification in conceptual hydrological modeling: Insights from an experimental catchment, Water Resour. Res., 47, W05501, https://doi.org/10.1029/2010wr009525, 2011.
Li, Y., Jiang, Y., Lei, X., Tian, F., Duan, H., and Lu, H.: Comparison of Precipitation and Streamflow Correcting for Ensemble Streamflow Forecasts, Water, 10, 177, https://doi.org/10.3390/w10020177, 2018.
Li, Z., Chen, M., Gao, S., Wen, Y., Gourley, J. J., Yang, T., Kolar, R., and Hong, Y.: Can re-infiltration process be ignored for flood inundation mapping and prediction during extreme storms? A case study in Texas Gulf Coast region, Environ. Modell. Softw., 155, 105450, https://doi.org/10.1016/j.envsoft.2022.105450, 2022.
Melsen, L. A., Teuling, A. J., Torfs, P. J. J. F., Uijlenhoet, R., Mizukami, N., and Clark, M. P.: HESS Opinions: The need for process-based evaluation of large-domain hyper-resolution models, Hydrol. Earth Syst. Sci., 20, 1069–1079, https://doi.org/10.5194/hess-20-1069-2016, 2016.
Mou, L., Tian, F., and Hu, H.: Artificial neural network model of runoff prediction in high and cold mountainous regions: A case study in the source drainage area of Urumqi River, J. Hydroel. Eng., 62–67, https://caod.oriprobe.com/articles/15688549/Artificial_neural_network_model_of_runoff_prediction_in_high_and_cold_.htm (last access: 15 March 2024), 2009.
Muñoz Sabater, J.: ERA5-Land monthly averaged data from 1981 to present, Copernicus Climate Change Service (C3S) Climate Data Store (CDS), https://doi.org/10.24381/cds.68d2bb30, 2019.
Myneni, R., Knyazikhin, Y., and Park, T.: MODIS/Terra Leaf Area Index/FPAR 8-Day L4 Global 500m SIN Grid V061, NASA EOSDIS Land Processes Distributed Active Archive Center [data set], Doi10.5067/MODIS/MOD15A2H.061, 2021.
Nan, Y. and Tian, F.: Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau, Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, 2024a.
Nan, Y. and Tian, F.: Isotope data-constrained hydrological model improves soil moisture simulation and runoff source apportionment, J. Hydrol., 633, 131006, https://doi.org/10.1016/j.jhydrol.2024.131006, 2024b.
Nan, Y., Tian, L., He, Z., Tian, F., and Shao, L.: The value of water isotope data on improving process understanding in a glacierized catchment on the Tibetan Plateau, Hydrol. Earth Syst. Sci., 25, 3653–3673, https://doi.org/10.5194/hess-25-3653-2021, 2021.
Obled, C., Zin, I., and Hingray, B.: Choix des pas de temps et d'espace pour des modélisations parcimonieuses en hydrologie des crues, La Houille Blanche, 81–87, https://doi.org/10.1051/lhb/2009059, 2009.
Oudin, L., Perrin, C., Mathevet, T., Andréassian, V., and Michel, C.: Impact of biased and randomly corrupted inputs on the efficiency and the parameters of watershed models, J. Hydrol., 320, 62–83, https://doi.org/10.1016/j.jhydrol.2005.07.016, 2006.
Reynolds, J. E., Halldin, S., Xu, C. Y., Seibert, J., and Kauffeldt, A.: Sub-daily runoff predictions using parameters calibrated on the basis of data with a daily temporal resolution, J. Hydrol., 550, 399–411, https://doi.org/10.1016/j.jhydrol.2017.05.012, 2017.
Seibert, J., Clerc-Schwarzenbach, F. M., and van Meerveld, H. J.: Getting your money's worth: Testing the value of data for hydrological model calibration, Hydrol. Process., 38, e15094, https://doi.org/10.1002/hyp.15094, 2024.
Socolofsky, S., Adams, E., and Entekhabi, D.: Disaggregation of daily rainfall for continuous watershed modeling, J. Hydrol. Eng., 6, 300–309, https://doi.org/10.1061/(asce)1084-0699(2001)6:4(300), 2001.
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, F., Hu, H., Lei, Z., and Sivapalan, M.: Extension of the Representative Elementary Watershed approach for cold regions via explicit treatment of energy related processes, Hydrol. Earth Syst. Sci., 10, 619–644, https://doi.org/10.5194/hess-10-619-2006, 2006.
Tian, F., Hu, H., and Lei, Z.: Thermodynamic watershed hydrological model: Constitutive relationship, Sci. China Ser. E, 51, 1353–1369, https://doi.org/10.1007/s11431-008-0147-0, 2008.
Tudaji, M., Nan, Y., and Tian, F.: Assesing the Value of High-Resolution Data and Parameters Transferability Across Temporal Scales in Hydrological Modeling: A Case Study in Northern China, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2966, 2024.
Viglione, A., Chirico, G. B., Komma, J., Woods, R., Borga, M., and Bloschl, G.: Quantifying space-time dynamics of flood event types, J. Hydrol., 394, 213–229, https://doi.org/10.1016/j.jhydrol.2010.05.041, 2010.
Xu, M., Fralick, D., Zheng, J. Z., Wang, B., Tu, X. M., and Feng, C.: The differences and similarities between two-sample t-test and paired t-test, Shanghai Archives of Psychiatry, 29, 184–188, https://doi.org/10.11919/j.issn.1002-0829.217070, 2017.
Xu, R., Hu, H., Tian, F., Li, C., and Khan, M. Y. A.: Projected climate change impacts on future streamflow of the Yarlung Tsangpo-Brahmaputra River, Glob. Planet. Change, 175, 144–159, https://doi.org/10.1016/j.gloplacha.2019.01.012, 2019.
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F., Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy map of global terrain elevations, Geophys. Res. Lett., 44, 5844–5853, https://doi.org/10.1002/2017GL072874, 2017.
Younis, J., Anquetin, S., and Thielen, J.: The benefit of high-resolution operational weather forecasts for flash flood warning, Hydrol. Earth Syst. Sci., 12, 1039–1051, https://doi.org/10.5194/hess-12-1039-2008, 2008.
Yu, B., Cakurs, U., and Rose, C. W.: An assessment of methods for estimating runoff rates at the plot scale, T. ASABE, 41, 653–661, https://doi.org/10.13031/2013.17233, 1998.
Zhang, J., Lin, P., Gao, S., and Fang, Z.: Understanding the re-infiltration process to simulating streamflow in North Central Texas using the WRF-hydro modeling system, J. Hydrol., 587, 124902, https://doi.org/10.1016/j.jhydrol.2020.124902, 2020.
Zhao, R., Wang, P., and Hu, F.: Relations between parameter values and corresponding natural conditions of Xinanjiang Model, Journal of Hohai University, 20, 52–59, 1992.
Short summary
Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
Common intuition holds that higher input data resolution leads to better results. To assess the...
