Articles | Volume 26, issue 16
https://doi.org/10.5194/hess-26-4323-2022
© Author(s) 2022. 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-26-4323-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Aug 2022
Research article |
| 24 Aug 2022
| 24 Aug 2022
Benchmarking global hydrological and land surface models against GRACE in a medium-sized tropical basin
Silvana Bolaños Chavarría
CORRESPONDING AUTHOR
Grupo de Ingeniería y Gestión Ambiental (GIGA), Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia
Grupo de Investigación en Ingeniería Sostenible (GIS), Facultad de Ingeniería, Politécnico Colombiano Jaime Isaza Cadavid, Medellín, Colombia
Micha Werner
Water Resources and Ecosystems Department, IHE Delft Institute for Water Education, Delft, the Netherlands
Juan Fernando Salazar
Grupo de Ingeniería y Gestión Ambiental (GIGA), Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia
Teresita Betancur Vargas
Grupo de Ingeniería y Gestión Ambiental (GIGA), Escuela Ambiental, Facultad de Ingeniería, Universidad de Antioquia, Medellín, Colombia
Publisher's note: Teresita Betancur Vargas was added as co-author to this paper on 19 October 2022. They originally contributed to the manuscript but were missing in the author list upon publication.
Related authors
No articles found.
Anne F. Van Loon, Sarra Kchouk, Alessia Matanó, Faranak Tootoonchi, Camila Alvarez-Garreton, Khalid E. A. Hassaballah, Minchao Wu, Marthe L. K. Wens, Anastasiya Shyrokaya, Elena Ridolfi, Riccardo Biella, Viorica Nagavciuc, Marlies H. Barendrecht, Ana Bastos, Louise Cavalcante, Franciska T. de Vries, Margaret Garcia, Johanna Mård, Ileen N. Streefkerk, Claudia Teutschbein, Roshanak Tootoonchi, Ruben Weesie, Valentin Aich, Juan P. Boisier, Giuliano Di Baldassarre, Yiheng Du, Mauricio Galleguillos, René Garreaud, Monica Ionita, Sina Khatami, Johanna K. L. Koehler, Charles H. Luce, Shreedhar Maskey, Heidi D. Mendoza, Moses N. Mwangi, Ilias G. Pechlivanidis, Germano G. Ribeiro Neto, Tirthankar Roy, Robert Stefanski, Patricia Trambauer, Elizabeth A. Koebele, Giulia Vico, and Micha Werner
Nat. Hazards Earth Syst. Sci., 24, 3173–3205, https://doi.org/10.5194/nhess-24-3173-2024, https://doi.org/10.5194/nhess-24-3173-2024, 2024
Short summary
Short summary
Drought is a creeping phenomenon but is often still analysed and managed like an isolated event, without taking into account what happened before and after. Here, we review the literature and analyse five cases to discuss how droughts and their impacts develop over time. We find that the responses of hydrological, ecological, and social systems can be classified into four types and that the systems interact. We provide suggestions for further research and monitoring, modelling, and management.
Juan F. Salazar, Ruben D. Molina, Jorge I. Zuluaga, and Jesus D. Gomez-Velez
Hydrol. Earth Syst. Sci., 28, 2919–2947, https://doi.org/10.5194/hess-28-2919-2024, https://doi.org/10.5194/hess-28-2919-2024, 2024
Short summary
Short summary
Global change is altering river basins and their discharge worldwide. We introduce the land–atmosphere reservoir (LAR) concept to investigate these changes in six of the world's largest basins. We found that low-latitude basins (Amazon, Paraná, and Congo) are getting wetter, whereas high-latitude basins (Mississippi, Ob, and Yenisei) are drying. If this continues, these long-term trends will disrupt the discharge regime and compromise the sustainability of these basins with widespread impacts.
Veit Blauhut, Michael Stoelzle, Lauri Ahopelto, Manuela I. Brunner, Claudia Teutschbein, Doris E. Wendt, Vytautas Akstinas, Sigrid J. Bakke, Lucy J. Barker, Lenka Bartošová, Agrita Briede, Carmelo Cammalleri, Ksenija Cindrić Kalin, Lucia De Stefano, Miriam Fendeková, David C. Finger, Marijke Huysmans, Mirjana Ivanov, Jaak Jaagus, Jiří Jakubínský, Svitlana Krakovska, Gregor Laaha, Monika Lakatos, Kiril Manevski, Mathias Neumann Andersen, Nina Nikolova, Marzena Osuch, Pieter van Oel, Kalina Radeva, Renata J. Romanowicz, Elena Toth, Mirek Trnka, Marko Urošev, Julia Urquijo Reguera, Eric Sauquet, Aleksandra Stevkov, Lena M. Tallaksen, Iryna Trofimova, Anne F. Van Loon, Michelle T. H. van Vliet, Jean-Philippe Vidal, Niko Wanders, Micha Werner, Patrick Willems, and Nenad Živković
Nat. Hazards Earth Syst. Sci., 22, 2201–2217, https://doi.org/10.5194/nhess-22-2201-2022, https://doi.org/10.5194/nhess-22-2201-2022, 2022
Short summary
Short summary
Recent drought events caused enormous damage in Europe. We therefore questioned the existence and effect of current drought management strategies on the actual impacts and how drought is perceived by relevant stakeholders. Over 700 participants from 28 European countries provided insights into drought hazard and impact perception and current management strategies. The study concludes with an urgent need to collectively combat drought risk via a European macro-level drought governance approach.
Agathe Bucherie, Micha Werner, Marc van den Homberg, and Simon Tembo
Nat. Hazards Earth Syst. Sci., 22, 461–480, https://doi.org/10.5194/nhess-22-461-2022, https://doi.org/10.5194/nhess-22-461-2022, 2022
Short summary
Short summary
Local communities in northern Malawi have well-developed knowledge of the conditions leading to flash floods, spatially and temporally. Scientific analysis of catchment geomorphology and global reanalysis datasets corroborates this local knowledge, underlining the potential of these large-scale scientific datasets. Combining local knowledge with contemporary scientific datasets provides a common understanding of flash flood events, contributing to a more people-centred warning to flash floods.
Alexander Kaune, Faysal Chowdhury, Micha Werner, and James Bennett
Hydrol. Earth Syst. Sci., 24, 3851–3870, https://doi.org/10.5194/hess-24-3851-2020, https://doi.org/10.5194/hess-24-3851-2020, 2020
Short summary
Short summary
This paper was developed from PhD research focused on assessing the value of using hydrological datasets in water resource management. Previous studies have assessed how well data can help in predicting river flows, but there is a lack of knowledge of how well data can help in water allocation decisions. In our research, it was found that using seasonal streamflow forecasts improves the available water estimates, resulting in better water allocation decisions in a highly regulated basin.
Mateo Duque-Villegas, Juan Fernando Salazar, and Angela Maria Rendón
Earth Syst. Dynam., 10, 631–650, https://doi.org/10.5194/esd-10-631-2019, https://doi.org/10.5194/esd-10-631-2019, 2019
Short summary
Short summary
Earth's climate can be studied as a system with different components that can be strongly altered by human influence. One possibility is that the El Niño phenomenon becomes more frequent. We investigated the potential impacts of the most frequent El Niño: a permanent one. The most noticeable impacts include variations in global water availability and vegetation productivity, potential dieback of the Amazon rainforest, greening of western North America, and further aridification of Australia.
Alexander Kaune, Micha Werner, Patricia López López, Erasmo Rodríguez, Poolad Karimi, and Charlotte de Fraiture
Hydrol. Earth Syst. Sci., 23, 2351–2368, https://doi.org/10.5194/hess-23-2351-2019, https://doi.org/10.5194/hess-23-2351-2019, 2019
Short summary
Short summary
The value of using longer periods of record of river discharge information from global precipitation datasets is assessed for irrigation area planning. Results show that for all river discharge simulations the benefit of choosing the irrigated area based on the 30 years of simulated data is higher compared to using only 5 years of observed discharge data. Hence, irrigated areas can be better planned using 30 years of river discharge information from global precipitation datasets.
Clara Linés, Ana Iglesias, Luis Garrote, Vicente Sotés, and Micha Werner
Hydrol. Earth Syst. Sci., 22, 5901–5917, https://doi.org/10.5194/hess-22-5901-2018, https://doi.org/10.5194/hess-22-5901-2018, 2018
Short summary
Short summary
In this paper we follow a user-based approach to examine operational drought management decisions and how the role of information on them can be assessed. The approach combines a stakeholder consultation and a decision model representing the interrelated decisions of the irrigation association and farmers. The decision model was extended to include information on snow cover from satellite. This contributed to better decisions in the simulation and ultimately higher benefits for the farmers.
Gaby J. Gründemann, Micha Werner, and Ted I. E. Veldkamp
Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, https://doi.org/10.5194/hess-22-4667-2018, 2018
Short summary
Short summary
Flooding in vulnerable and data-sparse regions such as the Limpopo basin in Southern Africa is a key concern. Data available to local flood managers are often limited, inconsistent or asymmetrically distributed. We demonstrate that freely available global datasets are well suited to provide essential information. Despite the poor performance of simulated discharges, these datasets hold potential in identifying damaging flood events, particularly for higher-resolution datasets and larger basins.
Juan Fernando Salazar, Juan Camilo Villegas, Angela María Rendón, Estiven Rodríguez, Isabel Hoyos, Daniel Mercado-Bettín, and Germán Poveda
Hydrol. Earth Syst. Sci., 22, 1735–1748, https://doi.org/10.5194/hess-22-1735-2018, https://doi.org/10.5194/hess-22-1735-2018, 2018
Short summary
Short summary
River flow regimes are being altered by global change. Understanding the mechanisms behind such alterations is crucial for hydrological prediction. We introduce a novel interpretation of river flow metrics (scaling) that allows any river basin to be classified as regulated or unregulated, and to identify transitions between these states. We propose the
forest reservoirhypothesis to explain how forest loss can force the Amazonian river basins from regulated to unregulated states.
María Carolina Rogelis and Micha Werner
Hydrol. Earth Syst. Sci., 22, 853–870, https://doi.org/10.5194/hess-22-853-2018, https://doi.org/10.5194/hess-22-853-2018, 2018
Short summary
Short summary
Numerical weather prediction (NWP) models are fundamental for flood early warning, particularly in tropical mountainous watersheds. This paper aims to assess the potential of NWP for flood early warning purposes, and the possible improvement that the post-processing of forecasts can provide, in a tropical mountainous area. The results show the potential of NWP but also the need for more detailed evaluation of the meteorological model in the study area.
Daniel Mercado-Bettín, Juan F. Salazar, and Juan Camilo Villegas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2017-550, https://doi.org/10.5194/hess-2017-550, 2017
Revised manuscript not accepted
Short summary
Short summary
Global changes in forest cover have been related to major scientific and social challenges. There are important uncertainties about the potential effects of ongoing forest loss on water cycle. Here we analysis the division of rainfall in evaporation and runoff (water in rivers) and the presence or absence of forest in 22 large regions. We found that in less forested regions, evaporation dominates the division while in more forested regions rainfall is equally divided into evaporation and runoff.
Clara Linés, Micha Werner, and Wim Bastiaanssen
Hydrol. Earth Syst. Sci., 21, 4747–4765, https://doi.org/10.5194/hess-21-4747-2017, https://doi.org/10.5194/hess-21-4747-2017, 2017
Short summary
Short summary
This paper aims at identifying Earth observation data sets that can help river basin managers detect drought conditions that may lead to impacts early enough to take mitigation actions. Six remote sensing products were assessed using two types of impact data as a benchmark: media records from a regional newspaper and crop yields. Precipitation, vegetation condition and evapotranspiration products showed the best results, offering early signs of impacts up to 6 months before the reported damages.
María Carolina Rogelis, Micha Werner, Nelson Obregón, and Nigel Wright
Nat. Hazards Earth Syst. Sci., 16, 833–853, https://doi.org/10.5194/nhess-16-833-2016, https://doi.org/10.5194/nhess-16-833-2016, 2016
Short summary
Short summary
A method to identify mountainous watersheds with the highest flood risk at the regional level is proposed and applied in Bogotá (Colombia). Vulnerability at the regional level was assessed and combined with an existing flood susceptibility indicator, thus providing an index that allows the watersheds to be prioritised. Results show that vulnerability can be expressed in terms of four constituent indicators and a sensitivity analysis shows that the classification of vulnerability is robust.
María Carolina Rogelis, Micha Werner, Nelson Obregón, and Nigel Wright
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-30, https://doi.org/10.5194/hess-2016-30, 2016
Manuscript not accepted for further review
Short summary
Short summary
A distributed model (TETIS), a semi-distributed model (TOPMODEL) and a lumped model (HEC HMS soil moisture accounting) were used to simulate the discharge response of a tropical high mountain basin. Performance analysis and diagnostics were carried out in order to identify the most appropriate model for the study area for flood early warning. The results show that TOPMODEL is the most realistic model of the three tested.
P. Trambauer, M. Werner, H. C. Winsemius, S. Maskey, E. Dutra, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 19, 1695–1711, https://doi.org/10.5194/hess-19-1695-2015, https://doi.org/10.5194/hess-19-1695-2015, 2015
M. C. Rogelis and M. Werner
Nat. Hazards Earth Syst. Sci., 14, 3043–3064, https://doi.org/10.5194/nhess-14-3043-2014, https://doi.org/10.5194/nhess-14-3043-2014, 2014
Short summary
Short summary
A method for assessing regional debris flow susceptibility at the watershed scale, based on an index composed of a morphometric indicator and a land cover indicator, is proposed and applied in 106 peri-urban mountainous watersheds in Bogota, Colombia. The indicator of debris flow susceptibility is obtained from readily available information common to most peri-urban mountainous areas and can be used to prioritise watersheds that can subsequently be subjected to detailed hazard analysis.
F. F. Worku, M. Werner, N. Wright, P. van der Zaag, and S. S. Demissie
Hydrol. Earth Syst. Sci., 18, 3837–3853, https://doi.org/10.5194/hess-18-3837-2014, https://doi.org/10.5194/hess-18-3837-2014, 2014
P. Trambauer, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 2925–2942, https://doi.org/10.5194/hess-18-2925-2014, https://doi.org/10.5194/hess-18-2925-2014, 2014
P. Trambauer, E. Dutra, S. Maskey, M. Werner, F. Pappenberger, L. P. H. van Beek, and S. Uhlenbrook
Hydrol. Earth Syst. Sci., 18, 193–212, https://doi.org/10.5194/hess-18-193-2014, https://doi.org/10.5194/hess-18-193-2014, 2014
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Uncertainty analysis
A data-centric perspective on the information needed for hydrological uncertainty predictions
A decomposition approach to evaluating the local performance of global streamflow reanalysis
Technical note: Complexity–uncertainty curve (c-u-curve) – a method to analyse, classify and compare dynamical systems
Technical note: The CREDIBLE Uncertainty Estimation (CURE) toolbox: facilitating the communication of epistemic uncertainty
On the importance of observation uncertainty when evaluating and comparing models: a hydrological example
Why do our rainfall–runoff models keep underestimating the peak flows?
Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies
Pitfalls and a feasible solution for using KGE as an informal likelihood function in MCMC methods: DREAM(ZS) as an example
Guidance on evaluating parametric model uncertainty at decision-relevant scales
Quantifying input uncertainty in the calibration of water quality models: reordering errors via the secant method
Sequential data assimilation for real-time probabilistic flood inundation mapping
Key challenges facing the application of the conductivity mass balance method: a case study of the Mississippi River basin
Coupled machine learning and the limits of acceptability approach applied in parameter identification for a distributed hydrological model
A systematic assessment of uncertainties in large-scale soil loss estimation from different representations of USLE input factors – a case study for Kenya and Uganda
Technical note: Uncertainty in multi-source partitioning using large tracer data sets
Assessment of climate change impact and difference on the river runoff in four basins in China under 1.5 and 2.0 °C global warming
A likelihood framework for deterministic hydrological models and the importance of non-stationary autocorrelation
Technical note: Analytical sensitivity analysis and uncertainty estimation of baseflow index calculated by a two-component hydrograph separation method with conductivity as a tracer
Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure
The effect of input data resolution and complexity on the uncertainty of hydrological predictions in a humid vegetated watershed
Parameter uncertainty analysis for an operational hydrological model using residual-based and limits of acceptability approaches
Technical note: Pitfalls in using log-transformed flows within the KGE criterion
Improvement of model evaluation by incorporating prediction and measurement uncertainty
Transferability of climate simulation uncertainty to hydrological impacts
Intercomparison of different uncertainty sources in hydrological climate change projections for an alpine catchment (upper Clutha River, New Zealand)
Mapping (dis)agreement in hydrologic projections
Consistency assessment of rating curve data in various locations using Bidirectional Reach (BReach)
The critical role of uncertainty in projections of hydrological extremes
Residual uncertainty estimation using instance-based learning with applications to hydrologic forecasting
Characterizing and reducing equifinality by constraining a distributed catchment model with regional signatures, local observations, and process understanding
Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales
Extending flood forecasting lead time in a large watershed by coupling WRF QPF with a distributed hydrological model
Quantifying uncertainty on sediment loads using bootstrap confidence intervals
Event-scale power law recession analysis: quantifying methodological uncertainty
Disentangling timing and amplitude errors in streamflow simulations
Reliability of lumped hydrological modeling in a semi-arid mountainous catchment facing water-use changes
Using dry and wet year hydroclimatic extremes to guide future hydrologic projections
Uncertainty contributions to low-flow projections in Austria
Accounting for dependencies in regionalized signatures for predictions in ungauged catchments
Climate change and its impacts on river discharge in two climate regions in China
Uncertainty in hydrological signatures
Climate model uncertainty versus conceptual geological uncertainty in hydrological modeling
Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments
Transferring global uncertainty estimates from gauged to ungauged catchments
Spatial sensitivity analysis of snow cover data in a distributed rainfall-runoff model
Uncertainty reduction and parameter estimation of a distributed hydrological model with ground and remote-sensing data
The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models
Flow pathways and nutrient transport mechanisms drive hydrochemical sensitivity to climate change across catchments with different geology and topography
The importance of hydrological uncertainty assessment methods in climate change impact studies
Regional water balance modelling using flow-duration curves with observational uncertainties
Andreas Auer, Martin Gauch, Frederik Kratzert, Grey Nearing, Sepp Hochreiter, and Daniel Klotz
Hydrol. Earth Syst. Sci., 28, 4099–4126, https://doi.org/10.5194/hess-28-4099-2024, https://doi.org/10.5194/hess-28-4099-2024, 2024
Short summary
Short summary
This work examines the impact of temporal and spatial information on the uncertainty estimation of streamflow forecasts. The study emphasizes the importance of data updates and global information for precise uncertainty estimates. We use conformal prediction to show that recent data enhance the estimates, even if only available infrequently. Local data yield reasonable average estimations but fall short for peak-flow events. The use of global data significantly improves these predictions.
Tongtiegang Zhao, Zexin Chen, Yu Tian, Bingyao Zhang, Yu Li, and Xiaohong Chen
Hydrol. Earth Syst. Sci., 28, 3597–3611, https://doi.org/10.5194/hess-28-3597-2024, https://doi.org/10.5194/hess-28-3597-2024, 2024
Short summary
Short summary
The local performance plays a critical part in practical applications of global streamflow reanalysis. This paper develops a decomposition approach to evaluating streamflow analysis at different timescales. The reanalysis is observed to be more effective in characterizing seasonal, annual and multi-annual features than daily, weekly and monthly features. Also, the local performance is shown to be primarily influenced by precipitation seasonality, longitude, mean precipitation and mean slope.
Uwe Ehret and Pankaj Dey
Hydrol. Earth Syst. Sci., 27, 2591–2605, https://doi.org/10.5194/hess-27-2591-2023, https://doi.org/10.5194/hess-27-2591-2023, 2023
Short summary
Short summary
We propose the
c-u-curvemethod to characterize dynamical (time-variable) systems of all kinds.
Uis for uncertainty and expresses how well a system can be predicted in a given period of time.
Cis for complexity and expresses how predictability differs between different periods, i.e. how well predictability itself can be predicted. The method helps to better classify and compare dynamical systems across a wide range of disciplines, thus facilitating scientific collaboration.
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.
Jerom P.M. Aerts, Jannis M. Hoch, Gemma Coxon, Nick C. van de Giesen, and Rolf W. Hut
EGUsphere, https://doi.org/10.5194/egusphere-2023-1156, https://doi.org/10.5194/egusphere-2023-1156, 2023
Short summary
Short summary
Hydrological model performance involves comparing simulated states and fluxes with observed counterparts. Often, it is overlooked that there is inherent uncertainty surrounding the observations. This can significantly impact the results. In this publication, we emphasize the significance of accounting for observation uncertainty in model comparison. We propose a practical method that is applicable for any observational time series with available uncertainty estimations.
András Bárdossy and Faizan Anwar
Hydrol. Earth Syst. Sci., 27, 1987–2000, https://doi.org/10.5194/hess-27-1987-2023, https://doi.org/10.5194/hess-27-1987-2023, 2023
Short summary
Short summary
This study demonstrates the fact that the large river flows forecasted by the models show an underestimation that is inversely related to the number of locations where precipitation is recorded, which is independent of the model. The higher the number of points where the amount of precipitation is recorded, the better the estimate of the river flows.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
Short summary
Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Yan Liu, Jaime Fernández-Ortega, Matías Mudarra, and Andreas Hartmann
Hydrol. Earth Syst. Sci., 26, 5341–5355, https://doi.org/10.5194/hess-26-5341-2022, https://doi.org/10.5194/hess-26-5341-2022, 2022
Short summary
Short summary
We adapt the informal Kling–Gupta efficiency (KGE) with a gamma distribution to apply it as an informal likelihood function in the DiffeRential Evolution Adaptive Metropolis DREAM(ZS) method. Our adapted approach performs as well as the formal likelihood function for exploring posterior distributions of model parameters. The adapted KGE is superior to the formal likelihood function for calibrations combining multiple observations with different lengths, frequencies and units.
Jared D. Smith, Laurence Lin, Julianne D. Quinn, and Lawrence E. Band
Hydrol. Earth Syst. Sci., 26, 2519–2539, https://doi.org/10.5194/hess-26-2519-2022, https://doi.org/10.5194/hess-26-2519-2022, 2022
Short summary
Short summary
Watershed models are used to simulate streamflow and water quality, and to inform siting and sizing decisions for runoff and nutrient control projects. Data are limited for many watershed processes that are represented in such models, which requires selecting the most important processes to be calibrated. We show that this selection should be based on decision-relevant metrics at the spatial scales of interest for the control projects. This should enable more robust project designs.
Xia Wu, Lucy Marshall, and Ashish Sharma
Hydrol. Earth Syst. Sci., 26, 1203–1221, https://doi.org/10.5194/hess-26-1203-2022, https://doi.org/10.5194/hess-26-1203-2022, 2022
Short summary
Short summary
Decomposing parameter and input errors in model calibration is a considerable challenge. This study transfers the direct estimation of an input error series to their rank estimation and develops a new algorithm, i.e., Bayesian error analysis with reordering (BEAR). In the context of a total suspended solids simulation, two synthetic studies and a real study demonstrate that the BEAR method is effective for improving the input error estimation and water quality model calibration.
Keighobad Jafarzadegan, Peyman Abbaszadeh, and Hamid Moradkhani
Hydrol. Earth Syst. Sci., 25, 4995–5011, https://doi.org/10.5194/hess-25-4995-2021, https://doi.org/10.5194/hess-25-4995-2021, 2021
Short summary
Short summary
In this study, daily observations are assimilated into a hydrodynamic model to update the performance of modeling and improve the flood inundation mapping skill. Results demonstrate that integrating data assimilation with a hydrodynamic model improves the performance of flood simulation and provides more reliable inundation maps. A flowchart provides the overall steps for applying this framework in practice and forecasting probabilistic flood maps before the onset of upcoming floods.
Hang Lyu, Chenxi Xia, Jinghan Zhang, and Bo Li
Hydrol. Earth Syst. Sci., 24, 6075–6090, https://doi.org/10.5194/hess-24-6075-2020, https://doi.org/10.5194/hess-24-6075-2020, 2020
Short summary
Short summary
Baseflow separation plays a critical role in science-based management of water resources. This study addressed key challenges hindering the application of the generally accepted conductivity mass balance (CMB). Monitoring data for over 200 stream sites of the Mississippi River basin were collected to answer the following questions. What are the characteristics of a watershed that determine the method suitability? What length of monitoring data is needed? How can the parameters be more accurate?
Aynom T. Teweldebrhan, Thomas V. Schuler, John F. Burkhart, and Morten Hjorth-Jensen
Hydrol. Earth Syst. Sci., 24, 4641–4658, https://doi.org/10.5194/hess-24-4641-2020, https://doi.org/10.5194/hess-24-4641-2020, 2020
Christoph Schürz, Bano Mehdi, Jens Kiesel, Karsten Schulz, and Mathew Herrnegger
Hydrol. Earth Syst. Sci., 24, 4463–4489, https://doi.org/10.5194/hess-24-4463-2020, https://doi.org/10.5194/hess-24-4463-2020, 2020
Short summary
Short summary
The USLE is a commonly used model to estimate soil erosion by water. It quantifies soil loss as a product of six inputs representing rainfall erosivity, soil erodibility, slope length and steepness, plant cover, and support practices. Many methods exist to derive these inputs, which can, however, lead to substantial differences in the estimated soil loss. Here, we analyze the effect of different input representations on the estimated soil loss in a large-scale study in Kenya and Uganda.
Alicia Correa, Diego Ochoa-Tocachi, and Christian Birkel
Hydrol. Earth Syst. Sci., 23, 5059–5068, https://doi.org/10.5194/hess-23-5059-2019, https://doi.org/10.5194/hess-23-5059-2019, 2019
Short summary
Short summary
The applications and availability of large tracer data sets have vastly increased in recent years leading to research into the contributions of multiple sources to a mixture. We introduce a method based on Taylor series approximation to estimate the uncertainties of such sources' contributions. The method is illustrated with examples of hydrology (14 tracers) and a MATLAB code is provided for reproducibility. This method can be generalized to any number of tracers across a range of disciplines.
Hongmei Xu, Lüliu Liu, Yong Wang, Sheng Wang, Ying Hao, Jingjin Ma, and Tong Jiang
Hydrol. Earth Syst. Sci., 23, 4219–4231, https://doi.org/10.5194/hess-23-4219-2019, https://doi.org/10.5194/hess-23-4219-2019, 2019
Short summary
Short summary
1.5 and 2 °C have become targets in the discussion of climate change impacts. However, climate research is also challenged to provide more robust information on the impact of climate change at local and regional scales to assist the development of sound scientific adaptation and mitigation measures. This study assessed the impacts and differences of 1.5 and 2.0 °C global warming on basin-scale river runoff by examining four river basins covering a wide hydroclimatic setting in China.
Lorenz Ammann, Fabrizio Fenicia, and Peter Reichert
Hydrol. Earth Syst. Sci., 23, 2147–2172, https://doi.org/10.5194/hess-23-2147-2019, https://doi.org/10.5194/hess-23-2147-2019, 2019
Short summary
Short summary
The uncertainty of hydrological models can be substantial, and its quantification and realistic description are often difficult. We propose a new flexible probabilistic framework to describe and quantify this uncertainty. It is show that the correlation of the errors can be non-stationary, and that accounting for temporal changes in correlation can lead to strongly improved probabilistic predictions. This is a promising avenue for improving uncertainty estimation in hydrological modelling.
Weifei Yang, Changlai Xiao, and Xiujuan Liang
Hydrol. Earth Syst. Sci., 23, 1103–1112, https://doi.org/10.5194/hess-23-1103-2019, https://doi.org/10.5194/hess-23-1103-2019, 2019
Short summary
Short summary
This paper analyzed the sensitivity of the baseflow index to the parameters of the conductivity two-component hydrograph separation method. The results indicated that the baseflow index is more sensitive to the conductivity of baseflow and the separation method may be more suitable for the long time series in a small watershed. After considering the mutual offset of the measurement errors of conductivity and streamflow, the uncertainty in baseflow index was reduced by half.
Xudong Zhou, Jan Polcher, Tao Yang, Yukiko Hirabayashi, and Trung Nguyen-Quang
Hydrol. Earth Syst. Sci., 22, 6087–6108, https://doi.org/10.5194/hess-22-6087-2018, https://doi.org/10.5194/hess-22-6087-2018, 2018
Short summary
Short summary
Model bias is commonly seen in discharge simulation by hydrological or land surface models. This study tested an approach with the Budyko hypothesis to retrospect the estimated discharge bias to different bias sources including the atmospheric variables and model structure. Results indicate that the bias is most likely caused by the forcing variables, and the forcing bias should firstly be assessed and reduced in order to perform pertinent analysis of the regional water cycle.
Linh Hoang, Rajith Mukundan, Karen E. B. Moore, Emmet M. Owens, and Tammo S. Steenhuis
Hydrol. Earth Syst. Sci., 22, 5947–5965, https://doi.org/10.5194/hess-22-5947-2018, https://doi.org/10.5194/hess-22-5947-2018, 2018
Short summary
Short summary
The paper analyzes the effect of two input data (DEMs and the combination of soil and land use data) with different resolution and complexity on the uncertainty of model outputs (the predictions of streamflow and saturated areas) and parameter uncertainty using SWAT-HS. Results showed that DEM resolution has significant effect on the spatial pattern of saturated areas and using complex soil and land use data may not necessarily improve model performance or reduce model uncertainty.
Aynom T. Teweldebrhan, John F. Burkhart, and Thomas V. Schuler
Hydrol. Earth Syst. Sci., 22, 5021–5039, https://doi.org/10.5194/hess-22-5021-2018, https://doi.org/10.5194/hess-22-5021-2018, 2018
Léonard Santos, Guillaume Thirel, and Charles Perrin
Hydrol. Earth Syst. Sci., 22, 4583–4591, https://doi.org/10.5194/hess-22-4583-2018, https://doi.org/10.5194/hess-22-4583-2018, 2018
Short summary
Short summary
The Kling and Gupta efficiency (KGE) is a score used in hydrology to evaluate flow simulation compared to observations. In order to force the evaluation on the low flows, some authors used the log-transformed flow to calculate the KGE. In this technical note, we show that this transformation should be avoided because it produced numerical flaws that lead to difficulties in the score value interpretation.
Lei Chen, Shuang Li, Yucen Zhong, and Zhenyao Shen
Hydrol. Earth Syst. Sci., 22, 4145–4154, https://doi.org/10.5194/hess-22-4145-2018, https://doi.org/10.5194/hess-22-4145-2018, 2018
Short summary
Short summary
In this study, the cumulative distribution function approach (CDFA) and the Monte Carlo approach (MCA) were used to develop two new approaches for model evaluation within an uncertainty framework. These proposed methods could be extended to watershed models to provide a substitution for traditional model evaluations within an uncertainty framework.
Hui-Min Wang, Jie Chen, Alex J. Cannon, Chong-Yu Xu, and Hua Chen
Hydrol. Earth Syst. Sci., 22, 3739–3759, https://doi.org/10.5194/hess-22-3739-2018, https://doi.org/10.5194/hess-22-3739-2018, 2018
Short summary
Short summary
Facing a growing number of climate models, many selection methods were proposed to select subsets in the field of climate simulation, but the transferability of their performances to hydrological impacts remains doubtful. We investigate the transferability of climate simulation uncertainty to hydrological impacts using two selection methods, and conclude that envelope-based selection of about 10 climate simulations based on properly chosen climate variables is suggested for impact studies.
Andreas M. Jobst, Daniel G. Kingston, Nicolas J. Cullen, and Josef Schmid
Hydrol. Earth Syst. Sci., 22, 3125–3142, https://doi.org/10.5194/hess-22-3125-2018, https://doi.org/10.5194/hess-22-3125-2018, 2018
Lieke A. Melsen, Nans Addor, Naoki Mizukami, Andrew J. Newman, Paul J. J. F. Torfs, Martyn P. Clark, Remko Uijlenhoet, and Adriaan J. Teuling
Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, https://doi.org/10.5194/hess-22-1775-2018, 2018
Short summary
Short summary
Long-term hydrological predictions are important for water management planning, but are also prone to uncertainty. This study investigates three sources of uncertainty for long-term hydrological predictions in the US: climate models, hydrological models, and hydrological model parameters. Mapping the results revealed spatial patterns in the three sources of uncertainty: different sources of uncertainty dominate in different regions.
Katrien Van Eerdenbrugh, Stijn Van Hoey, Gemma Coxon, Jim Freer, and Niko E. C. Verhoest
Hydrol. Earth Syst. Sci., 21, 5315–5337, https://doi.org/10.5194/hess-21-5315-2017, https://doi.org/10.5194/hess-21-5315-2017, 2017
Short summary
Short summary
Consistency in stage–discharge data is investigated using a methodology called Bidirectional Reach (BReach). Various measurement stations in the UK, New Zealand and Belgium are selected based on their historical ratings information and their characteristics related to data consistency. When applying a BReach analysis on them, the methodology provides results that appear consistent with the available knowledge and thus facilitates a reliable assessment of (in)consistency in stage–discharge data.
Hadush K. Meresa and Renata J. Romanowicz
Hydrol. Earth Syst. Sci., 21, 4245–4258, https://doi.org/10.5194/hess-21-4245-2017, https://doi.org/10.5194/hess-21-4245-2017, 2017
Short summary
Short summary
Evaluation of the uncertainty in projections of future hydrological extremes in the mountainous catchment was performed. The uncertainty of the estimate of 1-in-100-year return maximum flow based on the 1971–2100 time series exceeds 200 % of its median value with the largest influence of the climate model uncertainty, while the uncertainty of the 1-in-100-year return minimum flow is of the same order (i.e. exceeds 200 %) but it is mainly influenced by the hydrological model parameter uncertainty.
Omar Wani, Joost V. L. Beckers, Albrecht H. Weerts, and Dimitri P. Solomatine
Hydrol. Earth Syst. Sci., 21, 4021–4036, https://doi.org/10.5194/hess-21-4021-2017, https://doi.org/10.5194/hess-21-4021-2017, 2017
Short summary
Short summary
We generate uncertainty intervals for hydrologic model predictions using a simple instance-based learning scheme. Errors made by the model in some specific hydrometeorological conditions in the past are used to predict the probability distribution of its errors during forecasting. We test it for two different case studies in England. We find that this technique, even though conceptually simple and easy to implement, performs as well as some other sophisticated uncertainty estimation methods.
Christa Kelleher, Brian McGlynn, and Thorsten Wagener
Hydrol. Earth Syst. Sci., 21, 3325–3352, https://doi.org/10.5194/hess-21-3325-2017, https://doi.org/10.5194/hess-21-3325-2017, 2017
Short summary
Short summary
Models are tools for understanding how watersheds function and may respond to land cover and climate change. Before we can use models towards these purposes, we need to ensure that a model adequately represents watershed-wide observations. In this paper, we propose a new way to evaluate whether model simulations match observations, using a variety of information sources. We show how this information can reduce uncertainty in inputs to models, reducing uncertainty in hydrologic predictions.
Gabriele Baroni, Matthias Zink, Rohini Kumar, Luis Samaniego, and Sabine Attinger
Hydrol. Earth Syst. Sci., 21, 2301–2320, https://doi.org/10.5194/hess-21-2301-2017, https://doi.org/10.5194/hess-21-2301-2017, 2017
Short summary
Short summary
Three methods are used to characterize the uncertainty in soil properties. The effect on simulated states and fluxes is quantified using a distributed hydrological model. Different impacts are identified as function of the perturbation method, of the model outputs and of the spatio-temporal resolution. The study underlines the importance of a proper characterization of the uncertainty in soil properties for a correct assessment of their role and further improvements in the model application.
Ji Li, Yangbo Chen, Huanyu Wang, Jianming Qin, Jie Li, and Sen Chiao
Hydrol. Earth Syst. Sci., 21, 1279–1294, https://doi.org/10.5194/hess-21-1279-2017, https://doi.org/10.5194/hess-21-1279-2017, 2017
Short summary
Short summary
Quantitative precipitation forecast produced by the WRF model has a similar pattern to that estimated by rain gauges in a southern China large watershed, hydrological model parameters should be optimized with QPF produced by WRF, and simulating floods by coupling the WRF QPF with a distributed hydrological model provides a good reference for large watershed flood warning and could benefit the flood management communities due to its longer lead time.
Johanna I. F. Slaets, Hans-Peter Piepho, Petra Schmitter, Thomas Hilger, and Georg Cadisch
Hydrol. Earth Syst. Sci., 21, 571–588, https://doi.org/10.5194/hess-21-571-2017, https://doi.org/10.5194/hess-21-571-2017, 2017
Short summary
Short summary
Determining measures of uncertainty on loads is not trivial, as a load is a product of concentration and discharge per time point, summed up over time. A bootstrap approach enables the calculation of confidence intervals on constituent loads. Ignoring the uncertainty on the discharge will typically underestimate the width of 95 % confidence intervals by around 10 %. Furthermore, confidence intervals are asymmetric, with the largest uncertainty on the upper limit.
David N. Dralle, Nathaniel J. Karst, Kyriakos Charalampous, Andrew Veenstra, and Sally E. Thompson
Hydrol. Earth Syst. Sci., 21, 65–81, https://doi.org/10.5194/hess-21-65-2017, https://doi.org/10.5194/hess-21-65-2017, 2017
Short summary
Short summary
The streamflow recession is the period following rainfall during which flow declines. This paper examines a common method of recession analysis and identifies sensitivity of the technique's results to necessary, yet subjective, methodological choices. The results have implications for hydrology, sediment and solute transport, and geomorphology, as well as for testing numerous hydrologic theories which predict the mathematical form of the recession.
Simon Paul Seibert, Uwe Ehret, and Erwin Zehe
Hydrol. Earth Syst. Sci., 20, 3745–3763, https://doi.org/10.5194/hess-20-3745-2016, https://doi.org/10.5194/hess-20-3745-2016, 2016
Short summary
Short summary
While the assessment of "vertical" (magnitude) errors of streamflow simulations is standard practice, "horizontal" (timing) errors are rarely considered. To assess their role, we propose a method to quantify both errors simultaneously which closely resembles visual hydrograph comparison. Our results reveal differences in time–magnitude error statistics for different flow conditions. The proposed method thus offers novel perspectives for model diagnostics and evaluation.
Paul Hublart, Denis Ruelland, Inaki García de Cortázar-Atauri, Simon Gascoin, Stef Lhermitte, and Antonio Ibacache
Hydrol. Earth Syst. Sci., 20, 3691–3717, https://doi.org/10.5194/hess-20-3691-2016, https://doi.org/10.5194/hess-20-3691-2016, 2016
Short summary
Short summary
Our paper explores the reliability of conceptual catchment models in the dry Andes. First, we show that explicitly accounting for irrigation water use improves streamflow predictions during dry years. Second, we show that sublimation losses can be easily incorporated into temperature-based melt models without increasing model complexity too much. Our work also highlights areas requiring additional research, including the need for a better conceptualization of runoff generation processes.
Stephen Oni, Martyn Futter, Jose Ledesma, Claudia Teutschbein, Jim Buttle, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 20, 2811–2825, https://doi.org/10.5194/hess-20-2811-2016, https://doi.org/10.5194/hess-20-2811-2016, 2016
Short summary
Short summary
This paper presents an important framework to improve hydrologic projections in cold regions. Hydrologic modelling/projections are often based on model calibration to long-term data. Here we used dry and wet years as a proxy to quantify uncertainty in projecting hydrologic extremes. We showed that projections based on long-term data could underestimate runoff by up to 35% in boreal regions. We believe the hydrologic modelling community will benefit from new insights derived from this study.
Juraj Parajka, Alfred Paul Blaschke, Günter Blöschl, Klaus Haslinger, Gerold Hepp, Gregor Laaha, Wolfgang Schöner, Helene Trautvetter, Alberto Viglione, and Matthias Zessner
Hydrol. Earth Syst. Sci., 20, 2085–2101, https://doi.org/10.5194/hess-20-2085-2016, https://doi.org/10.5194/hess-20-2085-2016, 2016
Short summary
Short summary
Streamflow estimation during low-flow conditions is important for estimation of environmental flows, effluent water quality, hydropower operations, etc. However, it is not clear how the uncertainties in assumptions used in the projections translate into uncertainty of estimated future low flows. The objective of the study is to explore the relative role of hydrologic model calibration and climate scenarios in the uncertainty of low-flow projections in Austria.
Susana Almeida, Nataliya Le Vine, Neil McIntyre, Thorsten Wagener, and Wouter Buytaert
Hydrol. Earth Syst. Sci., 20, 887–901, https://doi.org/10.5194/hess-20-887-2016, https://doi.org/10.5194/hess-20-887-2016, 2016
Short summary
Short summary
The absence of flow data to calibrate hydrologic models may reduce the ability of such models to reliably inform water resources management. To address this limitation, it is common to condition hydrological model parameters on regionalized signatures. In this study, we justify the inclusion of larger sets of signatures in the regionalization procedure if their error correlations are formally accounted for and thus enable a more complete use of all available information.
H. Xu and Y. Luo
Hydrol. Earth Syst. Sci., 19, 4609–4618, https://doi.org/10.5194/hess-19-4609-2015, https://doi.org/10.5194/hess-19-4609-2015, 2015
Short summary
Short summary
This study quantified the climate impact on river discharge in the River Huangfuchuan in semi-arid northern China and the River Xiangxi in humid southern China. Climate projections showed trends toward warmer and wetter conditions, particularly for the River Huangfuchuan. The main projected hydrologic impact was a more pronounced increase in annual discharge in both catchments. Peak flows are projected to appear earlier than usual in the River Huangfuchuan and later than usual in River Xiangxi.
I. K. Westerberg and H. K. McMillan
Hydrol. Earth Syst. Sci., 19, 3951–3968, https://doi.org/10.5194/hess-19-3951-2015, https://doi.org/10.5194/hess-19-3951-2015, 2015
Short summary
Short summary
This study investigated the effect of uncertainties in data and calculation methods on hydrological signatures. We present a widely applicable method to evaluate signature uncertainty and show results for two example catchments. The uncertainties were often large (i.e. typical intervals of ±10–40% relative uncertainty) and highly variable between signatures. It is therefore important to consider uncertainty when signatures are used for hydrological and ecohydrological analyses and modelling.
T. O. Sonnenborg, D. Seifert, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 19, 3891–3901, https://doi.org/10.5194/hess-19-3891-2015, https://doi.org/10.5194/hess-19-3891-2015, 2015
Short summary
Short summary
The impacts of climate model uncertainty and geological model uncertainty on hydraulic head, stream flow, travel time and capture zones are evaluated. Six versions of a physically based and distributed hydrological model, each containing a unique interpretation of the geological structure of the model area, are forced by 11 climate model projections. Geology is the dominating uncertainty source for travel time and capture zones, while climate dominates for hydraulic heads and steam flow.
N. Dogulu, P. López López, D. P. Solomatine, A. H. Weerts, and D. L. Shrestha
Hydrol. Earth Syst. Sci., 19, 3181–3201, https://doi.org/10.5194/hess-19-3181-2015, https://doi.org/10.5194/hess-19-3181-2015, 2015
F. Bourgin, V. Andréassian, C. Perrin, and L. Oudin
Hydrol. Earth Syst. Sci., 19, 2535–2546, https://doi.org/10.5194/hess-19-2535-2015, https://doi.org/10.5194/hess-19-2535-2015, 2015
T. Berezowski, J. Nossent, J. Chormański, and O. Batelaan
Hydrol. Earth Syst. Sci., 19, 1887–1904, https://doi.org/10.5194/hess-19-1887-2015, https://doi.org/10.5194/hess-19-1887-2015, 2015
F. Silvestro, S. Gabellani, R. Rudari, F. Delogu, P. Laiolo, and G. Boni
Hydrol. Earth Syst. Sci., 19, 1727–1751, https://doi.org/10.5194/hess-19-1727-2015, https://doi.org/10.5194/hess-19-1727-2015, 2015
M. C. Demirel, M. J. Booij, and A. Y. Hoekstra
Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, https://doi.org/10.5194/hess-19-275-2015, 2015
Short summary
Short summary
This paper investigates the skill of 90-day low-flow forecasts using three models. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.
J. Crossman, M. N. Futter, P. G. Whitehead, E. Stainsby, H. M. Baulch, L. Jin, S. K. Oni, R. L. Wilby, and P. J. Dillon
Hydrol. Earth Syst. Sci., 18, 5125–5148, https://doi.org/10.5194/hess-18-5125-2014, https://doi.org/10.5194/hess-18-5125-2014, 2014
Short summary
Short summary
We projected potential hydrochemical responses in four neighbouring catchments to a range of future climates. The highly variable responses in streamflow and total phosphorus (TP) were governed by geology and flow pathways, where larger catchment responses were proportional to greater soil clay content. This suggests clay content might be used as an indicator of catchment sensitivity to climate change, and highlights the need for catchment-specific management plans.
M. Honti, A. Scheidegger, and C. Stamm
Hydrol. Earth Syst. Sci., 18, 3301–3317, https://doi.org/10.5194/hess-18-3301-2014, https://doi.org/10.5194/hess-18-3301-2014, 2014
I. K. Westerberg, L. Gong, K. J. Beven, J. Seibert, A. Semedo, C.-Y. Xu, and S. Halldin
Hydrol. Earth Syst. Sci., 18, 2993–3013, https://doi.org/10.5194/hess-18-2993-2014, https://doi.org/10.5194/hess-18-2993-2014, 2014
Cited articles
Alfieri, L., Burek, P., Dutra, E., Krzeminski, B., Muraro, D., Thielen, J., and Pappenberger, F.: GloFAS – global ensemble streamflow forecasting and flood early warning, Hydrol. Earth Syst. Sci., 17, 1161–1175, https://doi.org/10.5194/hess-17-1161-2013, 2013. a
Angarita, H., Wickel, A. J., Sieber, J., Chavarro, J., Maldonado-Ocampo, J. A., Herrera-R., G. A., Delgado, J., and Purkey, D.: Basin-scale impacts of hydropower development on the Mompós Depression wetlands, Colombia, Hydrol. Earth Syst. Sci., 22, 2839–2865, https://doi.org/10.5194/hess-22-2839-2018, 2018. a
Arduini, G., Fink, G., Martinez de la Torre, A., Nikolopoulos, E., Anagnostou,
E., Balsamo, G., and Boussetta, S.: End-user-focused improvements and
descriptions of the advances introduced between the WRR tier1 and WRR tier2, http://www.earth2observe.eu/?page_id=4704 (last access: 20 November 2018), 2017. a, b
Balsamo, G., Beljaars, A., Scipal, K., Viterbo, P., van den Hurk, B., Hirschi,
M., and Betts, A. K.: A revised hydrology for the ECMWF model: Verification
from field site to terrestrial water storage and impact in the Integrated
Forecast System, J. Hydrometeorol., 10, 623–643, 2009. a
Beck, H. E., van Dijk, A. I., De Roo, A., Miralles, D. G., McVicar, T. R.,
Schellekens, J., and Bruijnzeel, L. A.: Global-scale regionalization of
hydrologic model parameters, Water Resour. Res., 52, 3599–3622, 2016. a
Beck, H. E., van Dijk, A. I. J. M., de Roo, A., Dutra, E., Fink, G., Orth, R., and Schellekens, J.: Global evaluation of runoff from 10 state-of-the-art hydrological models, Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, 2017a. a, b, c, d
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25° global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017b. a
Bedoya-Soto, J. M., Poveda, G., Trenberth, K. E., and Vélez-Upegui, J. J.:
Interannual hydroclimatic variability and the 2009–2011 extreme ENSO phases
in Colombia: from Andean glaciers to Caribbean lowlands, Theor.
Appl. Climatol., 135, 1531–1544, 2019. a
Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a
Bierkens, M. F.: Global hydrology 2015: State, trends, and directions, Water Resour. Res., 51, 4923–4947, 2015. a
Bolaños, S., Salazar, J. F., Betancur, T., and Werner, M.: GRACE reveals
depletion of water storage in northwestern South America between ENSO
extremes, J. Hydrol., 596, 125687, https://doi.org/10.1016/j.jhydrol.2020.125687, 2020. a, b, c, d
Buytaert, W. and Beven, K.: Models as multiple working hypotheses: hydrological
simulation of tropical alpine wetlands, Hydrol. Process., 25,
1784–1799, 2011. a
Camacho, L., Rodríguez, E., and Pinilla, G.: Modelación dinámica
integrada de cantidad y calidad del agua del Canal del Dique y su sistema
lagunar, Colombia, in: XXIII Latinamerican Congress on Hydraulic (IARH), The International Association for Hydro-Environment
Engineering and Research (IAHR), ISBN 9789597160175, 2008. a
Casson, D. R., Werner, M., Weerts, A., and Solomatine, D.: Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed, Hydrol. Earth Syst. Sci., 22, 4685–4697, https://doi.org/10.5194/hess-22-4685-2018, 2018. a
Chen, J., Famigliett, J. S., Scanlon, B. R., and Rodell, M.: Groundwater storage changes: present status from GRACE observa15 tions, in: Remote Sens. and Water Resources, edited by: Cazenave A., Champollion, N., Benveniste, J., and Chen, J., Springer, Switzerland, 207–227, https://doi.org/10.1007/978-3-319-32449-4, 2016. a
Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a
Clark, M. P., Bierkens, M. F. P., Samaniego, L., Woods, R. A., Uijlenhoet, R., Bennett, K. E., Pauwels, V. R. N., Cai, X., Wood, A. W., and Peters-Lidard, C. D.: The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism, Hydrol. Earth Syst. Sci., 21, 3427–3440, https://doi.org/10.5194/hess-21-3427-2017, 2017. a, b
Cleveland, R. B., Cleveland, W. S., McRae, J. E., and Terpenning, I.: STL: a
seasonal-trend decomposition, J. Off. Stat., 6, 3–73, 1990. a
Decharme, B., Alkama, R., Douville, H., Becker, M., and Cazenave, A.: Global
evaluation of the ISBA-TRIP continental hydrological system, Part II:
Uncertainties in river routing simulation related to flow velocity and
groundwater storage, J. Hydrometeorol., 11, 601–617, 2010. a
Dutra, E., Balsamo, G., Calvet, J., Minvielle, M., Eisner, S., Fink, G.,
Pessenteiner, S., Orth, R., Burke, S., van Dijk, A., Polcher, J., Beck, H., Martinez de la Torre, A., and Sterk, G.: Report on the current state-of-the-art Water
Resources Reanalysis, http://www.earth2observe.eu/?page_id=4704 (last access: 20 November 2018), 2015. a, b
Dutra, E., Balsamo, G., Calvet, J.-C., Munier, S., Burke, S., Fink, G., van Dijk, A., Martinez de la Torre, A., van Beek, R., de Roo, A., and Polcher, J.: Report on the
improved Water Resources Reanalysis (WRR2), EartH2Observe, Report, p. 94, https://doi.org/10.13140/RG.2.2.14523.67369, 2017. a, b, c, d, e, f
Famiglietti, J.: Remote sensing of terrestrial water storage, soil moisture and surface waters, Washington DC American Geophysical Union Geophysical
Monograph Series, 150, 197–207, 2004. a
Flörke, M., Kynast, E., Bärlund, I., Eisner, S., Wimmer, F., and
Alcamo, J.: Domestic and industrial water uses of the past 60 years as a
mirror of socio-economic development: A global simulation study, Global
Environ. Chang., 23, 144–156, 2013. a
Getirana, A., Rodell, M., Kumar, S., Beaudoing, H. K., Arsenault, K., Zaitchik,
B., Save, H., and Bettadpur, S.: GRACE improves seasonal groundwater forecast
initialization over the United States, J. Hydrometeorol., 21, 59–71, 2020. a
González-Zeas, D., Erazo, B., Lloret, P., De Bièvre, B.,
Steinschneider, S., and Dangles, O.: Linking global climate change to local
water availability: Limitations and prospects for a tropical mountain
watershed, Sci. Total Environ., 650, 2577–2586, 2019. a
Gründemann, G. J., Werner, M., and Veldkamp, T. I. E.: The potential of global reanalysis datasets in identifying flood events in Southern Africa, Hydrol. Earth Syst. Sci., 22, 4667–4683, https://doi.org/10.5194/hess-22-4667-2018, 2018. a, b, c, d
Gudmundsson, L., Wagener, T., Tallaksen, L., and Engeland, K.: Evaluation of
nine large-scale hydrological models with respect to the seasonal runoff
climatology in Europe, Water Resour. Res., 48, W11504, https://doi.org/10.1029/2011WR01091, 2012. a
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
Hassan, A. and Jin, S.: Water storage changes and balances in Africa observed
by GRACE and hydrologic models, Geodesy and Geodynamics, 7, 39–49, 2016. a
Hoyos, N., Escobar, J., Restrepo, J., Arango, A., and Ortiz, J.: Impact of the
2010–2011 La Niña phenomenon in Colombia, South America: the human toll
of an extreme weather event, Appl. Geogr., 39, 16–25, 2013. a
Hoyos, N., Correa-Metrio, A., Sisa, A., Ramos-Fabiel, M., Espinosa, J.,
Restrepo, J., and Escobar, J.: The environmental envelope of fires in the
Colombian Caribbean, Appl. Geogr., 84, 42–54, 2017. a
Kleidon, A., Renner, M., and Porada, P.: Estimates of the climatological land surface energy and water balance derived from maximum convective power, Hydrol. Earth Syst. Sci., 18, 2201–2218, https://doi.org/10.5194/hess-18-2201-2014, 2014. a
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J.,
Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic
global vegetation model for studies of the coupled atmosphere-biosphere
system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005. a
Lettenmaier, D. P. and Famiglietti, J. S.: Hydrology: Water from on high,
Nature, 444, 562–563, https://doi.org/10.1038/444562a, 2006. a
Liesch, T. and Ohmer, M.: Comparison of GRACE data and groundwater levels for
the assessment of groundwater depletion in Jordan, Hydrogeol. J., 24, 1547–1563, 2016. a
Lindström, G., Johansson, B., Persson, M., Gardelin, M., and Bergström,
S.: Development and test of the distributed HBV-96 hydrological model,
J. Hydrol., 201, 272–288, 1997. a
Liu, L., Xie, J., Gu, H., and Xu, Y.-P.: Estimating the added value of GRACE
total water storage and uncertainty quantification in seasonal streamflow
forecasting, Hydrol. Sci. J., 67, 304–318,
doi10.1080/02626667.2021.1998510, 2022. a
López López, P., Immerzeel, W. W., Rodríguez Sandoval, E. A.,
Sterk, G., and Schellekens, J.: Spatial downscaling of satellite-based
precipitation and its impact on discharge simulations in the Magdalena River
basin in Colombia, Front. Earth Sci., 6, ISSN 2296-6463, https://doi.org/10.3389/feart.2018.00068, 2018. a
Miralles, D. G., Gash, J. H., Holmes, T. R., de Jeu, R. A., and Dolman, A.:
Global canopy interception from satellite observations, J.
Geophys. Res.-Atmos., 115, D16122, https://doi.org/10.1029/2009JD013530, 2010. a
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D.,
and Veith, T. L.: Model evaluation guidelines for systematic quantification
of accuracy in watershed simulations, T. ASABE, 50, 885–900, 2007. a
Müller Schmied, H., Cáceres, D., Eisner, S., Flörke, M., Herbert, C., Niemann, C., Peiris, T. A., Popat, E., Portmann, F. T., Reinecke, R., Schumacher, M., Shadkam, S., Telteu, C.-E., Trautmann, T., and Döll, P.: The global water resources and use model WaterGAP v2.2d: model description and evaluation, Geosci. Model Dev., 14, 1037–1079, https://doi.org/10.5194/gmd-14-1037-2021, 2021. a
Orth, R. and Seneviratne, S. I.: Predictability of soil moisture and streamflow
on subseasonal timescales: A case study, J. Geophys. Res.-Atmos., 118, 10963–10979, https://doi.org/10.1002/jgrd.50846, 2013. a
Ouma, Y. O., Aballa, D., Marinda, D., Tateishi, R., and Hahn, M.: Use of GRACE
time-variable data and GLDAS-LSM for estimating groundwater storage
variability at small basin scales: a case study of the Nzoia River Basin,
Int. J. Remote Sens., 36, 5707–5736, 2015. a
Poveda, G. and Mesa, O.: Extreme phases of the ENSO phenomenon(El Nino and La
Nina) and its effects on the hydrology of Colombia, Ing. Hidral. Mexico, 11, 21–37, 1996. a
Pozzi, W., Sheffield, J., Stefanski, R., Cripe, D., Pulwarty, R., Vogt, J. V.,
Heim, R. R., Brewer, M. J., Svoboda, M., Westerhoff, R., van Dijk, A., Lloyd-Hughes, B.,
Pappenberger, F., Werner, M., Dutra, E., Wetterhall, F., Wagner, W., Schubert, S.,
Mo, K., Nicholson, M., Bettio, L., Nunez, L., van Beek, R., Bierkens, M., Goncalves
de Goncalves, L., Zell de Mattos, J., and Lawford, R.: Toward
global drought early warning capability: Expanding international cooperation
for the development of a framework for monitoring and forecasting, Bull. Am. Meteorol. Soc., 94, 776–785, https://doi.org/10.1175/BAMS-D-11-00176.1, 2013. a
Ramillien, G., Frappart, F., Güntner, A., Ngo-Duc, T., Cazenave, A., and
Laval, K.: Time variations of the regional evapotranspiration rate from
Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry, Water
Resour. Res., 42, W10403, https://doi.org/10.1029/2005WR004331, 2006. a
Reager, J. and Famiglietti, J. S.: Characteristic mega-basin water storage
behavior using GRACE, Water Resour. Res., 49, 3314–3329, 2013. a
Restrepo, J. and Kjerfve, B.: Magdalena river: interannual variability
(1975–1995) and revised water discharge and sediment load estimates, J. Hydrol., 235, 137–149, 2000. a
Rodríguez, E., Sánchez, I., Duque, N., Arboleda, P., Vega, C., Zamora,
D., López, P., Kaune, A., Werner, M., García, C., and Burke, S.: Combined
Use of Local and Global Hydro Meteorological Data with Hydrological Models
for Water Resour. Manag. in the Magdalena-Cauca Macro Basin–Colombia,
Water Resour. Manag., 34, 2179-2199, https://doi.org/10.1007/s11269-019-02236-5, 2019. a, b, c, d
Rodríguez, N. and Armenteras, D.: Ecosistemas naturales de la cuenca del
río Magdalena, in: Los sedimentos del río Magdalena: reflejo de la
crisis ambiental, Universidad Eafit, edited by: Restrepo Ángel, J. D., 79–98, ISBN 9588173906, 2005. a
Rougé, C., Reed, P. M., Grogan, D. S., Zuidema, S., Prusevich, A., Glidden, S., Lamontagne, J. R., and Lammers, R. B.: Coordination and control – limits in standard representations of multi-reservoir operations in hydrological modeling, Hydrol. Earth Syst. Sci., 25, 1365–1388, https://doi.org/10.5194/hess-25-1365-2021, 2021. a
Save, H., Bettadpur, S., and Tapley, B. D.: High-resolution CSR GRACE RL05
mascons, J. Geophys. Res.-Solid Earth, 121, 7547–7569, 2016. a
Scanlon, B., Zhang, Z., Save, H., Sun, A., Schmied, H., van Beek, L., Wiese,
D., Wada, Y., Long, D., Reedy, R. C., Longuevergne, L., Döll, P., and Bierkens, M.: Global models underestimate
large decadal declining and rising water storage trends relative to GRACE
satellite data, Proc. Natl. Acad. Sci., 115, E1080–E1089, https://doi.org/10.1073/pnas.1704665115, 2018. a, b, c, d, e, f
Scanlon, B., Zhang, Z., Rateb, A., Sun, A., Wiese, D., Save, H., Beaudoing, H.,
Lo, M., Müller-Schmied, H., Döll, P., van Beek, R., Swenson, S., Lawrence, D., Croteau
M., and Reedy, R.: Tracking seasonal
fluctuations in land water storage using global models and GRACE satellites,
Geophys. Res. Lett., 46, 5254–5264, https://doi.org/10.1029/2018GL081836, 2019. a, b
Schellekens, J., Dutra, E., Balsamo, G., van Dijk, A., Sperna Weiland, F., Minvielle,
M., Calvet, C., Decharme, B., Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van
Beek, R., Polcher, J., Beck, H., Martínez-de la Torre, A., Orth, R., Calton, B., Burke,
S, and Weedon, G.: earth2observe/water-resource-reanalysis-v1: Revised
Release (1.02), Zenodo [data set], https://doi.org/10.5281/zenodo.167070, https://wci.earth2observe.eu/ (last access: 20 November 2018), 2016. a
Schellekens, J., Dutra, E., Martínez-de la Torre, A., Balsamo, G., van Dijk, A., Sperna Weiland, F., Minvielle, M., Calvet, J.-C., Decharme, B., Eisner, S., Fink, G., Flörke, M., Peßenteiner, S., van Beek, R., Polcher, J., Beck, H., Orth, R., Calton, B., Burke, S., Dorigo, W., and Weedon, G. P.: A global water resources ensemble of hydrological models: the eartH2Observe Tier-1 dataset, Earth Syst. Sci. Data, 9, 389–413, https://doi.org/10.5194/essd-9-389-2017, 2017. a, b, c, d, e, f, g, h, i, j, k
Schumacher, M., Forootan, E., van Dijk, A. I., Schmied, H. M., Crosbie, R. S.,
Kusche, J., and Döll, P.: Improving drought simulations within the
Murray-Darling Basin by combined calibration/assimilation of GRACE data into
the WaterGAP Global Hydrology Model, Remote Sens. Environ., 204,
212–228, 2018. a
Shamsudduha, M., Taylor, R., and Longuevergne, L.: Monitoring groundwater
storage changes in the highly seasonal humid tropics: Validation of GRACE
measurements in the Bengal Basin, Water Resour. Res., 48, W02508,
https://doi.org/10.1029/2011WR010993, 2012. a
Shamsudduha, M., Taylor, R. G., Jones, D., Longuevergne, L., Owor, M., and Tindimugaya, C.: Recent changes in terrestrial water storage in the Upper Nile Basin: an evaluation of commonly used gridded GRACE products, Hydrol. Earth Syst. Sci., 21, 4533–4549, https://doi.org/10.5194/hess-21-4533-2017, 2017. a
Sperna Weiland, F. C., van Beek, L. P. H., Kwadijk, J. C. J., and Bierkens, M. F. P.: Global patterns of change in discharge regimes for 2100, Hydrol. Earth Syst. Sci., 16, 1047–1062, https://doi.org/10.5194/hess-16-1047-2012, 2012. a
Sutanudjaja, E. H., van Beek, R., Wanders, N., Wada, Y., Bosmans, J. H. C., Drost, N., van der Ent, R. J., de Graaf, I. E. M., Hoch, J. M., de Jong, K., Karssenberg, D., López López, P., Peßenteiner, S., Schmitz, O., Straatsma, M. W., Vannametee, E., Wisser, D., and Bierkens, M. F. P.: PCR-GLOBWB 2: a 5 arcmin global hydrological and water resources model, Geosci. Model Dev., 11, 2429–2453, https://doi.org/10.5194/gmd-11-2429-2018, 2018. a, b
Swenson, S. and Lawrence, D.: A GRACE-based assessment of interannual
groundwater dynamics in the Community Land Model, Water Resour. Res.,
51, 8817–8833, 2015. a
Syed, T. H., Famiglietti, J. S., Rodell, M., Chen, J., and Wilson, C. R.:
Analysis of terrestrial water storage changes from GRACE and GLDAS, Water Resour. Res., 44, W02433, https://doi.org/10.1029/2006WR005779, 2008. a, b
Tang, Q., Gao, H., Yeh, P., Oki, T., Su, F., and Lettenmaier, D. P.: Dynamics
of terrestrial water storage change from satellite and surface observations
and modeling, J. Hydrometeorol., 11, 156–170, 2010. a
Tangdamrongsub, N., Steele-Dunne, S. C., Gunter, B. C., Ditmar, P. G., Sutanudjaja, E. H., Sun, Y., Xia, T., and Wang, Z.: Improving estimates of water resources in a semi-arid region by assimilating GRACE data into the PCR-GLOBWB hydrological model, Hydrol. Earth Syst. Sci., 21, 2053–2074, https://doi.org/10.5194/hess-21-2053-2017, 2017. a
Tapley, B. D., Bettadpur, S., Watkins, M., and Reigber, C.: The gravity
recovery and climate experiment: Mission overview and early results,
Geophys. Res. Lett., 31, L09607, https://doi.org/10.1029/2004GL019920, 2004. a, b
Taylor, K. E.: Summarizing multiple aspects of model performance in a single
diagram, Journal of Geophys. Res.-Atmos., 106, 7183–7192, 2001. a
Van Beek, L., Wada, Y., and Bierkens, M. F.: Global monthly water stress: 1.
Water balance and water availability, Water Resour. Res., 47, W07517,
https://doi.org/10.1029/2010WR009791, 2011. a
Van Der Knijff, J., Younis, J., and De Roo, A.: LISFLOOD: a GIS-based
distributed model for river basin scale water balance and flood simulation,
Int. J. Geogr. Inf. Sci., 24, 189–212, 2010. a
van Dijk, A. I. J. M., Renzullo, L. J., Wada, Y., and Tregoning, P.: A global water cycle reanalysis (2003–2012) merging satellite gravimetry and altimetry observations with a hydrological multi-model ensemble, Hydrol. Earth Syst. Sci., 18, 2955–2973, https://doi.org/10.5194/hess-18-2955-2014, 2014. a
Vargas, G., Hernández, Y., and Pabón, J. D.: La Niña event
2010–2011: hydroclimatic effects and socioeconomic impacts in Colombia, in: Climate Change, Extreme Events and Disaster Risk Reduction, edited by: Mal., S., Singh, R., and Huggel, C., Springer, 217–232, https://doi.org/10.1007/978-3-319-56469-2, 2018. a
Veldkamp, T., Wada, Y., Aerts, J., Döll, P., Gosling, S. N., Liu, J.,
Masaki, Y., Oki, T., Ostberg, S., Pokhrel, Y., Satoh, Y., Kim, H., and Ward, P.: Water scarcity
hotspots travel downstream due to human interventions in the 20th and 21st
century, Nat. Commun., 8, 15697, https://doi.org/10.1038/ncomms15697, 2017.
a
Veldkamp, T. I. E., Zhao, F., Ward, P. J., de Moel, H., Aerts, J. C., Schmied,
H. M., Portmann, F. T., Masaki, Y., Pokhrel, Y., Liu, X., Satoh, Y., Gerten, D., Gosling, S.,
Zaherpour, J., and Wada, J.: Human
impact parameterizations in global hydrological models improve estimates of
monthly discharges and hydrological extremes: a multi-model validation study, Environ. Res. Lett., 13, 055008, https://doi.org/10.1088/1748-9326/aab96f, 2018. a
Viviroli, D., Kummu, M., Meybeck, M., Kallio, M., and Wada, Y.: Increasing
dependence of lowland populations on mountain water resources, Nat.
Sustain., 3, 917–928, 2020. a
Watkins, M. M., Wiese, D. N., Yuan, D.-N., Boening, C., and Landerer, F. W.:
Improved methods for observing Earth's time variable mass distribution with
GRACE using spherical cap mascons, J. Geophys. Res.-Solid Earth, 120, 2648–2671, https://grace.jpl.nasa.gov/data/get-data/jpl_global_mascons/ (last access: 11 February 2019), 2015. a, b, c
Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo, P.: The WFDEI meteorological forcing data set: WATCH Forcing Data methodology
applied to ERA-Interim reanalysis data, Water Resour. Res., 50,
7505–7514, 2014. a
Wiese, D. N., Landerer, F. W., and Watkins, M. M.: Quantifying and reducing
leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res., 52, 7490–7502, 2016. a
Wijngaard, R. R., Biemans, H., Lutz, A. F., Shrestha, A. B., Wester, P., and Immerzeel, W. W.: Climate change vs. socio-economic development: understanding the future South Asian water gap, Hydrol. Earth Syst. Sci., 22, 6297–6321, https://doi.org/10.5194/hess-22-6297-2018, 2018. a
Xiao, R., He, X., Zhang, Y., Ferreira, V., and Chang, L.: Monitoring
groundwater variations from satellite gravimetry and hydrological models: a
comparison with in-situ measurements in the Mid-Atlantic region of the United
States, Remote Sens., 7, 686–703, 2015. a
Zhang, L.: Terrestrial water storage from GRACE gravity data for
hydrometeorological applications, PhD thesis, Institut für Meteorologie
Freie Universität Berlin, urn:nbn:de:kobv:188-fudissthesis000000104220-7, 2017. a
Zhang, L., Dobslaw, H., Stacke, T., Güntner, A., Dill, R., and Thomas, M.: Validation of terrestrial water storage variations as simulated by different global numerical models with GRACE satellite observations, Hydrol. Earth Syst. Sci., 21, 821–837, https://doi.org/10.5194/hess-21-821-2017, 2017. a, b, c
Download
Please read the editorial note first before accessing the article.
- Article
(5565 KB) - Full-text XML
-
Supplement
(2302 KB) - BibTeX
- EndNote
Short summary
Using total water storage (TWS) from GRACE satellites, we assess the reliability of global hydrological and land surface models over a medium-sized tropical basin with a well-developed gauging network. We find the models poorly represent TWS for the monthly series, but they improve in representing seasonality and long-term trends. We conclude that GRACE provides a valuable dataset to benchmark global simulations of TWS change, offering a useful tool to improve global models in tropical basins.
Using total water storage (TWS) from GRACE satellites, we assess the reliability of global...
