Articles | Volume 28, issue 14
https://doi.org/10.5194/hess-28-3133-2024
© Author(s) 2024. 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-28-3133-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 Jul 2024
Research article |
| 19 Jul 2024
| 19 Jul 2024
Leveraging a novel hybrid ensemble and optimal interpolation approach for enhanced streamflow and flood prediction
Mohamad El Gharamti
CORRESPONDING AUTHOR
NCAR, Computational and Information Systems Laboratory (CISL), Boulder, CO, USA
Arezoo Rafieeinasab
NCAR, Research Applications Laboratory (RAL), Boulder, CO, USA
James L. McCreight
UCAR, CPAESS Cooperative Programs for the Advancement of Earth System Science, Boulder, CO, USA
Related authors
Mohamad El Gharamti, James L. McCreight, Seong Jin Noh, Timothy J. Hoar, Arezoo RafieeiNasab, and Benjamin K. Johnson
Hydrol. Earth Syst. Sci., 25, 5315–5336, https://doi.org/10.5194/hess-25-5315-2021, https://doi.org/10.5194/hess-25-5315-2021, 2021
Short summary
Short summary
The article introduces novel ensemble data assimilation (DA) techniques for streamflow forecasting using WRF-Hydro and DART. Model-related biases are tackled through spatially and temporally varying adaptive prior and posterior inflation. Spurious and physically incorrect correlations, on the other hand, are mitigated using a topologically based along-the-stream localization. Hurricane Florence (2018) in the Carolinas, USA, is used as a test case to investigate the performance of DA techniques.
Mohamad E. Gharamti, Johan Valstar, Gijs Janssen, Annemieke Marsman, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 4561–4583, https://doi.org/10.5194/hess-20-4561-2016, https://doi.org/10.5194/hess-20-4561-2016, 2016
Short summary
Short summary
The paper addresses the issue of sampling errors when using the ensemble Kalman filter, in particular its hybrid and second-order formulations. The presented work is aimed at estimating concentration and biodegradation rates of subsurface contaminants at the port of Rotterdam in the Netherlands. Overall, we found that accounting for both forecast and observation sampling errors in the joint data assimilation system helps recover more accurate state and parameter estimates.
Boujemaa Ait-El-Fquih, Mohamad El Gharamti, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 3289–3307, https://doi.org/10.5194/hess-20-3289-2016, https://doi.org/10.5194/hess-20-3289-2016, 2016
Short summary
Short summary
We derive a new dual ensemble Kalman filter (EnKF) for state-parameter estimation. The derivation is based on the one-step-ahead smoothing formulation, and unlike the standard dual EnKF, it is consistent with the Bayesian formulation of the state-parameter estimation problem and uses the observations in both state smoothing and forecast. This is shown to enhance the performance and robustness of the dual EnKF in experiments conducted with a two-dimensional synthetic groundwater aquifer model.
Arezoo Rafieeinasab, Amir Mazrooei, Thomas Enzminger, Ishita Srivastava, Aubrey Dugger, David Gochis, Nina Omani, Joe Grim, Kevin Sampson, Yongxin Zhang, Jacob LaFontaine, Roland Viger, Yuqiong Liu, and Tim Schneider
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-262, https://doi.org/10.5194/hess-2024-262, 2024
Manuscript not accepted for further review
Short summary
Short summary
Integrated Water Availability Assessments is a national initiative to characterize water availability in the U.S. The WRF-Hydro model is used to generate an estimate of hydrological fluxes and storage across the conterminous United States. The streamflow performance is reasonable especially in the eastern and western U.S. Model performance in estimating snow, evapotranspiration and soil moisture is also reasonable with some differences against the verification datasets in certain areas.
Luiz Bacelar, Arezoo ReifeeiNasab, Nathaniel Chaney, and Ana Barros
EGUsphere, https://doi.org/10.5194/egusphere-2023-2088, https://doi.org/10.5194/egusphere-2023-2088, 2023
Preprint archived
Short summary
Short summary
The study explores a computationally efficient probabilistic precipitation forecast approach to generate multiple flood scenarios. It reveals the limitations in predicting flash floods accurately and the need for advanced ensemble methodologies to combine different sources of precipitation forecasts. It highlights the scale-dependency of flood predictions at higher spatial resolutions, shedding light on the relationship between river hydraulics and flood propagation in the river network.
Aaron Heldmyer, Ben Livneh, James McCreight, Laura Read, Joseph Kasprzyk, and Toby Minear
Hydrol. Earth Syst. Sci., 26, 6121–6136, https://doi.org/10.5194/hess-26-6121-2022, https://doi.org/10.5194/hess-26-6121-2022, 2022
Short summary
Short summary
Measurements of channel characteristics are important for accurate forecasting in the NOAA National Water Model (NWM) but are scarcely available. We seek to improve channel representativeness in the NWM by updating channel geometry and roughness parameters using a large, previously unpublished, dataset of approximately 48 000 gauges. We find that the updated channel parameterization from this new dataset leads to improvements in simulated streamflow performance and channel representation.
Mohamad El Gharamti, James L. McCreight, Seong Jin Noh, Timothy J. Hoar, Arezoo RafieeiNasab, and Benjamin K. Johnson
Hydrol. Earth Syst. Sci., 25, 5315–5336, https://doi.org/10.5194/hess-25-5315-2021, https://doi.org/10.5194/hess-25-5315-2021, 2021
Short summary
Short summary
The article introduces novel ensemble data assimilation (DA) techniques for streamflow forecasting using WRF-Hydro and DART. Model-related biases are tackled through spatially and temporally varying adaptive prior and posterior inflation. Spurious and physically incorrect correlations, on the other hand, are mitigated using a topologically based along-the-stream localization. Hurricane Florence (2018) in the Carolinas, USA, is used as a test case to investigate the performance of DA techniques.
Erin Towler and James L. McCreight
Hydrol. Earth Syst. Sci., 25, 2599–2615, https://doi.org/10.5194/hess-25-2599-2021, https://doi.org/10.5194/hess-25-2599-2021, 2021
Short summary
Short summary
We present a wavelet-based approach to quantify streamflow timing errors for model evaluation and development. We demonstrate the method using real and simulated stream discharge data from several locations. We show how results can be used to identify potential hydrologic processes contributing to the timing errors. Furthermore, we illustrate how the method can document model performance by comparing timing errors across versions of the National Water Model.
Mohamad E. Gharamti, Johan Valstar, Gijs Janssen, Annemieke Marsman, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 4561–4583, https://doi.org/10.5194/hess-20-4561-2016, https://doi.org/10.5194/hess-20-4561-2016, 2016
Short summary
Short summary
The paper addresses the issue of sampling errors when using the ensemble Kalman filter, in particular its hybrid and second-order formulations. The presented work is aimed at estimating concentration and biodegradation rates of subsurface contaminants at the port of Rotterdam in the Netherlands. Overall, we found that accounting for both forecast and observation sampling errors in the joint data assimilation system helps recover more accurate state and parameter estimates.
Boujemaa Ait-El-Fquih, Mohamad El Gharamti, and Ibrahim Hoteit
Hydrol. Earth Syst. Sci., 20, 3289–3307, https://doi.org/10.5194/hess-20-3289-2016, https://doi.org/10.5194/hess-20-3289-2016, 2016
Short summary
Short summary
We derive a new dual ensemble Kalman filter (EnKF) for state-parameter estimation. The derivation is based on the one-step-ahead smoothing formulation, and unlike the standard dual EnKF, it is consistent with the Bayesian formulation of the state-parameter estimation problem and uses the observations in both state smoothing and forecast. This is shown to enhance the performance and robustness of the dual EnKF in experiments conducted with a two-dimensional synthetic groundwater aquifer model.
Related subject area
Subject: Water Resources Management | Techniques and Approaches: Modelling approaches
Evaluating an Earth system model from a water manager perspective
Creating a national urban flood dataset for China from news texts (2000–2022) at the county level
Spatially explicit assessment of water stress and potential mitigating solutions in a large water-limited basin: the Yellow River basin in China
A scalable and modular reservoir implementation for large-scale integrated hydrologic simulations
The interprovincial green water flow in China and its teleconnected effects on the social economy
Modeling hydropower operations at the scale of a power grid: a demand-based approach
Determining the threshold of issuing flash flood warnings based on people's response process simulation
Modeling water balance components of conifer species using the Noah-MP model in an eastern Mediterranean ecosystem
Assessment of upscaling methodologies for daily crop transpiration using sap flows and two-source energy balance models in almonds under different water statuses and production systems
Making a case for power-sensitive water modelling: a literature review
Developing water supply reservoir operating rules for large-scale hydrological modelling
An investigation of anthropogenic influences on hydrologic connectivity using model stress tests
The H2Ours game to explore water use, resources and sustainability: connecting issues in two landscapes in Indonesia
Drainage assessment of irrigation districts: on the precision and accuracy of four parsimonious models
Impact of reservoir evaporation on future water availability in north-eastern Brazil: a multi-scenario assessment
How economically and environmentally viable are multiple dams in the upper Cauvery Basin, India? A hydro-economic analysis using a landscape-based hydrological model
Value of seasonal flow forecasts for enhancing reservoir operation and drought management in South Korea
Optimising Ensemble Streamflow Predictions with Bias-Correction and Data Assimilation Techniques
Can adaptations of crop and soil management prevent yield losses during water scarcity? – A modelling study
A generalised ecohydrological landscape classification for assessing ecosystem risk in Australia due to an altering water regime
Process-based three-layer synergistic optimal-allocation model for complex water resource systems considering reclaimed water
Joint optimal operation of the South-to-North Water Diversion Project considering the evenness of water deficit
Employing the generalized Pareto distribution to analyze extreme rainfall events on consecutive rainy days in Thailand's Chi watershed: implications for flood management
How to account for irrigation withdrawals in a watershed model
Inferring reservoir filling strategies under limited-data-availability conditions using hydrological modeling and Earth observations: the case of the Grand Ethiopian Renaissance Dam (GERD)
The precision of satellite-based net irrigation quantification in the Indus and Ganges basins
Developing a Bayesian network model for understanding river catchment resilience under future change scenarios
Quantifying the trade-offs in re-operating dams for the environment in the Lower Volta River
Dynamically coupling system dynamics and SWAT+ models using Tinamït: application of modular tools for coupled human–water system models
Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes
Cooperation in a transboundary river basin: a large-scale socio-hydrological model of the Eastern Nile
Flexible forecast value metric suitable for a wide range of decisions: application using probabilistic subseasonal streamflow forecasts
An improved model of shade-affected stream temperature in Soil & Water Assessment Tool
Seasonal forecasting of snow resources at Alpine sites
Operationalizing equity in multipurpose water systems
Evaluation of a new observationally based channel parameterization for the National Water Model
High-resolution drought simulations and comparison to soil moisture observations in Germany
Cooperation under conflict: participatory hydrological modeling for science policy dialogues for the Aculeo Lake
Socio-hydrological modeling of the tradeoff between flood control and hydropower provided by the Columbia River Treaty
Challenges and benefits of quantifying irrigation through the assimilation of Sentinel-1 backscatter observations into Noah-MP
A system dynamic model to quantify the impacts of water resources allocation on water–energy–food–society (WEFS) nexus
Net irrigation requirement under different climate scenarios using AquaCrop over Europe
The role of multi-criteria decision analysis in a transdisciplinary process: co-developing a flood forecasting system in western Africa
Unfolding the relationship between seasonal forecast skill and value in hydropower production: a global analysis
Drought impact links to meteorological drought indicators and predictability in Spain
Opportunities for seasonal forecasting to support water management outside the tropics
Probabilistic modelling of the inherent field-level pesticide pollution risk in a small drinking water catchment using spatial Bayesian belief networks
Are maps of nitrate reduction in groundwater altered by climate and land use changes?
Historical simulation of maize water footprints with a new global gridded crop model ACEA
Future upstream water consumption and its impact on downstream water availability in the transboundary Indus Basin
Mari R. Tye, Ming Ge, Jadwiga H. Richter, Ethan D. Gutmann, Allyson Rugg, Cindy L. Bruyère, Sue Ellen Haupt, Flavio Lehner, Rachel McCrary, Andrew J. Newman, and Andy Wood
Hydrol. Earth Syst. Sci., 29, 1117–1133, https://doi.org/10.5194/hess-29-1117-2025, https://doi.org/10.5194/hess-29-1117-2025, 2025
Short summary
Short summary
There is a perceived mismatch between the spatial scales on which global climate models can produce data and those needed for water management decisions. However, poor communication of specific metrics relevant to local decisions is also a problem. We assessed the credibility of a set of water management decision metrics in the Community Earth System Model v2 (CESM2). CESM2 shows potentially greater use of its output in long-range water management decisions.
Shengnan Fu, David M. Schultz, Heng Lyu, Zhonghua Zheng, and Chi Zhang
Hydrol. Earth Syst. Sci., 29, 767–783, https://doi.org/10.5194/hess-29-767-2025, https://doi.org/10.5194/hess-29-767-2025, 2025
Short summary
Short summary
We create China’s first open county-level urban flood dataset (2000–2022) using news media data with the help of deep learning. The dataset reflects both natural and societal influences and includes 7595 urban flood events across 2051 counties, covering 46 % of China’s land area. It reveals the predominance of summer floods, an upward trend since 2000, and a decline from southeast to northwest. Notably, some highly developed regions show a decrease, likely due to improved flood management.
Weibin Zhang, Xining Zhao, Xuerui Gao, Wei Liang, Junyi Li, and Baoqing Zhang
Hydrol. Earth Syst. Sci., 29, 507–524, https://doi.org/10.5194/hess-29-507-2025, https://doi.org/10.5194/hess-29-507-2025, 2025
Short summary
Short summary
The Yellow River basin shows worsening water stress indicators (WSIs) over 1965‒2020. Water withdrawal is the main factor driving WSI before 2000, balanced by water availability. Local water yield and upstream flows are key drivers of sub-basin water availability. Water demand is expected to rise by 6.5 % in the 2030s, creating an 8.36 km³ surface water deficit. Enhanced irrigation efficiency can cut this deficit by 25 %, maintaining the stress level but worsening it for 44.9% of the population.
Benjamin D. West, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 29, 245–259, https://doi.org/10.5194/hess-29-245-2025, https://doi.org/10.5194/hess-29-245-2025, 2025
Short summary
Short summary
This article describes the addition of reservoirs to the hydrologic model ParFlow. ParFlow is particularly good at helping us understand some of the broader drivers behind different parts of the water cycle. By having reservoirs in such a model, we hope to be able to better understand both our impacts on the environment and how to adjust our management of reservoirs to changing conditions.
Shan Sang, Yan Li, Chengcheng Hou, Shuangshuang Zi, and Huiqing Lin
Hydrol. Earth Syst. Sci., 29, 67–84, https://doi.org/10.5194/hess-29-67-2025, https://doi.org/10.5194/hess-29-67-2025, 2025
Short summary
Short summary
Green water exchanges between each province in China form an interconnected flow network and have substantial socioeconomic values. Green water flow and its teleconnected socioeconomic effects should be considered in water resource management in addition to blue water.
Laure Baratgin, Jan Polcher, Patrice Dumas, and Philippe Quirion
Hydrol. Earth Syst. Sci., 28, 5479–5509, https://doi.org/10.5194/hess-28-5479-2024, https://doi.org/10.5194/hess-28-5479-2024, 2024
Short summary
Short summary
Hydrological modeling is valuable for estimating the potential impact of climate change on hydropower generation. This study presents a comprehensive approach to modeling the management of hydroelectric reservoirs in hydrological models. The total power grid demand for hydropower is distributed to the various power plants to compute their release. The method is tested on the French national power grid, and it is demonstrated that it successfully reproduces the observed behavior of reservoirs.
Ruikang Zhang, Dedi Liu, Lihua Xiong, Jie Chen, Hua Chen, and Jiabo Yin
Hydrol. Earth Syst. Sci., 28, 5229–5247, https://doi.org/10.5194/hess-28-5229-2024, https://doi.org/10.5194/hess-28-5229-2024, 2024
Short summary
Short summary
Flash flood warnings cannot be effective without people’s responses to them. We propose a method to determine the threshold of issuing warnings based on a people’s response process simulation. The results show that adjusting the warning threshold according to people’s tolerance levels to the failed warnings can improve warning effectiveness, but the prerequisite is to increase forecasting accuracy and decrease forecasting variance.
Mohsen Amini Fasakhodi, Hakan Djuma, Ioannis Sofokleous, Marinos Eliades, and Adriana Bruggeman
Hydrol. Earth Syst. Sci., 28, 5209–5227, https://doi.org/10.5194/hess-28-5209-2024, https://doi.org/10.5194/hess-28-5209-2024, 2024
Short summary
Short summary
This study examined the water use of pine and cypress trees in a semiarid Mediterranean forest environment. We applied a widely used land surface model (Noah-MP) to simulate the water balance of the ecosystem. We found good modeling results for soil moisture. However, the model underestimated the transpiration of the trees during the dry summer months. These findings indicate that more research is needed to improve the modeling of ecosystem responses to climate and land use change.
Manuel Quintanilla-Albornoz, Xavier Miarnau, Ana Pelechá, Héctor Nieto, and Joaquim Bellvert
Hydrol. Earth Syst. Sci., 28, 4797–4818, https://doi.org/10.5194/hess-28-4797-2024, https://doi.org/10.5194/hess-28-4797-2024, 2024
Short summary
Short summary
Remote sensing can be a helpful tool for monitoring crop transpiration (T) for agricultural water management. Since remote sensing provides instantaneous data, upscaling techniques are required to estimate T on a daily scale. This study assesses optimal image acquisition times and four upscaling approaches to estimate daily T. The results indicate that the main errors derive from measurement time and water stress levels, which can be mitigated by choosing a proper upscaling approach.
Rozemarijn ter Horst, Rossella Alba, Jeroen Vos, Maria Rusca, Jonatan Godinez-Madrigal, Lucie V. Babel, Gert Jan Veldwisch, Jean-Philippe Venot, Bruno Bonté, David W. Walker, and Tobias Krueger
Hydrol. Earth Syst. Sci., 28, 4157–4186, https://doi.org/10.5194/hess-28-4157-2024, https://doi.org/10.5194/hess-28-4157-2024, 2024
Short summary
Short summary
The exact power of models often remains hidden, especially when neutrality is claimed. Our review of 61 scientific articles shows that in the scientific literature little attention is given to the power of water models to influence development processes and outcomes. However, there is a lot to learn from those who are openly reflexive. Based on lessons from the review, we call for power-sensitive modelling, which means that people are critical about how models are made and with what effects.
Saskia Salwey, Gemma Coxon, Francesca Pianosi, Rosanna Lane, Chris Hutton, Michael Bliss Singer, Hilary McMillan, and Jim Freer
Hydrol. Earth Syst. Sci., 28, 4203–4218, https://doi.org/10.5194/hess-28-4203-2024, https://doi.org/10.5194/hess-28-4203-2024, 2024
Short summary
Short summary
Reservoirs are essential for water resource management and can significantly impact downstream flow. However, representing reservoirs in hydrological models can be challenging, particularly across large scales. We design a new and simple method for simulating river flow downstream of water supply reservoirs using only open-access data. We demonstrate the approach in 264 reservoir catchments across Great Britain, where we can significantly improve the simulation of reservoir-impacted flow.
Amelie Herzog, Jost Hellwig, and Kerstin Stahl
Hydrol. Earth Syst. Sci., 28, 4065–4083, https://doi.org/10.5194/hess-28-4065-2024, https://doi.org/10.5194/hess-28-4065-2024, 2024
Short summary
Short summary
Surface water–groundwater interaction can vary along a river. This study used a groundwater model that reproduced relative observed longitudinal and vertical connectivity patterns in the river network to assess the system's response to imposed stress tests. For the case study, imposed groundwater abstraction appears to influence connectivity relatively more than altered recharge, but a quantification of absolute exchange flows will require further model improvements.
Lisa Tanika, Rika Ratna Sari, Arief Lukman Hakim, Meine van Noordwijk, Marielos Peña-Claros, Beria Leimona, Edi Purwanto, and Erika N. Speelman
Hydrol. Earth Syst. Sci., 28, 3807–3835, https://doi.org/10.5194/hess-28-3807-2024, https://doi.org/10.5194/hess-28-3807-2024, 2024
Short summary
Short summary
The H2Ours game is designed to facilitate knowledge transfer and sharing among stakeholders to trigger commitment and collaborative action to restore hydrological conditions. The adaptability of the H2Ours game was proven in two different landscapes: groundwater recharge in upper to middle sub-watersheds with (over)use of water in the lowland zone and a peatland with drainage, rewetting, oil palm conversion and fire as issues. The game evaluation shows that the H2Ours game meets its purpose.
Pierre Laluet, Luis Olivera-Guerra, Víctor Altés, Vincent Rivalland, Alexis Jeantet, Julien Tournebize, Omar Cenobio-Cruz, Anaïs Barella-Ortiz, Pere Quintana-Seguí, Josep Maria Villar, and Olivier Merlin
Hydrol. Earth Syst. Sci., 28, 3695–3716, https://doi.org/10.5194/hess-28-3695-2024, https://doi.org/10.5194/hess-28-3695-2024, 2024
Short summary
Short summary
Monitoring agricultural drainage flow in irrigated areas is key to water and soil management. In this paper, four simple drainage models are evaluated on two irrigated sub-basins where drainage flow is measured daily. The evaluation of their precision shows that they simulate drainage very well when calibrated with drainage data and that one of them is slightly better. The evaluation of their accuracy shows that only one model can provide rough drainage estimates without calibration data.
Gláuber Pontes Rodrigues, Arlena Brosinsky, Ítalo Sampaio Rodrigues, George Leite Mamede, and José Carlos de Araújo
Hydrol. Earth Syst. Sci., 28, 3243–3260, https://doi.org/10.5194/hess-28-3243-2024, https://doi.org/10.5194/hess-28-3243-2024, 2024
Short summary
Short summary
The research focuses on a 4-million-inhabitant tropical region supplied by a network of open-water reservoirs where the dry season lasts for 8 months (Jun−Dec). We analysed the impact of four climate change scenarios on the evaporation rate and the associated availability (water yield distributed per year). The worst-case scenario shows that by the end of the century (2071−2099), the evaporation rate in the dry season could increase by 6 %, which would reduce stored water by about 80 %.
Anjana Ekka, Yong Jiang, Saket Pande, and Pieter van der Zaag
Hydrol. Earth Syst. Sci., 28, 3219–3241, https://doi.org/10.5194/hess-28-3219-2024, https://doi.org/10.5194/hess-28-3219-2024, 2024
Short summary
Short summary
For the first time, we analyse the economic and ecological performance of existing multiple big reservoirs on a daily timescale for a major river basin (upper Cauvery) in India, where pre-intervention data were not available but where there are increasing calls for such assessments. Results show that smaller reservoirs on smaller streams that maximize the economic value of stored water are better for the basin economy and the environment. The approach can help to prioritize dam removals.
Yongshin Lee, Andres Peñuela, Francesca Pianosi, and Miguel Angel Rico-Ramirez
EGUsphere, https://doi.org/10.5194/egusphere-2024-1985, https://doi.org/10.5194/egusphere-2024-1985, 2024
Short summary
Short summary
This study assesses the value of Seasonal Flow Forecasts (SFFs) in informing decision-making for drought management in South Korea and introduces a novel method for assessing value benchmarked against historical operations. Our results show the importance of considering flow forecast uncertainty in reservoir operations. But the difference in value between SFFs and Ensemble Streamflow Prediction is negligible. The method for selecting a compromise release schedule is a key control of the value.
Maliko Tanguy, Michael Eastman, Amulya Chevuturi, Eugene Magee, Elizabeth Cooper, Robert H. B. Johnson, Katie Facer-Childs, and Jamie Hannaford
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-179, https://doi.org/10.5194/hess-2024-179, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Our research compares two techniques, Bias-Correction (BC) and Data Assimilation (DA), for improving river flow forecasts across 316 UK catchments. BC, which corrects errors post-simulation, showed broad improvements, while DA, adjusting model states pre-forecast, excelled in specific conditions like snowmelt and high base flows. Each method's unique strengths suit different scenarios. These insights can enhance forecasting systems, offering reliable and user-friendly hydrological predictions.
Malve Heinz, Maria Eliza Turek, Bettina Schaefli, Andreas Keiser, and Annelie Holzkämper
EGUsphere, https://doi.org/10.5194/egusphere-2024-1201, https://doi.org/10.5194/egusphere-2024-1201, 2024
Short summary
Short summary
Potato farmers in Switzerland are facing drier conditions and water restrictions. We explored how improving soil health and planting early maturing potato varieties might help to adapt. Using a computer model, we simulated potato yields and irrigation water needs under water scarcity. Our results show that earlier maturing potato varieties reduce the reliance on irrigation but result in lower yields. However, improving soil health can significantly reduce yield losses.
Alexander Herr, Linda E. Merrin, Patrick J. Mitchell, Anthony P. O'Grady, Kate L. Holland, Richard E. Mount, David A. Post, Chris R. Pavey, and Ashley D. Sparrow
Hydrol. Earth Syst. Sci., 28, 1957–1979, https://doi.org/10.5194/hess-28-1957-2024, https://doi.org/10.5194/hess-28-1957-2024, 2024
Short summary
Short summary
We develop an ecohydrological classification for regions with limited hydrological records. It provides causal links of landscape features and their water requirement. The classification is an essential framework for modelling the impact of future coal resource developments via water on the features. A rule set combines diverse data with prioritisation, resulting in a transparent, repeatable and adjustable approach. We show examples of linking ecohydrology with environmental impacts.
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024, https://doi.org/10.5194/hess-28-1325-2024, 2024
Short summary
Short summary
Applying optimal water allocation models to simultaneously enable economic benefits, water preferences, and environmental demands at different decision levels, timescales, and regions is a challenge. In this study, a process-based three-layer synergistic optimal-allocation model (PTSOA) is established to achieve these goals. Reused, reclaimed water is also coupled to capture environmentally friendly solutions. Network analysis was introduced to reduce competition among different stakeholders.
Bing-Yi Zhou, Guo-Hua Fang, Xin Li, Jian Zhou, and Hua-Yu Zhong
Hydrol. Earth Syst. Sci., 28, 817–832, https://doi.org/10.5194/hess-28-817-2024, https://doi.org/10.5194/hess-28-817-2024, 2024
Short summary
Short summary
The current unreasonable inter-basin water transfer operation leads to the problem of spatial and temporal imbalances in water allocation. This paper defines a water deficit evenness index and incorporates it into a joint optimization model for the Jiangsu section of the South-to-North Water Diversion Project considering ecology and economy. At the same time, the lake storage capacity performs well, and the water transfer efficiency of the river is significantly improved.
Tossapol Phoophiwfa, Prapawan Chomphuwiset, Thanawan Prahadchai, Jeong-Soo Park, Arthit Apichottanakul, Watchara Theppang, and Piyapatr Busababodhin
Hydrol. Earth Syst. Sci., 28, 801–816, https://doi.org/10.5194/hess-28-801-2024, https://doi.org/10.5194/hess-28-801-2024, 2024
Short summary
Short summary
This study examines the impact of extreme rainfall events on flood risk management in Thailand's Chi watershed. By analyzing historical data, we identified regions, notably Udon Thani and Chaiyaphum, with a high risk of flash flooding. To aid in flood risk assessment, visual maps were created. The study underscores the importance of preparing for extreme rainfall events, particularly in the context of climate change, to effectively mitigate potential flood damage.
Elisabeth Brochet, Youen Grusson, Sabine Sauvage, Ludovic Lhuissier, and Valérie Demarez
Hydrol. Earth Syst. Sci., 28, 49–64, https://doi.org/10.5194/hess-28-49-2024, https://doi.org/10.5194/hess-28-49-2024, 2024
Short summary
Short summary
This study aims to take into account irrigation withdrawals in a watershed model. The model we used combines agriculture and hydrological modeling. Two different crop models were compared, the first based on air temperature and the second based on Sentinel-2 satellite data. Results show that including remote sensing data leads to better emergence dates. Both methods allow us to simulate the daily irrigation withdrawals and downstream flow with a good accuracy, especially during low-flow periods.
Awad M. Ali, Lieke A. Melsen, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 27, 4057–4086, https://doi.org/10.5194/hess-27-4057-2023, https://doi.org/10.5194/hess-27-4057-2023, 2023
Short summary
Short summary
Using a new approach based on a combination of modeling and Earth observation, useful information about the filling of the Grand Ethiopian Renaissance Dam can be obtained with limited data and proper rainfall selection. While the monthly streamflow into Sudan has decreased significantly (1.2 × 109–5 × 109 m3) with respect to the non-dam scenario, the negative impact has been masked due to higher-than-average rainfall. We reveal that the dam will need 3–5 more years to complete filling.
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
Short summary
Short summary
This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Kerr J. Adams, Christopher A. J. Macleod, Marc J. Metzger, Nicola Melville, Rachel C. Helliwell, Jim Pritchard, and Miriam Glendell
Hydrol. Earth Syst. Sci., 27, 2205–2225, https://doi.org/10.5194/hess-27-2205-2023, https://doi.org/10.5194/hess-27-2205-2023, 2023
Short summary
Short summary
We applied participatory methods to create a hybrid equation-based Bayesian network (BN) model to increase stakeholder understanding of catchment-scale resilience to the impacts of both climatic and socio-economic stressors to a 2050 time horizon. Our holistic systems-thinking approach enabled stakeholders to gain new perspectives on how future scenarios may influence their specific sectors and how their sector impacted other sectors and environmental conditions within the catchment system.
Afua Owusu, Jazmin Zatarain Salazar, Marloes Mul, Pieter van der Zaag, and Jill Slinger
Hydrol. Earth Syst. Sci., 27, 2001–2017, https://doi.org/10.5194/hess-27-2001-2023, https://doi.org/10.5194/hess-27-2001-2023, 2023
Short summary
Short summary
The construction of two dams in the Lower Volta River, Ghana, adversely affected downstream riverine ecosystems and communities. In contrast, Ghana has enjoyed vast economic benefits from the dams. Herein lies the challenge; there exists a trade-off between water for river ecosystems and water for anthropogenic water demands such hydropower. In this study, we quantify these trade-offs and show that there is room for providing environmental flows under current and future climatic conditions.
Joel Z. Harms, Julien J. Malard-Adam, Jan F. Adamowski, Ashutosh Sharma, and Albert Nkwasa
Hydrol. Earth Syst. Sci., 27, 1683–1693, https://doi.org/10.5194/hess-27-1683-2023, https://doi.org/10.5194/hess-27-1683-2023, 2023
Short summary
Short summary
To facilitate the meaningful participation of stakeholders in water management, model choice is crucial. We show how system dynamics models (SDMs), which are very visual and stakeholder-friendly, can be automatically combined with physically based hydrological models that may be more appropriate for modelling the water processes of a human–water system. This allows building participatory SDMs with stakeholders and delegating hydrological components to an external hydrological model.
Erhu Du, Feng Wu, Hao Jiang, Naliang Guo, Yong Tian, and Chunmiao Zheng
Hydrol. Earth Syst. Sci., 27, 1607–1626, https://doi.org/10.5194/hess-27-1607-2023, https://doi.org/10.5194/hess-27-1607-2023, 2023
Short summary
Short summary
This study develops an integrated socio-hydrological modeling framework that can simulate the entire flood management processes, including flood inundation, flood management policies, public responses, and evacuation activities. The model is able to holistically examine flood evacuation performance under the joint impacts of hydrological conditions, management policies (i.e., shelter location distribution), and human behaviors (i.e., evacuation preparation time and route-searching strategy).
Mohammad Ghoreishi, Amin Elshorbagy, Saman Razavi, Günter Blöschl, Murugesu Sivapalan, and Ahmed Abdelkader
Hydrol. Earth Syst. Sci., 27, 1201–1219, https://doi.org/10.5194/hess-27-1201-2023, https://doi.org/10.5194/hess-27-1201-2023, 2023
Short summary
Short summary
The study proposes a quantitative model of the willingness to cooperate in the Eastern Nile River basin. Our results suggest that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. The model can be used to explore the effects of changes in future dam operations and other management decisions on the emergence of basin cooperation.
Richard Laugesen, Mark Thyer, David McInerney, and Dmitri Kavetski
Hydrol. Earth Syst. Sci., 27, 873–893, https://doi.org/10.5194/hess-27-873-2023, https://doi.org/10.5194/hess-27-873-2023, 2023
Short summary
Short summary
Forecasts may be valuable for user decisions, but current practice to quantify it has critical limitations. This study introduces RUV (relative utility value, a new metric that can be tailored to specific decisions and decision-makers. It illustrates how critical this decision context is when evaluating forecast value. This study paves the way for agencies to tailor the evaluation of their services to customer decisions and researchers to study model improvements through the lens of user impact.
Efrain Noa-Yarasca, Meghna Babbar-Sebens, and Chris Jordan
Hydrol. Earth Syst. Sci., 27, 739–759, https://doi.org/10.5194/hess-27-739-2023, https://doi.org/10.5194/hess-27-739-2023, 2023
Short summary
Short summary
Riparian vegetation has been identified as a strategy to control rising stream temperatures by shading streams. Riparian vegetation is included within a sub-basin-scale hydrological model and evaluated for full and efficient restoration scenarios. Results showed average temperature reductions of 0.91 and 0.86 °C for full and efficient riparian restoration, respectively. Notwithstanding the similar benefits, efficient restoration was 14.4 % cheaper than full riparian vegetation restoration.
Silvia Terzago, Giulio Bongiovanni, and Jost von Hardenberg
Hydrol. Earth Syst. Sci., 27, 519–542, https://doi.org/10.5194/hess-27-519-2023, https://doi.org/10.5194/hess-27-519-2023, 2023
Short summary
Short summary
Reliable seasonal forecasts of the abundance of mountain snowpack over the winter/spring ahead provide valuable information for water management, hydropower production and ski tourism. We present a climate service prototype to generate multi-model ensemble seasonal forecasts of mountain snow depth, based on Copernicus seasonal forecast system meteorological data used to force the SNOWPACK model. The prototype shows skill at predicting snow depth below and above normal and extremely dry seasons.
Guang Yang, Matteo Giuliani, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 27, 69–81, https://doi.org/10.5194/hess-27-69-2023, https://doi.org/10.5194/hess-27-69-2023, 2023
Short summary
Short summary
Participatory decision-making is a well-established approach to address the increasing pressure on water systems that searches for system-wise efficient solutions but often does not quantify how the resulting benefits are distributed across stakeholders. In this work, we show how including equity principles into the design of water system operations enriches the solution space by generating more compromise solutions that balance efficiency and justice.
Aaron Heldmyer, Ben Livneh, James McCreight, Laura Read, Joseph Kasprzyk, and Toby Minear
Hydrol. Earth Syst. Sci., 26, 6121–6136, https://doi.org/10.5194/hess-26-6121-2022, https://doi.org/10.5194/hess-26-6121-2022, 2022
Short summary
Short summary
Measurements of channel characteristics are important for accurate forecasting in the NOAA National Water Model (NWM) but are scarcely available. We seek to improve channel representativeness in the NWM by updating channel geometry and roughness parameters using a large, previously unpublished, dataset of approximately 48 000 gauges. We find that the updated channel parameterization from this new dataset leads to improvements in simulated streamflow performance and channel representation.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
Short summary
Short summary
In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Anahi Ocampo-Melgar, Pilar Barría, Cristián Chadwick, and Cesar Rivas
Hydrol. Earth Syst. Sci., 26, 5103–5118, https://doi.org/10.5194/hess-26-5103-2022, https://doi.org/10.5194/hess-26-5103-2022, 2022
Short summary
Short summary
This article examines how a hydrological model exploring the causes of a lake desiccation was turned into a 5-step participatory process to better adjust the model to address questions that were causing suspicions and conflicts in the community. Although the process was key in finding a combination of strategies that were of moderate impact and higher local acceptability, we address the challenges of such collaboration in modeling when conflict is deeply embedded in the context.
Ashish Shrestha, Felipe Augusto Arguello Souza, Samuel Park, Charlotte Cherry, Margaret Garcia, David J. Yu, and Eduardo Mario Mendiondo
Hydrol. Earth Syst. Sci., 26, 4893–4917, https://doi.org/10.5194/hess-26-4893-2022, https://doi.org/10.5194/hess-26-4893-2022, 2022
Short summary
Short summary
Equitable sharing of benefits is key to successful cooperation in transboundary water resource management. However, external changes can shift the split of benefits and shifts in the preferences regarding how an actor’s benefits compare to the other’s benefits. To understand how these changes can impact the robustness of cooperative agreements, we develop a socio-hydrological system dynamics model of the benefit sharing provision of the Columbia River Treaty and assess a series of scenarios.
Sara Modanesi, Christian Massari, Michel Bechtold, Hans Lievens, Angelica Tarpanelli, Luca Brocca, Luca Zappa, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 4685–4706, https://doi.org/10.5194/hess-26-4685-2022, https://doi.org/10.5194/hess-26-4685-2022, 2022
Short summary
Short summary
Given the crucial impact of irrigation practices on the water cycle, this study aims at estimating irrigation through the development of an innovative data assimilation system able to ingest high-resolution Sentinel-1 radar observations into the Noah-MP land surface model. The developed methodology has important implications for global water resource management and the comprehension of human impacts on the water cycle and identifies main challenges and outlooks for future research.
Yujie Zeng, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Jiabo Yin, and Zhenhui Wu
Hydrol. Earth Syst. Sci., 26, 3965–3988, https://doi.org/10.5194/hess-26-3965-2022, https://doi.org/10.5194/hess-26-3965-2022, 2022
Short summary
Short summary
The sustainability of the water–energy–food (WEF) nexus remains challenge, as interactions between WEF and human sensitivity and water resource allocation in water systems are often neglected. We incorporated human sensitivity and water resource allocation into a WEF nexus and assessed their impacts on the integrated system. This study can contribute to understanding the interactions across the water–energy–food–society nexus and improving the efficiency of resource management.
Louise Busschaert, Shannon de Roos, Wim Thiery, Dirk Raes, and Gabriëlle J. M. De Lannoy
Hydrol. Earth Syst. Sci., 26, 3731–3752, https://doi.org/10.5194/hess-26-3731-2022, https://doi.org/10.5194/hess-26-3731-2022, 2022
Short summary
Short summary
Increasing amounts of water are used for agriculture. Therefore, we looked into how irrigation requirements will evolve under a changing climate over Europe. Our results show that, by the end of the century and under high emissions, irrigation water will increase by 30 % on average compared to the year 2000. Also, the irrigation requirement is likely to vary more from 1 year to another. However, if emissions are mitigated, these effects are reduced.
Judit Lienert, Jafet C. M. Andersson, Daniel Hofmann, Francisco Silva Pinto, and Martijn Kuller
Hydrol. Earth Syst. Sci., 26, 2899–2922, https://doi.org/10.5194/hess-26-2899-2022, https://doi.org/10.5194/hess-26-2899-2022, 2022
Short summary
Short summary
Many western Africans encounter serious floods every year. The FANFAR project co-designed a pre-operational flood forecasting system (FEWS) with 50 key western African stakeholders. Participatory multi-criteria decision analysis (MCDA) helped prioritize a FEWS that meets their needs: it should provide accurate, clear, and timely flood risk information and work reliably in tough conditions. As a theoretical contribution, we propose an assessment framework for transdisciplinary hydrology research.
Donghoon Lee, Jia Yi Ng, Stefano Galelli, and Paul Block
Hydrol. Earth Syst. Sci., 26, 2431–2448, https://doi.org/10.5194/hess-26-2431-2022, https://doi.org/10.5194/hess-26-2431-2022, 2022
Short summary
Short summary
To fully realize the potential of seasonal streamflow forecasts in the hydropower industry, we need to understand the relationship between reservoir design specifications, forecast skill, and value. Here, we rely on realistic forecasts and simulated hydropower operations for 753 dams worldwide to unfold such relationship. Our analysis shows how forecast skill affects hydropower production, what type of dams are most likely to benefit from seasonal forecasts, and where these dams are located.
Herminia Torelló-Sentelles and Christian L. E. Franzke
Hydrol. Earth Syst. Sci., 26, 1821–1844, https://doi.org/10.5194/hess-26-1821-2022, https://doi.org/10.5194/hess-26-1821-2022, 2022
Short summary
Short summary
Drought affects many regions worldwide, and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments on how these indicators are linked to impacts are still lacking. Our results show that meteorological indices are best linked to impact occurrences.
Leah A. Jackson-Blake, François Clayer, Elvira de Eyto, Andrew S. French, María Dolores Frías, Daniel Mercado-Bettín, Tadhg Moore, Laura Puértolas, Russell Poole, Karsten Rinke, Muhammed Shikhani, Leon van der Linden, and Rafael Marcé
Hydrol. Earth Syst. Sci., 26, 1389–1406, https://doi.org/10.5194/hess-26-1389-2022, https://doi.org/10.5194/hess-26-1389-2022, 2022
Short summary
Short summary
We explore, together with stakeholders, whether seasonal forecasting of water quantity, quality, and ecology can help support water management at five case study sites, primarily in Europe. Reliable forecasting, a season in advance, has huge potential to improve decision-making. However, managers were reluctant to use the forecasts operationally. Key barriers were uncertainty and often poor historic performance. The importance of practical hands-on experience was also highlighted.
Mads Troldborg, Zisis Gagkas, Andy Vinten, Allan Lilly, and Miriam Glendell
Hydrol. Earth Syst. Sci., 26, 1261–1293, https://doi.org/10.5194/hess-26-1261-2022, https://doi.org/10.5194/hess-26-1261-2022, 2022
Short summary
Short summary
Pesticides continue to pose a threat to surface water quality worldwide. Here, we present a spatial Bayesian belief network (BBN) for assessing inherent pesticide risk to water quality. The BBN was applied in a small catchment with limited data to simulate the risk of five pesticides and evaluate the likely effectiveness of mitigation measures. The probabilistic graphical model combines diverse data and explicitly accounts for uncertainties, which are often ignored in pesticide risk assessments.
Ida Karlsson Seidenfaden, Torben Obel Sonnenborg, Jens Christian Refsgaard, Christen Duus Børgesen, Jørgen Eivind Olesen, and Dennis Trolle
Hydrol. Earth Syst. Sci., 26, 955–973, https://doi.org/10.5194/hess-26-955-2022, https://doi.org/10.5194/hess-26-955-2022, 2022
Short summary
Short summary
This study investigates how the spatial nitrate reduction in the subsurface may shift under changing climate and land use conditions. This change is investigated by comparing maps showing the spatial nitrate reduction in an agricultural catchment for current conditions, with maps generated for future projected climate and land use conditions. Results show that future climate flow paths may shift the catchment reduction noticeably, while implications of land use changes were less substantial.
Oleksandr Mialyk, Joep F. Schyns, Martijn J. Booij, and Rick J. Hogeboom
Hydrol. Earth Syst. Sci., 26, 923–940, https://doi.org/10.5194/hess-26-923-2022, https://doi.org/10.5194/hess-26-923-2022, 2022
Short summary
Short summary
As the global demand for crops is increasing, it is vital to understand spatial and temporal patterns of crop water footprints (WFs). Previous studies looked into spatial patterns but not into temporal ones. Here, we present a new process-based gridded crop model to simulate WFs and apply it for maize in 1986–2016. We show that despite the average unit WF reduction (−35 %), the global WF of maize production has increased (+50 %), which might harm ecosystems and human livelihoods in some regions.
Wouter J. Smolenaars, Sanita Dhaubanjar, Muhammad K. Jamil, Arthur Lutz, Walter Immerzeel, Fulco Ludwig, and Hester Biemans
Hydrol. Earth Syst. Sci., 26, 861–883, https://doi.org/10.5194/hess-26-861-2022, https://doi.org/10.5194/hess-26-861-2022, 2022
Short summary
Short summary
The arid plains of the lower Indus Basin rely heavily on the water provided by the mountainous upper Indus. Rapid population growth in the upper Indus is expected to increase the water that is consumed there. This will subsequently reduce the water that is available for the downstream plains, where the population and water demand are also expected to grow. In future, this may aggravate tensions over the division of water between the countries that share the Indus Basin.
Cited articles
Abbaszadeh, P., Gavahi, K., and Moradkhani, H.: Multivariate remotely sensed and in-situ data assimilation for enhancing community WRF-Hydro model forecasting, Adv. Water Resour., 145, 103721, https://doi.org/10.1016/j.advwatres.2020.103721, 2020. a
Anderson, J. L.: A method for producing and evaluating probabilistic forecasts from ensemble model integrations, J. Climate, 9, 1518–1530, 1996. a
Anderson, J. L.: A non-Gaussian ensemble filter update for data assimilation, Mon. Weather Rev., 138, 4186–4198, 2010. a
Anderson, J. L.: Localization and sampling error correction in ensemble Kalman filter data assimilation, Mon. Weather Rev., 140, 2359–2371, 2012. a
Anderson, J. L.: A quantile-conserving ensemble filter framework. Part I: Updating an observed variable, Mon. Weather Rev., 150, 1061–1074, 2022. a
Anderson, J. L. and Anderson, S. L.: A Monte Carlo implementation of the nonlinear filtering problem to produce ensemble assimilations and forecasts, Mon. Weather Rev., 127, 2741–2758, 1999. a
Bannister, R. N.: A review of operational methods of variational and ensemble-variational data assimilation, Q. J. Roy. Meteor. Soc., 143, 607–633, 2017. a
Berner, J., Ha, S.-Y., Hacker, J., Fournier, A., and Snyder, C.: Model uncertainty in a mesoscale ensemble prediction system: Stochastic versus multiphysics representations, Mon. Weather Rev., 139, 1972–1995, 2011. a
Boucher, M.-A., Quilty, J., and Adamowski, J.: Data assimilation for streamflow forecasting using extreme learning machines and multilayer perceptrons, Water Resour. Res., 56, e2019WR026226, https://doi.org/10.1029/2019WR026226, 2020. a
Bucci, L., Alaka, L., Hagen, A., Delgado, S., and Beven, J.: Hurricane Ian, https://www.nhc.noaa.gov/data/tcr/AL092022_Ian.pdf (last access: 5 February 2023), 2023. a
Burgers, G., Van Leeuwen, P. J., and Evensen, G.: Analysis scheme in the ensemble Kalman filter, Mon. Weather Rev., 126, 1719–1724, 1998. a
Chao, L., Zhang, K., Wang, S., Gu, Z., Xu, J., and Bao, H.: Assimilation of surface soil moisture jointly retrieved by multiple microwave satellites into the WRF-Hydro model in ungauged regions: Towards a robust flood simulation and forecasting, Environ. Modell. Softw., 154, 105421, https://doi.org/10.1016/j.envsoft.2022.105421, 2022. a
Computational and Information Systems Laboratory: Cheyenne: HPE/SGI ICE XA System (NCAR Community Computing), Boulder, CO, National Center for Atmospheric Research, https://doi.org/10.5065/D6RX99HX, 2019.
Cosgrove, B., Gochis, D., Flowers, T., Dugger, A., Ogden, F., Graziano, T., Clark, E., Cabell, R., Casiday, N., Cui, Z. and Eicher, K., Fall, G., Feng, X., Fitzgerald, K., Frazier, N., George, C., Gibbs, R., Hernandez, L., Johnson, D., Jones, R., Karsten, L., Kefelegn, H., Kitzmiller, D., Lee, H., Liu, Y, Mashriqui, H., Mattern, D., McCluskey, A., McCreight, J. L., McDaniel, R., Midekisa, A., Newman, A., Pan, L., Pham, C., RafieeiNasab, A., Rasmussen, R., Read, L., Rezaeianzadeh, M., Salas, F., Sang, D., Sampson, K., Schneider, T., Shi, Q., Sood, G., Wood, A., Wu, W., Yates, D., Yu, W., and Yongxin, Z.: NOAA's National Water Model: Advancing operational hydrology through continental-scale modeling, J. Am. Water Resour. As., 60, 247–272, https://doi.org/10.1111/1752-1688.13184, 2024. a, b, c, d
Counillon, F., Sakov, P., and Bertino, L.: Application of a hybrid EnKF-OI to ocean forecasting, Ocean Sci., 5, 389–401, https://doi.org/10.5194/os-5-389-2009, 2009. a
Cuntz, M., Mai, J., Samaniego, L., Clark, M., Wulfmeyer, V., Branch, O., Attinger, S., and Thober, S.: The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model, J. Geophys. Res.-Atmos., 121, 10676–10700, 2016. a
DART team: DART, Data Assimilation Research Section (DAReS), DAReS/CISL/NCAR, National Center for Atmospheric Research (NCAR) [code], https://doi.org/10.5065/D6WQ0202, 2022. a
DeChant, C. M. and Moradkhani, H.: Improving the characterization of initial condition for ensemble streamflow prediction using data assimilation, Hydrol. Earth Syst. Sci., 15, 3399–3410, https://doi.org/10.5194/hess-15-3399-2011, 2011. a
DeChant, C. M. and Moradkhani, H.: Toward a reliable prediction of seasonal forecast uncertainty: Addressing model and initial condition uncertainty with ensemble data assimilation and sequential Bayesian combination, J. Hydrol., 519, 2967–2977, 2014. a
Desroziers, G., Berre, L., Chapnik, B., and Poli, P.: Diagnosis of observation, background and analysis-error statistics in observation space, Q. J. Roy. Meteor. Soc., 131, 3385–3396, 2005. a
El Gharamti, M.: Enhanced adaptive inflation algorithm for ensemble filters, Mon. Weather Rev., 146, 623–640, 2018. a
El Gharamti, M.: Hybrid HydroDART Data, Zenodo [code and data set], https://doi.org/10.5281/zenodo.8309815, 2023. a
El Gharamti, M.: DART hybrid EnKF-OI code, Zenodo [code], https://doi.org/10.5281/zenodo.12707479, 2024. a
El Gharamti, M., Raeder, K., Anderson, J., and Wang, X.: Comparing adaptive prior and posterior inflation for ensemble filters using an atmospheric general circulation model, Mon. Weather Rev., 147, 2535–2553, 2019. a
El Gharamti, M., McCreight, J. L., Noh, S. J., Hoar, T. J., RafieeiNasab, A., and Johnson, B. K.: Ensemble streamflow data assimilation using WRF-Hydro and DART: novel localization and inflation techniques applied to Hurricane Florence flooding, Hydrol. Earth Syst. Sci., 25, 5315–5336, https://doi.org/10.5194/hess-25-5315-2021, 2021. a, b, c, d, e, f, g, h, i, j, k
Emery, C. M., David, C. H., Andreadis, K. M., Turmon, M. J., Reager, J. T., Hobbs, J. M., Pan, M., Famiglietti, J. S., Beighley, E., and Rodell, M.: Underlying Fundamentals of Kalman Filtering for River Network Modeling, J. Hydrometeorol., 21, 453–474, 2020. a
Evensen, G.: Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics, J. Geophys. Res.-Oceans, 99, 10143–10162, 1994. a
Falcone, J. A.: GAGES-II: Geospatial attributes of gages for evaluating streamflow, Tech. rep., US Geological Survey, https://doi.org/10.3133/70046617, 2011. a
Fall, G., Kitzmiller, D., Pavlovic, S., Zhang, Z., Patrick, N., St. Laurent, M., Trypaluk, C., Wu, W., and Miller, D.: The Office of Water Prediction's Analysis of Record for Calibration, version 1.1: Dataset description and precipitation evaluation, J. Am. Water Resour. As., 59, 1246–1272, https://doi.org/10.1111/1752-1688.13143, 2023. a
Furrer, R. and Bengtsson, T.: Estimation of high-dimensional prior and posterior covariance matrices in Kalman filter variants, Journal of Multivariate Analysis, 98, 227–255, 2007. a
Gaspari, G. and Cohn, S. E.: Construction of correlation functions in two and three dimensions, Q. J. Roy. Meteor. Soc., 125, 723–757, 1999. a
Gochis, D., Barlage, M., Cabell, R., Casali, M., Dugger, A., FitzGerald, K., McAllister, M., McCreight, J., RafieeiNasab, A., Read, L., Sampson, K., Yates, D., and Zhang, Y.: The WRF-Hydro® modeling system technical description, Version 5.2.0, Tech. rep., https://ral.ucar.edu/sites/default/files/public/projects/wrf-hydro/technical-description-user-guide/wrf-hydrov5.2technicaldescription.pdf (last access: 1 February 2023), 2020. a, b
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, 2009. a
He, C., Valayamkunnath, P., Barlage, M., Chen, F., Gochis, D., Cabell, R., Schneider, T., Rasmussen, R., Niu, G-Y., Yang, Z.-L., Niyogi, D., and Ek, M.: The community Noah-MP land surface modeling system technical description version 5.0, Tech. rep., NCAR Technical Note NCAR/TN-575+ STR, https://doi.org/10.5065/ew8g-yr95, 2023. a
Hernández, F. and Liang, X.: Hybridizing Bayesian and variational data assimilation for high-resolution hydrologic forecasting, Hydrol. Earth Syst. Sci., 22, 5759–5779, https://doi.org/10.5194/hess-22-5759-2018, 2018. a, b
Hersbach, H.: Decomposition of the continuous ranked probability score for ensemble prediction systems, Weather Forecast., 15, 559–570, 2000. a
Houser, P. R., Shuttleworth, W. J., Famiglietti, J. S., Gupta, H. V., Syed, K. H., and Goodrich, D. C.: Integration of soil moisture remote sensing and hydrologic modeling using data assimilation, Water Resour. Res., 34, 3405–3420, 1998. a
Houtekamer, P. L. and Mitchell, H. L.: A sequential ensemble Kalman filter for atmospheric data assimilation, Mon. Weather Rev., 129, 123–137, 2001. a
Huang, C., Newman, A. J., Clark, M. P., Wood, A. W., and Zheng, X.: Evaluation of snow data assimilation using the ensemble Kalman filter for seasonal streamflow prediction in the western United States, Hydrol. Earth Syst. Sci., 21, 635–650, https://doi.org/10.5194/hess-21-635-2017, 2017. a
Kalman, R. E.: A new approach to linear filtering and prediction problems, J. Basic Eng. Mar., 82, 35–45, 1960. a
Kerandi, N., Arnault, J., Laux, P., Wagner, S., Kitheka, J., and Kunstmann, H.: Joint atmospheric-terrestrial water balances for East Africa: a WRF-Hydro case study for the upper Tana River basin, Theor. Appl. Climatol., 131, 1337–1355, 2018. a
Kim, S., Shen, H., Noh, S., Seo, D.-J., Welles, E., Pelgrim, E., Weerts, A., Lyons, E., and Philips, B.: High-resolution modeling and prediction of urban floods using WRF-Hydro and data assimilation, J. Hydrol., 598, 126236, https://doi.org/10.1016/j.jhydrol.2021.126236, 2021. a
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019. a
Lee, H., Shen, H., Noh, S. J., Kim, S., Seo, D.-J., and Zhang, Y.: Improving flood forecasting using conditional bias-penalized ensemble Kalman filter, J. Hydrol., 575, 596–611, 2019. a
Lei, L., Wang, Z., and Tan, Z.-M.: Integrated hybrid data assimilation for an ensemble Kalman filter, Mon. Weather Rev., 149, 4091–4105, 2021. a
Lorenc, A. C.: Analysis methods for numerical weather prediction, Q. J. Roy. Meteor. Soc., 112, 1177–1194, 1986. a
Margulis, S. A., McLaughlin, D., Entekhabi, D., and Dunne, S.: Land data assimilation and estimation of soil moisture using measurements from the Southern Great Plains 1997 Field Experiment, Water Resour. Res., 38, 1299, https://doi.org/10.1029/2001WR001114, 2002. a
Margulis, S. A., Girotto, M., Cortés, G., and Durand, M.: A particle batch smoother approach to snow water equivalent estimation, J. Hydrometeorol., 16, 1752–1772, 2015. a
Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage. Sci., 22, 1087–1096, 1976. a
Mazrooei, A., Sankarasubramanian, A., and Wood, A. W.: Potential in improving monthly streamflow forecasting through variational assimilation of observed streamflow, J. Hydrol., 600, 126559, https://doi.org/10.1016/j.jhydrol.2021.126559, 2021. a
McKay, L., Bondelid, T., Dewald, T., Johnston, J., Moore, R., and Rea, A.: NHDPlus version 2: User guide, US Environmental Protection Agency, https://www.epa.gov/system/files/documents/2023-04/NHDPlusV2_User_Guide.pdf (last access: 1 July 2023), 2012. a
McMillan, H. K., Hreinsson, E. Ö., Clark, M. P., Singh, S. K., Zammit, C., and Uddstrom, M. J.: Operational hydrological data assimilation with the recursive ensemble Kalman filter, Hydrol. Earth Syst. Sci., 17, 21–38, https://doi.org/10.5194/hess-17-21-2013, 2013. a
Mendoza, P. A., Clark, M. P., Barlage, M., Rajagopalan, B., Samaniego, L., Abramowitz, G., and Gupta, H.: Are we unnecessarily constraining the agility of complex process-based models?, Water Resour. Res., 51, 716–728, 2015. a
Meng, S., Xie, X., and Liang, S.: Assimilation of soil moisture and streamflow observations to improve flood forecasting with considering runoff routing lags, J. Hydrol., 550, 568–579, 2017. a
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements, J. Geophys. Res.-Atmos., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011. a
Noh, S. J., Tachikawa, Y., Shiiba, M., and Kim, S.: Ensemble Kalman filtering and particle filtering in a lag-time window for short-term streamflow forecasting with a distributed hydrologic model, J. Hydrol. Eng., 18, 1684–1696, 2013. a
Nunez, C. and Yang, A.: Here's how Hurricanes Form-and why they're so destructive, https://www.nationalgeographic.com/environment/article/hurricanes-typhoons-cyclones (last access: 15 October 2023), 2023. a
Parrish, D. F. and Derber, J. C.: The National Meteorological Center's spectral statistical-interpolation analysis system, Mon. Weather Rev., 120, 1747–1763, 1992. a
Pauwels, V. R. and De Lannoy, G. J.: Improvement of modeled soil wetness conditions and turbulent fluxes through the assimilation of observed discharge, J. Hydrometeorol., 7, 458–477, 2006. a
Pauwels, V. R. and De Lannoy, G. J.: Ensemble-based assimilation of discharge into rainfall-runoff models: A comparison of approaches to mapping observational information to state space, Water Resour. Res., 45, W08428, https://doi.org/10.1029/2008WR007590, 2009. a
Rakovec, O., Weerts, A. H., Hazenberg, P., Torfs, P. J. J. F., and Uijlenhoet, R.: State updating of a distributed hydrological model with Ensemble Kalman Filtering: effects of updating frequency and observation network density on forecast accuracy, Hydrol. Earth Syst. Sci., 16, 3435–3449, https://doi.org/10.5194/hess-16-3435-2012, 2012. a
Rappaport, E. N.: Fatalities in the United States from Atlantic tropical cyclones: New data and interpretation, B. Am. Meteorol. Soc., 95, 341–346, 2014. a
Read, L., Yates, D., McCreight, J., Rafieeinasab, A., Sampson, K., and Gochis, D.: Development and evaluation of the channel routing model and parameters within the National Water Model, J. Am. Water Resour. As., 59, 1051–1066, 2023. a
Reichle, R. H.: Data assimilation methods in the Earth sciences, Adv. Water Resour., 31, 1411–1418, 2008. a
Renard, B., Kavetski, D., Kuczera, G., Thyer, M., and Franks, S. W.: Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors, Water Resour. Res., 46, W05521, https://doi.org/10.1029/2009WR008328, 2010. a
Sacher, W. and Bartello, P.: Sampling errors in ensemble Kalman filtering. Part I: Theory, Mon. Weather Rev., 136, 3035–3049, 2008. a
Senatore, A., Mendicino, G., Gochis, D. J., Yu, W., Yates, D. N., and Kunstmann, H.: Fully coupled atmosphere-hydrology simulations for the central M editerranean: Impact of enhanced hydrological parameterization for short and long time scales, J. Adv. Model. Earth Sy., 7, 1693–1715, 2015. a
Seo, D.-J., Cajina, L., Corby, R., and Howieson, T.: Automatic state updating for operational streamflow forecasting via variational data assimilation, J. Hydrol., 367, 255–275, 2009. a
Smith, A. B.: U.S. billion-dollar weather and climate disasters, 1980–present (NCEI accession 0209268), NOAA National Centers for Environmental Information, https://doi.org/10.25921/stkw-7w73, 2020. a
Son, Y., Di Lorenzo, E., and Luo, J.: WRF-Hydro-CUFA: A scalable and adaptable coastal-urban flood model based on the WRF-Hydro and SWMM models, Environ. Modell. Softw., 167, 105770, https://doi.org/10.1016/j.envsoft.2023.105770, 2023. a
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res.-Atmos., 106, 7183–7192, 2001. a
Tolson, B. A. and Shoemaker, C. A.: Dynamically dimensioned search algorithm for computationally efficient watershed model calibration, Water Resour. Res., 43, W01413, https://doi.org/10.1029/2005WR004723, 2007. a
Troin, M., Arsenault, R., Wood, A. W., Brissette, F., and Martel, J.-L.: Generating ensemble streamflow forecasts: A review of methods and approaches over the past 40 years, Water Resour. Res., 57, e2020WR028392, https://doi.org/10.1029/2020WR028392, 2021. a
Wang, W., Liu, J., Xu, B., Li, C., Liu, Y., and Yu, F.: A WRF/WRF-Hydro coupling system with an improved structure for rainfall-runoff simulation with mixed runoff generation mechanism, J. Hydrol., 612, 128049, https://doi.org/10.1016/j.jhydrol.2022.128049, 2022. a
Weerts, A. H. and El Serafy, G. Y.: Particle filtering and ensemble Kalman filtering for state updating with hydrological conceptual rainfall-runoff models, Water Resour. Res., 42, W09403, https://doi.org/10.1029/2005WR004093, 2006. a
Whitaker, J. S. and Hamill, T. M.: Evaluating methods to account for system errors in ensemble data assimilation, Mon. Weather Rev., 140, 3078–3089, 2012. a
WRF-Hydro team: WRF-Hydro, RAL/NCAR, National Center for Atmospheric Research (NCAR) [code], https://ral.ucar.edu/projects/wrf_hydro (last access: 6 July 2022), 2022. a
Yang, Z.-L., Niu, G.-Y., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Longuevergne, L., Manning, K., Niyogi, D., Tewari, M., and Xia, Y.: The community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins, J. Geophys. Res.-Atmos., 116, D12110, https://doi.org/10.1029/2010JD015140, 2011. a
Yucel, I., Onen, A., Yilmaz, K., and Gochis, D.: Calibration and evaluation of a flood forecasting system: Utility of numerical weather prediction model, data assimilation and satellite-based rainfall, J. Hydrol., 523, 49–66, 2015. a
Zhang, F., Snyder, C., and Sun, J.: Impacts of initial estimate and observation availability on convective-scale data assimilation with an ensemble Kalman filter, Mon. Weather Rev., 132, 1238–1253, 2004. a
Short summary
This study introduces a hybrid data assimilation scheme for precise streamflow predictions during intense rainfall and hurricanes. Tested in real events, it outperforms traditional methods by up to 50 %, utilizing ensemble and climatological background covariances. The adaptive algorithm ensures reliability with a small ensemble, offering improved forecasts up to 18 h in advance, marking a significant advancement in flood prediction capabilities.
This study introduces a hybrid data assimilation scheme for precise streamflow predictions...
