Articles | Volume 26, issue 13
https://doi.org/10.5194/hess-26-3419-2022
© 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-26-3419-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
07 Jul 2022
Research article |
| 07 Jul 2022
| 07 Jul 2022
Revisiting parameter sensitivities in the variable infiltration capacity model across a hydroclimatic gradient
Ulises M. Sepúlveda
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Advanced Mining Technology Center, Universidad de Chile, Santiago,
Chile
Naoki Mizukami
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Andrew J. Newman
Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
Related authors
No articles found.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-221, https://doi.org/10.5194/hess-2024-221, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what it truly reflects in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and time scales for accurate drought characterization and monitoring.
Guoqiang Tang, Andrew W. Wood, Andrew J. Newman, Martyn P. Clark, and Simon Michael Papalexiou
Geosci. Model Dev., 17, 1153–1173, https://doi.org/10.5194/gmd-17-1153-2024, https://doi.org/10.5194/gmd-17-1153-2024, 2024
Short summary
Short summary
Ensemble geophysical datasets are crucial for understanding uncertainties and supporting probabilistic estimation/prediction. However, open-access tools for creating these datasets are limited. We have developed the Python-based Geospatial Probabilistic Estimation Package (GPEP). Through several experiments, we demonstrate GPEP's ability to estimate precipitation, temperature, and snow water equivalent. GPEP will be a useful tool to support uncertainty analysis in Earth science applications.
Diego Araya, Pablo A. Mendoza, Eduardo Muñoz-Castro, and James McPhee
Hydrol. Earth Syst. Sci., 27, 4385–4408, https://doi.org/10.5194/hess-27-4385-2023, https://doi.org/10.5194/hess-27-4385-2023, 2023
Short summary
Short summary
Dynamical systems are used by many agencies worldwide to produce seasonal streamflow forecasts, which are critical for decision-making. Such systems rely on hydrology models, which contain parameters that are typically estimated using a target performance metric (i.e., objective function). This study explores the effects of this decision across mountainous basins in Chile, illustrating tradeoffs between seasonal forecast quality and the models' capability to simulate streamflow characteristics.
Mari R. Tye, Ming Ge, Jadwiga H. Richter, Ethan D. Gutmann, Allyson Rugg, Cindy L. Bruyère, Sue Ellen Haupt, Flavio Lehner, Rachel McCrary, Andrew J. Newman, and Andrew Wood
EGUsphere, https://doi.org/10.5194/egusphere-2023-2326, https://doi.org/10.5194/egusphere-2023-2326, 2023
Short summary
Short summary
There is a perceived mismatch between the spatial scales that global climate models can produce data and that needed for water management decisions. However, poor communication of specific metrics relevant to local decisions is also a problem. We identified a potential set of water use decision metrics to assess their credibility in the Community Earth System Model v2 (CESM2). CESM2 can reliably reproduce many of these metrics and shows potential to support long-range water resource decisions.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo A. Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci., 27, 3505–3524, https://doi.org/10.5194/hess-27-3505-2023, https://doi.org/10.5194/hess-27-3505-2023, 2023
Short summary
Short summary
This paper shows how important river models can be for water resource applications that involve hydrological models and, in particular, parameter calibration. To this end, we conduct numerical experiments in a pilot basin using a combination of hydrologic model simulations obtained from a large sample of parameter sets and different routing methods. We find that routing can affect streamflow simulations, even at monthly time steps; the choice of parameters; and relevant streamflow metrics.
Zhi Li, Shang Gao, Mengye Chen, Jonathan Gourley, Naoki Mizukami, and Yang Hong
Geosci. Model Dev., 15, 6181–6196, https://doi.org/10.5194/gmd-15-6181-2022, https://doi.org/10.5194/gmd-15-6181-2022, 2022
Short summary
Short summary
Operational streamflow prediction at a continental scale is critical for national water resources management. However, limited computational resources often impede such processes, with streamflow routing being one of the most time-consuming parts. This study presents a recent development of a hydrologic system that incorporates a vector-based routing scheme with a lake module that markedly speeds up streamflow prediction. Moreover, accuracy is improved and flood false alarms are mitigated.
Inne Vanderkelen, Shervan Gharari, Naoki Mizukami, Martyn P. Clark, David M. Lawrence, Sean Swenson, Yadu Pokhrel, Naota Hanasaki, Ann van Griensven, and Wim Thiery
Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, https://doi.org/10.5194/gmd-15-4163-2022, 2022
Short summary
Short summary
Human-controlled reservoirs have a large influence on the global water cycle. However, dam operations are rarely represented in Earth system models. We implement and evaluate a widely used reservoir parametrization in a global river-routing model. Using observations of individual reservoirs, the reservoir scheme outperforms the natural lake scheme. However, both schemes show a similar performance due to biases in runoff timing and magnitude when using simulated runoff.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Pablo A. Mendoza, Ian McNamara, Hylke E. Beck, Joschka Thurner, Alexandra Nauditt, Lars Ribbe, and Nguyen Xuan Thinh
Hydrol. Earth Syst. Sci., 25, 5805–5837, https://doi.org/10.5194/hess-25-5805-2021, https://doi.org/10.5194/hess-25-5805-2021, 2021
Short summary
Short summary
Most rivers worldwide are ungauged, which hinders the sustainable management of water resources. Regionalisation methods use information from gauged rivers to estimate streamflow over ungauged ones. Through hydrological modelling, we assessed how the selection of precipitation products affects the performance of three regionalisation methods. We found that a precipitation product that provides the best results in hydrological modelling does not necessarily perform the best for regionalisation.
Andrew J. Newman, Amanda G. Stone, Manabendra Saharia, Kathleen D. Holman, Nans Addor, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 5603–5621, https://doi.org/10.5194/hess-25-5603-2021, https://doi.org/10.5194/hess-25-5603-2021, 2021
Short summary
Short summary
This study assesses methods that estimate flood return periods to identify when we would obtain a large flood return estimate change if the method or input data were changed (sensitivities). We include an examination of multiple flood-generating models, which is a novel addition to the flood estimation literature. We highlight the need to select appropriate flood models for the study watershed. These results will help operational water agencies develop more robust risk assessments.
Guoqiang Tang, Martyn P. Clark, Simon Michael Papalexiou, Andrew J. Newman, Andrew W. Wood, Dominique Brunet, and Paul H. Whitfield
Earth Syst. Sci. Data, 13, 3337–3362, https://doi.org/10.5194/essd-13-3337-2021, https://doi.org/10.5194/essd-13-3337-2021, 2021
Short summary
Short summary
Probabilistic estimates are useful to quantify the uncertainties in meteorological datasets. This study develops the Ensemble Meteorological Dataset for North America (EMDNA). EMDNA has 100 members with daily precipitation amount, mean daily temperature, and daily temperature range at 0.1° spatial resolution from 1979 to 2018. It is expected to be useful for hydrological and meteorological applications in North America.
Manuela I. Brunner, Lieke A. Melsen, Andrew W. Wood, Oldrich Rakovec, Naoki Mizukami, Wouter J. M. Knoben, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 25, 105–119, https://doi.org/10.5194/hess-25-105-2021, https://doi.org/10.5194/hess-25-105-2021, 2021
Short summary
Short summary
Assessments of current, local, and regional flood hazards and their future changes often involve the use of hydrologic models. A reliable model ideally reproduces both local flood characteristics and regional aspects of flooding. In this paper we investigate how such characteristics are represented by hydrologic models. Our results show that both the modeling of local and regional flood characteristics are challenging, especially under changing climate conditions.
Shervan Gharari, Martyn P. Clark, Naoki Mizukami, Wouter J. M. Knoben, Jefferson S. Wong, and Alain Pietroniro
Hydrol. Earth Syst. Sci., 24, 5953–5971, https://doi.org/10.5194/hess-24-5953-2020, https://doi.org/10.5194/hess-24-5953-2020, 2020
Short summary
Short summary
This work explores the trade-off between the accuracy of the representation of geospatial data, such as land cover, soil type, and elevation zones, in a land (surface) model and its performance in the context of modeling. We used a vector-based setup instead of the commonly used grid-based setup to identify this trade-off. We also assessed the often neglected parameter uncertainty and its impact on the land model simulations.
Guoqiang Tang, Martyn P. Clark, Andrew J. Newman, Andrew W. Wood, Simon Michael Papalexiou, Vincent Vionnet, and Paul H. Whitfield
Earth Syst. Sci. Data, 12, 2381–2409, https://doi.org/10.5194/essd-12-2381-2020, https://doi.org/10.5194/essd-12-2381-2020, 2020
Short summary
Short summary
Station observations are critical for hydrological and meteorological studies, but they often contain missing values and have short measurement periods. This study developed a serially complete dataset for North America (SCDNA) from 1979 to 2018 for 27 276 precipitation and temperature stations. SCDNA is built on multiple data sources and infilling/reconstruction strategies to achieve high-quality estimates which can be used for a variety of applications.
Manuela I. Brunner, Lieke A. Melsen, Andrew J. Newman, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 24, 3951–3966, https://doi.org/10.5194/hess-24-3951-2020, https://doi.org/10.5194/hess-24-3951-2020, 2020
Short summary
Short summary
Streamflow seasonality is changing and expected to further change under the influence of climate change. We here assess how annual streamflow hydrographs will change in future by using a newly developed classification scheme. Our comparison of future with current annual hydrograph classes shows that robust changes are expected only for currently melt-influenced regions in the Rocky Mountains. These upstream changes may require the adaptation of management strategies in downstream regions.
Gerardo Zegers, Pablo A. Mendoza, Alex Garces, and Santiago Montserrat
Nat. Hazards Earth Syst. Sci., 20, 1919–1930, https://doi.org/10.5194/nhess-20-1919-2020, https://doi.org/10.5194/nhess-20-1919-2020, 2020
Short summary
Short summary
We perform a sensitivity analysis on the parameters of a numerical debris flow model and examine the effects of using post-event measurements on two creeks in Chile. Our results demonstrate the utility of sensitivity analysis in debris flow modeling and the benefits of post-event observations on parameter identifiability. This study provides guidance on the choice of uncertain parameters, contributing to more reliable simulations for debris flow risk assessments and land use planning.
Andrew J. Newman and Martyn P. Clark
Geosci. Model Dev., 13, 1827–1843, https://doi.org/10.5194/gmd-13-1827-2020, https://doi.org/10.5194/gmd-13-1827-2020, 2020
Short summary
Short summary
This paper introduces the Topographically InformEd Regression (TIER) model, which uses terrain attributes to turn observations of precipitation and temperature into spatial maps. TIER allows our understanding of complex atmospheric processes such as terrain-enhanced precipitation to be modeled in a very simple way. TIER lets users change the model so they can experiment with different ways of making maps. A key conclusion is that small changes in TIER will change the final map.
Naoki Mizukami, Oldrich Rakovec, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, Hoshin V. Gupta, and Rohini Kumar
Hydrol. Earth Syst. Sci., 23, 2601–2614, https://doi.org/10.5194/hess-23-2601-2019, https://doi.org/10.5194/hess-23-2601-2019, 2019
Short summary
Short summary
We find that Nash–Sutcliffe (NSE)-based model calibrations result in poor reproduction of high-flow events, such as the annual peak flows that are used for flood frequency estimation. The use of Kling–Gupta efficiency (KGE) results in annual peak flow estimates that are better than from NSE, with only a slight degradation in performance with respect to other related metrics.
Gwo-Jong Huang, Viswanathan N. Bringi, Andrew J. Newman, Gyuwon Lee, Dmitri Moisseev, and Branislav M. Notaroš
Atmos. Meas. Tech., 12, 1409–1427, https://doi.org/10.5194/amt-12-1409-2019, https://doi.org/10.5194/amt-12-1409-2019, 2019
Short summary
Short summary
This paper proposes a method for snow rate (SR) estimation using observations collected by NASA dual-frequency dual-polarized (D3R) radar during the GPM Cold-season Precipitation Experiment (GCPEx). The new method utilizes dual-wavelength radar reflectivity ratio (DWR) and 2-D-video disdrometer (2DVD) measurements to improve SR estimation accuracy. It is validated by comparing the D3R radar-retrieved SR with accumulated SR directly measured by a Pluvio gauge for an entire GCPEx synoptic event.
Camila Alvarez-Garreton, Pablo A. Mendoza, Juan Pablo Boisier, Nans Addor, Mauricio Galleguillos, Mauricio Zambrano-Bigiarini, Antonio Lara, Cristóbal Puelma, Gonzalo Cortes, Rene Garreaud, James McPhee, and Alvaro Ayala
Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, https://doi.org/10.5194/hess-22-5817-2018, 2018
Short summary
Short summary
CAMELS-CL provides a catchment dataset in Chile, including 516 catchment boundaries, hydro-meteorological time series, and 70 catchment attributes quantifying catchments' climatic, hydrological, topographic, geological, land cover and anthropic intervention features. By using CAMELS-CL, we characterise hydro-climatic regional variations, assess precipitation and potential evapotranspiration uncertainties, and analyse human intervention impacts on catchment response.
Sanjib Sharma, Ridwan Siddique, Seann Reed, Peter Ahnert, Pablo Mendoza, and Alfonso Mejia
Hydrol. Earth Syst. Sci., 22, 1831–1849, https://doi.org/10.5194/hess-22-1831-2018, https://doi.org/10.5194/hess-22-1831-2018, 2018
Short summary
Short summary
We investigate the relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1–7). For this purpose, we develop and implement a regional hydrologic ensemble prediction system (RHEPS). Overall analysis shows that implementing both preprocessing and postprocessing ensures the most skill improvements, but postprocessing alone can often be a competitive alternative.
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.
Cameron Wobus, Ethan Gutmann, Russell Jones, Matthew Rissing, Naoki Mizukami, Mark Lorie, Hardee Mahoney, Andrew W. Wood, David Mills, and Jeremy Martinich
Nat. Hazards Earth Syst. Sci., 17, 2199–2211, https://doi.org/10.5194/nhess-17-2199-2017, https://doi.org/10.5194/nhess-17-2199-2017, 2017
Short summary
Short summary
We linked modeled changes in the frequency of historical 100-year flood events to a national inventory of built assets within mapped floodplains of the United States. This allowed us to project changes in inland flooding damages nationwide under two alternative greenhouse gas (GHG) emissions scenarios. Our results suggest that more aggressive GHG reductions could reduce the projected monetary damages from inland flooding, potentially saving billions of dollars annually by the end of the century.
Nans Addor, Andrew J. Newman, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, https://doi.org/10.5194/hess-21-5293-2017, 2017
Short summary
Short summary
We introduce a data set describing the landscape of 671 catchments in the contiguous USA: we synthesized various data sources to characterize the topography, climate, streamflow, land cover, soil, and geology of each catchment. This extends the daily time series of meteorological forcing and discharge provided by an earlier study. The diversity of these catchments will help to improve our understanding and modeling of how the interplay between catchment attributes shapes hydrological processes.
Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold
Hydrol. Earth Syst. Sci., 21, 3915–3935, https://doi.org/10.5194/hess-21-3915-2017, https://doi.org/10.5194/hess-21-3915-2017, 2017
Short summary
Short summary
Water supply forecasts are critical to support water resources operations and planning. The skill of such forecasts depends on our knowledge of (i) future meteorological conditions and (ii) the amount of water stored in a basin. We address this problem by testing several approaches that make use of these sources of predictability, either separately or in a combined fashion. The main goal is to understand the marginal benefits of both information and methodological complexity in forecast skill.
Chengcheng Huang, Andrew J. Newman, Martyn P. Clark, Andrew W. Wood, and Xiaogu Zheng
Hydrol. Earth Syst. Sci., 21, 635–650, https://doi.org/10.5194/hess-21-635-2017, https://doi.org/10.5194/hess-21-635-2017, 2017
Short summary
Short summary
This study examined the potential of snow water equivalent data assimilation to improve seasonal streamflow predictions. We examined aspects of the data assimilation system over basins with varying climates across the western US. We found that varying how the data assimilation system is implemented impacts forecast performance, and basins with good initial calibrations see less benefit. This implies that basin-specific configurations and benefits should be expected given this modeling system.
Naoki Mizukami, Martyn P. Clark, Kevin Sampson, Bart Nijssen, Yixin Mao, Hilary McMillan, Roland J. Viger, Steve L. Markstrom, Lauren E. Hay, Ross Woods, Jeffrey R. Arnold, and Levi D. Brekke
Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, https://doi.org/10.5194/gmd-9-2223-2016, 2016
Short summary
Short summary
mizuRoute version 1 is a stand-alone runoff routing tool that post-processes runoff outputs from any distributed hydrologic models to produce streamflow estimates in large-scale river network. mizuRoute is flexible to river network representation and includes two different river routing schemes. This paper demonstrates mizuRoute's capability of multi-decadal streamflow estimations in the river networks over the entire contiguous Unites States, which contains over 54 000 river segments.
Lieke Melsen, Adriaan Teuling, Paul Torfs, Massimiliano Zappa, Naoki Mizukami, Martyn Clark, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 20, 2207–2226, https://doi.org/10.5194/hess-20-2207-2016, https://doi.org/10.5194/hess-20-2207-2016, 2016
Short summary
Short summary
In this study we investigated the sensitivity of a large-domain hydrological model for spatial and temporal resolution. We evaluated the results on a mesoscale catchment in Switzerland. Our results show that the model was hardly sensitive for the spatial resolution, which implies that spatial variability is likely underestimated. Our results provide a motivation to improve the representation of spatial variability in hydrological models in order to increase their credibility on a smaller scale.
Lieke A. Melsen, Adriaan J. Teuling, Paul J. J. F. Torfs, Remko Uijlenhoet, Naoki Mizukami, and Martyn P. Clark
Hydrol. Earth Syst. Sci., 20, 1069–1079, https://doi.org/10.5194/hess-20-1069-2016, https://doi.org/10.5194/hess-20-1069-2016, 2016
Short summary
Short summary
A meta-analysis on 192 peer-reviewed articles reporting applications of a land surface model in a distributed way reveals that the spatial resolution at which the model is applied has increased over the years, while the calibration and validation time interval has remained unchanged. We argue that the calibration and validation time interval should keep pace with the increase in spatial resolution in order to resolve the processes that are relevant at the applied spatial resolution.
A. J. Newman, M. P. Clark, K. Sampson, A. Wood, L. E. Hay, A. Bock, R. J. Viger, D. Blodgett, L. Brekke, J. R. Arnold, T. Hopson, and Q. Duan
Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, https://doi.org/10.5194/hess-19-209-2015, 2015
Short summary
Short summary
The focus of this paper is to (1) present a community data set of daily forcing and hydrologic response data for 671 unimpaired basins across the contiguous United States that spans a very wide range of hydroclimatic conditions, and (2) provide a calibrated model performance benchmark using a common conceptual snow and hydrologic modeling system. This benchmark provides a reference level of model performance across a very large basin sample and highlights regional variations in performance.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models
Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
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
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
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
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Extended range forecasting of stream water temperature with deep learning models
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?
Analyzing the generalization capabilities of hybrid hydrological models for extrapolation to extreme events
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
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?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric-hydrological model
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
Scale-dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
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
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
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
Short summary
This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
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 Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed 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.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
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 catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
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 to better prepare for and respond to floods.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
Short summary
Short summary
To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
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.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-3355, https://doi.org/10.5194/egusphere-2024-3355, 2024
Short summary
Short summary
Long Short-Term Memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modeling. However, most studies focus on daily-scale predictions, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use input of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
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
Revised manuscript accepted 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.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-221, https://doi.org/10.5194/hess-2024-221, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what it truly reflects in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and time scales for accurate drought characterization and monitoring.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
EGUsphere, https://doi.org/10.5194/egusphere-2024-2591, https://doi.org/10.5194/egusphere-2024-2591, 2024
Short summary
Short summary
We generate operational forecasts of daily maximum stream water temperature for the next month at 54 stations in Switzerland with our best performing data-driven model. The average forecast error is 0.38 °C for 1 day ahead and increases to 0.90 °C for 1 month ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
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.
Eduardo Acuna Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
EGUsphere, https://doi.org/10.5194/egusphere-2024-2147, https://doi.org/10.5194/egusphere-2024-2147, 2024
Short summary
Short summary
Data-driven techniques have shown the potential to outperform process-based models in rainfall-runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions we test their generalization capabilities for extreme hydrological events.
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.
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.
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.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
EGUsphere, https://doi.org/10.5194/egusphere-2024-1464, https://doi.org/10.5194/egusphere-2024-1464, 2024
Short summary
Short summary
Our study conducted a detailed analysis of runoff component and future trend in the Yarlung Tsangpo River basin owing to the existed differences in the published results, and find that the contributions of snowmelt and glacier melt runoff to streamflow were limited, both for ~5 % which were much lower than previous results. The streamflow there will continuously increase in the future, but the overestimated contribution from glacier melt would lead to an underestimation on such increasing trend.
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.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart Lane, and Francesco Comiti
EGUsphere, https://doi.org/10.5194/egusphere-2024-1687, https://doi.org/10.5194/egusphere-2024-1687, 2024
Short summary
Short summary
In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until an overparametrization limit is reached.
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.
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.
Cited articles
Abbaspour, K. C., Rouholahnejad, E., Vaghefi, S., Srinivasan, R., Yang, H.,
and Kløve, B.: A continental-scale hydrology and water quality model for
Europe: Calibration and uncertainty of a high-resolution large-scale SWAT
model, J. Hydrol., 524, 733–752, https://doi.org/10.1016/j.jhydrol.2015.03.027, 2015.
Abdulla, F. A. and Lettenmaier, D. P.: Development of regional parameter
estimation equations for a macroscale hydrologic model, J. Hydrol., 197, 230–257, https://doi.org/10.1016/S0022-1694(96)03262-3, 1997.
Addor, N. and Melsen, L. A.: Legacy, Rather Than Adequacy, Drives the
Selection of Hydrological Models, Water Resour. Res., 55, 378–390,
https://doi.org/10.1029/2018WR022958, 2019.
Addor, N., Nearing, G., Prieto, C., Newman, A. J., Le Vine, N., and Clark, M.
P.: A Ranking of Hydrological Signatures Based on Their Predictability in
Space, Water Resour. Res., 54, 8792–8812, https://doi.org/10.1029/2018WR022606, 2018.
Al Nakshabandi, G. and Kohnke, H.: Thermal conductivity and diffusivity of
soils as related to moisture tension and other physical properties, Agric.
Meteorol., 2, 271–279, https://doi.org/10.1016/0002-1571(65)90013-0, 1965.
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G.,
Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment
attributes and meteorology for large sample studies – Chile dataset,
Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018,
2018.
Andreadis, K. M. and Lettenmaier, D. P.: Trends in 20th century drought over
the continental United States, Geophys. Res. Lett., 33, 1–4,
https://doi.org/10.1029/2006GL025711, 2006.
Andreadis, K. M., Storck, P., and Lettenmaier, D. P.: Modeling snow
accumulation and ablation processes in forested environments, Water Resour.
Res., 45, W05429, https://doi.org/10.1029/2008WR007042, 2009.
Arheimer, B., Pimentel, R., Isberg, K., Crochemore, L., Andersson, J. C. M.,
Hasan, A., and Pineda, L.: Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation, Hydrol. Earth Syst.
Sci., 24, 535–559, https://doi.org/10.5194/hess-24-535-2020, 2020.
Bastidas, L. A., Gupta, H. V., Sorooshian, S., Shuttleworth, W. J., and Yang,
Z. L.: Sensitivity analysis of a land surface scheme using multicriteria
methods, J. Geophys. Res., 104, 19481–19490, 1999.
Bastidas, L. A., Hogue, T. S., Sorooshian, S., Gupta, H. V., and Shuttleworth, W. J.: Parameter sensitivity analysis for different complexity
land surface models using multicriteria methods, J. Geophys. Res., 111,
D20101, https://doi.org/10.1029/2005JD006377, 2006.
Beck, H. E., van Dijk, A. I. J. M., 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,
https://doi.org/10.1002/2015WR018247, 2016.
Bennett, K. E., Urrego Blanco, J. R., Jonko, A., Bohn, T. J., Atchley, A.
L., Urban, N. M., and Middleton, R. S.: Global Sensitivity of Simulated Water
Balance Indicators Under Future Climate Change in the Colorado Basin, Water
Resour. Res., 54, 132–149, https://doi.org/10.1002/2017WR020471, 2018.
Berg, P., Donnelly, C., and Gustafsson, D.: Near-real-time adjusted reanalysis forcing data for hydrology, Hydrol. Earth Syst. Sci., 22, 989–1000, https://doi.org/10.5194/hess-22-989-2018, 2018.
Blondin, C.: Parameterization of Land-Surface Processes in Numerical Weather
Prediction, L. Surf. Evaporation, Springer, 31–54,
https://doi.org/10.1007/978-1-4612-3032-8_3, 1991.
Bohn, T. J. and Vivoni, E. R.: Process-based characterization of evapotranspiration sources over the North American monsoon region, Water Resour. Res., 52, 358–384, https://doi.org/10.1002/2015WR017934, 2016.
Boisier, J. P., Alvarez-Garretón, C., Cepeda, J., Osses, A., Vásquez, N., and Rondanelli, R.: CR2MET: A high-resolution precipitation and temperature dataset for hydroclimatic research in Chile, ADS [data set],
https://www.cr2.cl/datos-productos-grillados/ (last access: 13 June 2022), 2018.
Brooks, R. H. and Corey, A. T.: Hydraulic Properties of Porous Media and Their Relation to Drainage Design, T. ASAE, 7, 0026–0028, https://doi.org/10.13031/2013.40684, 1964.
Budyko, M. I.: Climate and Life, Academic Press, ISBN 0121394506, ISBN 13 978-0121394509, 1974.
Casper, M. C., Grigoryan, G., Gronz, O., Gutjahr, O., Heinemann, G., Ley, R.,
and Rock, A.: Analysis of projected hydrological behavior of catchments based on signature indices, Hydrol. Earth Syst. Sci., 16, 409–421,
https://doi.org/10.5194/hess-16-409-2012, 2012.
Cayan, D. R., Das, T., Pierce, D. W., Barnett, T. P., Tyree, M., and Gershunov, A.: Future dryness in the southwest US and the hydrology of the
early 21st century drought, P. Natl. Acad. Sci. USA, 107, 21271–21276, https://doi.org/10.1073/pnas.0912391107, 2010.
Chaney, N. W., Herman, J. D., Reed, P. M., and Wood, E. F.: Flood and drought
hydrologic monitoring: The role of model parameter uncertainty, Hydrol.
Earth Syst. Sci., 19, 3239–3251, https://doi.org/10.5194/hess-19-3239-2015, 2015.
Chawla, I. and Mujumdar, P. P.: Isolating the impacts of land use and climate change on streamflow, Hydrol. Earth Syst. Sci., 19, 3633–3651,
https://doi.org/10.5194/hess-19-3633-2015, 2015.
Chegwidden, O. S. S., Nijssen, B., Rupp, D. E. E., Arnold, J. R. R., Clark,
M. P. P., Hamman, J. J. J., Kao, S. C. S. C., Mao, Y., Mizukami, N., Mote,
P. W., Pan, M., Pytlak, E., and Xiao, M.: How do modeling decisions affect
the spread among hydrologic climate change projections? Exploring a large
ensemble of simulations across a diversity of hydroclimates, Earth's Future,
7, 623–637, https://doi.org/10.1029/2018EF001047, 2019.
Chen, F., Barlage, M., Tewari, M., Rasmussen, R., Jin, J., Lettenmaier, D.,
Livneh, B., Lin, C., Miguez-Macho, G., Niu, G., Wen, L., and Yang, Z.: Modeling seasonal snowpack evolution in the complex terrain and forested Colorado Headwaters region: A model intercomparison study, J. Geophys. Res.-Atmos., 119, 13795–13819, https://doi.org/10.1002/2014JD022167, 2014.
Cherkauer, K. A., Bowling, L. C., and Lettenmaier, D. P.: Variable
infiltration capacity cold land process model updates, Global Planet. Change,
38, 151–159, https://doi.org/10.1016/S0921-8181(03)00025-0, 2003.
Chipman, H. A., George, E. I., and McCulloch, R. E.: BART: Bayesian additive
regression trees, Ann. Appl. Stat., 4, 266–298, https://doi.org/10.1214/09-AOAS285, 2010.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D., Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for
process-based hydrologic modeling: 1. Modeling concept, Water Resour. Res.,
51, 2498–2514, https://doi.org/10.1002/2015WR017198, 2015.
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.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A Statistical
Exploration of the Relationships of Soil Moisture Characteristics to the
Physical Properties of Soils, Water Resour. Res., 20, 682–690,
https://doi.org/10.1029/WR020i006p00682, 1984.
C3S and Copernicus Climate Change Service (C3S): ERA5: Fifth generation of
ECMWF atmospheric reanalyses of the global climate, C3S, https://cds.climate.copernicus.eu/cdsapp#!/home (last access: 20 January 2018), 2017.
Cuntz, M., Mai, J., Samaniego, L., Clark, M., Wulfmeyer, V., Branch, O.,
Attinger, S., and Thober, S.: The impact of standard and hard-coded parameters on the hydrologic fluxes in the Noah-MP land surface model, J.
Geophys. Res.-Atmos., 121, 10676–10700, https://doi.org/10.1002/2016JD025097, 2016.
DeChant, C. M. and Moradkhani, H.: Toward a reliable prediction of seasonal
forecast uncertainty: Addressing model and initial condition uncertainty
with ensemble data assimilation and Sequential Bayesian Combination, J.
Hydrol., 519, 2967–2977, https://doi.org/10.1016/j.jhydrol.2014.05.045, 2014.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N.,
Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S.
B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., Mcnally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Demaria, E. M., Nijssen, B., and Wagener, T.: Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity
model, J. Geophys. Res., 112, 1–15, https://doi.org/10.1029/2006JD007534, 2007.
DGA: Actualización del Balance Hídrico Nacional, SIT No. 417, https://snia.mop.gob.cl/repositoriodga/handle/20.500.13000/6919 (last access: 13 June 2022), 2017.
DGA: Aplicación de la metodología de actualización del balance
hídrico nacional a las macrozonas Norte y Centro, SIT No. 435, https://snia.mop.gob.cl/repositoriodga/handle/20.500.13000/6718 (last access: 13 June 2022), 2018.
DGA: Aplicación de la metodología de actualización del balance
hídrico nacional en las cuencas de la macrozona Sur y parte de la
Macrozona Austral, SIT No. 441, https://snia.mop.gob.cl/repositoriodga/handle/20.500.13000/7038 (last access: 13 June 2022), 2019a.
DGA: Aplicación de la metodología de actualización del balance
hídrico nacional en las cuencas de la parte sur de la macrozona Austral
e Isla de Pascua, SIT No. 444, https://snia.mop.gob.cl/repositoriodga/handle/20.500.13000/7043 (last access: 13 June 2022), 2019b.
Do, H. X., Gudmundsson, L., Leonard, M., and Westra, S.: The Global
Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a
daily streamflow archive and metadata, Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, 2018.
Dorman, J. and Sellers, P.: A global climatology of albedo, roughness length
and stomatal resistance for atmospheric general circulation models as represented by the simple biosphere model (SiB), J. Appl. Meteorol., 28,
833–855, 1989.
Ducoudré, N. I., Laval, K., and Perrier, A.: SECHIBA, a New Set of
Parameterizations of the Hydrologic Exchanges at the Land-Atmosphere Interface within the LMD Atmospheric General Circulation Model, J. Climate,
6, 248–273, https://doi.org/10.1175/1520-0442(1993)006<0248:sansop>2.0.co;2, 1993.
Fang, H., Wei, S., Jiang, C., and Scipal, K.: Theoretical uncertainty analysis of global MODIS, CYCLOPES, and GLOBCARBON LAI products using a triple collocation method, Remote Sens. Environ., 124, 610–621,
https://doi.org/10.1016/j.rse.2012.06.013, 2012.
Fang, H., Jiang, C., Li, W., Wei, S., Baret, F., Chen, J. M., Garcia-Haro,
J., Liang, S., Liu, R., Myneni, R. B., Pinty, B., Xiao, Z., and Zhu, Z.:
Characterization and intercomparison of global moderate resolution leaf area
index (LAI) products: Analysis of climatologies and theoretical uncertainties, J. Geophys. Res.-Biogeo., 118, 529–548,
https://doi.org/10.1002/jgrg.20051, 2013.
Foglia, L., Hill, M. C., Mehl, S. W., and Burlando, P.: Sensitivity analysis,
calibration, and testing of a distributed hydrological model using
error-based weighting and one objective function, Water Resour. Res., 45,
W06427, https://doi.org/10.1029/2008WR007255, 2009.
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.
Friedman, J. H.: Multivariate Adaptive Regression Splines, Ann. Stat., 19, 590–606, https://doi.org/10.1214/aos/1176347963, 1991.
Gates, D. M. and Evans, L. T.: Environmental Control of Plant Growth, Bull.
Torrey Bot. Club, 91, 235, https://doi.org/10.2307/2483533, 1964.
Gharari, S., Clark, M. P., Mizukami, N., Wong, J. S., Pietroniro, A., and
Wheater, H. S.: Improving the representation of subsurface water movement in
land models, J. Hydrometeorol., 20, 2401–2418, https://doi.org/10.1175/JHM-D-19-0108.1, 2019.
Ghiggi, G., Humphrey, V., Seneviratne, S. I., and Gudmundsson, L.: GRUN: an observation-based global gridded runoff dataset from 1902 to 2014, Earth Syst. Sci. Data, 11, 1655–1674, https://doi.org/10.5194/essd-11-1655-2019, 2019.
Göhler, M., Mai, J., and Cuntz, M.: Use of eigendecomposition in a parameter sensitivity analysis of the Community Land Model, J. Geophys. Res.-Biogeo., 118, 904–921, https://doi.org/10.1002/jgrg.20072, 2013.
Gou, J., Miao, C., Duan, Q., Tang, Q., Di, Z., Liao, W., Wu, J., and Zhou, R.: Sensitivity Analysis-Based Automatic Parameter Calibration of the VIC
Model for Streamflow Simulations Over China, Water Resour. Res., 56, 1–19, https://doi.org/10.1029/2019WR025968, 2020.
Gou, J., Miao, C., Samaniego, L., Xiao, M., Wu, J., and Guo, X.: CNRD v1.0: A
High-Quality Natural Runoff Dataset for Hydrological and Climate Studies in
China, B. Am. Meteorol. Soc., 102, E929–E947, https://doi.org/10.1175/BAMS-D-20-0094.1, 2021.
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.
Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y.: The
variable infiltration capacity model version 5 (VIC-5): Infrastructure
improvements for new applications and reproducibility, Geosci. Model Dev.,
11, 3481–3496, https://doi.org/10.5194/gmd-11-3481-2018, 2018.
Hengl, T., De Jesus, J. M., Heuvelink, G. B. M., Gonzalez, M. R., Kilibarda,
M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer-Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A.,
Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and
Kempen, B.: SoilGrids250m: Global gridded soil information based on machine
learning, PLoS ONE, 12, e0169748, https://doi.org/10.1371/journal.pone.0169748, 2017.
Hogue, T. S., Bastidas, L., Gupta, H., Sorooshian, S., Mitchell, K., and
Emmerich, W.: Evaluation and transferability of the Noah land surface model
in semiarid environments, J. Hydrometeorol., 6, 68–84, 2005.
Hornberger, G. M. and Spear, R. C.: Approach to the preliminary analysis of
environmental systems, J. Environ. Manage., 12, 7–18, 1981.
Hou, Z., Huang, M., Leung, L. R., Lin, G., and Ricciuto, D. M.: Sensitivity
of surface flux simulations to hydrologic parameters based on an uncertainty
quantification framework applied to the Community Land Model, J. Geophys.
Res.-Atmos., 117, 1–18, https://doi.org/10.1029/2012JD017521, 2012.
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.
Huang, M. and Liang, X.: On the assessment of the impact of reducing parameters and identification of parameter uncertainties for a hydrologic
model with applications to ungauged basins, J. Hydrol., 320, 37–61,
https://doi.org/10.1016/j.jhydrol.2005.07.010, 2006.
Lawrence, D. M., Fisher, R. A., Koven, C. D., Oleson, K. W., Swenson, S. C.,
Bonan, G., Collier, N., Ghimire, B., van Kampenhout, L., Kennedy, D., Kluzek, E., Lawrence, P. J., Li, F., Li, H., Lombardozzi, D., Riley, W. J., Sacks, W. J., Shi, M., Vertenstein, M., Wieder, W. R., Xu, C., Ali, A. A., Badger, A. M., Bisht, G., van den Broeke, M., Brunke, M. A., Burns, S. P., Buzan, J., Clark, M., Craig, A., Dahlin, K., Drewniak, B., Fisher, J. B., Flanner, M., Fox, A. M., Gentine, P., Hoffman, F., Keppel-Aleks, G., Knox, R., Kumar, S., Lenaerts, J., Leung, L. R., Lipscomb, W. H., Lu, Y., Pandey, A., Pelletier, J. D., Perket, J., Randerson, J. T., Ricciuto, D. M., Sanderson, B. M., Slater, A., Subin, Z. M., Tang, J., Thomas, R. Q., Val Martin, M., and Zeng, X.: The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty, J. Adv. Model. Earth Syst., 11, 4245–4287, https://doi.org/10.1029/2018MS001583, 2019.
Liang, X. and Guo, J.: Intercomparison of land-surface parameterization
schemes: sensitivity of surface energy and water fluxes to model parameters,
J. Hydrol., 279, 182–209, https://doi.org/10.1016/S0022-1694(03)00168-9, 2003.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99, 14415–14428,
https://doi.org/10.1029/94jd00483, 1994.
Liang, X., Wood, E. F., and Lettenmaier, D. P.: Surface soil moisture
parameterization of the VIC-2L model: Evaluation and modification, Global
Planet. Change, 13, 195–206, https://doi.org/10.1016/0921-8181(95)00046-1, 1996.
Liang, X., Wood, E. F., and Lettenmaier, D. P.: Modeling ground heat flux in
land surface parameterization schemes, J. Geophys. Res.-Atmos., 104,
9581–9600, https://doi.org/10.1029/98JD02307, 1999.
Lilhare, R., Pokorny, S., Déry, S. J., Stadnyk, T. A., and Koenig, K. A.:
Sensitivity analysis and uncertainty assessment in water budgets simulated by the variable infiltration capacity model for Canadian subarctic watersheds, Hydrol. Process., 34, 2057–2075, https://doi.org/10.1002/hyp.13711, 2020.
Lohmann, D., Raschke, E., Nijssen, B., and Lettenmaier, D. P.: Hydrologie
à l'échelle régionale: II. Application du modèle VIC-2L sur
la rivière Weser, Allemagne, Hydrolog. Sci. J., 43, 143–158,
https://doi.org/10.1080/02626669809492108, 1998.
Marks, D. and Dozier, J.: Climate and Energy Exchange at the Snow Surface in
the Alpine Region of the Sierra Nevada 2. Snow Cover Energy Balance, Water
Resour. Res., 28, 3043–3054, 1992.
Massoud, E. C., Xu, C., Fisher, R. A., Knox, R. G., Walker, A. P., Serbin, S. P., Christoffersen, B. O., Holm, J. A., Kueppers, L. M., Ricciuto, D. M., Wei, L., Johnson, D. J., Chambers, J. Q., Koven, C. D., McDowell, N. G., and
Vrugt, J. A.: Identification of key parameters controlling demographically
structured vegetation dynamics in a land surface model: CLM4.5(FATES),
Geosci. Model Dev., 12, 4133–4164, https://doi.org/10.5194/gmd-12-4133-2019, 2019.
McCabe, M. F., Rodell, M., Alsdorf, D. E., Miralles, D. G., Uijlenhoet, R.,
Wagner, W., Lucieer, A., Houborg, R., Verhoest, N. E. C., Franz, T. E., Shi,
J., Gao, H., and Wood, E. F.: The future of Earth observation in hydrology,
Hydrol. Earth Syst. Sci., 21, 3879–3914, https://doi.org/10.5194/hess-21-3879-2017,
2017.
Melsen, L., Teuling, A., Torfs, P., Zappa, M., Mizukami, N., Clark, M., and
Uijlenhoet, R.: Representation of spatial and temporal variability in
large-domain hydrological models: Case study for a mesoscale pre-Alpine basin, Hydrol. Earth Syst. Sci., 20, 2207–2226,
https://doi.org/10.5194/hess-20-2207-2016, 2016.
Melsen, L. A. and Guse, B.: Climate change impacts model parameter sensitivity-implications for calibration strategy and model diagnostic
evaluation, Hydrol. Earth Syst. Sci., 25, 1307–1332,
https://doi.org/10.5194/hess-25-1307-2021, 2021.
Melsen, L. A., Teuling, A. J., Torfs, P. J. J. F., Zappa, M., Mizukami, N.,
Mendoza, P. A., Clark, M. P., and Uijlenhoet, R.: Subjective modeling decisions can significantly impact the simulation of flood and drought events, J. Hydrol., 568, 1093–1104, https://doi.org/10.1016/j.jhydrol.2018.11.046, 2019.
Mendoza, P. A., Clark, M. P., Barlage, M., Rajagopalan, B., Samaniego, L.,
Abramowitz, G., and Gupta, H.: Are we unnecessarily constraining the agility
of complex process-based models?, Water Resour. Res., 51, 716–728, https://doi.org/10.1002/2014WR015820, 2015a.
Mendoza, P. A., Clark, M. P., Mizukami, N., Newman, A., Barlage, M., Gutmann, E., Rasmussen, R., Rajagopalan, B., Brekke, L., and Arnold, J.: Effects of hydrologic model choice and calibration on the portrayal of climate change impacts, J. Hydrometeorol., 16, 762–780, https://doi.org/10.1175/JHM-D-14-0104.1, 2015b.
Misirli, F., Gupta, H. V, Sorooshian, S., and Thiemann, M.: Bayesian recursive estimation of parameter and output uncertainty for watershed models, in: vol. 6, edited by: Duan, Q., Gupta, H. V., Sorooshian, S.,
Rousseau, A. N., and Turcotte, R., American Geophysical Union, Washington, DC, 113–124, https://doi.org/10.1029/WS006, 2003.
Mitchell, K. E., Lohmann, D., Houser, P. R., Wood, E. F., Schaake, J. C.,
Robock, A., Cosgrove, B. A., Sheffield, J., Duan, Q., Luo, L., Higgins, W.,
Pinker, R. T., Tarpley, J. D., Lettenmaier, D. P., Marshall, C. H., Entin,
J. K., Pan, M., Shi, W., Koren, V., Meng, J., Ramsay, B. H., and Bailey, A.
A.: The multi-institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system, J. Geophys. Res., 109, D07S90, https://doi.org/10.1029/2003JD003823, 2004.
Mizukami, N., Clark, M., Slater, A., Brekke, L., Elsner, M., Arnold, J., Gangopadhyay, S., Clark, M. P., Slater, A. G., Brekke, L. D., Elsner, M. M., Arnold, J. R., Gangopadhyay, S., Clark, M., Slater, A., Brekke, L., Elsner, M., and Arnold, J.: Hydrologic Implications of Different Large-Scale Meteorological Model Forcing Datasets in Mountainous Regions, J. Hydrometeorol., 15, 474–488, https://doi.org/10.1175/JHM-D-13-036.1, 2014.
Mizukami, N., Clark, M. P., Gutmann, E. D., Mendoza, P. A., Newman, A. J.,
Nijssen, B., Livneh, B., Hay, L. E., Arnold, J. R., and Brekke, L. D.:
Implications of the Methodological Choices for Hydrologic Portrayals of
Climate Change over the Contiguous United States: Statistically Downscaled
Forcing Data and Hydrologic Models, J. Hydrometeorol., 17, 73–98,
https://doi.org/10.1175/JHM-D-14-0187.1, 2016.
Montgomery, D. C.: Design and analysis of experiments, Wiley, ISBN 9781118146927, 1991.
Morris, M. D.: Factorial sampling plans for preliminary computational
experiments, Technometrics, 33, 161–174, https://doi.org/10.1080/00401706.1991.10484804, 1991.
Myneni, R. B., Ramakrishna, R., Nemani, R., and Running, S. W.: Estimation of
global leaf area index and absorbed par using radiative transfer models, IEEE T. Geosci. Remote, 35, 1380–1393, https://doi.org/10.1109/36.649788, 1997.
Nash, J. and Sutcliffe, J.: River ?ow forecasting through conceptual models
part I – A discussion of principles, J. Hydrol., 10, 282–290,
https://doi.org/10.1016/0022-1694(70)90255-6, 1970.
Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale
measurements, J. Geophys. Res., 116, D12109, https://doi.org/10.1029/2010JD015139, 2011.
Pi, H. and Peterson, C.: Finding the Embedding Dimension and Variable
Dependencies in Time Series, Neural Comput., 6, 509–520,
https://doi.org/10.1162/neco.1994.6.3.509, 1994.
Pokhrel, P. and Gupta, H. V.: On the use of spatial regularization strategies to improve calibration of distributed watershed models, Water Resour. Res., 46, W01505, https://doi.org/10.1029/2009WR008066, 2010.
Prihodko, L., Denning, A. S. S., Hanan, N. P. P., Baker, I., and Davis, K.:
Sensitivity, uncertainty and time dependence of parameters in a complex land
surface model, Agr. Forest Meteorol., 148, 268–287,
https://doi.org/10.1016/j.agrformet.2007.08.006, 2008.
Rakovec, O., Hill, M. C., Clark, M. P., Weerts, A. H., Teuling, A. J., and
Uijlenhoet, R.: Distributed Evaluation of Local Sensitivity Analysis (DELSA), with application to hydrologic models, Water Resour. Res., 50, 1–18, https://doi.org/10.1002/2013WR014063, 2014.
Rawls, W. J., Ahuja, L. R., Brakensiek, D. L., and Shirmohammadi, A.: Infiltration and soil water movement, in: Handbook of hydrology, edited by:
Maidment, D. R., McGraw-Hill Inc., New York, 5.1–5.51, ISBN 0070397325, 1992.
Razavi, S. and Gupta, H. V.: What do we mean by sensitivity analysis? The
need for comprehensive characterization of “global” sensitivity in Earth
and Environmental systems models, Water Resour. Res., 51, 3070–3092,
https://doi.org/10.1002/2014WR016527, 2015.
Razavi, S. and Gupta, H. V.: A new framework for comprehensive, robust, and
efficient global sensitivity analysis: 2. Application, Water Resour. Res., 52, 423–439, https://doi.org/10.1002/2015WR017558, 2016.
Reba, M. L., Marks, D., Link, T. E., Pomeroy, J., and Winstral, A.: Sensitivity of model parameterizations for simulated latent heat flux at the
snow surface for complex mountain sites, Hydrol. Process., 28, 868–881,
https://doi.org/10.1002/hyp.9619, 2014.
Reynolds, C. A., Jackson, T. J., and Rawls, W. J.: Estimating soil water-holding capacities by linking the Food and Agriculture Organization
soil map of the world with global pedon databases and continuous pedotransfer functions, Water Resour. Res., 36, 3653–3662, https://doi.org/10.1029/2000WR900130, 2000.
Rosero, E., Yang, Z.-L., Wagener, T., Gulden, L. E., Yatheendradas, S., and
Niu, G.-Y.: Quantifying parameter sensitivity, interaction, and transferability in hydrologically enhanced versions of the Noah land surface
model over transition zones during the warm season, J. Geophys. Res., 115, 1–21, https://doi.org/10.1029/2009JD012035, 2010.
Rosolem, R., Gupta, H. V., Shuttleworth, W. J., Zeng, X., and de Gonçalves, L. G. G.: A fully multiple-criteria implementation of the
Sobol' method for parameter sensitivity analysis, J. Geophys. Res., 117, 1–18, https://doi.org/10.1029/2011JD016355, 2012.
Roudier, P., Andersson, J. C. M., Donnelly, C., Feyen, L., Greuell, W., and
Ludwig, F.: Projections of future floods and hydrological droughts in Europe
under a +2 ∘C global warming, Climatic Change, 135, 341–355,
https://doi.org/10.1007/s10584-015-1570-4, 2016.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni, J., Gatelli,
D., Saisana, M., and Tarantola, S.: Global Sensitivity Analysis The Primer,
https://doi.org/10.1002/9780470725184, 2008.
Schmied, H. M., Eisner, S., Franz, D., Wattenbach, M., Portmann, F. T.,
Flörke, M., and Döll, P.: Sensitivity of simulated global-scale
freshwater fluxes and storages to input data, hydrological model structure,
human water use and calibration, Hydrol. Earth Syst. Sci., 18, 3511–3538, https://doi.org/10.5194/hess-18-3511-2014, 2014.
Sheikholeslami, R., Gharari, S., Papalexiou, S. M., and Clark, M. P.:
VISCOUS: A Variance-Based Sensitivity Analysis Using Copulas for Efficient
Identification of Dominant Hydrological Processes, Water Resour. Res., 57, 1–24, https://doi.org/10.1029/2020wr028435, 2021.
Shi, X., Wood, A. W., and Lettenmaier, D. P.: How essentialis hydrologic model calibration to seasonal stream flow forecasting?, J. Hydrometeorol., 9, 1350–1363, https://doi.org/10.1175/2008JHM1001.1, 2008.
Shukla, S., Sheffield, J., Wood, E. F., and Lettenmaier, D. P.: On the sources of global land surface hydrologic predictability, Hydrol. Earth Syst. Sci., 17, 2781–2796, https://doi.org/10.5194/hess-17-2781-2013, 2013.
Sobol', I. M.: Global sensitivity indices for nonlinear mathematical models
and their Monte Carlo estimates, Math. Comput. Simul., 55, 271–280, 2001.
Sobol', I. M. and Kucherenko, S.: A new derivative based importance criterion for groups of variables and its link with the global sensitivity indices, Comput. Phys. Commun., 181, 1212–1217, https://doi.org/10.1016/j.cpc.2010.03.006, 2010.
Tang, G., Clark, M. P., Papalexiou, S. M., Newman, A. J., Wood, A. W., Brunet, D., and Whitfield, P. H.: Emdna: An ensemble meteorological dataset
for north america, Earth Syst. Sci. Data, 13, 3337–3362,
https://doi.org/10.5194/essd-13-3337-2021, 2021.
Tian, S., Tregoning, P., Renzullo, L. J., van Dijk, A. I. J. M., Walker, J.
P., Pauwels, V. R. N., and Allgeyer, S.: Improved water balance component estimates through joint assimilation of GRACE water storage and SMOS soil
moisture retrievals, Water Resour. Res., 53, 1820–1840,
https://doi.org/10.1002/2016WR019641, 2017.
Tian, Y., Woodcock, C. E., Wang, Y., Privette, J. L., Shabanov, N. V., Zhou,
L., Zhang, Y., Buermann, W., Dong, J., Veikkanen, B., Häme, T., Andersson, K., Ozdogan, M., Knyazikhin, Y., and Myneni, R. B.: Multiscale analysis and validation of the MODIS LAI product I. Uncertainty assessment,
Remote Sens. Environ., 83, 414–430, https://doi.org/10.1016/S0034-4257(02)00047-0,
2002.
Todini, E.: The ARNO rainfall-runoff model, J. Hydrol., 175, 339–382, 1996.
Tonkin, M. J. and Doherty, J.: A hybrid regularized inversion methodology
for highly parameterized environmental models, Water Resour. Res., 41, 1–16, https://doi.org/10.1029/2005WR003995, 2005.
UNEP: World atlas of desertification, ed. 2, edited by: Middleton, N. and
Thomas, D., Arnold, Hodder Headline, PLC, https://wedocs.unep.org/20.500.11822/30300 (last access: 13 June 2022), 1997.
USACE: Snow hydrology: Summary report of the snow investigations, North
Pacific Division, Corps of Engineers, US Army, https://usace.contentdm.oclc.org/digital/collection/p266001coll1/id/4172/ (last access: 13 June 2022), 1956.
USGS: EarthExplorer, USGS [data set], https://earthexplorer.usgs.gov/, last access: 13 June 2022.
Vano, J. A. and Lettenmaier, D. P.: A sensitivity-based approach to evaluating future changes in Colorado River discharge, Climatic Change, 122,
621–634, https://doi.org/10.1007/s10584-013-1023-x, 2014.
Vásquez, N., Cepeda, J., Gómez, T., Mendoza, P. A., Lagos, M., Boisier, J. P., Álvarez-Garretón, C., and Vargas, X.: Catchment-Scale
Natural Water Balance in Chile, in: Water Resources of Chile, Springer, 189–208, https://doi.org/10.1007/978-3-030-56901-3_9, 2021.
Verbist, K., Santibañez, F., Gabriels, D., and Soto, G.: Documento
Técnico No. 25, Atlas de Zonas Áridas de América Latina y el
Caribe, https://unesdoc.unesco.org/ark:/48223/pf0000216333 (last access: 13 June 2022), 2010.
Vicuña, S., Vargas, X., Boisier, J. P., Mendoza, P. A., Gómez, T.,
Vásquez, N., and Cepeda, J.: Impacts of Climate Change on Water Resources
in Chile, in: Water Resources of Chile, vol. 13, Springer, 347–363, https://doi.org/10.1007/978-3-030-56901-3_19, 2021.
Vořechovský, M.: Hierarchical Refinement of Latin Hypercube Samples,
Comput. Civ. Infrastruct. Eng., 30, 394–411, https://doi.org/10.1111/mice.12088, 2015.
Wi, S., Ray, P., Demaria, E. M. C., 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.
Wood, A. W., Kumar, A., and Lettenmaier, D. P.: A retrospective assessment of
National Centers for Environmental prediction climate model-based ensemble
hydrologic forecasting in the western United States, J. Geophys. Res.-Atmos., 110, 1–16, https://doi.org/10.1029/2004JD004508, 2005.
Wood, E. F., Lettenmaier, D. P.., and Zartarian, V. G.: A Land-Surface Hydrology Parameterization With Subgrid Variability for General Circulation Models, J. Geophys. Res., 97, 2717–2728, https://doi.org/10.1029/91JD01786, 1992.
Woodward, J. L.: Estimating the Flammable Mass of a Vapor Cloud, John Wiley & Sons, Inc., Hoboken, NJ, USA, https://doi.org/10.1002/9780470935361, 1999.
Xia, Y., Mitchell, K., Ek, M., Sheffield, J., Cosgrove, B., Wood, E., Luo,
L., Alonge, C., Wei, H., Meng, J., Livneh, B., Lettenmaier, D., Koren, V.,
Duan, Q., Mo, K., Fan, Y., and Mocko, D.: Continental-scale water and energy
flux analysis and validation for the North American Land Data Assimilation
System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products, J. Geophys. Res., 117, D03109, https://doi.org/10.1029/2011JD016048, 2012.
Xie, Z., Yuan, F., Duan, Q., Zheng, J., Liang, M., and Chen, F.: Regional
parameter estimation of the VIC land surface model: Methodology and application to river basins in China, J. Hydrometeorol., 8, 447–468,
https://doi.org/10.1175/JHM568.1, 2007.
Yadav, M., Wagener, T., and Gupta, H.: Regionalization of constraints on
expected watershed response behavior for improved predictions in ungauged
basins, Adv. Water Resour., 30, 1756–1774, https://doi.org/10.1016/j.advwatres.2007.01.005, 2007.
Yang, Y., Pan, M., Beck, H. E., Fisher, C. K., Beighley, R. E., Kao, S. C.,
Hong, Y., and Wood, E. F.: In Quest of Calibration Density and Consistency in
Hydrologic Modeling: Distributed Parameter Calibration against Streamflow
Characteristics, Water Resour. Res., 55, 7784–7803, https://doi.org/10.1029/2018WR024178, 2019.
Yang, Y., Pan, M., Lin, P., Beck, H. E., Zeng, Z., Yamazaki, D., David, C.
H., Lu, H., Yang, K., Hong, Y., and Wood, E. F.: Global reach-level 3-hourly
river flood reanalysis (1980–2019), B. Am. Meteorol. Soc., 102, E2086–E2105, https://doi.org/10.1175/BAMS-D-20-0057.1, 2021.
Yang, Z.-L., Niu, G.-Y., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M.,
Longuevergne, L., Manning, K., Niyogi, D., Tewari, M., and Xia, Y.: The
community Noah land surface model with multiparameterization options (Noah-MP): 2. Evaluation over global river basins, J. Geophys. Res.,
116, 1–16, https://doi.org/10.1029/2010JD015140, 2011.
Yeste, P., García-Valdecasas Ojeda, M., 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.
Zegers, G., Mendoza, P. A., Garces, A., and Montserrat, S.: Sensitivity and
identifiability of rheological parameters in debris flow modeling, Nat.
Hazards Earth Syst. Sci., 20, 1919–1930, https://doi.org/10.5194/nhess-20-1919-2020,
2020.
Zhao, Q., Ye, B., Ding, Y., Zhang, S., Yi, S., Wang, J., Shangguan, D., Zhao, C., and Han, H.: Coupling a glacier melt model to the Variable Infiltration Capacity (VIC) model for hydrological modeling in north-western China, Environ. Earth Sci., 68, 87–101, https://doi.org/10.1007/s12665-012-1718-8, 2013.
Zhao, R.-J., Zuang, Y.-L., Fang, L.-R., Liu, X.-R., and Zhang, Q.-S.: Xinanjiang Model, IAHS-AISH Publ., 129, 351–356, 1980.
Zink, M., Kumar, R., Cuntz, M., and Samaniego, L.: A high-resolution dataset
of water fluxes and states for Germany accounting for parametric uncertainty, Hydrol. Earth Syst. Sci., 21, 1769–1790, https://doi.org/10.5194/hess-21-1769-2017, 2017.
Short summary
This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly used macroscale hydrological model, including a suite of eight performance metrics and 43 soil, vegetation and snow parameters. The results show that the model is highly overparameterized and, more importantly, help to provide guidance on the most relevant parameters for specific target processes across diverse climatic types.
This paper characterizes parameter sensitivities across more than 5500 grid cells for a commonly...
