Articles | Volume 24, issue 2
https://doi.org/10.5194/hess-24-615-2020
© Author(s) 2020. 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-24-615-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
13 Feb 2020
Research article |
| 13 Feb 2020
| 13 Feb 2020
Dual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: evaluation of a large-scale implementation with Soil Moisture Active Passive (SMAP) satellite data
Yixin Mao
Department of Civil & Environmental Engineering, University of
Washington, Seattle, WA, USA
Wade T. Crow
Hydrology and Remote Sensing Laboratory, Agricultural Research Service, USDA, Beltsville, MD, USA
Department of Civil & Environmental Engineering, University of
Washington, Seattle, WA, USA
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Variable Infiltration Capacity (VIC) is a widely used hydrologic model. This paper documents the development of VIC version 5, which includes a reconfiguration of the model source code to support a wider range of modeling applications. It also represents a significant step forward for the VIC user community in terms of support for a range of modeling applications, reproducibility, and scientific robustness.
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LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Jianxiu Qiu, Jianzhi Dong, Wade T. Crow, Xiaohu Zhang, Rolf H. Reichle, and Gabrielle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 25, 1569–1586, https://doi.org/10.5194/hess-25-1569-2021, https://doi.org/10.5194/hess-25-1569-2021, 2021
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The SMAP L4 dataset has been extensively used in hydrological applications. We innovatively use a machine learning method to analyze how the efficiency of the L4 data assimilation (DA) system is determined. It shows that DA efficiency is mainly related to Tb innovation, followed by error in precipitation forcing and microwave soil roughness. Since the L4 system can effectively filter out precipitation error, future development should focus on correctly specifying the SSM–RZSM coupling strength.
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272, https://doi.org/10.5194/hess-25-257-2021, https://doi.org/10.5194/hess-25-257-2021, 2021
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Geosci. Model Dev., 13, 5029–5052, https://doi.org/10.5194/gmd-13-5029-2020, https://doi.org/10.5194/gmd-13-5029-2020, 2020
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Jianxiu Qiu, Wade T. Crow, Jianzhi Dong, and Grey S. Nearing
Hydrol. Earth Syst. Sci., 24, 581–594, https://doi.org/10.5194/hess-24-581-2020, https://doi.org/10.5194/hess-24-581-2020, 2020
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Andrew R. Bennett, Joseph J. Hamman, and Bart Nijssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-179, https://doi.org/10.5194/gmd-2019-179, 2019
Preprint withdrawn
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MetSim is a software package for simulating meteorologic processes, and aims to be applied in the environmental and Earth sciences. It can simulate processes such as solar and thermal radiation, specific humidity, and vapor pressure across large spatial areas in an efficient manner. This paper describes the software and analyzes it's ability to be used in large simulations. We describe how MetSim can be used and provide details on the various options that are available.
Michael A. Brunke, John J. Cassano, Nicholas Dawson, Alice K. DuVivier, William J. Gutowski Jr., Joseph Hamman, Wieslaw Maslowski, Bart Nijssen, J. E. Jack Reeves Eyre, José C. Renteria, Andrew Roberts, and Xubin Zeng
Geosci. Model Dev., 11, 4817–4841, https://doi.org/10.5194/gmd-11-4817-2018, https://doi.org/10.5194/gmd-11-4817-2018, 2018
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Joseph J. Hamman, Bart Nijssen, Theodore J. Bohn, Diana R. Gergel, and Yixin Mao
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Thomas R. H. Holmes, Christopher R. Hain, Wade T. Crow, Martha C. Anderson, and William P. Kustas
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In an effort to apply cloud-tolerant microwave data to satellite-based monitoring of evapotranspiration (ET), this study reports on an experiment where microwave-based land surface temperature is used as the key diagnostic input to a two-source energy balance method for the estimation of ET. Comparisons of this microwave ET with the conventional thermal infrared estimates show widespread agreement in spatial and temporal patterns from seasonal to inter-annual timescales over Africa and Europe.
Abraham Endalamaw, W. Robert Bolton, Jessica M. Young-Robertson, Don Morton, Larry Hinzman, and Bart Nijssen
Hydrol. Earth Syst. Sci., 21, 4663–4680, https://doi.org/10.5194/hess-21-4663-2017, https://doi.org/10.5194/hess-21-4663-2017, 2017
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Kenneth J. Tobin, Roberto Torres, Wade T. Crow, and Marvin E. Bennett
Hydrol. Earth Syst. Sci., 21, 4403–4417, https://doi.org/10.5194/hess-21-4403-2017, https://doi.org/10.5194/hess-21-4403-2017, 2017
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This study applied the exponential filter to produce an estimate of root-zone soil moisture at 20 to 25 cm depths. Four types of microwave, surface satellite soil moisture were used. The study focused on the continental United States, and in situ data were used from the International Soil Moisture Network for comparison. This study spans almost two decades (1997 to 2014). Root mean square error was close to 0.04, which is the baseline value for accuracy designated for many satellite missions.
Christian Massari, Wade Crow, and Luca Brocca
Hydrol. Earth Syst. Sci., 21, 4347–4361, https://doi.org/10.5194/hess-21-4347-2017, https://doi.org/10.5194/hess-21-4347-2017, 2017
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The paper explores a method for the assessment of the performance of global rainfall estimates without relying on ground-based observations. Thanks to this method, different global correlation maps are obtained (for the first time without relying on a benchmark dataset) for some of the most used globally available rainfall products. This is central for hydroclimatic studies within data-scarce regions, where ground observations are scarce to evaluate the relative quality of a rainfall product
Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold
Hydrol. Earth Syst. Sci., 21, 3915–3935, https://doi.org/10.5194/hess-21-3915-2017, https://doi.org/10.5194/hess-21-3915-2017, 2017
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Wade T. Crow, Eunjin Han, Dongryeol Ryu, Christopher R. Hain, and Martha C. Anderson
Hydrol. Earth Syst. Sci., 21, 1849–1862, https://doi.org/10.5194/hess-21-1849-2017, https://doi.org/10.5194/hess-21-1849-2017, 2017
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Terrestrial water storage is defined as the total volume of water stored within the land surface and sub-surface and is a key variable for tracking long-term variability in the global water cycle. Currently, annual variations in terrestrial water storage can only be measured at extremely coarse spatial resolutions (> 200 000 km2) using gravity-based remote sensing. Here we provide evidence that microwave-based remote sensing of soil moisture can be applied to enhance this resolution.
Thomas R. H. Holmes, Christopher R. Hain, Martha C. Anderson, and Wade T. Crow
Hydrol. Earth Syst. Sci., 20, 3263–3275, https://doi.org/10.5194/hess-20-3263-2016, https://doi.org/10.5194/hess-20-3263-2016, 2016
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We test the cloud tolerance of two technologies to estimate land surface temperature (LST) from space: microwave (MW) and thermal infrared (TIR). Although TIR has slightly lower errors than MW with ground data under clear-sky conditions, it suffers increasing negative bias as cloud cover increases. In contrast, we find no direct impact of clouds on the accuracy and bias of MW-LST. MW-LST can therefore be used to improve TIR cloud screening and increase sampling in clouded regions.
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, https://doi.org/10.5194/gmd-9-2223-2016, 2016
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mizuRoute version 1 is a stand-alone runoff routing tool that post-processes runoff outputs from any distributed hydrologic models to produce streamflow estimates in large-scale river network. mizuRoute is flexible to river network representation and includes two different river routing schemes. This paper demonstrates mizuRoute's capability of multi-decadal streamflow estimations in the river networks over the entire contiguous Unites States, which contains over 54 000 river segments.
C. Alvarez-Garreton, D. Ryu, A. W. Western, C.-H. Su, W. T. Crow, D. E. Robertson, and C. Leahy
Hydrol. Earth Syst. Sci., 19, 1659–1676, https://doi.org/10.5194/hess-19-1659-2015, https://doi.org/10.5194/hess-19-1659-2015, 2015
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We assimilate satellite soil moisture into a rainfall-runoff model for improving flood prediction within a data-scarce region. We argue that the spatially distributed satellite data can alleviate the model prediction limitations. We show that satellite soil moisture DA reduces the uncertainty of the streamflow ensembles. We propose new techniques for the DA scheme, including seasonal error characterisation, bias correction of the satellite retrievals, and model error representation.
T. R. H. Holmes, W. T. Crow, and C. Hain
Hydrol. Earth Syst. Sci., 17, 3695–3706, https://doi.org/10.5194/hess-17-3695-2013, https://doi.org/10.5194/hess-17-3695-2013, 2013
Related subject area
Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
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A semi-parametric hourly space–time weather generator
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Local moisture recycling across the globe
How well does a convection-permitting regional climate model represent the reverse orographic effect of extreme hourly precipitation?
Regionalisation of rainfall depth–duration–frequency curves with different data types in Germany
The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting
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Daily ensemble river discharge reforecasts and real-time forecasts from the operational Global Flood Awareness System
Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau
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Declining water resources in response to global warming and changes in atmospheric circulation patterns over southern Mediterranean France
Linking the complementary evaporation relationship with the Budyko framework for ungauged areas in Australia
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Pan evaporation is increased by submerged macrophytes
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Hydrol. Earth Syst. Sci., 28, 3777–3797, https://doi.org/10.5194/hess-28-3777-2024, https://doi.org/10.5194/hess-28-3777-2024, 2024
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The accurate estimation of precipitation and its spatial variability within a watershed is crucial for reliable discharge simulations. The study is the first detailed analysis of the potential usage of the cellular automata technique to merge different rainfall data inputs to hydrological models. This work shows an improvement in the performance of hydrological simulations when satellite and rain gauge data are merged.
Beijing Fang, Emanuele Bevacqua, Oldrich Rakovec, and Jakob Zscheischler
Hydrol. Earth Syst. Sci., 28, 3755–3775, https://doi.org/10.5194/hess-28-3755-2024, https://doi.org/10.5194/hess-28-3755-2024, 2024
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We use grid-based runoff from a hydrological model to identify large spatiotemporally connected flood events in Europe, assess extent trends over the last 70 years, and attribute the trends to different drivers. Our findings reveal a general increase in flood extent, with regional variations driven by diverse factors. The study not only enables a thorough examination of flood events across multiple basins but also highlights the potential challenges arising from changing flood extents.
Alexandre Devers, Jean-Philippe Vidal, Claire Lauvernet, Olivier Vannier, and Laurie Caillouet
Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, https://doi.org/10.5194/hess-28-3457-2024, 2024
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Daily streamflow series for 661 near-natural French catchments are reconstructed over 1871–2012 using two ensemble datasets: HydRE and HydREM. They include uncertainties coming from climate forcings, streamflow measurement, and hydrological model error (for HydrREM). Comparisons with other hydrological reconstructions and independent/dependent observations show the added value of the two reconstructions in terms of quality, uncertainty estimation, and representation of extremes.
María Agostina Bracalenti, Omar V. Müller, Miguel A. Lovino, and Ernesto Hugo Berbery
Hydrol. Earth Syst. Sci., 28, 3281–3303, https://doi.org/10.5194/hess-28-3281-2024, https://doi.org/10.5194/hess-28-3281-2024, 2024
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The Gran Chaco is a large, dry forest in South America that has been heavily deforested, particularly in the dry Chaco subregion. This deforestation, mainly driven by the expansion of the agricultural frontier, has changed the land's characteristics, affecting the local and regional climate. The study reveals that deforestation has resulted in reduced precipitation, soil moisture, and runoff, and if intensive agriculture continues, it could make summers in this arid region even drier and hotter.
Rutong Liu, Jiabo Yin, Louise Slater, Shengyu Kang, Yuanhang Yang, Pan Liu, Jiali Guo, Xihui Gu, Xiang Zhang, and Aliaksandr Volchak
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Climate change accelerates the water cycle and alters the spatiotemporal distribution of hydrological variables, thus complicating the projection of future streamflow and hydrological droughts. We develop a cascade modeling chain to project future bivariate hydrological drought characteristics over China, using five bias-corrected global climate model outputs under three shared socioeconomic pathways, five hydrological models, and a deep-learning model.
Lu Su, Dennis P. Lettenmaier, Ming Pan, and Benjamin Bass
Hydrol. Earth Syst. Sci., 28, 3079–3097, https://doi.org/10.5194/hess-28-3079-2024, https://doi.org/10.5194/hess-28-3079-2024, 2024
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We fine-tuned the variable infiltration capacity (VIC) and Noah-MP models across 263 river basins in the Western US. We developed transfer relationships to similar basins and extended the fine-tuned parameters to ungauged basins. Both models performed best in humid areas, and the skills improved post-calibration. VIC outperforms Noah-MP in all but interior dry basins following regionalization. VIC simulates annual mean streamflow and high flow well, while Noah-MP performs better for low flows.
Valentin Dura, Guillaume Evin, Anne-Catherine Favre, and David Penot
Hydrol. Earth Syst. Sci., 28, 2579–2601, https://doi.org/10.5194/hess-28-2579-2024, https://doi.org/10.5194/hess-28-2579-2024, 2024
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The increase in precipitation as a function of elevation is poorly understood in areas with complex topography. In this article, the reproduction of these orographic gradients is assessed with several precipitation products. The best product is a simulation from a convection-permitting regional climate model. The corresponding seasonal gradients vary significantly in space, with higher values for the first topographical barriers exposed to the dominant air mass circulations.
Caroline Legrand, Benoît Hingray, Bruno Wilhelm, and Martin Ménégoz
Hydrol. Earth Syst. Sci., 28, 2139–2166, https://doi.org/10.5194/hess-28-2139-2024, https://doi.org/10.5194/hess-28-2139-2024, 2024
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Climate change is expected to increase flood hazard worldwide. The evolution is typically estimated from multi-model chains, where regional hydrological scenarios are simulated from weather scenarios derived from coarse-resolution atmospheric outputs of climate models. We show that two such chains are able to reproduce, from an atmospheric reanalysis, the 1902–2009 discharge variations and floods of the upper Rhône alpine river, provided that the weather scenarios are bias-corrected.
Nenghan Wan, Xiaomao Lin, Roger A. Pielke Sr., Xubin Zeng, and Amanda M. Nelson
Hydrol. Earth Syst. Sci., 28, 2123–2137, https://doi.org/10.5194/hess-28-2123-2024, https://doi.org/10.5194/hess-28-2123-2024, 2024
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Global warming occurs at a rate of 0.21 K per decade, resulting in about 9.5 % K−1 of water vapor response to temperature from 1993 to 2021. Terrestrial areas experienced greater warming than the ocean, with a ratio of 2 : 1. The total precipitable water change in response to surface temperature changes showed a variation around 6 % K−1–8 % K−1 in the 15–55° N latitude band. Further studies are needed to identify the mechanisms leading to different water vapor responses.
Kyungmin Sung, Max C. A. Torbenson, and James H. Stagge
Hydrol. Earth Syst. Sci., 28, 2047–2063, https://doi.org/10.5194/hess-28-2047-2024, https://doi.org/10.5194/hess-28-2047-2024, 2024
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This study examines centuries of nonstationary trends in meteorological drought and pluvial climatology. A novel approach merges tree-ring proxy data (North American Seasonal Precipitation Atlas – NASPA) with instrumental precipitation datasets by temporally downscaling proxy data, correcting biases, and analyzing shared trends in normal and extreme precipitation anomalies. We identify regions experiencing recent unprecedented shifts towards drier or wetter conditions and shifts in seasonality.
Baoying Shan, Niko E. C. Verhoest, and Bernard De Baets
Hydrol. Earth Syst. Sci., 28, 2065–2080, https://doi.org/10.5194/hess-28-2065-2024, https://doi.org/10.5194/hess-28-2065-2024, 2024
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This study developed a convenient and new method to identify the occurrence of droughts, heatwaves, and co-occurring droughts and heatwaves (CDHW) across four seasons. Using this method, we could establish the start and/or end dates of drought (or heatwave) events. We found an increase in the frequency of heatwaves and CDHW events in Belgium caused by climate change. We also found that different months have different chances of CDHW events.
Georgina M. Falster, Nicky M. Wright, Nerilie J. Abram, Anna M. Ukkola, and Benjamin J. Henley
Hydrol. Earth Syst. Sci., 28, 1383–1401, https://doi.org/10.5194/hess-28-1383-2024, https://doi.org/10.5194/hess-28-1383-2024, 2024
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Multi-year droughts have severe environmental and economic impacts, but the instrumental record is too short to characterise multi-year drought variability. We assessed the nature of Australian multi-year droughts using simulations of the past millennium from 11 climate models. We show that multi-decadal
megadroughtsare a natural feature of the Australian hydroclimate. Human-caused climate change is also driving a tendency towards longer droughts in eastern and southwestern Australia.
Peng Huang, Agnès Ducharne, Lucia Rinchiuso, Jan Polcher, Laure Baratgin, Vladislav Bastrikov, and Eric Sauquet
EGUsphere, https://doi.org/10.5194/egusphere-2024-445, https://doi.org/10.5194/egusphere-2024-445, 2024
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We conducted a high-resolution hydrological simulation from 1959 to 2020 across France. We used a simple trial-and-error calibration to reduce the biases of the simulated water budget compared to observations. The selected simulation satisfactorily reproduces water fluxes, including their spatial contrasts and temporal trends. This work offers a thorough historical overview of water resources and a robust configuration for climate change impact analysis at the nationwide scale of France.
Urmin Vegad, Yadu Pokhrel, and Vimal Mishra
Hydrol. Earth Syst. Sci., 28, 1107–1126, https://doi.org/10.5194/hess-28-1107-2024, https://doi.org/10.5194/hess-28-1107-2024, 2024
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A large population is affected by floods, which leave their footprints through human mortality, migration, and damage to agriculture and infrastructure, during almost every summer monsoon season in India. Despite the massive damage of floods, sub-basin level flood risk assessment is still in its infancy and needs to be improved. Using hydrological and hydrodynamic models, we reconstructed sub-basin level observed floods for the 1901–2020 period.
Qi Sun, Patrick Olschewski, Jianhui Wei, Zhan Tian, Laixiang Sun, Harald Kunstmann, and Patrick Laux
Hydrol. Earth Syst. Sci., 28, 761–780, https://doi.org/10.5194/hess-28-761-2024, https://doi.org/10.5194/hess-28-761-2024, 2024
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Tropical cyclones (TCs) often cause high economic loss due to heavy winds and rainfall, particularly in densely populated regions such as the Pearl River Delta (China). This study provides a reference to set up regional climate models for TC simulations. They contribute to a better TC process understanding and assess the potential changes and risks of TCs in the future. This lays the foundation for hydrodynamical modelling, from which the cities' disaster management and defence could benefit.
Simon Parry, Jonathan D. Mackay, Thomas Chitson, Jamie Hannaford, Eugene Magee, Maliko Tanguy, Victoria A. Bell, Katie Facer-Childs, Alison Kay, Rosanna Lane, Robert J. Moore, Stephen Turner, and John Wallbank
Hydrol. Earth Syst. Sci., 28, 417–440, https://doi.org/10.5194/hess-28-417-2024, https://doi.org/10.5194/hess-28-417-2024, 2024
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We studied drought in a dataset of possible future river flows and groundwater levels in the UK and found different outcomes for these two sources of water. Throughout the UK, river flows are likely to be lower in future, with droughts more prolonged and severe. However, whilst these changes are also found in some boreholes, in others, higher levels and less severe drought are indicated for the future. This has implications for the future balance between surface water and groundwater below.
Francesco Marra, Marika Koukoula, Antonio Canale, and Nadav Peleg
Hydrol. Earth Syst. Sci., 28, 375–389, https://doi.org/10.5194/hess-28-375-2024, https://doi.org/10.5194/hess-28-375-2024, 2024
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We present a new physical-based method for estimating extreme sub-hourly precipitation return levels (i.e., intensity–duration–frequency, IDF, curves), which are critical for the estimation of future floods. The proposed model, named TENAX, incorporates temperature as a covariate in a physically consistent manner. It has only a few parameters and can be easily set for any climate station given sub-hourly precipitation and temperature data are available.
Amy Charlotte Green, Chris G. Kilsby, and András Bárdossy
EGUsphere, https://doi.org/10.5194/egusphere-2024-26, https://doi.org/10.5194/egusphere-2024-26, 2024
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Weather radar is a crucial tool in rainfall estimation, but radar rainfall estimates are subject to many error sources, with the true rainfall field unknown. A flexible model for simulating errors relating to the radar rainfall estimation process is implemented, inverting standard processing methods. This flexible and efficient model performs well at generating realistic weather radar images visually, for a large range of event types.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-11, https://doi.org/10.5194/hess-2024-11, 2024
Revised manuscript accepted for HESS
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Our findings revealed runoff generation is dominated by rainfall runoff in the YZ, and the largest glacier runoff contribution is in the downstream sub-basin. Annual runoff trends indicate an increase in the NX but a decrease in the NX-BXK for 1971–2020, due to contrasting precipitation changes. Total runoff across the sub-basins will consistently increase through the 21st century, mostly resulting from increased rainfall runoff.
Louise Arnal, Martyn P. Clark, Alain Pietroniro, Vincent Vionnet, David R. Casson, Paul H. Whitfield, Vincent Fortin, Andrew W. Wood, Wouter J. M. Knoben, Brandi W. Newton, and Colleen Walford
EGUsphere, https://doi.org/10.5194/egusphere-2023-3040, https://doi.org/10.5194/egusphere-2023-3040, 2024
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Forecasting river flows months in advance is crucial for many water sectors and society. In N. America, snowmelt is a key driver of river flow. This study presents a statistical workflow using snow data to forecast flows months ahead in N. American snow-fed rivers. Variations in predictability across the continent are evident, raising concerns about future river flow predictability amid a changing (snow) climate. The reproducible workflow hosted on GitHub supports collaborative and open science.
Alexander Gelfan, Andrey Panin, Andrey Kalugin, Polina Morozova, Vladimir Semenov, Alexey Sidorchuk, Vadim Ukraintsev, and Konstantin Ushakov
Hydrol. Earth Syst. Sci., 28, 241–259, https://doi.org/10.5194/hess-28-241-2024, https://doi.org/10.5194/hess-28-241-2024, 2024
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Paleogeographical data show that 17–13 ka BP, the Caspian Sea level was 80 m above the current level. There are large disagreements on the genesis of this “Great” Khvalynian transgression of the sea, and we tried to shed light on this issue. Using climate and hydrological models as well as the paleo-reconstructions, we proved that the transgression could be initiated solely by hydroclimatic factors within the deglaciation period in the absence of the glacial meltwater effect.
Joeri B. Reinders and Samuel E. Munoz
Hydrol. Earth Syst. Sci., 28, 217–227, https://doi.org/10.5194/hess-28-217-2024, https://doi.org/10.5194/hess-28-217-2024, 2024
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Flooding presents a major hazard for people and infrastructure along waterways; however, it is challenging to study the likelihood of a flood magnitude occurring regionally due to a lack of long discharge records. We show that hydroclimatic variables like Köppen climate regions and precipitation intensity explain part of the variance in flood frequency distributions and thus reduce the uncertainty of flood probability estimates. This gives water managers a tool to locally improve flood analysis.
Mehrad Rahimpour Asenjan, Francois Brissette, Jean-Luc Martel, and Richard Arsenault
Hydrol. Earth Syst. Sci., 27, 4355–4367, https://doi.org/10.5194/hess-27-4355-2023, https://doi.org/10.5194/hess-27-4355-2023, 2023
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Climate models are central to climate change impact studies. Some models project a future deemed too hot by many. We looked at how including hot models may skew the result of impact studies. Applied to hydrology, this study shows that hot models do not systematically produce hydrological outliers.
Ross Pidoto and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 3957–3975, https://doi.org/10.5194/hess-27-3957-2023, https://doi.org/10.5194/hess-27-3957-2023, 2023
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Long continuous time series of meteorological variables (i.e. rainfall, temperature) are required for the modelling of floods. Observed time series are generally too short or not available. Weather generators are models that reproduce observed weather time series. This study extends an existing station-based rainfall model into space by enforcing observed spatial rainfall characteristics. To model other variables (i.e. temperature) the model is then coupled to a simple resampling approach.
Kajsa Maria Parding, Rasmus Emil Benestad, Anita Verpe Dyrrdal, and Julia Lutz
Hydrol. Earth Syst. Sci., 27, 3719–3732, https://doi.org/10.5194/hess-27-3719-2023, https://doi.org/10.5194/hess-27-3719-2023, 2023
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Intensity–duration–frequency (IDF) curves describe the likelihood of extreme rainfall and are used in hydrology and engineering, for example, for flood forecasting and water management. We develop a model to estimate IDF curves from daily meteorological observations, which are more widely available than the observations on finer timescales (minutes to hours) that are needed for IDF calculations. The method is applied to all data at once, making it efficient and robust to individual errors.
Kaltrina Maloku, Benoit Hingray, and Guillaume Evin
Hydrol. Earth Syst. Sci., 27, 3643–3661, https://doi.org/10.5194/hess-27-3643-2023, https://doi.org/10.5194/hess-27-3643-2023, 2023
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High-resolution precipitation data, needed for many applications in hydrology, are typically rare. Such data can be simulated from daily precipitation with stochastic disaggregation. In this work, multiplicative random cascades are used to disaggregate time series of 40 min precipitation from daily precipitation for 81 Swiss stations. We show that very relevant statistics of precipitation are obtained when precipitation asymmetry is accounted for in a continuous way in the cascade generator.
Peter E. Levy and the COSMOS-UK team
EGUsphere, https://doi.org/10.5194/egusphere-2023-2041, https://doi.org/10.5194/egusphere-2023-2041, 2023
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Having accurate up-to-date maps of soil moisture is important for many purposes. However, current modelled and remotely-sensed maps are rather coarse and not very accurate. Here, we demonstrate a simple but accurate approach which is closely linked to direct measurements of soil moisture at a network sites across the UK, and to the water balance (precipitation minus drainage and evaporation) measured at a large number of catchments (1212), as well as to remotely-sensed satellite estimates.
Theresa Boas, Heye Reemt Bogena, Dongryeol Ryu, Harry Vereecken, Andrew Western, and Harrie-Jan Hendricks Franssen
Hydrol. Earth Syst. Sci., 27, 3143–3167, https://doi.org/10.5194/hess-27-3143-2023, https://doi.org/10.5194/hess-27-3143-2023, 2023
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In our study, we tested the utility and skill of a state-of-the-art forecasting product for the prediction of regional crop productivity using a land surface model. Our results illustrate the potential value and skill of combining seasonal forecasts with modelling applications to generate variables of interest for stakeholders, such as annual crop yield for specific cash crops and regions. In addition, this study provides useful insights for future technical model evaluations and improvements.
Yuanhong You, Chunlin Huang, Zuo Wang, Jinliang Hou, Ying Zhang, and Peipei Xu
Hydrol. Earth Syst. Sci., 27, 2919–2933, https://doi.org/10.5194/hess-27-2919-2023, https://doi.org/10.5194/hess-27-2919-2023, 2023
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This study aims to investigate the performance of a genetic particle filter which was used as a snow data assimilation scheme across different snow climates. The results demonstrated that the genetic algorithm can effectively solve the problem of particle degeneration and impoverishment in a particle filter algorithm. The system has revealed a low sensitivity to the particle number in point-scale application of the ground snow depth measurement.
Patricia Lawston-Parker, Joseph A. Santanello Jr., and Nathaniel W. Chaney
Hydrol. Earth Syst. Sci., 27, 2787–2805, https://doi.org/10.5194/hess-27-2787-2023, https://doi.org/10.5194/hess-27-2787-2023, 2023
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Irrigation has been shown to impact weather and climate, but it has only recently been considered in prediction models. Prescribing where (globally) irrigation takes place is important to accurately simulate its impacts on temperature, humidity, and precipitation. Here, we evaluated three different irrigation maps in a weather model and found that the extent and intensity of irrigated areas and their boundaries are important drivers of weather impacts resulting from human practices.
Marcos Julien Alexopoulos, Hannes Müller-Thomy, Patrick Nistahl, Mojca Šraj, and Nejc Bezak
Hydrol. Earth Syst. Sci., 27, 2559–2578, https://doi.org/10.5194/hess-27-2559-2023, https://doi.org/10.5194/hess-27-2559-2023, 2023
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For rainfall-runoff simulation of a certain area, hydrological models are used, which requires precipitation data and temperature data as input. Since these are often not available as observations, we have tested simulation results from atmospheric models. ERA5-Land and COSMO-REA6 were tested for Slovenian catchments. Both lead to good simulations results. Their usage enables the use of rainfall-runoff simulation in unobserved catchments as a requisite for, e.g., flood protection measures.
Tuantuan Zhang, Zhongmin Liang, Wentao Li, Jun Wang, Yiming Hu, and Binquan Li
Hydrol. Earth Syst. Sci., 27, 1945–1960, https://doi.org/10.5194/hess-27-1945-2023, https://doi.org/10.5194/hess-27-1945-2023, 2023
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We use circulation classifications and spatiotemporal deep neural networks to correct raw daily forecast precipitation by combining large-scale circulation patterns with local spatiotemporal information. We find that the method not only captures the westward and northward movement of the western Pacific subtropical high but also shows substantially higher bias-correction capabilities than existing standard methods in terms of spatial scale, timescale, and intensity.
Zeyu Xue, Paul Ullrich, and Lai-Yung Ruby Leung
Hydrol. Earth Syst. Sci., 27, 1909–1927, https://doi.org/10.5194/hess-27-1909-2023, https://doi.org/10.5194/hess-27-1909-2023, 2023
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We examine the sensitivity and robustness of conclusions drawn from the PGW method over the NEUS by conducting multiple PGW experiments and varying the perturbation spatial scales and choice of perturbed meteorological variables to provide a guideline for this increasingly popular regional modeling method. Overall, we recommend PGW experiments be performed with perturbations to temperature or the combination of temperature and wind at the gridpoint scale, depending on the research question.
Louise J. Slater, Louise Arnal, Marie-Amélie Boucher, Annie Y.-Y. Chang, Simon Moulds, Conor Murphy, Grey Nearing, Guy Shalev, Chaopeng Shen, Linda Speight, Gabriele Villarini, Robert L. Wilby, Andrew Wood, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 27, 1865–1889, https://doi.org/10.5194/hess-27-1865-2023, https://doi.org/10.5194/hess-27-1865-2023, 2023
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Hybrid forecasting systems combine data-driven methods with physics-based weather and climate models to improve the accuracy of predictions for meteorological and hydroclimatic events such as rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. We review recent developments in hybrid forecasting and outline key challenges and opportunities in the field.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
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The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Jolanda J. E. Theeuwen, Arie Staal, Obbe A. Tuinenburg, Bert V. M. Hamelers, and Stefan C. Dekker
Hydrol. Earth Syst. Sci., 27, 1457–1476, https://doi.org/10.5194/hess-27-1457-2023, https://doi.org/10.5194/hess-27-1457-2023, 2023
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Evaporation changes over land affect rainfall over land via moisture recycling. We calculated the local moisture recycling ratio globally, which describes the fraction of evaporated moisture that rains out within approx. 50 km of its source location. This recycling peaks in summer as well as over wet and elevated regions. Local moisture recycling provides insight into the local impacts of evaporation changes and can be used to study the influence of regreening on local rainfall.
Eleonora Dallan, Francesco Marra, Giorgia Fosser, Marco Marani, Giuseppe Formetta, Christoph Schär, and Marco Borga
Hydrol. Earth Syst. Sci., 27, 1133–1149, https://doi.org/10.5194/hess-27-1133-2023, https://doi.org/10.5194/hess-27-1133-2023, 2023
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Convection-permitting climate models could represent future changes in extreme short-duration precipitation, which is critical for risk management. We use a non-asymptotic statistical method to estimate extremes from 10 years of simulations in an orographically complex area. Despite overall good agreement with rain gauges, the observed decrease of hourly extremes with elevation is not fully represented by the model. Climate model adjustment methods should consider the role of orography.
Bora Shehu, Winfried Willems, Henrike Stockel, Luisa-Bianca Thiele, and Uwe Haberlandt
Hydrol. Earth Syst. Sci., 27, 1109–1132, https://doi.org/10.5194/hess-27-1109-2023, https://doi.org/10.5194/hess-27-1109-2023, 2023
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Rainfall volumes at varying duration and frequencies are required for many engineering water works. These design volumes have been provided by KOSTRA-DWD in Germany. However, a revision of the KOSTRA-DWD is required, in order to consider the recent state-of-the-art and additional data. For this purpose, in our study, we investigate different methods and data available to achieve the best procedure that will serve as a basis for the development of the new KOSTRA-DWD product.
Sandra M. Hauswirth, Marc F. P. Bierkens, Vincent Beijk, and Niko Wanders
Hydrol. Earth Syst. Sci., 27, 501–517, https://doi.org/10.5194/hess-27-501-2023, https://doi.org/10.5194/hess-27-501-2023, 2023
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Forecasts on water availability are important for water managers. We test a hybrid framework based on machine learning models and global input data for generating seasonal forecasts. Our evaluation shows that our discharge and surface water level predictions are able to create reliable forecasts up to 2 months ahead. We show that a hybrid framework, developed for local purposes and combined and rerun with global data, can create valuable information similar to large-scale forecasting models.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Shaun Harrigan, Ervin Zsoter, Hannah Cloke, Peter Salamon, and Christel Prudhomme
Hydrol. Earth Syst. Sci., 27, 1–19, https://doi.org/10.5194/hess-27-1-2023, https://doi.org/10.5194/hess-27-1-2023, 2023
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Real-time river discharge forecasts and reforecasts from the Global Flood Awareness System (GloFAS) have been made publicly available, together with an evaluation of forecast skill at the global scale. Results show that GloFAS is skillful in over 93 % of catchments in the short (1–3 d) and medium range (5–15 d) and skillful in over 80 % of catchments in the extended lead time (16–30 d). Skill is summarised in a new layer on the GloFAS Web Map Viewer to aid decision-making.
Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao
Hydrol. Earth Syst. Sci., 26, 6413–6426, https://doi.org/10.5194/hess-26-6413-2022, https://doi.org/10.5194/hess-26-6413-2022, 2022
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Spatial quantification of oceanic moisture contribution to the precipitation over the Tibetan Plateau (TP) contributes to the reliable assessments of regional water resources and the interpretation of paleo archives in the region. Based on atmospheric reanalysis datasets and numerical moisture tracking, this work reveals the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer.
Urmin Vegad and Vimal Mishra
Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, https://doi.org/10.5194/hess-26-6361-2022, 2022
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Floods cause enormous damage to infrastructure and agriculture in India. However, the utility of ensemble meteorological forecast for hydrologic prediction has not been examined. Moreover, Indian river basins have a considerable influence of reservoirs that alter the natural flow variability. We developed a hydrologic modelling-based streamflow prediction considering the influence of reservoirs in India.
Camille Labrousse, Wolfgang Ludwig, Sébastien Pinel, Mahrez Sadaoui, Andrea Toreti, and Guillaume Lacquement
Hydrol. Earth Syst. Sci., 26, 6055–6071, https://doi.org/10.5194/hess-26-6055-2022, https://doi.org/10.5194/hess-26-6055-2022, 2022
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The interest of this study is to demonstrate that we identify two zones in our study area whose hydroclimatic behaviours are uneven. By investigating relationships between the hydroclimatic conditions in both clusters for past observations with the overall atmospheric functioning, we show that the inequalities are mainly driven by a different control of the atmospheric teleconnection patterns over the area.
Daeha Kim, Minha Choi, and Jong Ahn Chun
Hydrol. Earth Syst. Sci., 26, 5955–5969, https://doi.org/10.5194/hess-26-5955-2022, https://doi.org/10.5194/hess-26-5955-2022, 2022
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We proposed a practical method that predicts the evaporation rates on land surfaces (ET) where only atmospheric data are available. Using a traditional equation that describes partitioning of precipitation into ET and streamflow, we could approximately identify the key parameter of the predicting formulation based on land–atmosphere interactions. The simple method conditioned by local climates outperformed sophisticated models in reproducing water-balance estimates across Australia.
Ruksana H. Rimi, Karsten Haustein, Emily J. Barbour, Sarah N. Sparrow, Sihan Li, David C. H. Wallom, and Myles R. Allen
Hydrol. Earth Syst. Sci., 26, 5737–5756, https://doi.org/10.5194/hess-26-5737-2022, https://doi.org/10.5194/hess-26-5737-2022, 2022
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Extreme rainfall events are major concerns in Bangladesh. Heavy downpours can cause flash floods and damage nearly harvestable crops in pre-monsoon season. While in monsoon season, the impacts can range from widespread agricultural loss, huge property damage, to loss of lives and livelihoods. This paper assesses the role of anthropogenic climate change drivers in changing risks of extreme rainfall events during pre-monsoon and monsoon seasons at local sub-regional-scale within Bangladesh.
Brigitta Simon-Gáspár, Gábor Soós, and Angela Anda
Hydrol. Earth Syst. Sci., 26, 4741–4756, https://doi.org/10.5194/hess-26-4741-2022, https://doi.org/10.5194/hess-26-4741-2022, 2022
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Due to climate change, it is extremely important to determine evaporation as accurately as possible. In nature, there are sediments and macrophytes in the open waters; thus, one of the aims was to investigate their effect on evaporation. The second aim of this paper was to estimate daily evaporation by using different models, which, according to results, have high priority in the evaporation prediction. Water management can obtain useful information from the results of the current research.
Haiyang Shi, Geping Luo, Olaf Hellwich, Mingjuan Xie, Chen Zhang, Yu Zhang, Yuangang Wang, Xiuliang Yuan, Xiaofei Ma, Wenqiang Zhang, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 26, 4603–4618, https://doi.org/10.5194/hess-26-4603-2022, https://doi.org/10.5194/hess-26-4603-2022, 2022
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There have been many machine learning simulation studies based on eddy-covariance observations for water flux and evapotranspiration. We performed a meta-analysis of such studies to clarify the impact of different algorithms and predictors, etc., on the reported prediction accuracy. It can, to some extent, guide future global water flux modeling studies and help us better understand the terrestrial ecosystem water cycle.
Yaozhi Jiang, Kun Yang, Hua Yang, Hui Lu, Yingying Chen, Xu Zhou, Jing Sun, Yuan Yang, and Yan Wang
Hydrol. Earth Syst. Sci., 26, 4587–4601, https://doi.org/10.5194/hess-26-4587-2022, https://doi.org/10.5194/hess-26-4587-2022, 2022
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Our study quantified the altitudinal precipitation gradients (PGs) over the Third Pole (TP). Most sub-basins in the TP have positive PGs, and negative PGs are found in the Himalayas, the Hengduan Mountains and the western Kunlun. PGs are positively correlated with wind speed but negatively correlated with relative humidity. In addition, PGs tend to be positive at smaller spatial scales compared to those at larger scales. The findings can assist precipitation interpolation in the data-sparse TP.
Francesca Carletti, Adrien Michel, Francesca Casale, Alice Burri, Daniele Bocchiola, Mathias Bavay, and Michael Lehning
Hydrol. Earth Syst. Sci., 26, 3447–3475, https://doi.org/10.5194/hess-26-3447-2022, https://doi.org/10.5194/hess-26-3447-2022, 2022
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High Alpine catchments are dominated by the melting of seasonal snow cover and glaciers, whose amount and seasonality are expected to be modified by climate change. This paper compares the performances of different types of models in reproducing discharge among two catchments under present conditions and climate change. Despite many advantages, the use of simpler models for climate change applications is controversial as they do not fully represent the physics of the involved processes.
Cited articles
Alvarez-Garreton, C., Ryu, D., Western, A. W., Crow, W. T., and Robertson, D. E.: The impacts of assimilating satellite soil moisture into a rainfall-runoff model in a semi-arid catchment, J. Hydrol., 519, 2763–2774,
https://doi.org/10.1016/j.jhydrol.2014.07.041, 2014.
Alvarez-Garreton, C., Ryu, D., Western, A. W., Crow, W. T., Su, C.-H., and
Robertson, D. R.: Dual assimilation of satellite soil moisture to improve
streamflow prediction in data-scarce catchments, Water Resour. Res., 52,
5357–5375, https://doi.org/10.1002/2015WR018429, 2016.
Aubert, D., Loumagne, C., and Oudin, L.: Sequential assimilation of soil
moisture and streamflow data in a conceptual rainfall-runoff model, J. Hydrol., 280, 145–161, https://doi.org/10.1016/S0022-1694(03)00229-4, 2003.
Bolten, J. D. and Crow, W. T.: Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture, Geophys. Res. Lett., 39, L19406, https://doi.org/10.1029/2012GL053470, 2012.
Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z.,
and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893,
https://doi.org/10.5194/hess-14-1881-2010, 2010.
Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn,
S.: Assimilation of surface-and root-zone ASCAT soil moisture products into
rainfall–runoff modeling, IEEE T. Geosci. Remote, 50, 2542–2555, https://doi.org/10.1109/TGRS.2011.2177468, 2012.
Brocca, L., Moramarco, T., Melone, F., and Wagner, W.: A new method for rainfall estimation through soil moisture observations, Geophys. Res. Lett.,
40, 853–858, https://doi.org/10.1002/grl.50173, 2013.
Brocca, L., Ciabatta, L., Massari, C., Moramarco, T., Hahn, S., Hasenauer, S., Kidd, R., Dorigo, W., Wagner, W., and Levizzani, V.: Soil as a natural rain gauge: Estimating global rainfall from satellite soil moisture data, J.
Geophys. Res.-Atmos., 119, 5128–5141, https://doi.org/10.1002/2014JD021489, 2014.
Brocca, L., Pellarin, T., Crow, W. T., Ciabatta, L., Massari, C., Ryu, D.,
Su, C.-H., Rüdiger, C., and Kerr, Y.: Rainfall estimation by inverting
SMOS soil moisture estimates: A comparison of different methods over Australia, J. Geophys. Res.-Atmos., 121, 12062–12079, https://doi.org/10.1002/2016JD025382, 2016.
Chan, S., Bindlish, R., O’Neill, P., Jackson, T., Chaubell, J., Piepmeier, J., Dunbar, S., Colliander, A., Chen, F., Entekhabi, D., Yueh, S., Cosh, M., Caldwell, T., Walker, J., Wu, X., Berg, A., Rowlandson, T., Pacheco, A., McNairn, H., Thibeault, M., Martínez-Fernández, J., González-Zamora, Á., Lopez-Baeza, E., Uldall, F., Seyfried, M., Bosch, D., Starks, P., Holifield C., Prueger, J., Su, Z., van der Velde, R., Asanuma, J., Palecki, M., Small, E., Zreda, M., Calvet, J.-C., Crow, W., and Kerr, Y.: Development and validation of the SMAP enhanced passive soil moisture product, in: 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), July 2017
Fort Worth, TX, United States, https://doi.org/10.1109/IGARSS.2017.8127512, 2017.
Chen, F., Crow, W. T., and Holmes, T. R. H.: Improving long-term, retrospective precipitation datasets using satellite-based surface soil
moisture retrievals and the Soil Moisture Analysis Rainfall Tool, J. Appl.
Remote Sens., 6, 063604, https://doi.org/10.1117/1.JRS.6.063604, 2012.
Chen, F., Crow, W. T., and Ryu, D.: Dual forcing and state correction via soil moisture assimilation for improved rainfall–runoff modeling, J.
Hydrometeorol., 15, 1832–1848, https://doi.org/10.1175/JHM-D-14-0002.1, 2014.
Colliander, A., Jackson, T. J., Bindlish, R., Chan, S., Das, N., Kim, S. B., Cosh, M. H., Dunbar, R. S., Dang, L., Pashaian, L., Asanuma, J., Aida, K., Berg, A., Rowlandson, T., Bosch, D., Caldwell, T., Caylor, K., Goodrich, D., al Jassar, H., Lopez-Baeza, E., Martínez-Fernández, J., González-Zamora, A., Livingston, S., McNairn, H., Pacheco, A., Moghaddam, M., Montzka, C., Niedrist, C., Pellarin, T., Prueger, J., Pulliainen, J., Notarnicola, C., Rautiainen, K., Ramos, J., Seyfried, M., Starks, P., Su, Z., Zeng, Y., van der Velde, R., Thibeault, M., Dorigo, W., Vreugdenhil, M., Walker, J. P., Wu, X., Monerris, A., O'Neill, P. E., Entekhabi, D., Njoku, E. G., and Yueh, S.: Validation of SMAP surface soil moisture products with core validation sites, Remote Sens. Environ., 191, 215–231, https://doi.org/10.1016/j.rse.2017.01.021, 2017.
Crow, W. T. and Bolten, J. D.: Estimating precipitation errors using spaceborne surface soil moisture retrievals, Geophys. Res. Lett., 34, L08403, https://doi.org/10.1029/2007GL029450, 2007.
Crow, W. T. and Ryu, D.: A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals, Hydrol. Earth Syst. Sci., 13, 1–16, https://doi.org/10.5194/hess-13-1-2009, 2009.
Crow, W. T. and van den Berg, M. J.: An improved approach for estimating
observation and model error parameters for soil moisture data assimilation,
Water Resour. Res., 46, W12519, https://doi.org/10.1029/2010WR009402, 2010.
Crow W. T., Huffman, G. J., Bindlish, R., and Jackson, T. J.: Improving
satellite-based rainfall accumulation estimates using spaceborne surface soil moisture retrievals, J. Hydrometeorol., 10, 199–212, https://doi.org/10.1175/2008JHM986.1, 2009.
Crow, W. T., van den Berg, M. J., Huffman, G. J., and Pellarin, T.: Correcting rainfall using satellite-based surface soil moisture retrievals:
The Soil Moisture Analysis Rainfall Tool (SMART), Water Resour. Res., 47,
W08521, https://doi.org/10.1029/2011WR010576, 2011.
Crow, W. T., Chen, F., Reichle, R. H., and Liu, Q.: L band microwave remote
sensing and land data assimilation improve the representation of prestorm soil moisture conditions for hydrologic forecasting, Geophys. Res. Lett., 44, 5495–5503, https://doi.org/10.1002/2017GL073642, 2017.
De Lannoy, G. J. M., Houser, P. R., Pauwels, V. R. N., and Verhoest, N. E. C.: Assessment of model uncertainty for soil moisture through ensemble
verification, J. Geophys. Res., 111, D10101, https://doi.org/10.1029/2005JD006367, 2006.
Dong, J., Crow, W. T., Reichle, R., Liu, Q., Lei, F., and Cosh, M.: A global
assessment of added value in the SMAP Level 4 soil moisture product relative
to its baseline land surface model, Geophys. Res. Lett., 46, 6604–6613,
https://doi.org/10.1029/2019GL083398, 2019.
Entekhabi, D., Njoku, E. G., O’Neill, P. E., Kellogg, K. H., Crow, W. T., Edelstein, W. N., Entin, J. K., Goodman, S. D., Jackson, T. J., Johnson, J., Kimball, J., Piepmeier, J. R., Koster, R. D., Martin, N., McDonald, K. C., Moghaddam, M., Moran, S., Reichle, R., Shi, J. C., Spencer, M. W., Thurman, S. W., Tsang, L., and Van Zyl, J.: The Soil Moisture Active and Passive (SMAP) Mission, Proc. IEEE, 98, 704–716, https://doi.org/10.1109/JPROC.2010.2043918, 2010.
Francois, C., Quesney, A., and Ottle, C.: Sequential assimilation of ERS-1 SAR data into a coupled land surface-hydrological model using an extended
Kalman filter, J. Hydrometeorol., 4, 473–487,
https://doi.org/10.1175/1525-7541(2003)4<473:SAOESD>2.0.CO;2, 2003.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based,
digitally-simulated hydrologic response model, J. Hydrol., 9, 237–258,
https://doi.org/10.1016/0022-1694(69)90020-1, 1969.
Gebregiorgis, A. S., Kirstetter, P.-E., Hong, Y. E., Gourley, J. J., Huffman, G. J. Petersen, W. A., Xue, X., and Schwaller, M. R.: To what extent is the day 1 GPM IMERG satellite precipitation estimate improved as compared to TRMM TMPA-RT?, J. Geophys. Res.-Atmos., 123, 1694–1707, https://doi.org/10.1002/2017JD027606, 2018.
Gruber, A., Crow, W. T., Dorigo, W., and Wagner, W.: The potential of 2D Kalman filtering for soil moisture data assimilation, Remote Sens. Environ., 171, 137–148, https://doi.org/10.1016/j.rse.2015.10.019, 2015.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hamman, J. J., Nijssen, B., Bohn, T., Franssen, W., Gergel, D., Mao, Y., Flores-Cervantes, J. H., Helgason, H., Peng, B., Craig, T., and The Gitter Badger: VIC 5.0.1, https://doi.org/10.5281/zenodo.267178, 2017.
Hamman, J. J., Nijssen, B., Roberts, A., Craig, A., Maslowski, W., and Osinski, R.: The coastal streamflow flux in the Regional Arctic System Model, J. Geophys. Res., 122, 1683–1701, https://doi.org/10.1002/2016JC012323, 2017.
Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y.: The
Variable Infiltration Capacity Model, Version 5 (VIC-5): Infrastructure
improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481–3496, https://doi.org/10.5194/gmd-11-3481-2018, 2018.
Hou, A. Y., Kakar, R. K., Neeck, S., Azarbarzin, A. A., Kummerow, C. D., Kojima, M., Oki, R., Nakamura, K., and Iguchi, T.: The Global Precipitation
Measurement mission, B. Am. Meteorol. Soc., 95, 701–722, https://doi.org/10.1175/BAMS-D-13-00164.1, 2014.
Huffman, G. J., Bolvin, D. T., and Nelkin, E. J.: Integrated Multi-Satellite
Retrievals for GPM (IMERG) Technical Documentation, Tech. Doc., NASA GSFC,
available at: https://docserver.gesdisc.eosdis.nasa.gov/public/project/GPM/IMERG_doc.05.pdf, 2015.
Huffman, G. J., Stocker, E. F., Bolvin, D. T., and Nelkin, E. J.: last updated 2018: IMERG L3 Early Run Data Sets. NASA/GSFC, Greenbelt, MD, USA,
available at: https://gpm1.gesdisc.eosdis.nasa.gov/opendap/hyrax/GPM_L3/GPM_3IMERGHHL.05/, last access: 29 August 2018.
Koster, R. D., Brocca, L., Crow, W. T., Burgin, M. S., and De Lannoy, G. J. M.: Precipitation estimation using L-band and C-band soil moisture retrievals, Water Resour. Res., 52, 7213–7225, https://doi.org/10.1002/2016WR019024,
2016.
Kumar, S. V., Peters-Lidard, C. D., Santanello, J. A., Reichle, R. H., Draper, C. S., Koster, R. D., Nearing, G., and Jasinski, M. F.: Evaluating the utility of satellite soil moisture retrievals over irrigated areas and the ability of land data assimilation methods to correct for unmodeled
processes, Hydrol. Earth Syst. Sci., 19, 4463–4478,
https://doi.org/10.5194/hess-19-4463-2015, 2015.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99, 14415–14428,
https://doi.org/10.1029/94JD00483, 1994.
Lievens, H., Tomer, S. K., Al Bitar, A., De Lannoy, G. J. M., Drusch, M., Dumedah, G., Hendricks Franssen, H.-J., Kerr, Y. H., Martens, B., Pan, M., Roundy, J. K., Vereecken, H., Walker, J. P., Wood, E. F., Verhoest, N. E. C., and Pauwels, V. R. N.: SMOS soil moisture assimilation for improved hydrologic simulation in the Murray Darling Basin, Australia, Remote Sens. Environ., 168, 146–162, https://doi.org/10.1016/j.rse.2015.06.025, 2015.
Lievens, H., De Lannoy, G. J. M., Al Bitar, A., Drusch, M., Dumedah, G.,
Hendricks Franssen, H.-J., Kerr, Y. H., Tomer, S. K., Martens, B., Merlin,
O., Pan, M., Roundy, J. K., Vereecken, H., and Walker, J. P.: Assimilation of SMOS soil moisture and brightness temperature products into a land surface model, Remote Sens. Environ., 180, 292–304, https://doi.org/10.1016/j.rse.2015.10.033, 2016.
Lohmann, D., Nolte-Holube, R., and Raschke, E.: A large-scale horizontal routing model to be coupled to land surface parametrization schemes, Tellus A, 48, 708–721, https://doi.org/10.1034/j.1600-0870.1996.t01-3-00009.x, 1996.
Lohmann, D., Raschke, E., Nijssen, B., and Lettenmaier, D. P.: Regional scale hydrology: I. Formulation of the VIC-2L model coupled to a routing model, Hydrolog. Sci. J., 43, 131–141, https://doi.org/10.1080/02626669809492107, 1998.
Mao, Y.: Dual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: Evaluation of a large-scale implementation with SMAP satellite data, https://doi.org/10.5281/zenodo.3547877, 2019.
Mao, Y., Crow, W. T., and Nijssen, B.: A framework for diagnosing factors
degrading the streamflow performance of a soil moisture data assimilation
system, J. Hydrometeorol., 20, 79–97, https://doi.org/10.1175/JHM-D-18-0115.1, 2019.
Massari, C., Brocca, L., Tarpanelli, A., and Moramarco, T.: Data Assimilation of Satellite Soil Moisture into Rainfall-Runoff Modelling: A Complex Recipe?, Remote Sens., 7, 11403–11433, https://doi.org/10.3390/rs70911403, 2015.
Massari, C., Camici, S., Ciabatta, L., and Brocca, L.: Exploiting satellite-based surface soil moisture for flood forecasting in the Mediterranean area: State update versus rainfall correction, Remote Sens.,
10, 292 https://doi.org/10.3390/rs10020292, 2018.
Maurer, E. P., Wood, A. W., Adam, J. C., Lettenmaier, D. P., and Nijssen, B.:
A long-term hydrologically-based data set of land surface fluxes and states
for the conterminous United States, J. Climate, 15, 3237–3251,
https://doi.org/10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2, 2002.
Mehra, R. K.: On-line identification of linear dynamic systems with applications to Kalman filtering, IEEE T. Autom. Control., 16, 12–21,
https://doi.org/10.1109/TAC.1971.1099621, 1971.
Nearing, G., Yatheendradas, S., Crow, W. T., Chen, F., and Zhan, X: The
efficiency of data assimilation, Water Resour. Res., 54, 6374–6392,
https://doi.org/10.1029/2017WR020991, 2018.
O'Neill, P. E., Chan, S., Njoku, E. G., Jackson, T., and Bindlish, R.: SMAP L3 Radiometer Global Daily 36 km EASE-Grid Soil Moisture, Version 4,
NASA National Snow and Ice Data Center Distributed Active Archive Center, Boulder, Colorado, USA, https://doi.org/10.5067/OBBHQ5W22HME, 2016.
Pan, M. and Wood, E. F.: A multiscale ensemble filtering system for hydrologic data assimilation. Part II: Application to land surface modeling
with satellite rainfall forcing, J. Hydrometeorol., 10, 1493–1506,
https://doi.org/10.1175/2009JHM1155.1, 2009.
Pan, M. and Wood, E. F.: Impact of accuracy, spatial availability, and revisit time of satellite-derived surface soil moisture in a multiscale
ensemble data assimilation system, IEEE J. Select. Top. Appl. Earth Obs. Rem. Sens., 3, 49–56, https://doi.org/10.1109/JSTARS.2010.2040585, 2010.
Pan, M., Wood, E. F., McLaughlin, D. B., and Entekhabi, D.: A multiscale ensemble filtering system for hydrologic data assimilation. Part I:
Implementation and synthetic experiment, J. Hydrometeorol., 10, 794–806,
https://doi.org/10.1175/2009JHM1088.1, 2009.
Qing, L., Reichle, R., Bindlish, R., Cosh, M. H., Crow, W. T., de Jeu, R., de Lannoy, G., Huffman, G. J., and Jackson, T. J.: The contributions of
precipitation and soil moisture observations to the skill of soil moisture
estimates in a land data assimilation system, J. Hydrometeorol., 12, 750–765, https://doi.org/10.1175/JHM-D-10-05000.1, 2011.
Reichle, R. H. and Koster, R. D.: Assessing the impact of horizontal error
correlations in background fields on soil moisture estimation, J. Hydrometeorol., 4, 1229–1242, https://doi.org/10.1175/1525-7541(2003)004<1229:ATIOHE>2.0.CO;2, 2003.
Reichle, R. H., Crow, W. T., Koster, R. D., Sharif, H., and Mahanama, S.:
Contribution of soil moisture retrievals to land data assimilation products,
Geophys. Res. Lett., 35, L01404, https://doi.org/10.1029/2007GL031986, 2008.
Shellito, P. J., Small, E. E., and Livneh B.: Controls on surface soil drying rates observed by SMAP and simulated by the Noah land surface model, Hydrol. Earth Syst. Sci., 22, 1649–1663, https://doi.org/10.5194/hess-22-1649-2018, 2018.
Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of probabilistic
prediction systems, technical report, Eur. Cent. for Medium-Range Weather
Forecast., Reading, UK, 1997.
USGS – United States Geological Survey: USGS Surface-water daily data for
the nation, available at: https://waterdata.usgs.gov/nwis/dv/?referred_module=sw, last access: 21 March 2018.
Wanders, N., Karssenberg, D., De Roo, A., De Jong, S. M., and Bierkens, M. F. P.: The suitability of remotely sensed soil moisture for improving operational flood forecasting, Hydrol. Earth Syst. Sci., 18, 2343–2357,
https://doi.org/10.5194/hess-18-2343-2014, 2014.
Western, A. W., Grayson, R. B., and Blöschl, G.: Scaling of soil moisture: a hydrologic perspective, Annu. Rev. Earth Planet. Sci., 30,
149–180, https://doi.org/10.1146/annurev.earth.30.091201.140434, 2002.
Wilks, D. S.: Statistical methods in the atmospheric sciences, 3rd Edn.,
Elsevier/Academic Press, Amsterdam, Boston, 2011.
Xia, Y., et al.: NCEP/EMC: NLDAS Primary Forcing Data L4 Hourly 0.125×0.125 degree V002, in: NASA/GSFC/HSL, edited by: Mocko, D., Goddard Earth Sciences Data and Information Services Center (GES DISC), Greenbelt, Maryland, USA,
https://doi.org/10.5067/6J5LHHOHZHN4, 2009.
Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo, L., Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V., Duan, Q., Mo, K., Fan, Y., and Mocko, D.: Continental-scale water and energy flux analysis and validation for the North American LandData Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products, J. Geophys. Res., 117, D03109, https://doi.org/10.1029/2011JD016048, 2012.
Yapo, P. O., Gupta, H. V., and Sorooshian, S.: Multi-objective global optimization for hydrologic models, J. Hydrol., 204, 83–97, https://doi.org/10.1016/S0022-1694(97)00107-8, 1998.
Yilmaz, M. T. and Crow, W. T.: The optimality of potential rescaling approaches in land data assimilation, J. Hydrometeorol., 14, 650–660,
https://doi.org/10.1175/JHM-D-12-052.1, 2013.
Short summary
The new generation of satellite soil moisture observations are used to correct the streamflow in a regional-scale river basin simulated by a mathematical model. The correction is done via both the direct updating of soil moisture and correction of rainfall input. Results show some streamflow improvement, but the magnitude is small. A larger improvement will need future generations of even higher-quality satellite soil moisture data and better process representation in the mathematical model.
The new generation of satellite soil moisture observations are used to correct the streamflow in...
