Articles | Volume 27, issue 19
https://doi.org/10.5194/hess-27-3485-2023
© Author(s) 2023. 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-27-3485-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 Oct 2023
Research article |
| 06 Oct 2023
| 06 Oct 2023
Calibrating macroscale hydrological models in poorly gauged and heavily regulated basins
Dung Trung Vu
CORRESPONDING AUTHOR
Pillar of Engineering Systems and Design, Singapore University of Technology and Design, Singapore, Singapore
Thanh Duc Dang
Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL, USA
Francesca Pianosi
School of Civil, Aerospace and Design Engineering, University of Bristol, Bristol, UK
Stefano Galelli
Pillar of Engineering Systems and Design, Singapore University of Technology and Design, Singapore, Singapore
School of Civil and Environmental Engineering, Cornell University, Ithaca, NY, USA
Related authors
Dung Trung Vu, Thanh Duc Dang, Stefano Galelli, and Faisal Hossain
Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, https://doi.org/10.5194/hess-26-2345-2022, 2022
Short summary
Short summary
The lack of data on how big dams are operated in the Upper Mekong, or Lancang, largely contributes to the ongoing controversy between China and the other Mekong countries. Here, we rely on satellite observations to reconstruct monthly storage time series for the 10 largest reservoirs in the Lancang. Our analysis shows how quickly reservoirs were filled in, what decisions were made during recent droughts, and how these decisions impacted downstream discharge.
Shanti Shwarup Mahto, Simone Fatichi, and Stefano Galelli
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-441, https://doi.org/10.5194/essd-2024-441, 2024
Preprint under review for ESSD
Short summary
Short summary
The MSEA-Res database offers an open-access dataset tracking absolute water storage for 185 large reservoirs across Mainland Southeast Asia from 1985–2023. It provides valuable insights into how reservoir storage has grown by 130 % between 2008 and 2017, driven by dams in key river basins. Our data also reveal how droughts, like the 2019–2020 event, significantly impacted water reservoirs. This resource can aid water management, drought planning, and research globally.
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.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
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.
Sanchit Minocha, Faisal Hossain, Pritam Das, Sarath Suresh, Shahzaib Khan, George Darkwah, Hyongki Lee, Stefano Galelli, Konstantinos Andreadis, and Perry Oddo
Geosci. Model Dev., 17, 3137–3156, https://doi.org/10.5194/gmd-17-3137-2024, https://doi.org/10.5194/gmd-17-3137-2024, 2024
Short summary
Short summary
The Reservoir Assessment Tool (RAT) merges satellite data with hydrological models, enabling robust estimation of reservoir parameters like inflow, outflow, surface area, and storage changes around the world. Version 3.0 of RAT lowers the barrier of entry for new users and achieves scalability and computational efficiency. RAT 3.0 also facilitates open-source development of functions for continuous improvement to mobilize and empower the global water management community.
Trevor Page, Paul Smith, Keith Beven, Francesca Pianosi, Fanny Sarrazin, Susana Almeida, Liz Holcombe, Jim Freer, Nick Chappell, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 27, 2523–2534, https://doi.org/10.5194/hess-27-2523-2023, https://doi.org/10.5194/hess-27-2523-2023, 2023
Short summary
Short summary
This publication provides an introduction to the CREDIBLE Uncertainty Estimation (CURE) toolbox. CURE offers workflows for a variety of uncertainty estimation methods. One of its most important features is the requirement that all of the assumptions on which a workflow analysis depends be defined. This facilitates communication with potential users of an analysis. An audit trail log is produced automatically from a workflow for future reference.
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.
Dung Trung Vu, Thanh Duc Dang, Stefano Galelli, and Faisal Hossain
Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, https://doi.org/10.5194/hess-26-2345-2022, 2022
Short summary
Short summary
The lack of data on how big dams are operated in the Upper Mekong, or Lancang, largely contributes to the ongoing controversy between China and the other Mekong countries. Here, we rely on satellite observations to reconstruct monthly storage time series for the 10 largest reservoirs in the Lancang. Our analysis shows how quickly reservoirs were filled in, what decisions were made during recent droughts, and how these decisions impacted downstream discharge.
Andres Peñuela, Christopher Hutton, and Francesca Pianosi
Hydrol. Earth Syst. Sci., 24, 6059–6073, https://doi.org/10.5194/hess-24-6059-2020, https://doi.org/10.5194/hess-24-6059-2020, 2020
Short summary
Short summary
In this paper we evaluate the potential use of seasonal weather forecasts to improve reservoir operation in a UK water supply system. We found that the use of seasonal forecasts can improve the efficiency of reservoir operation but only if the forecast uncertainty is explicitly considered. We also found the degree of efficiency improvement is strongly affected by the decision maker priorities and the hydrological conditions.
Elisa Bozzolan, Elizabeth Holcombe, Francesca Pianosi, and Thorsten Wagener
Nat. Hazards Earth Syst. Sci., 20, 3161–3177, https://doi.org/10.5194/nhess-20-3161-2020, https://doi.org/10.5194/nhess-20-3161-2020, 2020
Short summary
Short summary
We include informal housing in slope stability analysis, considering different slope properties and precipitation events (including climate change). The dominant failure processes are identified, and their relative role in slope failure is quantified. A new rainfall threshold is assessed for urbanised slopes. Instability
rulesare provided to recognise urbanised slopes most at risk. The methodology is suitable for regions with scarce field measurements and landslide inventories.
Thanh Duc Dang, A. F. M. Kamal Chowdhury, and Stefano Galelli
Hydrol. Earth Syst. Sci., 24, 397–416, https://doi.org/10.5194/hess-24-397-2020, https://doi.org/10.5194/hess-24-397-2020, 2020
Short summary
Short summary
A common problem in catchment hydrology lies in the representation of dams in numerical models. Here, we contribute to the existing literature by showing that the representation of water reservoirs can largely impact the model parameters, a result attained by comparing the parameters of a model for the upper Mekong basin built with or without reservoirs. We show that a flawed parameter estimation affects the representation of key physical processes and the downstream applications of the model.
Fanny Sarrazin, Andreas Hartmann, Francesca Pianosi, Rafael Rosolem, and Thorsten Wagener
Geosci. Model Dev., 11, 4933–4964, https://doi.org/10.5194/gmd-11-4933-2018, https://doi.org/10.5194/gmd-11-4933-2018, 2018
Short summary
Short summary
We propose the first large-scale vegetation–recharge model for karst regions (V2Karst), which enables the analysis of the impact of changes in climate and land cover on karst groundwater recharge. We demonstrate the plausibility of V2Karst simulations against observations at FLUXNET sites and of controlling modelled processes using sensitivity analysis. We perform virtual experiments to further test the model and gain insight into its sensitivity to precipitation pattern and vegetation cover.
Sean W. D. Turner, James C. Bennett, David E. Robertson, and Stefano Galelli
Hydrol. Earth Syst. Sci., 21, 4841–4859, https://doi.org/10.5194/hess-21-4841-2017, https://doi.org/10.5194/hess-21-4841-2017, 2017
Short summary
Short summary
This study investigates the relationship between skill and value of ensemble seasonal streamflow forecasts. Using data from a modern forecasting system, we show that skilled forecasts are more likely to provide benefits for reservoirs operated to maintain a target water level rather than reservoirs operated to satisfy a target demand. We identify the primary causes for this behaviour and provide specific recommendations for assessing the value of forecasts for reservoirs with supply objectives.
Susana Almeida, Elizabeth Ann Holcombe, Francesca Pianosi, and Thorsten Wagener
Nat. Hazards Earth Syst. Sci., 17, 225–241, https://doi.org/10.5194/nhess-17-225-2017, https://doi.org/10.5194/nhess-17-225-2017, 2017
Short summary
Short summary
Landslides threaten communities globally, yet predicting their occurrence is challenged by uncertainty about slope properties and climate change. We present an approach to identify the dominant drivers of slope instability and the critical thresholds at which slope failure may occur. This information helps decision makers to target data acquisition to improve landslide predictability, and supports policy development to reduce landslide occurrence and impacts in highly uncertain environments.
A. Hartmann, T. Gleeson, R. Rosolem, F. Pianosi, Y. Wada, and T. Wagener
Geosci. Model Dev., 8, 1729–1746, https://doi.org/10.5194/gmd-8-1729-2015, https://doi.org/10.5194/gmd-8-1729-2015, 2015
Short summary
Short summary
We present a new approach to assess karstic groundwater recharge over Europe and the Mediterranean. Cluster analysis is used to subdivide all karst regions into four typical karst landscapes and to simulate karst recharge with a process-based karst model. We estimate its parameters by a combination of a priori information and observations of soil moisture and evapotranspiration. Independent observations of recharge that present large-scale models significantly under-estimate karstic recharge.
S. Galelli and A. Castelletti
Hydrol. Earth Syst. Sci., 17, 2669–2684, https://doi.org/10.5194/hess-17-2669-2013, https://doi.org/10.5194/hess-17-2669-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments
The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa
Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
On the use of streamflow transformations for hydrological model calibration
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Projections of streamflow intermittence under climate change in European drying river networks
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Achieving water budget closure through physical hydrological processes modelling: insights from a large-sample study
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Heavy-tailed flood peak distributions: What is the effect of the spatial variability of rainfall and runoff generation?
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
State updating in the Xin'anjiang Model: Joint assimilating streamflow and multi-source soil moisture data via Asynchronous Ensemble Kalman Filter with enhanced Error Models
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
A diversity centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Lack of robustness of hydrological models: A large-sample diagnosis and an attempt to identify the hydrological and climatic drivers
Exploring the Potential Processes Controls for Changes of Precipitation-Runoff Relationships in Non-stationary Environments
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
CH-RUN: A data-driven spatially contiguous runoff monitoring product for Switzerland
Simulating the Tone River Eastward Diversion Project in Japan Carried Out Four Centuries Ago
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
Short summary
Short summary
The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
Short summary
Short summary
Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
Short summary
Short summary
This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
Short summary
Short summary
Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
Short summary
Short summary
Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
Short summary
Short summary
We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
Short summary
Short summary
Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
Short summary
Short summary
The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
Short summary
Short summary
We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
Short summary
Short summary
Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
Short summary
Short summary
We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-272, https://doi.org/10.5194/hess-2024-272, 2024
Preprint under review for HESS
Short summary
Short summary
Our study projects how climate change will affect drying of river segments and stream networks in Europe, using advanced modeling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent, intense and start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists in evaluating the ecological health of river ecosystem.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-230, https://doi.org/10.5194/hess-2024-230, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Water budget non-closure is a widespread phenomenon among multisource datasets, which undermines the robustness of hydrological inferences. This study proposes a Multisource Datasets Correction Framework grounded in Physical Hydrological Processes Modelling to enhance water budget closure, called PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset, and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-181, https://doi.org/10.5194/hess-2024-181, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small compared to large catchments, and that spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show an effect. The results can improve estimations of occurrence probabilities of extreme floods.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-211, https://doi.org/10.5194/hess-2024-211, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping better prepare for and respond to floods.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
Short summary
A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary
Short summary
Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
Short summary
Short summary
Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-169, https://doi.org/10.5194/hess-2024-169, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine-learning models are increasingly being applied for flood forecasting. Such models are typically trained to large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets, that maximise the spatiotemproal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
Short summary
Short summary
In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-118, https://doi.org/10.5194/hess-2024-118, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
This study develops an integrated framework based on the novel Driving index for changes in Precipitation-Runoff Relationships (DPRR) to explore the controls for changes in precipitation-runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation-runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
Short summary
Short summary
It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
EGUsphere, https://doi.org/10.5194/egusphere-2024-993, https://doi.org/10.5194/egusphere-2024-993, 2024
Short summary
Short summary
This study uses deep learning to predict spatially contiguous water runoff in Switzerland from 1962–2023. It outperforms traditional models, requiring less data and computational power. Key findings include increased dry years and summer water scarcity. This method offers significant advancements in water monitoring.
Joško Trošelj and Naota Hanasaki
EGUsphere, https://doi.org/10.5194/egusphere-2024-595, https://doi.org/10.5194/egusphere-2024-595, 2024
Short summary
Short summary
This study presents the first distributed hydrological simulation which confirms the claims raised by historians that the Eastward Diversion Project of the Tone River in Japan was conducted four centuries ago to increase low flows and subsequent travelling possibilities surrounding the Capitol Edo (Tokyo) using inland navigation. We reconstructed six historical river maps and indirectly validated the historical simulations with reachable ancient river ports via increased low-flow water levels.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Cited articles
Biancamaria, S., Lettenmaier, D. P., and Pavelsky, T. M.: The SWOT mission
and its capabilities for land hydrology, Springer International Publishing, 117–147, https://doi.org/10.1007/978-3-319-32449-4_6, 2016. a
Bierkens, M. F. P.: Global hydrology 2015: State, trends, and directions,
Water Resour. Res., 51, 4923–4947, https://doi.org/10.1002/2015wr017173, 2015. a, b
Birkinshaw, S. J., O'Donnell, G. M., Moore, P., Kilsby, C. G., Fowler, H. J.,
and Berry, P. A. M.: Using satellite altimetry data to augment flow
estimation techniques on the Mekong River, Hydrol. Process., 24,
3811–3825, https://doi.org/10.1002/hyp.7811, 2010. a
Biswas, N. K., Hossain, F., Bonnema, M., Lee, H., and Chishtie, F.: Towards a
global Reservoir Assessment Tool for predicting hydrologic impacts and
operating patterns of existing and planned reservoirs, Environ. Model. Softw., 140, 105043, https://doi.org/10.1016/j.envsoft.2021.105043, 2021. a
Bonnema, M. and Hossain, F.: Inferring reservoir operating patterns across the Mekong Basin using only space observations, Water Resour. Res., 53,
3791–3810, https://doi.org/10.1002/2016wr019978, 2017. a, b
Bose, I., Jayasinghe, S., Meechaiya, C., Ahmad, S. K., Biswas, N., and Hossain, F.: Developing a baseline characterization of river bathymetry and
time-Varying height for Chindwin River in Myanmar using SRTM and
Landsat data, J. Hydrol. Eng., 26, 05021030,
https://doi.org/10.1061/(asce)he.1943-5584.0002126, 2021. a
Chow, V. T.: Open-channel hydraulic, McGraw-Hill Book Company, New York, ISBN 007085906X, ISBN 9780070859067, 1959. a
Chowdhury, A. K., Dang, T. D., Nguyen, H. T. T., Koh, R., and Galelli, S.: The Greater Mekong's climate-water-energy nexus: How ENSO-triggered
regional droughts affect power supply and CO2 emissions, Earth's Future,
9, e2020ef001814, https://doi.org/10.1029/2020ef001814, 2021. a
Chuphal, D. S. and Mishra, V.: Increased hydropower but with an elevated risk
of reservoir operations in India under the warming climate, iScience, 26, 105986, https://doi.org/10.1016/j.isci.2023.105986, 2023. a
Costa-Cabral, M. C., Richey, J. E., Goteti, G., Lettenmaier, D. P.,
Feldkötter, C., and Snidvongs, A.: Landscape structure and use, climate, and water movement in the Mekong River Basin, Hydrol. Process., 22,
1731–1746, https://doi.org/10.1002/hyp.6740, 2007. a
Critical-Infrastructure-Systems-Lab: VICRes, GitHub [code], https://github.com/Critical-Infrastructure-Systems-Lab/VICRes (last access: 29 September 2023), 2023. a
Dahiti: Database for Hydrological Time Series of Inland Waters (DAHITI), https://dahiti.dgfi.tum.de/ (last access: 29 September 2023), 2023. a
Dan, L., Ji, J., Xie, Z., Chen, F., Wen, G., and Richey, J. E.: Hydrological
projections of climate change scenarios over the 3H region of China: A
VIC model assessment, J. Geogr. Res., 117, D11102,
https://doi.org/10.1029/2011jd017131, 2012. a
Dang, T. D., Chowdhury, A. K., and Galelli, S.: On the representation of water reservoir storage and operations in large-scale hydrological models:
implications on model parameterization and climate change impact assessments, Hydrol. Earth Syst. Sci., 24, 397–416, https://doi.org/10.5194/hess-24-397-2020, 2020a. a, b, c, d, e
Dang, T. D., Vu, D. T., Chowdhury, A. K., and Galelli, S.: A software package
for the representation and optimization of water reservoir operations in the
VIC hydrologic model, Environ. Model. Softw., 126, 104673,
https://doi.org/10.1016/j.envsoft.2020.104673, 2020b. a, b
Dawson, C. W., Abrahart, R. J., and See, L. M.: HydroTest: Further
development of a web resource for the standardised assessment of hydrological
models, Environ. Model. Softw., 25, 1481–1482, https://doi.org/10.1016/j.envsoft.2009.01.001, 2010. a
Döll, P., Berkhoff, K., Bormann, H., Fohrer, N., Gerten, D., Hagemann, S., and Krol, M.: Advances and visions in large-scale hydrological modelling:
findings from the 11th Workshop on large-scale hydrological modelling,
Adv. Geosci., 18, 51–56, https://doi.org/10.5194/adgeo-18-51-2008, 2008. a
dtvu2205: 210520, GitHub [code and data st], https://github.com/dtvu2205/210520 (last access: 29 September 2023), 2023. a
Du, T. L. T., Lee, H., Bui, D. D., Arheimer, B., Li, H.-Y., Olsson, J., Darby, S. E., Sheffield, J., Kim, D., and Hwang, E.: Streamflow prediction in
“geopolitically ungauged” basins using satellite observations and
regionalization at subcontinental scale, J. Hydrol., 588, 125016,
https://doi.org/10.1016/j.jhydrol.2020.125016, 2020. a
Durand, M., Gleason, C. J., Garambois, P. A., Bjerklie, D., Smith, L. C., Roux, H., Rodriguez, E., Bates, P. D., Pavelsky, T. M., Monnier, J., Chen, X., Baldassarre, G. D., Fiset, J.-M., Flipo, N., d. M. Frasson, R. P., Fulton, J., Goutal, N., Hossain, F., Humphries, E., Minear, J. T., Mukolwe, M. M., Neal, J. C., Ricci, S., Sanders, B. F., Schumann, G., Schubert, J. E., and Vilmin, L.: An intercomparison of remote sensing river discharge estimation algorithms from measurements of river height, width, and slope, Water Resour. Res., 52, 4527–4549, https://doi.org/10.1002/2015wr018434, 2016. a
Efstratiadis, A. and Koutsoyiannis, D.: One decade of multi-objective
calibration approaches in hydrological modelling: A review, Hydrolog. Sci. J., 55, 58–78, https://doi.org/10.1080/02626660903526292, 2010. a
Egüen, M., Aguilar, C., Herrero, J., Millares, A., and Polo, M. J.: On the influence of cell size in physically-based distributed hydrological modelling to assess extreme values in water resource planning, Nat. Hazards Earth Syst. Sci., 12, 1573–1582, https://doi.org/10.5194/nhess-12-1573-2012, 2012. a
Engineering ToolBox: Manning's roughness coefficients,
https://www.engineeringtoolbox.com/mannings-roughness-d_799.html (last access: 22 December 2022), 2004. a
Franchini, M. and Pacciani, M.: Comparative analysis of several conceptual
rainfall-runoff models, J. Hydrol., 122, 161–219, https://doi.org/10.1016/0022-1694(91)90178-k, 1991. a
Funk, C., Peterson, P., Landsfeld, M., Pedreros, D., Verdin, J., Shukla, S.,
Rowland, G. H. J., Harrison, L., and Michaelsen, A. H. J.: The climate
hazards infrared precipitation with stations – a new environmental record for monitoring extremes, Sci. Data, 2, 150066, https://doi.org/10.1038/sdata.2015.66, 2015. a
Galelli, S., Dang, T. D., Ng, J. Y., Chowdhury, A. K., and Arias, M. E.:
Opportunities to curb hydrological alterations via dam re-operation in the
Mekong, Nat. Sustainabil., 5, 1058–1069, https://doi.org/10.1038/s41893-022-00971-z, 2022. a
Gao, H., Birkett, C., and Lettenmaier, D. P.: Global monitoring of large
reservoir storage from satellite remote sensing, Water Resour. Res., 48, w09504, https://doi.org/10.1029/2012wr012063, 2012. a
Gleason, C. J. and Smith, L. C.: Toward global mapping of river discharge using satellite images and at-many-stations hydraulic geometry, P. Natl. Acad. Sci. USA, 111, 4788–4791, https://doi.org/10.1073/pnas.1317606111, 2014. a
Grill, G., Lehner, B., Thieme, M., Geenen, B., Tickner, D., Antonelli, F.,
Babu, S., Borrelli, P., Cheng, L., Crochetiere, H., Macedo, H. E.,
Filgueiras, R., Goichot, M., Higgins, J., Hogan, Z., Lip, B., McClain, M. E.,
Meng, J., Mulligan, M., Nilsson, C., Olden, J. D., Opperman, J. J., Petry,
P., Liermann, C. R., Sáenz, L., Salinas-Rodríguez, S., Schelle, P., Schmitt, R. J. P., Snider, J., Tan, F., Tockner, K., Valdujo, P. H., van Soesbergen, A., and Zarfl, C.: Mapping the world's free-flowing rivers, Nature, 59, 215–221, https://doi.org/10.1038/s41586-019-1111-9, 2019. a
Haddeland, I., Skaugen, T., and Lettenmaier, D. P.: Anthropogenic impacts on
continental surface water fluxes, Geophys. Res. Lett., 33, l08406,
https://doi.org/10.1029/2006gl026047, 2006. a
Haddeland, I., Heinke, J., Biemans, H., Eisner, S., Florke, M., Hanasaki, N.,
Konzmann, M., and Ludwig, F.: Global water resources affected by human
interventions and climate change, P. Natl. Acad. Sci. USA, 111, 3251–3256,
https://doi.org/10.1073/pnas.1222475110, 2014. a
Hagemann, M. W., Gleason, C. J., and Durand, M. T.: BAM: Bayesian
AMHG-Manning inference of discharge using remotely sensed stream width,
slope, and height, Water Resour. Res., 53, 9692–9707, https://doi.org/10.1002/2017wr021626, 2017. a
Hecht, J. S., Lacombe, G., Arias, M. E., Dang, T. D., and Pimanh, T.:
Hydropower dams of the Mekong River Basin: A review of their
hydrological impactss, J. Hydrol., 568, 285–300, https://doi.org/10.1016/j.jhydrol.2018.10.045, 2019. a
Hrachowitz, M., Savenije, H. H. G., Blöschl, G., McDonnell, J. J., Sivapalan,
M., Pomeroy, J. W., Arheimer, B., Blume, T., Clark, M. P., Ehret, U.,
Fenicia, F., Freer, J. E., Gelfan, A., Gupta, H. V., Hughes, D. A., Hut,
R. W., Montanari, A., Pande, S., Tetzlaff, D., Troch, P. A., Uhlenbrook, S.,
Wagener, T., Winsemius, H. C., Woods, R. A., Zehe, E., and Cudennec, C.: A
decade of Predictions in Ungauged Basins (PUB) – a review, Hydrolog. Sci. J., 58, 1198–1255, https://doi.org/10.1080/02626667.2013.803183, 2013. a
Huang, Q., Long, D., Du, M., Han, Z., and Han, P.: Daily continuous river
discharge estimation for ungauged basins using a hydrologic model calibrated
by satellite altimetry: Implications for the SWOT mission, Water Resour. Res., 56, e2020wr027309, https://doi.org/10.1029/2020wr027309, 2020. a
International Rivers: The environmental and social impacts of Lancang dams,
https://archive.internationalrivers.org/sites/default/files/attached-files/ir_lancang_dams_researchbrief_final.pdf
(last access: 22 April 2023), 2014. a
Johnson, K.: China commits to share year-round water data with Mekong River Commission, Reuters,
https://www.reuters.com/article/us-mekong-river/china-commits-to-share-year-round-water-data-with-mekong
(last access: 22 December 2022), 2020. a
JPL: SWOT: Surface Water and Ocean Topography,
https://swot.jpl.nasa.gov/ (last access: 22 December 2022), 2022. a
Kabir, T., Pokhrel, Y., and Felfelani, F.: On the precipitation-induced
uncertainties in process-based hydrological modeling in the Mekong River
Basin, Water Resour. Res., 58, e2021wr030828, https://doi.org/10.1029/2021wr030828, 2022. a, b, c
Khan, S. I., Hong, Y., Vergara, H. J., Gourley, J. J., Brakenridge, G. R.,
Groeve, T. D., Flamig, Z. L., Policelli, F., and Yong, B.: Microwave satellite data for hydrologic modeling in ungauged basins, IEEE Geosci. Remote Sens. Lett., 9, 663–667, https://doi.org/10.1109/lgrs.2011.2177807, 2012. a
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.-Atmos., 99, 14415–14428, https://doi.org/10.1029/94jd00483, 2014. a
Lima, F. N., Fernandes, W., and Nascimento, N.: Joint calibration of a
hydrological model and rating curve parameters for simulation of flash flood
in urban areas, Brazil. J. Water Resour., 24, https://doi.org/10.1590/2318-0331.241920180066, 2019. a, b
Liu, G., Schwartz, F. W., Tseng, K.-H., and Shum, C. K.: Discharge and
water-depth estimates for ungauged rivers: Combining hydrologic, hydraulic,
and inverse modeling with stage and water-area measurements from satellites,
Water Resour. Res., 51, 6017–6035, https://doi.org/10.1002/2015wr016971, 2015. a
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/10.3402/tellusa.v48i5.12200, 1996. a
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. a
MRC: The flow of the Mekong, Mekong River Commission Secretariat, Vientiane, https://www.mrcmekong.org/assets/Publications/report-management-develop/MRC-IM-No2-the-flow-of-the-mekong.pdf (last access: 22 December 2022), 2009. a
MRC – Mekong River Commission: Discharge Time-series, https://portal.mrcmekong.org/time-series/discharge/ (last access: 22 December 2022), 2022. a
Nazemi, A. and Wheater, H. S.: On inclusion of water resource management in
Earth system models – Part 1: Problem definition and representation of
water demand, Hydrol. Earth Syst. Sci., 19, 33–61, https://doi.org/10.5194/hess-19-33-2015, 2015a. a
Nazemi, A. and Wheater, H. S.: On inclusion of water resource management in
Earth system models – Part 2: Representation of water supply and allocation and opportunities for improved modeling, Hydrol. Earth Syst. Sci., 19, 63–90, https://doi.org/10.5194/hess-19-63-2015, 2015b. a
Papa, F., Bala, S. K., Pandey, R. K., Durand, F., Gopalakrishna, V. V., Rahman, A., and Rossow, W. B.: Ganga-Brahmaputra river discharge from Jason-2 radar altimetry: An update to the long-term satellite-derived estimates of continental freshwater forcing flux into the Bay of Bengal, J. Geophys. Res., 117, c11021, https://doi.org/10.1029/2012jc008158, 2012. a
Park, D. and Markus, M.: Analysis of a changing hydrologic flood regime using
the Variable Infiltration Capacity model, J. Hydrol., 515, 627–280, https://doi.org/10.1016/j.jhydrol.2014.05.004, 2014. a
Pianosi, F., Beven, K., Freer, J., Hall, J. W., Rougier, J., Stephenson, D. B., and Wagener, T.: Sensitivity analysis of environmental models: A systematic review with practical workflow, Environ. Model. Softw., 79,
214–232, https://doi.org/10.1016/j.envsoft.2016.02.008, 2016. a
Reed, P. M., Hadka, D., Herman, J. D., Kasprzyk, J. R., and Kollat, J. B.:
Evolutionary multiobjective optimization in water resources: The past,
present, and future, Adv. Water Resour., 51, 438–456, https://doi.org/10.1016/j.advwatres.2012.01.005, 2013. a, b
Ren-Jun, Z.: The Xinanjiang model applied in China, J. Hydrol., 135, 371–381, https://doi.org/10.1016/0022-1694(92)90096-e, 1992. a
Shin, S., Pokhrel, Y., Yamazaki, D., Huang, X., Torbick, N., Qi, J.,
Pattanakiat, S., Ngo-Duc, T., and Nguyen, T. D.: High resolution modeling of
river-floodplain-reservoir inundation dynamics in the Mekong River Basin, Water Resour. Res., 56, e2019wr026449, https://doi.org/10.1029/2019wr026449, 2020. a
Steyaert, J. C., Condon, L. E., Turner, S. W. D., and Voisin, N.: ResOpsUS, a dataset of historical reservoir operations in the contiguous United
States, Sci. Data, 9, 1–8, https://doi.org/10.1038/s41597-022-01134-7, 2022. a
Sun, W., Fan, J., Wang, G., Ishidaira, H., Bastola, S., Yu, J., Fu, Y. H.,
Kiem, A. S., Zuo, D., and Xu, Z.: Calibrating a hydrological model in a
regional river of the Qinghai–Tibet plateau using river water width
determined from high spatial resolution satellite images, Remote Sens. Environ., 214, 100–114, https://doi.org/10.1016/j.rse.2018.05.020, 2018. a
Tarpanelli, A., Paris, A., Sichangi, A. W., OLoughlin, F., and Papa, F.: Water resources in Africa: The role of earth observation data and hydrodynamic modeling to derive river discharge, Surv. Geophys., 44, 97–122,
https://doi.org/10.1007/s10712-022-09744-x, 2022. a
Tatsumi, K. and Yamashiki, Y.: Effect of irrigation water withdrawals on water and energy balance in the Mekong River Basin using an improved VIC land surface model with fewer calibration parameters, Agr. Water Manage., 159, 92–106, https://doi.org/10.1016/j.agwat.2015.05.011, 2015. a
Todini, E.: The ARNO rainfall–runoff model, J. Hydrol., 175, 339–382, https://doi.org/10.1016/S0022-1694(96)80016-3, 1996. a
USGS – United States Geological Survey: Space Shuttle Radar Topography Mission (SRTM) DEM, https://earthexplorer.usgs.gov/ (last access: 22 December 2022), 2022. a
van Vliet, M. T. H., Wiberg, D., Leduc, S., and Riahi, K.: Power-generation
system vulnerability and adaptation to changes in climate and water resources, Nat. Clim. Change, 6, 375–380, https://doi.org/10.1038/nclimate2903, 2016. a
Vegad, U. and Mishra, V.: Ensemble streamflow prediction considering the
influence of reservoirs in India, Hydrol. Earth Syst. Sci., 26, 6361–6378, https://doi.org/10.5194/hess-26-6361-2022, 2022. a
Vu, D. T.: Codes and data of satellite observations reveal 13 years of
reservoir filling strategies, operating rules, and hydrological alterations
in the Upper Mekong River Basin, Zenodo [code and data set], https://doi.org/10.5281/zenodo.6299041, 2022. a
Vu, D. T., Dang, T. D., Galelli, S., and Hossain, F.: Satellite observations
reveal 13 years of reservoir filling strategies, operating rules, and
hydrological alterations in the Upper Mekong River basin, Hydrol. Earth Syst. Sci., 26, 2345–2364, https://doi.org/10.5194/hess-26-2345-2022, 2022. a, b, c, d, e, f
Wagener, T. and Pianosi, F.: What has Global Sensitivity Analysis ever
done for us? A systematic review to support scientific advancement and to
inform policy-making in earth system modelling, Earth-Sci. Rev., 194, 1–18, https://doi.org/10.1016/j.earscirev.2019.04.006, 2019. a
Wi, S., Ray, P., M.C.Demaria, E., Steinschneider, S., and Brown, C.: A
user-friendly software package for VIC hydrologic model development,
Environ. Model. Softw., 98, 35–53, https://doi.org/10.1016/j.envsoft.2017.09.006, 2017. a
WLE Mekong: Greater Mekong dam observatory,
https://wle-mekong.cgiar.org/changes/our-research/greater-mekong-dams-observatory/
(last access: 22 December 2022), 2022. a
Xiong, J., Guo, S., and Yin, J.: Discharge estimation using integrated
satellite data and hybrid model in the Midstream Yangtze River, Remote
Sens., 13, 2272, https://doi.org/10.3390/rs13122272, 2021. a
Xue, X., Zhang, K., Hong, Y., and Gourley, J. J.: New multisite cascading
calibration approach for hydrological models: Case study in the Red
River Basin using the VIC model, J. Hydrol. Eng., 21, 05015019, https://doi.org/10.5194/hess-23-3735-2019, 2015.
a
Yeste, P., Ojeda, M. G.-V., Gámiz-Fortis, S. R., Castro-Díez, Y., and
Esteban-Parra, M. J.: Integrated sensitivity analysis of a macroscale
hydrologic model in the north of the Iberian Peninsula, J. Hydrol., 590, 125230, https://doi.org/10.1016/j.jhydrol.2020.125230, 2020. a, b
Yun, X., Tang, Q., Wang, J., Liu, X., Zhang, Y., Lu, H., Wang, Y., Zhang, L.,
and Chen, D.: Impacts of climate change and reservoir operation on streamflow
and flood characteristics in the Lancang-Mekong River Basin, J. Hydrol., 590, 125472, https://doi.org/10.1016/j.jhydrol.2020.125472, 2020. a
Zhai, K., Wu, X., Qin, Y., and Du, P.: Comparison of surface water extraction
performances of different classic water indices using OLI and TM
imageries in different situations, Geospat. Inform. Sci., 18, 34–42, https://doi.org/10.1080/10095020.2015.1017911, 2015. a
Zhang, S., Gao, H., and Naz, B. S.: Monitoring reservoir storage in South
Asia from multisatellite remote sensing, Water Resour. Res., 50, 8927–8943, https://doi.org/10.1002/2014wr015829, 2014. a
Short summary
The calibration of hydrological models over extensive spatial domains is often challenged by the lack of data on river discharge and the operations of hydraulic infrastructures. Here, we use satellite data to address the lack of data that could unintentionally bias the calibration process. Our study is underpinned by a computational framework that quantifies this bias and provides a safe approach to the calibration of models in poorly gauged and heavily regulated basins.
The calibration of hydrological models over extensive spatial domains is often challenged by the...
