Abstract
Hydrological monitoring and seasonal forecasting is an active research field because of its potential applications in hydrological risk assessment, preparedness and mitigation. In recent decades, developments in ground and satellite measurements have made the hydrometeorological information readily available, and advances in information technology have facilitated the data analysis in a real-time manner. New progress in climate research and modeling has enabled the prediction of seasonal climate with reasonable accuracy and increased resolution. These emerging techniques and advances have enabled more timely acquisition of accurate hydrological fluxes and status, and earlier warning of extreme hydrological events such as droughts and floods. This paper gives current state-of-the-art understanding of the uncertainties in hydrological monitoring and forecasting, reviews the efforts and progress in operational hydrological monitoring system assisted by observations from various sources and experimental seasonal hydrological forecasting, and briefly introduces the current monitoring and forecasting practices in China. The grand challenges and perspectives for the near future are also discussed, including acquiring and extracting reliable information for monitoring and forecasting, predicting realistic hydrological fluxes and states in the river basin being significantly altered by human activity, and filling the gap between numerical models and the end user. We highlight the importance of understanding the needs of the operational water management and the priority to transfer research knowledge to decision-makers.
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References
Ajami N K, Duan Q, Sorooshian S, 2007. An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction. Water Resources Research, 43: W01403.
Andreadis K M, Clark E A, Wood A W et al., 2005. Twentieth-century drought in the conterminous United States. Journal of Hydrometeorology, 6(6): 985–1001.
Andreadis K M, Lettenmaier D P, 2006. Assimilating remotely sensed snow observations into a macroscale hydrology model. Advances in Water Resources, 29: 872–886.
Bao H, Zhao L, 2012. Flood forecast of Huaihe River based on TIGGE Ensemble Prediction. Journal of Hydraulic Engineering, 43(2): 216–224.
Barnston A G, Tippett M K, L’Heureux M L et al., 2012. Skill of real-time seasonal ENSO model predictions during 2002-11: Is our capability increasing? Bulletin of the American Meteorological Society, 93: 631–651.
Bastola S, Misra V, Li H, 2013. Seasonal hydrological forecasts for watersheds over the southeastern United States for the boreal summer and fall seasons. Earth Interactions, 17: 1–22.
Below R, Grover-Kopec E, Dilley M, 2007. Documenting drought-related disasters: A global reassessment. The Journal of Environment & Development, 16: 328–344.
Beven K J, Binley A M, 1992. The future of distributed models: model calibration and uncertainty prediction. Hydrological Processes, 6: 279–298.
Bierkens M, van Beek L, 2009. Seasonal predictability of European discharge: NAO and hydrological response time. Journal of Hydrometeorology, 10: 953–968.
Clark M P, Rupp D E, Woods R A et al., 2008. Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model. Advances in Water Resources, 31: 1309–1324.
Day G N, 1985. Extended streamflow forecasting using NWSRFS. Journal of Water Resources Planning and Management (ASCE), 111: 157–170.
De Lannoy G, Reichle R H, Arsenault K R et al., 2012. Multiscale assimilation of Advanced Microwave Scanning Radiometer-EOS snow water equivalent and Moderate Resolution Imaging Spectroradiometer snow cover fraction observations in northern Colorado. Water Resources Research, 48: W01522.
De Lannoy G, Reichle R H, Houser P R et al., 2010. Satellite-scale snow water equivalent assimilation into a high-resolution land surface model. Journal of Hydrometeorology, 11: 352–369.
De Sales F, Xue Y, 2013. Dynamic downscaling of CFS winter seasonal simulations with the UCLAETA regional climate model over the United States. Climate Dynamics, 41: 255–275.
Demargne J, 2014. The science of NOAA’s operational hydrologic ensemble forecast service. Bulletin of the American Meteorological Society, 95: 79–98.
Di C L, Yang X H, Wang X C, 2014. A four-stage hybrid model for hydrological time series forecasting. PLoS One, 9(8): e104663.
Döll P, Fiedler K, Zhang J, 2009. Global-scale analysis of river flow alterations due to water withdrawals and reservoirs. Hydrology and Earth System Sciences, 13: 2413–2432.
Duan Q, Schaake J, Andréassian V et al., 2006. Model Parameter Estimation Experiment (MOPEX): An overview of science strategy and major results from the second and third workshops. Journal of Hydrology, 320: 3–17.
Duan Q, Sorooshian S, Gupta V, 1992. Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research, 28(4): 1015–1031.
Entekhabi D, Njoku E G, O’Neill P E et al., 2010. The Soil Moisture Active Passive (SMAP) Mission. Proceedings of the IEEE, 98: 704–716.
Evensen G, 1997. Advanced data assimilation in strongly nonlinear dynamics. Monthly Weather Review, 125: 1342–1354.
Ferguson I M, Maxwell R M, 2012. Human impacts on terrestrial hydrology: Climate change versus pumping and irrigation. Environmental Research Letters, 7: 044022.
Fujii H, Koike T, Imaoka K, 2009. Improvement of the AMSR-E algorithm for soil moisture estimation by introducing a fractional vegetation coverage dataset derived from MODIS data. Journal of the Remote Sensing Society of Japan, 29(1): 282–292.
Gao H, Tang Q, Ferguson C R et al., 2010. Estimating the water budget of major U.S. river basins via remote sensing. International Journal of Remote Sensing, 31: 3955–3978.
Garen D C, 1992. Improved techniques in regression-based streamflow volume forecasting. Journal of Water Resources Planning and Management (ASCE), 118: 654–670.
Gerten D, Rost S, von Bloh W et al., 2008. Causes of change in 20th century global river discharge. Geophysical Research Letters, 35: L20405.
Glahn H R, Lowry D A, 1972. The use of Model Output Statistics (MOS) in objective weather forecasting. Journal of Applied Meteorology and Climatology, 11(8): 1203–1211.
Haddeland I, Clark D B, Franssen W et al., 2011. Multimodel estimate of the global terrestrial water balance: Setup and first results. Journal of Hydrometeorology, 12: 869–884.
Hamlet A F, Lettenmaier D P, 1999. Columbia River streamflow forecasting based on ENSO and PDO climate signals. Journal of Water Resources Planning and Management (ASCE), 125(6): 333–341.
Han E, Crow W T, Holmes T et al., 2014. Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring. Journal of Hydrometeorology, 15: 1117–1134.
He X, Zhao T, Yang D, 2013. Prediction of monthly inflow to the Danjiangkou reservoir by distributed hydrological model and hydro-climatic teleconnections. Journal of Hydroelectric Engineering, 32(3): 4–9.
Hirabayashi Y, Kanae S, Emori S et al., 2008. Global projections of changing risks of floods and droughts in a changing climate. Hydrological Sciences Journal, 53(4): 754–772.
Hirabayashi Y, Mahendran R, Koirala S et al., 2013. Global flood risk under climate change. Nature Climate Change, 3: 816–821.
Hong Y, Adler R F, Hossain F et al., 2007. A first approach to global runoff simulation using satellite rainfall estimation. Water Resources Research, 43: W08502.
Hou A Y, Kakar R K, Neeck S et al., 2014. The Global Precipitation Measurement Mission. Bulletin of the American Meteorological Society, 95: 701–722.
Houborg R, Rodell M, Li B et al., 2012. Drought indicators based on model-assimilated Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage observations. Water Resources Research, 48: W07525.
Hu S S, Zheng H X, Liu C M et al., 2012. Assessing the impacts of climate variability and human activities on streamflow in the water source area of Baiyangdian Lake. Acta Geographica Sinica, 67(1): 62–70. (in Chinese)
Huang X, Xiao Q N, Barker D M et al., 2009. Four-dimensional variational data assimilation for WRF: Formulation and preliminary results. Monthly Weather Review, 137: 299–314.
Huffman G J, Bolvin D T, Nelkin E J et al., 2007. The TRMM multisatellite precipitation analysis (TMPA): Quasi-global, multiyear, combined-sensor precipitation estimates at fine scales. Journal of Hydrometeorology, 8(1): 38–55.
Kavetski D, Franks S W, Kuczera G, 2002. Confronting input uncertainty in environmental modeling. In: Duan Q, Gupta H, Sorooshian S et al. (eds.). Calibration of Watershed Models. Water Science and Application Series 6, American Geophysical Union, Washington D. C.: 49–68.
Kim S, Liu Y Y, Johnson F M et al., 2015. A global comparison of alternate AMSR2 soil moisture products: Why do they differ? Remote Sensing of Environment, 161: 43–52.
Koster R D, Mahanama S, Livneh B et al., 2010. Skill in streamflow forecasts derived from large-scale estimates of soil moisture and snow. Nature Geoscience, 3: 613–616.
Krishnamurti T N, Kishtawal C M, LaRow T E et al., 1999. Improved weather and seasonal climate forecasts from multimodel superensemble. Science, 285: 1548–1550
Krzysztofowicz R, Sigrest A A, 1999. Calibration of probabilistic quantitative precipitation forecasts. Weather Forecast, 14(3): 427–442.
Kwon H-H, Brown C, Xu K et al., 2009. Seasonal and annual maximum streamflow forecasting using climate information: Application to the Three Gorges Dam in the Yangtze River basin, China. Hydrological Sciences Journal, 54: 582–595.
Lan Y H, Ding Y J, Kang E et al., 2003. The relationship between ENSO cycle and high and low-flow in the upper Yellow River. Journal of Geographical Sciences, 13(1): 105–111.
Leng G, Huang M, Tang Q et al., 2013. Modeling the effects of irrigation on land surface fluxes and states over the conterminous United States: Sensitivity to input data and model parameters. Journal of Geophysical Research: Atmospheres, 118(17): 9789–9803.
Leng G, Huang M, Tang Q et al., 2014. Modeling the effects of groundwater-fed irrigation on terrestrial hydrology over the conterminous United States. Journal of Hydrometeorology, 15: 957–972.
Leng G Y, Tang Q H, Huang S Z et al., 2016. Assessments of joint hydrological extreme risks in a warming climate in China. International Journal of Climatology, 36: 1632–1642
Leng G Y, Tang Q H, Rayburg S, 2015. Climate change impacts on meteorological, agricultural and hydrological droughts in China. Global and Planetary Change, 126: 23–34.
Li H, Luo L, Wood E F, 2008. Seasonal hydrologic predictions of low-flow conditions over eastern USA during the 2007 drought. Atmospheric Science Letters, 9: 61–66.
Li H, Luo L, Wood E F, Schaake J, 2009. The role of initial conditions and forcing uncertainties in seasonal hydrologic forecasting. Journal of Geophysical Research: Atmospheres, 114: D04114.
Li Q Z, Yan N N, Zhang F F et al., 2010. Drought monitoring and its impacts assessment in Southwest China using remote sensing in the spring of 2010. Acta Geographica Sinica, 65(7): 771–780. (in Chinese)
Li X, Liu S M, Xiao Q et al., 2013. Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific objectives and experimental design. Bulletin of the American Meteorological Society, 94: 1145–1160
Li X, Toshio K, Mahadevan P, 2004. A very fast simulated re-annealing (VFSA) approach for land data assimilation. Computers & Geosciences, 30: 239–248.
Li Y, Hu J, Wang J et al., 2008. Application of Ensemble Streamflow Prediction (ESP) to medium- and long-term water resources prediction. Journal of China Hydrology, 28(1): 25–27.
Liu F, Chen S L, Dong P et al., 2012. Spatial and temporal variability of water discharge in the Yellow River Basin over the past 60 years. Journal of Geographical Sciences, 22(6): 1013–1033.
Liu J, Zhang J, 2005. Development and prospects of hydrological forecasting technique in China. Journal of China Hydrology, 25(6): 1–5. (in Chinese)
Liu Y, Weerts A H, Clark M et al., 2012. Advancing data assimilation in operational hydrologic forecasting: Progresses, challenges, and emerging opportunities. Hydrology and Earth System Sciences, 16: 3863–3887.
Lu G H, Wu Z Y, Wen L et al., 2008. Real-time flood forecast and flood alert map over the Huaihe River Basin in China using a coupled hydro-meteorological modeling system. Science in China, Series E: Technological Sciences, 51(7): 1049–1063.
Luo L, Wood E F, 2007. Monitoring and predicting the 2007 U.S. drought. Geophysical Research Letters, 34: L22702.
Luo L, Wood E F, 2008. Use of Bayesian merging techniques in a multimodel seasonal hydrologic ensemble prediction system for the eastern United States. Journal of Hydrometeorology, 9: 866–884.
Luo L, Wood E F, Pan M, 2007. Bayesian merging of multiple climate model forecasts for seasonal hydrological predictions. Journal of Geophysical Research: Atmospheres, 112: D10102.
Ma F, Yuan X, Ye A, 2015. Seasonal drought predictability and forecast skill over China. Journal of Geophysical Research, 120: 8264–8275.
Maurer E P, Lettenmaier D P, Mantua N J, 2004. Variability and potential sources of predictability of North American runoff. Water Resources Research, 40(9): W09306.
Maurer E P, Wood A W, Adam J C et al., 2002. A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States. Journal of Climate, 15: 3237–3251.
Milly P C D, Wetherald R T, Dunne K A et al., 2002. Increasing risk of great floods in a changing climate. Nature, 415: 514–517.
Mitchell K E, Lohmann D, Houser P R et al., 2004. The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system. Journal of Geophysical Research: Atmospheres, 109: D07S90.
Mo K C, Lettenmaier D P, 2014. Hydrologic prediction over the conterminous United States using the National Multi-Model Ensemble. Journal of Hydrometeorology, 15: 1457–1472.
Mo K C, Shukla S, Lettenmaier D P et al., 2012). Do Climate Forecast System (CFSv2) forecasts improve seasonal SM prediction? Geophysical Research Letters, 39: L23703.
Nijssen B, Shukla S, Lin C Y et al., 2014. A prototype global drought information system based on multiple land surface models. Journal of Hydrometeorology, 15: 1661–1676.
Pagano T C, Garen D C, Perkins T R et al., 2009. Daily updating of operational statistical seasonal water supply forecasts for the western U.S. Journal of the American Water Resources Association (JAWRA), 45: 767–778.
Pan M, Sahoo A K, Troy T J, 2012. Multisource estimation of long-term terrestrial water budget for major global river basins. Journal of Climate, 25: 3191–3206.
Pan M, Wood E F, Wojcik R et al., 2008. Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation. Remote Sensing of Environment, 112(4): 1282–1294.
Pozzi W, Sheffield J, Stefanski R et al., 2013. Toward global drought early warning capability: Expanding international cooperation for the development of a framework for monitoring and forecasting. Bulletin of the American Meteorological Society, 94: 776–785.
Raftery A E, Gneiting T, Balabdaoui F et al., 2005. Using Bayesian model averaging to calibrate forecast ensembles. Monthly Weather Review, 133: 1155–1174.
Robertson D E, Wang Q J, 2012. A Bayesian approach to predictor selection for seasonal streamflow forecasting. Journal of Hydrometeorology, 13: 155–171.
Rodell M, Houser P R, Jambor U et al., 2004. The Global Land Data Assimilation System. Bulletin of the American Meteorological Society, 85: 381–394.
Saha S, Moorthi S, Wu X R et al., 2014. The NCEP climate forecast system version 2. Journal of Climate, 27: 2185–2208.
Schaake J, Demargne J, Hartman R et al., 2007. Precipitation and temperature ensemble forecasts from single- value forecasts. Hydrology and Earth System Sciences, 4: 655–717.
Sheffield J, Ferguson C R, Troy T J et al., 2009. Closing the terrestrial water budget from satellite remote sensing. Geophysical Research Letters, 36: L07403.
Sheffield J, Wood E F, 2007. Characteristics of global and regional drought, 1950–2000: Analysis of soil moisture data from off-line simulation of the terrestrial hydrologic cycle. Journal of Geophysical Research: Atmospheres, 112: D17115.
Sheffield J, Wood E F, 2008. Global trends and variability in soil moisture and drought characteristics, 1950–2000, from observation-driven simulations of the terrestrial hydrologic cycle. Journal of Climate, 21: 432–458.
Sheffield J, Wood E F, Chaney N et al., 2014. A drought monitoring and forecasting system for sub-Sahara African water resources and food security. Bulletin of the American Meteorological Society, 95: 861–882.
Shukla S, Lettenmaier D P, 2011a. Seasonal hydrologic prediction in the United States: Understanding the role of initial hydrologic conditions and seasonal climate forecast skill. Hydrology and Earth System Sciences, 15: 3529–3538.
Shukla S, Lettenmaier D P, 2013. Multi-RCM ensemble downscaling of NCEP CFS winter season forecasts: Implications for seasonal hydrologic forecast skill. Journal of Geophysical Research: Atmospheres, 118: 10770–10790.
Shukla S, Steinemann A C, Lettenmaier D P, 2011b. Drought monitoring for Washington State: Indicators and applications. Journal of Hydrometeorology, 12: 66–83.
Shukla S, Sheffield J, Wood E F et al., 2013. On the sources of global land surface hydrologic predictability. Hydrology and Earth System Sciences, 17: 2781–2796.
Singh V P, Cui H, 2015. Entropy theory for streamflow forecasting. Environmental Processes, 2: 449–460.
Sinha T, Sankarasubramanian A, 2013. Role of climate forecasts and initial conditions in developing streamflow and soil moisture forecasts in a rainfall-runoff regime. Hydrology and Earth System Sciences, 17: 721–733.
Smith D M, Scaife A A, Kirtman B P, 2012. What is the current state of scientific knowledge with regard to seasonal to decadal forecasting. Environmental Research Letters, 7: 015602.
Staudinger M, Seibert J, 2014. Predictability of low flow: An assessment with simulation experiments. Journal of Hydrology, 519: 1383–1393.
Tang Q, Oki T, Kanae S et al., 2007. The influence of precipitation variability and partial irrigation within grid cells on a hydrological simulation. Journal of Hydrometeorology, 8: 499–512.
Tang Q, Oki T, Kanae S et al., 2008. Hydrological cycles change in the Yellow River basin during the last half of the 20th century. Journal of Climate, 21: 1790–1806.
Tang Q, Wood A W, Lettenmaier D P, 2009a. Real-time precipitation estimation based on index station percentiles. Journal of Hydrometeorology, 10: 266–277.
Tang Q, Gao H, Lu H et al., 2009b. Remote sensing: Hydrology. Progress in Physical Geography, 33: 490–509.
Tang Q, Peterson S, Cuenca R H et al., 2009c. Satellite-based near-real-time estimation of irrigated crop water consumption. Journal of Geophysical Research: Atmospheres, 114: D05114.
Tapley B D, Bettadpur S, Ries J C et al., 2004. GRACE measurements of mass variability in the Earth system. Science, 305(5683): 503–505.
Thober S, Kumar R, Sheffield J et al., 2015. Seasonal soil moisture drought prediction over Europe using the North American Multi-Model Ensemble (NMME). Journal of Hydrometeorology, 16: 2329–2344.
Tobin K J, Bennett M E, 2010. Adjusting satellite precipitation data to facilitate hydrologic modeling. Journal of Hydrometeorology, 11: 966–978.
van Dijk A, Peña-Arancibia J L, Wood E F et al., 2013. Global analysis of seasonal streamflow predictability using an ensemble prediction system and observations from 6192 small catchments worldwide. Water Resources Research, 49: 2729–2746.
Van Shaar J R, Haddeland I, Lettenmaier D P, 2002. Effects of land cover changes on the hydrologic response of interior Columbia River Basin forested catchments. Hydrological Processes, 16(13): 2499–2520.
Vogt J V, Barbosa P, Hofer B et al., 2011. Developing a European drought observatory for monitoring assessing and forecasting droughts across the European continent. AGU Fall Meeting Abstracts 1, NH24A–07.
Wang A, Lettenmaier D P, Sheffield J, 2011a. Soil moisture drought in China, 1950–2006. Journal of Climate, 24: 3257–3271.
Wang C, Duan Q, Gong W et al., 2014. An evaluation of adaptive surrogate modeling based optimization with two benchmark problems. Environmental Modelling & Software, 60: 167–179.
Wang C, Duan Q, Tong C H et al., 2016. A GUI platform for uncertainty quantification of complex dynamical models. Environmental Modelling & Software, 76: 1–12.
Wang E, Zhang Y, Luo J et al., 2011b. Monthly and seasonal streamflow forecasts using rainfall-runoff modeling and historical weather data. Water Resources Research, 47: W05516.
Wang X, Barker D M, Snyder C et al., 2008. A hybrid ETKF-3DVAR data assimilation scheme for the WRF model. Part I: Observing system simulation experiment. Monthly Weather Review, 136: 5116–5131.
Werner K, Brandon D, Clark M et al., 2004. Climate index weighting schemes for NWS ESP-based seasonal volume forecasts. Journal of Hydrometeorology, 5: 1076–1090.
Werner K, Brandon D, Clark M et al., 2005. Incorporating medium-range numerical weather model output into the ensemble streamflow prediction system of the National Weather Service. Journal of Hydrometeorology, 6: 101–114.
Westra S, Sharma A, Brown C et al., 2008. Multivariate streamflow forecasting using independent component analysis. Water Resources Research, 44: W02437.
Wilhite D A, 2000. Drought as a natural hazard: Concepts and definitions. In: Wilhite D A. Droughts: A Global Assessment. London: Routledge, 3–18.
Wood A W, Kumar A, Lettenmaier D P, 2005. A retrospective assessment of National Centers for Environmental Prediction climate model-based ensemble hydrologic forecasting in the western United States. Journal of Geophysical Research: Atmospheres, 110: D04105.
Wood A W, Lettenmaier D P, 2006. A test bed for new seasonal hydrologic forecasting approaches in the western United States. Bulletin of the American Meteorological Society, 87: 1699–1712.
Wood A W, Lettenmaier D P, 2008. An ensemble approach for attribution of hydrologic prediction uncertainty. Geophysical Research Letters, 35: L14401.
Wood A W, Maurer E P, Kumar A et al., 2002. Long-range experimental hydrologic forecasting for the eastern United States. Journal of Geophysical Research: Atmospheres, 107: 4429.
Wu H, Adler R F, Tian Y et al., 2014. Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model. Water Resources Research, 50: 2693–2717.
Xia Y, Mitchell K, Ek M et al., 2012. Continental-scale water and energy flux analysis and validation for the North-American Land Data Assimilation System Project Phase 2 (NLDAS-2) (Part I): Intercomparison and application of model products. Journal of Geophysical Research: Atmospheres, 117: D03109.
Yang D W, Li C, Ni G H et al., 2004. Application of a distributed hydrological model to Yellow River basin. Acta Geographica Sinica, 59(1): 143–154. (in Chinese)
Yang L, Tian F, Sun Y et al., 2014. Attribution of hydrologic forecast uncertainty within scalable forecast windows. Hydrology and Earth System Sciences, 18: 775–786.
Yilmaz K K, Adler R F, Tian Y et al., 2010. Evaluation of a satellite-based global flood monitoring system. International Journal of Remote Sensing, 31(14): 3763–3782.
Yossef N C, Winsemius H, Weerts A et al., 2013. Skill of a global seasonal streamflow forecasting system, relative roles of initial conditions and meteorological forcing. Water Resources Research, 49: 4687–4699.
Yuan X, Liang X Z, 2011. Improving cold season precipitation prediction by the nested CWRF-CFS system Geophysical Research Letters, 38: L02706.
Yuan X, Ma Z, Pan M et al., 2015a. Microwave remote sensing of short-term droughts during crop growing seasons. Geophysical Research Letters, 42: 4394–4401.
Yuan X, Roundy J, Wood E F et al., 2015b. Seasonal forecasting of global hydrologic extremes: System development and evaluation over GEWEX basins. Bulletin of the American Meteorological Society, 96: 1895–1912.
Yuan X, Wood E F, Chaney N W et al., 2013a. Probabilistic seasonal forecasting of African drought by dynamical models. Journal of Hydrometeorology, 14: 1706–1720.
Yuan X, Wood E F, Roundy J K et al., 2013b. CFSv2-based seasonal hydroclimatic forecasts over the conterminous United States. Journal of Climate, 26: 4828–4847.
Yuan X, Wood E F, Liang M, 2014. Integrating weather and climate prediction: Toward seamless hydrologic forecasting. Geophysical Research Letters, 41: 5891–5896.
Yuan X, Wood E F, Ma Z, 2015c. A review on climate-model-based seasonal hydrologic forecasting: Physical understanding and system development. WIREs Water, 2: 523–536.
Zaitchik B F, Rodell M, Reichle R H, 2008. Assimilation of GRACE terrestrial water storage data into a land surface model: Results for the Mississippi River Basin. Journal of Hydrometeorology, 9(3): 535–548.
Zeng H W, Li L J, Li J Y, 2012. The evaluation of TRMM Multisatellite Precipitation Analysis (TMPA) in drought monitoring in the Lancang River Basin. Journal of Geographical Sciences, 22(2): 273–282.
Zhai J, Su B, Krysanova V et al., 2010. Spatial variation and trends in PDSI and SPI indices and their relation to streamflow in 10 large regions of China. Journal of Climate, 23: 649–663.
Zhang J, Liu Z, 2006. Hydrological monitoring and flood management in China. Frontiers in Flood Research, 305: 93–101.
Zhang X J, Tang Q, 2015. Combining satellite precipitation and long-term ground observations for hydrological monitoring in China, Journal of Geophysical Research: Atmospheres, 120: 6426–6443.
Zhang X J, Tang Q H, Pan M et al., 2014. A long-term land surface hydrologic fluxes and states dataset for China. Journal of Hydrometeorology, 15: 2067–2084.
Zhao H G, Yang S T, Wang Z W et al., 2015. Evaluating the suitability of TRMM satellite rain-fall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China. Journal of Geographical Sciences, 25(2): 177–195.
Zhou T, Nijssen B, Huffman G J et al., 2014. Evaluation of real-time satellite precipitation data for global drought monitoring. Journal of Hydrometeorology, 15: 1651–1660.
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Foundation: National Natural Science Foundation of China, No.41425002; National Basic Research Program of China, No.2012CB955403; National Youth Top-notch Talent Support Program in China; China Special Fund for Meteorological Research in the Public Interest (Major projects), No.GYHY201506001-7; The Beijing Science and Technology Plan Project, No.Z141100003614052
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Tang, Q., Zhang, X., Duan, Q. et al. Hydrological monitoring and seasonal forecasting: Progress and perspectives. J. Geogr. Sci. 26, 904–920 (2016). https://doi.org/10.1007/s11442-016-1306-z
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DOI: https://doi.org/10.1007/s11442-016-1306-z