Articles | Volume 18, issue 2
https://doi.org/10.5194/hess-18-775-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-775-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
26 Feb 2014
Research article |
| 26 Feb 2014
Attribution of hydrologic forecast uncertainty within scalable forecast windows
State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Y. Sun
State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
Department of Civil and Environmental Engineering, Princeton University, New Jersey 08540, USA
H. Hu
State Key Laboratory of Hydro-science and Engineering, Department of Hydraulic Engineering, Tsinghua University, Beijing 100084, China
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Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Heidi Kreibich, Kai Schröter, Giuliano Di Baldassarre, Anne F. Van Loon, Maurizio Mazzoleni, Guta Wakbulcho Abeshu, Svetlana Agafonova, Amir AghaKouchak, Hafzullah Aksoy, Camila Alvarez-Garreton, Blanca Aznar, Laila Balkhi, Marlies H. Barendrecht, Sylvain Biancamaria, Liduin Bos-Burgering, Chris Bradley, Yus Budiyono, Wouter Buytaert, Lucinda Capewell, Hayley Carlson, Yonca Cavus, Anaïs Couasnon, Gemma Coxon, Ioannis Daliakopoulos, Marleen C. de Ruiter, Claire Delus, Mathilde Erfurt, Giuseppe Esposito, Didier François, Frédéric Frappart, Jim Freer, Natalia Frolova, Animesh K. Gain, Manolis Grillakis, Jordi Oriol Grima, Diego A. Guzmán, Laurie S. Huning, Monica Ionita, Maxim Kharlamov, Dao Nguyen Khoi, Natalie Kieboom, Maria Kireeva, Aristeidis Koutroulis, Waldo Lavado-Casimiro, Hong-Yi Li, Maria Carmen LLasat, David Macdonald, Johanna Mård, Hannah Mathew-Richards, Andrew McKenzie, Alfonso Mejia, Eduardo Mario Mendiondo, Marjolein Mens, Shifteh Mobini, Guilherme Samprogna Mohor, Viorica Nagavciuc, Thanh Ngo-Duc, Huynh Thi Thao Nguyen, Pham Thi Thao Nhi, Olga Petrucci, Nguyen Hong Quan, Pere Quintana-Seguí, Saman Razavi, Elena Ridolfi, Jannik Riegel, Md Shibly Sadik, Nivedita Sairam, Elisa Savelli, Alexey Sazonov, Sanjib Sharma, Johanna Sörensen, Felipe Augusto Arguello Souza, Kerstin Stahl, Max Steinhausen, Michael Stoelzle, Wiwiana Szalińska, Qiuhong Tang, Fuqiang Tian, Tamara Tokarczyk, Carolina Tovar, Thi Van Thu Tran, Marjolein H. J. van Huijgevoort, Michelle T. H. van Vliet, Sergiy Vorogushyn, Thorsten Wagener, Yueling Wang, Doris E. Wendt, Elliot Wickham, Long Yang, Mauricio Zambrano-Bigiarini, and Philip J. Ward
Earth Syst. Sci. Data, 15, 2009–2023, https://doi.org/10.5194/essd-15-2009-2023, https://doi.org/10.5194/essd-15-2009-2023, 2023
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Yuxin Li, Sisi Chen, Jun Yin, and Xing Yuan
Hydrol. Earth Syst. Sci., 27, 1077–1087, https://doi.org/10.5194/hess-27-1077-2023, https://doi.org/10.5194/hess-27-1077-2023, 2023
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Ruidong Li, Ting Sun, Fuqiang Tian, and Guang-Heng Ni
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We developed SHAFTS (Simultaneous building Height And FootprinT extraction from Sentinel imagery), a multi-task deep-learning-based Python package, to estimate average building height and footprint from Sentinel imagery. Evaluation in 46 cities worldwide shows that SHAFTS achieves significant improvement over existing machine-learning-based methods.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 26, 4147–4167, https://doi.org/10.5194/hess-26-4147-2022, https://doi.org/10.5194/hess-26-4147-2022, 2022
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Tracer-aided hydrological models are useful tool to reduce uncertainty of hydrological modeling in cold basins, but there is little guidance on the sampling strategy for isotope analysis, which is important for large mountainous basins. This study evaluated the reliance of the tracer-aided modeling performance on the availability of isotope data in the Yarlung Tsangpo river basin, and provides implications for collecting water isotope data for running tracer-aided hydrological models.
Yongping Wei, Jing Wei, Gen Li, Shuanglei Wu, David Yu, Mohammad Ghoreishi, You Lu, Felipe Augusto Arguello Souza, Murugesu Sivapalan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 26, 2131–2146, https://doi.org/10.5194/hess-26-2131-2022, https://doi.org/10.5194/hess-26-2131-2022, 2022
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There is increasing tension among the riparian countries of transboundary rivers. This article proposes a socio-hydrological framework that incorporates the slow and less visible societal processes into existing hydro-economic models, revealing the slow and hidden feedbacks between societal and hydrological processes. This framework will contribute to process-based understanding of the complex mechanism that drives conflict and cooperation in transboundary river management.
Liying Guo, Jing Wei, Keer Zhang, Jiale Wang, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 26, 1165–1185, https://doi.org/10.5194/hess-26-1165-2022, https://doi.org/10.5194/hess-26-1165-2022, 2022
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Data support is crucial for the research of conflict and cooperation on transboundary rivers. Conventional, manual constructions of datasets cannot meet the requirements for fast updates in the big data era. This study brings up a revised methodological framework, based on the conventional method, and a toolkit for the news media dataset tracking of conflict and cooperation dynamics on transboundary rivers. A dataset with good tradeoffs between data relevance and coverage is generated.
Junjiang Liu, Xing Yuan, Junhan Zeng, Yang Jiao, Yong Li, Lihua Zhong, and Ling Yao
Hydrol. Earth Syst. Sci., 26, 265–278, https://doi.org/10.5194/hess-26-265-2022, https://doi.org/10.5194/hess-26-265-2022, 2022
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Hourly streamflow ensemble forecasts with the CSSPv2 land surface model and ECMWF meteorological forecasts reduce both the probabilistic and deterministic forecast error compared with the ensemble streamflow prediction approach during the first week. The deterministic forecast error can be further reduced in the first 72 h when combined with the long short-term memory (LSTM) deep learning method. The forecast skill for LSTM using only historical observations drops sharply after the first 24 h.
Yi Nan, Zhihua He, Fuqiang Tian, Zhongwang Wei, and Lide Tian
Hydrol. Earth Syst. Sci., 25, 6151–6172, https://doi.org/10.5194/hess-25-6151-2021, https://doi.org/10.5194/hess-25-6151-2021, 2021
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Hydrological modeling has large problems of uncertainty in cold regions. Tracer-aided hydrological models are increasingly used to reduce uncertainty and refine the parameterizations of hydrological processes, with limited application in large basins due to the unavailability of spatially distributed precipitation isotopes. This study explored the utility of isotopic general circulation models in driving a tracer-aided hydrological model in a large basin on the Tibetan Plateau.
Kunbiao Li, Fuqiang Tian, Mohd Yawar Ali Khan, Ran Xu, Zhihua He, Long Yang, Hui Lu, and Yingzhao Ma
Earth Syst. Sci. Data, 13, 5455–5467, https://doi.org/10.5194/essd-13-5455-2021, https://doi.org/10.5194/essd-13-5455-2021, 2021
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Due to complex climate and topography, there is still a lack of a high-quality rainfall dataset for hydrological modeling over the Tibetan Plateau. This study aims to establish a high-accuracy daily rainfall product over the southern Tibetan Plateau through merging satellite rainfall estimates based on a high-density rainfall gauge network. Statistical and hydrological evaluation indicated that the new dataset outperforms the raw satellite estimates and several other products of similar types.
Cited articles
Beven, K.: Changing Ideas in Hydrology – The Case of Physically-Based Models, J. Hydrol., 105, 157–172, 1989.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, 1992.
Day, G.: Extended streamflow forecasting using NWSRFS, J. Water Resour. Plann. Manage., 111, 157–170, 1985.
Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II, evolutionary computation, IEEE Trans., 6, 182–197, https://doi.org/10.1109/4235.996017, 2002.
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: Effect of different uncertainty sources on the skill of 10 day ensemble low flow forecasts for two hydrological models, Water Resour. Res., 49, 4035–4053, https://doi.org/10.1002/wrcr.20294, 2013.
Guo, S., Guo, J., Zhang, J., and Chen, H.: VIC distributed hydrological model to predict climate change impact in the Hanjiang basin, Sci. China Ser. E, 52, 3234–3239, 2009.
Hamlet, A. and Lettenmaier, D.: Columbia river streamflow forecasting based on ENSO and PDO climate signals, J. Water Resour. Plann. Manage., 125, 333–341, 1999.
Hashino, T., Bradley, A. A., and Schwartz, S. S.: Evaluation of bias-correction methods for ensemble streamflow volume forecasts, Hydrol. Earth Syst. Sci., 11, 939–950, https://doi.org/10.5194/hess-11-939-2007, 2007.
Hoeting, J. A., Madigan, D., Raftery, A. E., and Volinsky, C. T.: Bayesian model averaging: A tutorial, Stat. Sci., 14, 382–401, 1999.
Kang, T. H., Kim, Y. O., and Hong, I. P.: Comparison of pre- and post-processors for ensemble streamflow prediction, Atmos. Sci. Lett., 11, 153–159, 2010.
Kirkby, M. J.: Hillslope Hydrology, John Wiely, Hoboken, New Jersey, 1978.
Koster, R. D., Mahanama, S. P. P., Livneh, B., Lettenmaier, D. P., and Reichle, R. H.: Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow, Nat. Geosci., 3, 613–616, 2010.
Lamb, K.: Improving ensemble streamflow prediction using interdecadal-interannual climate variability, Doctoral thesis, University of Nevada, Las Vegas, 2010.
Li, H., Luo, L., Wood, E. F., and Schaake, J.: The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting, J. Geophys. Res.-Atmos., 114, D04114, https://doi.org/10.1029/2008JD010969, 2009.
Li, H., Sivapalan, M., and Tian, F.: Comparative diagnostic analysis of runoff generation processes in Oklahoma DMIP2 basins: The Blue River and the Illinois River, J. Hydrol., 418–419, 90–109, 2012.
Liu, D., Tian, F., Hu, H., and Hu, H.: The role of run-on for overland flow and the characteristics of runoff generation in the Loess Plateau, China, Hydrol. Sci. J., 57, 1107–1117, 2012.
Luo, L. and Wood, E. F.: Use of Bayesian merging techniques in a multimodel seasonal hydrologic ensemble prediction system for the eastern United States. J. Hydrometeorol., 9, 866-884, 2008.
Mahanama, S. P. P., Koster, R. D., Reichle, R. H., and Zubair, L.: The role of soil moisture initialization in subseasonal and seasonal streamflow prediction-A case study in Sri Lanka, Adv. Water Resour., 31, 1333–1343, 2008.
Mahanama, S., Livneh, B., Koster, R., Lettenmaier, D., and Reichle, R.: Soil moisture, snow, and seasonal streamflow forecasts in the United States, J. Hydrometeorol., 13, 189–203, 2011.
Maurer, E. P. and Lettenmaier, D. P.: Predictability of seasonal runoff in the Mississippi River basin, J. Geophys. Res.-Atmos., 108, 8607, https://doi.org/10.1029/2002JD002555, 2003.
Mou, L., Tian, F., Hu, H., and Sivapalan, M.: Extension of the representative elementary watershed approach for cold regions: constitutive relationships and an application, Hydrol. Earth Syst. Sci., 12, 565–585, https://doi.org/10.5194/hess-12-565-2008, 2008.
Nash, J. E. and Sutcliffe, J. V.: River flow forecasting through conceptual models part I-a discussion of principles, J. Hydrol., 10, 282–290, 1970.
Reed, P., Minsker, B. S., and Goldberg, D. E.: Simplifying multiobjective optimization: An automated design methodology for the nondominated sorted genetic algorithm-II, Water Resour. Res., 39, 1196, https://doi.org/10.1029/2002WR001483, 2003.
Reggiani, P., Hassanizadeh, S. M., Sivapalan, M., and Gray, W. G.: A unifying framework for watershed thermodynamics: constitutive relationships, Adv. Water Resour., 23, 15–39, 1999.
Shi, X., Wood, A. W., and Lettenmaier, D. P.: How essential is hydrologic model calibration to seasonal streamflow forecasting?, J. Hydrometeorol., 9, 1350–1363, 2008.
Shukla, S. and Lettenmaier, D. P.: Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill, Hydrol. Earth Syst. Sci, 15, 3529–3538, https://doi.org/10.5194/hess-15-3529-2011, 2011.
Shukla, S., Sheffield, J., Wood, E. F., and Lettenmaier, D. P.: On the sources of global land surface hydrologic predictability, Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, 2013.
Singla, S., Céron, J. P., Martin, E., Regimbeau, F., Déqué, M., Habets, F., and Vidal, J. P.: Predictability of soil moisture and river flows over France for the spring season, Hydrol. Earth Syst. Sci., 16, 201–216, https://doi.org/10.5194/hess-16-201-2012, 2012.
Smith, J., Day, G., and Kane, M.: Nonparametric framework for long-range streamflow forecasting, J. Water Resour. Plann. Manage., 118, 82–92, 1992.
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., 58, 170–180, 2014.
Tian, F.: Study on thermodynamic watershed hydrological modeling (THModel), Doctoral thesis, Tsinghua University, Beijing, China, 168 pp., 2006.
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., Mou L., and Hu H.: Characteristic of soil water retention curve on the macroscale, Sci. China Ser. E, 52, 2990–2996, 2009.
Tian, F., Li, H., and Sivapalan, M.: Model diagnostic analysis of seasonal switching of runoff generation mechanisms in the Blue River basin, Oklahoma, J. Hydrol., 418–419, 136–149, 2012.
Walker, W. E., Harremoes, P., Rotmans, J., Sluijs, J. P. v. d., Asselt, M. B. A. v., Janssen, P., and Krauss, M. P. K. v.: Defining uncertainty: a conceptual basis for uncertainty management in model-based decision support, Integr. Assess., 4, 5–17, 2005.
Wang, E., Zhang, Y., Luo, J., Chiew, F. H. S., and Wang, Q. J.: Monthly and seasonal streamflow forecasts using rainfall-runoff modeling and historical weather data, Water Resour. Res., 47, W05516, https://doi.org/10.1029/2010WR009922, 2011.
Werner, K., Brandon, D., Clark, M., and Gangopadhyay, S.: Climate index weighting schemes for NWS ESP-based seasonal volume forecasts, J. Hydrometeol., 5, 1076–1090, 2004.
Wood, A. W. and Lettenmaier, D. P.: An ensemble approach for attribution of hydrologic prediction uncertainty, Geophy. Res. Let., 35, L14401, https://doi.org/10.1029/2008GL034648, 2008.
Wood, A. W. and Schaake, J. C.: Correcting errors in streamflow forecast ensemble mean and spread, J. Hydrometeorol., 9, 132–148, 2008.
Wood, A. W., Kumar, A., and Lettenmaier, D. P.: A retrospective assessment of national centers for environmental prediction climate model–based ensemble hydrologic forecasting in the western United States, J. Geophys. Res.-Atmos., 110, D04115, https://doi.org/10.1029/2004JD004508, 2005.
Yang, L., Tian, F., and Hu, H.: Modified ESP with the information of atmospheric circulation and teleconnection incorporated and its application, J. Tsinghua University (Science and Technology), 53, 606–612, 2013.
Yuan, X. and Wood, E. F.: Downscaling precipitation or bias-correcting streamflow? some implications for coupled general circulation model (CGCM)-based ensemble seasonal hydrologic forecast, Water Resour. Res., 48, W12519, https://doi.org/10.1029/2012WR012256, 2012.
Yuan, X., Wood, E. F., Roundy, J. K., and Pan, M.: CFSv2-based seasonal hydro climatic forecasts over conterminous United States, J. Climate, 26, 4828–4847, https://doi.org/10.1175/JCLI-D-12-00683.1, 2013.
Zappa, M., Jaun, S., Germann, U., Walser, A., and Fundel, F.: Superposition of three sources of uncertainties in operational flood forecasting chains, Atmos. Res., 100, 246–262, 2011.
Zhou, M., Tian, F., Lall, U., and Hu, H.: Insights from a joint analysis of Indian and Chinese monsoon rainfall data, Hydrol. Earth Syst. Sci., 15, 2709–2715, https://doi.org/10.5194/hess-15-2709-2011, 2011.
