Articles | Volume 29, issue 8
https://doi.org/10.5194/hess-29-2109-2025
© 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-29-2109-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Apr 2025
Research article |
| 28 Apr 2025
| 28 Apr 2025
Evaluating the effects of topography and land use change on hydrological signatures: a comparative study of two adjacent watersheds
Haifan Liu
Department of Civil Engineering, University of Hong Kong, Hong Kong SAR, China
Haochen Yan
Department of Civil Engineering, University of Hong Kong, Hong Kong SAR, China
Department of Civil Engineering, University of Hong Kong, Hong Kong SAR, China
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Cited articles
Ayalew, T. B., Krajewski, W. F., and Mantilla, R.: Insights into expected changes in regulated flood frequencies due to the spatial configuration of flood retention ponds, J. Hydrol. Eng., 20, 04015010, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001229, 2015.
Bai, P., Liu, X., Zhang, Y., and Liu, C.: Assessing the impacts of vegetation greenness change on evapotranspiration and water yield in China, Water Resour. Res., 56, e2019WR027019, https://doi.org/10.1029/2019WR027019, 2020.
Baroni, G., Facchi, A., Gandolfi, C., Ortuani, B., Horeschi, D., and van Dam, J. C.: Uncertainty in the determination of soil hydraulic parameters and its influence on the performance of two hydrological models of different complexity, Hydrol. Earth Syst. Sci., 14, 251–270, https://doi.org/10.5194/hess-14-251-2010, 2010.
Bear, J.: Dynamics of fluids in porous media. Dover Publications, New York, NY, ISBN 9780486656755, 1988.
Beven, K. J.: Rainfall-runoff modelling: the primer, John Wiley & Sons, Chichester, UK, ISBN 9780470714591, 2012.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. B., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Beven, K. J, Young, P., Romanowicz, R., O'Connell, P. E., Ewen, J., O'Donnell, G., Holman, I., Posthumus, H., Morris, J., Hollis, J., Rose, S., Lamb, R., and Archer, D.: Analysis of historical data sets to look for impacts of land use and management change on flood generation, Final Report FD2120, Defra, London, 2008.
Blyth, E. M.: Estimating potential evaporation over a hill, Bound.-Lay. Meteorol., 92, 185–193, https://doi.org/10.1023/A:1001820114384, 1999.
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.
Brandhorst, N. and Neuweiler, I.: Impact of parameter updates on soil moisture assimilation in a 3D heterogeneous hillslope model, Hydrol. Earth Syst. Sci., 27, 1301–1323, https://doi.org/10.5194/hess-27-1301-2023, 2023.
Brath, A., Montanari, A., and Moretti, G.: Assessing the effect on flood frequency of land use change via hydrological simulation (with uncertainty), J. Hydrol., 324, 141–153, https://doi.org/10.1016/j.jhydrol.2005.10.001, 2006.
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.
Brown, C. F., Brumby, S. P., Guzder-Williams, B., Birch, T., Brooks Hyde, S., Mazzariello, J., Czerwinski, W., Pasquarella, V. J., Haertel, R., Ilyushchenko, S., Schwehr, K., Weisse, M., Stolle, F., Hanson, C., Guinan, O., Moore, R., and Tait, A. M.: Dynamic World, Near real-time global 10 m land use land cover mapping, Sci. Data, 9, 251, https://doi.org/10.1038/s41597-022-01307-4, 2022.
Buji Sub-district Office: Interpretation of the 2020 work plan for enhancing river water quality in the Shenzhen River Basin and improving sewage treatment efficiency in Buji Sub-district, Longgang District Buji Sub-district Office, https://www.lg.gov.cn/xxgk/zwgk/flfg/lgqzcwjjd/content/post_7829865.html (last access: 2 April 2024).
Cai, S., Fan, J., and Yang, W.: Flooding risk assessment and analysis based on GIS and the TFN-AHP method: A case study of Chongqing, China, Atmoshere, 12, 623, https://doi.org/10.3390/ATMOS12050623, 2021.
Camporese, M., Paniconi, C., Putti, M., and McDonnell, J. J.: Fill and Spill Hillslope Runoff Representation With a Richards Equation-Based Model, Water Resour. Res., 55, 8445–8462, https://doi.org/10.1029/2019WR025726, 2019.
Chan, F., Wright, N., Cheng, X., and Griffiths, J.: After Sandy: Rethinking Flood Risk Management in Asian Coastal Megacities, Nat. Hazards Rev., 15, 101–103, 2014.
Chan, F. K. S., Yang, L. E., Mitchell, G., Wright, N., Guan, M., Lu, X., Wang, Z., Montz, B., and Adekola, O.: Comparison of sustainable flood risk management by four countries – the United Kingdom, the Netherlands, the United States, and Japan – and the implications for Asian coastal megacities, Nat. Hazards Earth Syst. Sci., 22, 2567–2588, https://doi.org/10.5194/nhess-22-2567-2022, 2022.
Chen, Y. D.: Sustainable development and management of water resources for urban water supply in Hong Kong, Water Int., 26, 119–128, https://doi.org/10.1080/02508060108686891, 2001.
Cheng, J., Chen, M., and Tang, S.: Shenzhen – A typical benchmark of Chinese rapid urbanization miracle, Cities, 140, 104421, https://doi.org/10.1016/j.cities.2023.104421, 2023.
Chu, H.-J., Lin, Y.-P., Huang, C.-W., Hsu, C.-Y., and Chen, H.-Y.: Modelling the hydrologic effects of dynamic land-use change using a distributed hydrologic model and a spatial land-use allocation model, Hydrol. Process., 24, 2538–2554, https://doi.org/10.1002/hyp.7667, 2010.
Costa, M. H., Botta, A., and Cardille, J. A.: Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia, J. Hydrol., 283, 206–217, https://doi.org/10.1016/S0022-1694(03)00267-1, 2003.
Das, B. M.: Principles of geotechnical engineering, Brooks Cole/Thompson Learning, Pacific Grove, California, ISBN 9780534921309, 1990.
Detty, J. M. and McGuire, K. J.: Topographic controls on shallow groundwater dynamics: implications of hydrologic connectivity between hillslopes and riparian zones in a till mantled catchment, Hydrol. Process., 24, 2222–2236, https://doi.org/10.1002/hyp.7656, 2010.
Diem, J. E., Pangle, L. A., Milligan, R. A., and Adams, E. A.: Intra-annual variability of urban effects on streamflow, Hydrol. Process., 35, e14371, https://doi.org/10.1002/hyp.14371, 2021.
Du, J., Qian, L., Rui, H., Zuo, T., Zheng, D., Xu, Y., and Xu, C. Y.: Assessing the effects of urbanization on annual runoff and flood events using an integrated hydrological modeling system for Qinhuai River basin, China, J. Hydrol., 464, 127–139, https://doi.org/10.1016/j.jhydrol.2012.07.007, 2012.
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad-Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq, M., Shen, C., van Verseveld, W., Volk, J., and Yamazaki, D.: Hillslope hydrology in global change research and Earth system modeling, Water Resour. Res., 55, 1737–1772, https://doi.org/10.1029/2018WR023903, 2019.
Fatichi, S., Vivoni, E. R., Ogden, F. L., Ivanov, V. Y., Mirus, B., Gochis, D., Downer, C. W., Camporese, M., Davison, J. H., Ebel, B., Jones, N., Kim, J., Mascaro., G., Niswonger, R., Restrepo, P., Rigon, R., Shen, C., Sulis, M., and Tarboton, D.: An overview of current applications, challenges, and future trends in distributed process-based models in hydrology, J. Hydrol., 537, 45–60, https://doi.org/10.1016/j.jhydrol.2016.03.026, 2016.
Freeze, R. A. and Cherry, J. A.: Groundwater, Prentice Hall, Inc., Englewood Cliffs, N. J., ISBN 9780133653120, 1979.
Gao, H., Birkel, C., Hrachowitz, M., Tetzlaff, D., Soulsby, C., and Savenije, H. H. G.: A simple topography-driven and calibration-free runoff generation module, Hydrol. Earth Syst. Sci., 23, 787–809, https://doi.org/10.5194/hess-23-787-2019, 2019.
Garg, V., Aggarwal, S. P., Gupta, P. K., Nikam, B. R., Thakur, P. K., Srivastav, S. K., and Senthil Kumar, A.: Assessment of land use land cover change impact on hydrological regime of a basin, Environ. Earth Sci., 76, 1–17, https://doi.org/10.1007/s12665-017-6976-z, 2017.
GeoCloud: GeoCloud Platform, China Geological Survey, https://geocloud.cgs.gov.cn/ (last access: 2 April 2024).
Greater Bay Area: Overview of the Greater Bay Area, Constitutional and Mainland Affairs Bureau, https://www.bayarea.gov.hk/en/about/overview.html (last access: 17 December 2024).
Guan, M., Sillanpää, N., and Koivusalo, H.: Modelling and assessment of hydrological changes in a developing urban catchment, Hydrol. Process., 29, 2880–2894, https://doi.org/10.1002/hyp.10410, 2015.
Guo, K., Guan, M., Yan, H., and Xia, X.: A spatially distributed hydrodynamic model framework for urban flood hydrological and hydraulic processes involving drainage flow quantification, J. Hydrol., 625, 130–135, https://doi.org/10.1016/j.jhydrol.2023.130135, 2023.
Gwak, Y. and Kim, S.: Factors affecting soil moisture spatial variability for a humid forest hillslope, Hydrol. Process., 31, 431–445, https://doi.org/10.1002/hyp.11064, 2017.
Hauke, J. and Kossowski, T.: Comparison of Values of Pearson's and Spearman's Correlation Coefficients on the Same Sets of Data, Quaest. Geogr., 30, 87–93, https://doi.org/10.2478/v10117-011-0021-1, 2011.
He, J., Qiang, Y., Luo, H., Zhou, S., and Zhang, L. M.: A stress test of urban system flooding upon extreme rainstorms in Hong Kong, J. Hydrol., 597, 125713, https://doi.org/10.1016/J.JHYDROL.2020.125713, 2021.
Hopp, L. and McDonnell, J. J.: Connectivity at the hillslope scale: Identifying interactions between storm size, bedrock permeability, slope angle and soil depth, J. Hydrol., 376, 378–391, https://doi.org/10.1016/j.jhydrol.2009.07.047, 2009.
Im, S., Kim, H., Kim, C., and Jang, C.: Assessing the impacts of land use changes on watershed hydrology using MIKE SHE, Environ. Geol., 57, 231–239, https://doi.org/10.1007/s00254-008-1303-3, 2009.
Jarecke, K. M., Bladon, K. D., and Wondzell, S. M.: The influence of local and nonlocal factors on soil water content in a steep forested catchment, Water Resour. Res., 57, e2020WR028343, https://doi.org/10.1029/2020WR028343, 2021.
Jencso, K. G. and McGlynn, B. L.: Hierarchical controls on runoff generation: Topographically driven hydrologic connectivity, geology, and vegetation, Water Resour. Res., 47, W11527, https://doi.org/10.1029/2011WR010666, 2011.
Kopecký, M., Kopecký, M., Macek, M., and Wild, J.: Topographic wetness index calculation guidelines based on measured soil moisture and plant species composition, Sci. Total Environ., 757, 143785, https://doi.org/10.1016/J.SCITOTENV.2020.143785, 2021.
Kumar, M.: Toward a Hydrologic Modeling System, PhD Thesis, The Pennsylvania State University, University Park, PA, 273 pp., 2009.
Kumar, M., Duffy, C. J., and Salvage, K. M.: A Second-Order Accurate, Finite Volume–Based, Integrated Hydrologic Modeling (FIHM) Framework for Simulation of Surface and Subsurface Flow, Vadose Zone J., 8, 873–890, https://doi.org/10.2136/vzj2009.0014, 2009.
Kumar, M., Denis, D. M., Kundu, A., Joshi, N., and Suryavanshi, S.: Understanding land use/land cover and climate change impacts on hydrological components of Usri watershed, India, Appl. Water Sci., 12, 39, https://doi.org/10.1007/s13201-021-01547-6, 2022.
Larson, J., Lidberg, W., Ågren, A. M., and Laudon, H.: Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices, Hydrol. Earth Syst. Sci., 26, 4837–4851, https://doi.org/10.5194/hess-26-4837-2022, 2022.
Lee, E. and Kim, S.: Spatiotemporal soil moisture response and controlling factors along a hillslope, J. Hydrol., 605, 127382, https://doi.org/10.1016/j.jhydrol.2021.127382, 2022.
Li, Z., Liu, W.-z., Zhang, X.-c., and Zheng, F.-l.: Impacts of land use change and climate variability on hydrology in an agricultural catchment on the Loess Plateau of China, J. Hydrol., 377, 35–42, https://doi.org/10.1016/j.jhydrol.2009.08.007, 2009.
Liang, C. and Guan, M.: Effects of urban drainage inlet layout on surface flood dynamics and discharge, J. Hydrol., 632, 130890, https://doi.org/10.1016/j.jhydrol.2024.130890, 2024.
Lilliefors, H. W.: On the Kolmogorov–Smirnov test for normality with mean and variance unknown, J. Am. Stat. Assoc., 62, 399–402, https://doi.org/10.2307/2283970, 1967.
Liu, H., Yan, H., and Guan, M.: Dataset Open Research dataset: scenario inputs, element and river shapefiles, and land cover data, Zenodo [data set], https://doi.org/10.5281/zenodo.14539888, 2024.
Liu, H., Dai, H., Niu, J., Hu, B. X., Gui, D., Qiu, H., Ye, M., Chen, X., Wu, C., Zhang, J., and Riley, W.: Hierarchical sensitivity analysis for a large-scale process-based hydrological model applied to an Amazonian watershed, Hydrol. Earth Syst. Sci., 24, 4971–4996, https://doi.org/10.5194/hess-24-4971-2020, 2020.
Liu, J., Zhang, Q., Singh, V. P., and Shi, P.: Contribution of multiple climatic variables and human activities to streamflow changes across China, J. Hydrol., 545, 145–162, https://doi.org/10.1016/j.jhydrol.2016.12.048, 2017.
Maxwell, R. M., Putti, M., Meyerhoff, S., Delfs, J.-O., Ferguson, I. M., Ivanov, V., Kim, J., Kolditz, O., Kollet, S. J., Kumar, M., Lopez, S., Niu, J., Paniconi, C., Park, Y.-J., Phanikumar, M. S., Shen, C., Sudicky, E. A., and Sulis, M.: Surface-subsurface model intercomparison: a first set of benchmark results to diagnose integrated hydrology and feedbacks, Water Resour. Res., 50, 1531–1549, https://doi.org/10.1002/2013wr013725, 2014.
McGrane, S. J.: Impacts of urbanisation on hydrological and water quality dynamics, and urban water management: a review, Hydrolog. Sci. J., 61, 2295–2311, https://doi.org/10.1080/02626667.2015.1128084, 2016.
Mirus, B. B. and Loague, K.: How runoff begins (and ends): Characterizing hydrologic response at the catchment scale, Water Resour. Res., 49, 2987–3006, https://doi.org/10.1002/wrcr.20218, 2013.
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., and Veith, T. L.: Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, T. ASABE, 50, 885–900, 2007.
Neal, J. and Hawker, L. (Creators), Uhe, P., Paulo, L., Sosa, J., Savage, J., Sampson, C. (Contributors): FABDEM V1-2, University of Bristol, https://doi.org/10.5523/bris.s5hqmjcdj8yo2ibzi9b4ew3sn, 2023.
Niehoff, D., Fritsch, U., and Bronstert, A.: Land-use impacts on storm-runoff generation: scenarios of land-use change and simulation of hydrological response in a meso-scale catchment in SW-Germany, J. Hydrol., 267, 80–93, https://doi.org/10.1016/S0022-1694(02)00142-7, 2002.
Niu, J., Shen, C., Chambers, J. Q., Melack, J. M., and Riley, W. J.: Interannual variation in hydrologic budgets in an Amazonian watershed with a coupled subsurface–land surface process model, J. Hydrometeorol., 18, 2597–2617, https://doi.org/10.1175/JHM-D-17-0108.1, 2017.
Nobre, A. D., Cuartas, L. A., Hodnett, M., Rennó, C. D., Rodrigues, G., Silveira, A., and Saleska, S.: Height Above the Nearest Drainage–a hydrologically relevant new terrain model, J. Hydrol., 404, 13–29, https://doi.org/10.1016/j.jhydrol.2011.03.051, 2011.
O'Loughlin, E. M.: Prediction of Surface Saturation Zones in Natural Catchments by Topographic Analysis, Water Resour. Res., 22, 794–804, https://doi.org/10.1029/WR022i005p00794, 1986.
Olang, L. O. and Fürst, J.: Effects of land cover change on flood peak discharges and runoff volumes: model estimates for the Nyando River Basin, Kenya, Hydrol. Process., 25, 80–89, https://doi.org/10.1002/hyp.7821, 2011.
Pang, X., Gu, Y., Launiainen, S., and Guan, M.: Urban hydrological responses to climate change and urbanization in cold climates, Sci. Total Environ., 817, 153066, https://doi.org/10.1016/j.scitotenv.2022.153066, 2022.
Qi, W., Ma, C., Xu, H., Chen, Z., Zhao, K., and Han, H.: A review on applications of urban flood models in flood mitigation strategies, Nat. Hazards, 108, 1–32, https://doi.org/10.1007/S11069-021-04715-8, 2021.
Qu, Y. and Duffy, C. J.: A semidiscrete finite volume formulation for multiprocess watershed simulation, Water Resour. Res., 43, W08419, https://doi.org/10.1029/2006WR005752, 2007.
RESDC: Spatial distribution data of soil types in China, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, https://www.resdc.cn/Default.aspx (last access: 2 April 2024).
Rinderer, M., van Meerveld, H. J., and Seibert, J.: Topographic controls on shallow groundwater levels in a steep, prealpine catchment: When are the TWI assumptions valid?, Water Resour. Res., 50, 6067–6080, https://doi.org/10.1002/2013WR015009, 2014.
Seibert, J., Bishop, K., Rodhe, A., and McDonnell, J. J.: Groundwater dynamics along a hillslope: A test of the steady state hypothesis, Water Resour. Res., 39, 1, https://doi.org/10.1029/2002WR001404, 2003.
Shao, M., Zhao, G., Kao, S. C., Cuo, L., Rankin, C., and Gao, H.: Quantifying the effects of urbanization on floods in a changing environment to promote water security—A case study of two adjacent basins in Texas, J. Hydrol., 589, 125154, https://doi.org/10.1016/j.jhydrol.2020.125154, 2020.
Shen, C. and Phanikumar, M. S.: A process-based, distributed hydrologic model based on a large-scale method for surface–subsurface coupling, Adv. Water Resour., 33, 1524–1541, https://doi.org/10.1016/j.advwatres.2010.09.002, 2010.
Shi, Y., Davis, K. J., Zhang, F., Duffy, C. J., and Yu, X.: Parameter estimation of a physically based land surface hydrologic model using the ensemble Kalman filter: A synthetic experiment, Water Resour. Res., 50, 706–724, https://doi.org/10.1002/2013WR014070, 2014.
Shu, L.: Simulator for Hydrologic Unstructured Domains, GitHub [code], https://github.com/SHUD-System/SHUD (last access: 11 April 2024), 2019.
Shu, L., Ullrich, P. A., and Duffy, C. J.: Simulator for Hydrologic Unstructured Domains (SHUD v1.0): numerical modeling of watershed hydrology with the finite volume method, Geosci. Model Dev., 13, 2743–2762, https://doi.org/10.5194/gmd-13-2743-2020, 2020.
Shu, L., Ullrich, P., Meng, X., Duffy, C., Chen, H., and Li, Z.: rSHUD v2.0: advancing the Simulator for Hydrologic Unstructured Domains and unstructured hydrological modeling in the R environment, Geosci. Model Dev., 17, 497–527, https://doi.org/10.5194/gmd-17-497-2024, 2024.
SHUD Book: Theory, practice, and applications of the SHUD, SHUD, https://www.shud.xyz/book_en/ (last access: 2 April 2024).
Sicaud, E., Fortier, D., Dedieu, J.-P., and Franssen, J.: Pairing remote sensing and clustering in landscape hydrology for large-scale change identification: an application to the subarctic watershed of the George River (Nunavik, Canada), Hydrol. Earth Syst. Sci., 28, 65–86, https://doi.org/10.5194/hess-28-65-2024, 2024.
Siddik, Md. S., Tulip, S. S., Rahman, A., Islam, Md. N., Haghighi, A. T., and Mustafa, S. Md. T.: The impact of land use and land cover change on groundwater recharge in northwestern Bangladesh, J. Environ. Manage., 315, 115130, https://doi.org/10.1016/j.jenvman.2022.115130, 2022.
Singh, N. K., Emanuel, R. E., McGlynn, B. L., and Miniat, C. F.: Soil moisture responses to rainfall: Implications for runoff generation, Water Resour. Res., 57, e2020WR028827, https://doi.org/10.1029/2020WR028827, 2021.
Smith, J. A., Cox, A. A., Baeck, M. L., Yang, L., and Bates, P.: Strange floods: The upper tail of flood peaks in the United States, Water Resour. Res., 54, 6510–6542, https://doi.org/10.1029/2018WR022539, 2018.
Song, X., Zhang, J., Zhan, C., Xuan, Y., Ye, M., and Xu, C.: Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications, J. Hydrol., 523, 739–757, https://doi.org/10.1016/j.jhydrol.2015.02.013, 2015.
Sørensen, R., Zinko, U., and Seibert, J.: On the calculation of the topographic wetness index: evaluation of different methods based on field observations, Hydrol. Earth Syst. Sci., 10, 101–112, https://doi.org/10.5194/hess-10-101-2006, 2006.
Strahler, A. N.: Quantitative analysis of watershed geomorphology, Eos Trans. AGU, 38, 913–920, https://doi.org/10.1029/TR038i006p00913, 1957.
Thanapakpawin, P., Richey, J., Thomas, D., Rodda, S., Campbell, B., and Logsdon, M.: Effects of landuse change on the hydrologic regime of the Mae Chaem river basin, NW Thailand, J. Hydrol., 334, 215–230, https://doi.org/10.1016/j.jhydrol.2006.10.012, 2007.
Thornton, J. M., Therrien, R., Mariéthoz, G., Linde, N., and Brunner, P.: Simulating fully-integrated hydrological dynamics in complex Alpine headwaters: Potential and challenges, Water Resour. Res., 58, e2020WR029390, https://doi.org/10.1029/2020WR029390, 2022.
Van Genuchten, M. T.: A Closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
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.
Yan, H., Guan, M., and Kong, Y.: Flood Retention Lakes in a Rural-Urban Catchment: Climate-Dominated and Configuration-Affected Performances, Water Resour. Res., 59, e2022WR032911, https://doi.org/10.1029/2022WR032911, 2023.
Yan, H., Gao, Y., Wilby, R., Yu, D., Wright, N., Yin, J., Chen, X., Chen, J., and Guan, M.: Urbanization further intensifies short-duration rainfall extremes in a warmer climate, Geophys. Res. Lett., 51, e2024GL108565, https://doi.org/10.1029/2024GL108565, 2024.
Yang, H., Zhang, L., Gao, L., Phoon, K.-K., and Wei, X.: On the importance of landslide management: Insights from a 32-year database of landslide consequences and rainfall in Hong Kong, Eng. Geol., 299, 106578, https://doi.org/10.1016/j.enggeo.2022.106578, 2022.
Yang, L., Smith, J. A., Baeck, M. L., and Zhang, Y.: Flash flooding in small urban watersheds: Storm event hydrologic response, Water Resour. Res., 52, 4571–4589, https://doi.org/10.1002/2016WR018699, 2016.
Yang, L., Smith, J., and Niyogi, D.: Urban impacts on extreme monsoon rainfall and flooding in complex terrain, Geophys. Res. Lett., 46, 5918–5927, https://doi.org/10.1029/2019GL083315, 2019.
Yereseme, A. K., Surendra, H. J., and Kuntoji, G.: Sustainable integrated urban flood management strategies for planning of smart cities: a review, Sustain, Water Resour. Manag., 8, 6665, https://doi.org/10.1007/s40899-022-00666-5, 2022.
Yin, J., Gao, Y., Chen, R., Yu, D., Wilby, R., Wright, N., Ge, Y., Bricker, J., Gong, H., and Guan, M.: Flash floods: why are more of them devastating the world's driest regions?, J. Hydrol., 15, 225–240, https://doi.org/10.1038/d41586-023-00626-9, 2023.
Yu, X., Luo, L., Hu, P., Tu, X., Chen, X., and Wei, J.: Impacts of sea-level rise on groundwater inundation and river floods under changing climate, J. Hydrol., 614, 128554, https://doi.org/10.1016/j.jhydrol.2022.128554, 2022.
Zanetti, F., Botter, G., and Camporese, M.: Stream Network Dynamics of Non-Perennial Rivers: Insights From Integrated Surface-Subsurface Hydrological Modeling of Two Virtual Catchments, Water Resour. Res., 60, e2023WR035631, https://doi.org/10.1029/2023WR035631, 2024.
Zhang, J., Zhang, Y., Sun, G., Song, C., Li, J., Hao, L., and Liu, N.: Climate variability masked greening effects on water yield in the Yangtze River Basin during 2001–2018, Water Resour. Res., 58, e2021WR030382, https://doi.org/10.1029/2021WR030382, 2022a.
Zhang, M., Liu, N., Harper, R., Li, Q., Liu, K., Wei, X., Ning, D., and Liu, S.: A global review on hydrological responses to forest change across multiple spatial scales: Importance of scale, climate, forest type and hydrological regime, J. Hydrol., 546, 44–59, https://doi.org/10.1016/j.jhydrol.2017.01.024, 2017.
Zhang, X., Jiao, J. J., and Guo, W.: How Does Topography Control Topography-Driven Groundwater Flow?, Geophys. Res. Lett., 49, e2022GL101005, https://doi.org/10.1029/2022GL101005, 2022b.
Zhou, G., Wei, X., Chen, X., Zhou, P., Liu, X., Xiao, Y., Sun, G., Scott, D. F., Zhou, S., Han, L., and Su, Y.: Global pattern for the effect of climate and land cover on water yield, Nat. Commun., 6, 5918, https://doi.org/10.1038/ncomms6918, 2015.
Short summary
Land changes and landscape features critically impact water systems. Studying two watersheds in China’s Greater Bay Area, we found slope strongly influences water processes in mountainous areas. However, this relationship is weak in the lower regions of steeper watersheds. Urbanization leads to an increase in annual surface runoff, while flatter watersheds exhibit a buffering capacity against this effect. However, this buffering capacity diminishes with increasing annual rainfall intensity.
Land changes and landscape features critically impact water systems. Studying two watersheds in...
