Articles | Volume 15, issue 15
https://doi.org/10.5194/gmd-15-6181-2022
© 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/gmd-15-6181-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Development and technical paper
| 
08 Aug 2022
Development and technical paper |
| 08 Aug 2022
CREST-VEC: a framework towards more accurate and realistic flood simulation across scales
School of Civil Engineering and Environmental Science, University of
Oklahoma, Norman, OK, 70372, USA
Shang Gao
School of Civil Engineering and Environmental Science, University of
Oklahoma, Norman, OK, 70372, USA
Mengye Chen
School of Civil Engineering and Environmental Science, University of
Oklahoma, Norman, OK, 70372, USA
Jonathan Gourley
NOAA/National Severe Storms Laboratory, Norman, OK, 73072, USA
Naoki Mizukami
National Centers for Atmospheric Research, Boulder, CO, 80307, USA
Yang Hong
CORRESPONDING AUTHOR
School of Civil Engineering and Environmental Science, University of
Oklahoma, Norman, OK, 70372, USA
Related authors
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766, https://doi.org/10.5194/essd-13-3755-2021, https://doi.org/10.5194/essd-13-3755-2021, 2021
Short summary
Short summary
This dataset is a compilation of multi-sourced flood records, retrieved from official reports, instruments, and crowdsourcing data since 1900. This study utilizes the flood database to analyze flood seasonality within major basins and socioeconomic impacts over time. It is anticipated that this dataset can support a variety of flood-related research, such as validation resources for hydrologic models, hydroclimatic studies, and flood vulnerability analysis across the United States.
Nils Poncet, Philippe Lucas-Picher, Yves Tramblay, Guillaume Thirel, Humberto Vergara, Jonathan Gourley, and Antoinette Alias
Nat. Hazards Earth Syst. Sci. Discuss., https://doi.org/10.5194/nhess-2023-82, https://doi.org/10.5194/nhess-2023-82, 2023
Preprint under review for NHESS
Short summary
Short summary
A high resolution convection-permitting climate model is coupled with hydrological models over a Mediterranean catchment to simulate historical and future flood events. Results show the added value of this new generation of climate models for simulating Mediterranean floods. Future projections show an increase of the magnitude of the largest floods while the moderate floods are expected to decrease. Most floods are expected to become flashier i.e. potentially catastrophic in a warmer climate.
Hanqing Chen, Debao Wen, Bin Yong, Jonathan J. Gourley, Leyang Wang, and Yang Hong
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2023-42, https://doi.org/10.5194/essd-2023-42, 2023
Manuscript not accepted for further review
Short summary
Short summary
A novel multi-source precipitation data fusion (MPDF) algorithm, which considers the dependency of precipitation errors on seasonality, was proposed to fully take advantage of the complementary strengths from satellite-only IMERG-Late, ERA5 reanalysis, and ground-based precipitation observations for generating a higher-quality global precipitation product. A new global precipitation product, namely MGP, is provided to the public.
Nicolás Cortés-Salazar, Nicolás Vásquez, Naoki Mizukami, Pablo Mendoza, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-338, https://doi.org/10.5194/hess-2022-338, 2022
Revised manuscript accepted for HESS
Short summary
Short summary
This paper shows how important river models can be for water resources 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 obtain that routing can affect streamflow simulations even at monthly time steps, the choice of parameters, and relevant streamflow metrics.
Ulises M. Sepúlveda, Pablo A. Mendoza, Naoki Mizukami, and Andrew J. Newman
Hydrol. Earth Syst. Sci., 26, 3419–3445, https://doi.org/10.5194/hess-26-3419-2022, https://doi.org/10.5194/hess-26-3419-2022, 2022
Short summary
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.
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.
Zhi Li, Mengye Chen, Shang Gao, Jonathan J. Gourley, Tiantian Yang, Xinyi Shen, Randall Kolar, and Yang Hong
Earth Syst. Sci. Data, 13, 3755–3766, https://doi.org/10.5194/essd-13-3755-2021, https://doi.org/10.5194/essd-13-3755-2021, 2021
Short summary
Short summary
This dataset is a compilation of multi-sourced flood records, retrieved from official reports, instruments, and crowdsourcing data since 1900. This study utilizes the flood database to analyze flood seasonality within major basins and socioeconomic impacts over time. It is anticipated that this dataset can support a variety of flood-related research, such as validation resources for hydrologic models, hydroclimatic studies, and flood vulnerability analysis across the United States.
Hanqing Chen, Bin Yong, Pierre-Emmanuel Kirstetter, Leyang Wang, and Yang Hong
Hydrol. Earth Syst. Sci., 25, 3087–3104, https://doi.org/10.5194/hess-25-3087-2021, https://doi.org/10.5194/hess-25-3087-2021, 2021
Yingzhao Ma, Xun Sun, Haonan Chen, Yang Hong, and Yinsheng Zhang
Hydrol. Earth Syst. Sci., 25, 359–374, https://doi.org/10.5194/hess-25-359-2021, https://doi.org/10.5194/hess-25-359-2021, 2021
Short summary
Short summary
A two-stage blending approach is proposed for the data fusion of multiple satellite precipitation estimates (SPEs), which firstly reduces the systematic errors of original SPEs based on a Bayesian correction model and then merges the bias-corrected SPEs with a Bayesian weighting model. The model is evaluated in the warm season of 2010–2014 in the northeastern Tibetan Plateau. Results show that the blended SPE is greatly improved compared with the original SPEs, even in heavy rainfall events.
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.
Zachary L. Flamig, Humberto Vergara, and Jonathan J. Gourley
Geosci. Model Dev., 13, 4943–4958, https://doi.org/10.5194/gmd-13-4943-2020, https://doi.org/10.5194/gmd-13-4943-2020, 2020
Short summary
Short summary
The Ensemble Framework For Flash Flood Forecasting (EF5) is used in the US National Weather Service for operational monitoring and short-term forecasting of flash floods. This article describes the hydrologic models supported by the framework and evaluates their accuracy by comparing simulations of streamflow from 2001 to 2011 at 4 366 observation sites with catchments less than 1000 km2. Overall, the uncalibrated models reasonably simulate flash flooding events.
Ziqiang Ma, Jintao Xu, Siyu Zhu, Jun Yang, Guoqiang Tang, Yuanjian Yang, Zhou Shi, and Yang Hong
Earth Syst. Sci. Data, 12, 1525–1544, https://doi.org/10.5194/essd-12-1525-2020, https://doi.org/10.5194/essd-12-1525-2020, 2020
Short summary
Short summary
Focusing on the potential drawbacks in generating the state-of-the-art IMERG data in both the TRMM and GPM era, a new daily calibration algorithm on IMERG was proposed, as well as a new AIMERG precipitation dataset (0.1°/half-hourly, 2000–2015, Asia) with better quality than IMERG for Asian scientific research and applications. The proposed daily calibration algorithm for GPM is promising and applicable in generating the future IMERG in either an operational scheme or a retrospective manner.
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.
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.
Ke Zhang, Xianwu Xue, Yang Hong, Jonathan J. Gourley, Ning Lu, Zhanming Wan, Zhen Hong, and Rick Wooten
Hydrol. Earth Syst. Sci., 20, 5035–5048, https://doi.org/10.5194/hess-20-5035-2016, https://doi.org/10.5194/hess-20-5035-2016, 2016
Short summary
Short summary
We developed a new approach to couple a distributed hydrological model, CREST, to a geotechnical landslide model, TRIGRS, to simulate both flood- and rainfall-triggered landslide hazards. By implementing more sophisticated and realistic representations of hydrological processes in the coupled model system, it shows better performance than the standalone landslide model in the case study. It highlights the important physical connection between rainfall, hydrological processes and slope stability.
Wen-Yu Yang, Guang-Heng Ni, You-Cun Qi, Yang Hong, and Ting Sun
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2016-388, https://doi.org/10.5194/amt-2016-388, 2016
Revised manuscript has not been submitted
Short summary
Short summary
Using a dataset consisting of one-year measurements by an X-band radar and distrometer, we found that error corrections greatly improve X-band-radar-based rainfall estimation. Specifically, the greatest improvement is realized by the beam integration. Derivation of localized Z-R relationships for specific rainfall systems is also of great importance. Moreover, wind drift correction improves quantitative estimates and temporal consistency.
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.
Related subject area
Hydrology
NEOPRENE v1.0.1: a Python library for generating spatial rainfall based on the Neyman–Scott process
Uncertainty estimation for a new exponential-filter-based long-term root-zone soil moisture dataset from Copernicus Climate Change Service (C3S) surface observations
Validating the Nernst–Planck transport model under reaction-driven flow conditions using RetroPy v1.0
DynQual v1.0: a high-resolution global surface water quality model
Data space inversion for efficient uncertainty quantification using an integrated surface and sub-surface hydrologic model
Simulation of crop yield using the global hydrological model H08 (crp.v1)
How is a global sensitivity analysis of a catchment-scale, distributed pesticide transfer model performed? Application to the PESHMELBA model
iHydroSlide3D v1.0: an advanced hydrological–geotechnical model for hydrological simulation and three-dimensional landslide prediction
GEB v0.1: a large-scale agent-based socio-hydrological model – simulating 10 million individual farming households in a fully distributed hydrological model
Tracing and visualisation of contributing water sources in the LISFLOOD-FP model of flood inundation (within CAESAR-Lisflood version 1.9j-WS)
Continental-scale evaluation of a fully distributed coupled land surface and groundwater model, ParFlow-CLM (v3.6.0), over Europe
Evaluating a global soil moisture dataset from a multitask model (GSM3 v1.0) with potential applications for crop threats
SERGHEI (SERGHEI-SWE) v1.0: a performance-portable high-performance parallel-computing shallow-water solver for hydrology and environmental hydraulics
Enhancing the representation of water management in global hydrological models
A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)
Customized deep learning for precipitation bias correction and downscaling
Implementation and sensitivity analysis of the Dam-Reservoir OPeration model (DROP v1.0) over Spain
Regional coupled surface–subsurface hydrological model fitting based on a spatially distributed minimalist reduction of frequency domain discharge data
Representing the impact of Rhizophora mangroves on flow and sediment transport in a hydrodynamic model (COAWST_rh v1.0): the importance of three-dimensional root system structures
Operational water forecast ability of the HRRR-iSnobal combination: an evaluation to adapt into production environments
Dynamic weighted ensemble of geoscientific models via automated machine learning-based classification
Prediction of algal blooms via data-driven machine learning models: an evaluation using data from a well-monitored mesotrophic lake
UniFHy v0.1.1: a community modelling framework for the terrestrial water cycle in Python
mesas.py v1.0: A flexible Python package for modeling solute transport and transit times using StorAge Selection functions
Basin-scale gyres and mesoscale eddies in large lakes: a novel procedure for their detection and characterization, assessed in Lake Geneva
SIMO v1.0: simplified model of the vertical temperature profile in a small, warm, monomictic lake
Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model
Water balance model (WBM) v.1.0.0: a scalable gridded global hydrologic model with water-tracking functionality
Coupling a large-scale hydrological model (CWatM v1.1) with a high-resolution groundwater flow model (MODFLOW 6) to assess the impact of irrigation at regional scale
RavenR v2.1.4: an open-source R package to support flexible hydrologic modelling
Developing a parsimonious canopy model (PCM v1.0) to predict forest gross primary productivity and leaf area index of deciduous broad-leaved forest
Synergy between satellite observations of soil moisture and water storage anomalies for runoff estimation
A physically based distributed karst hydrological model (QMG model-V1.0) for flood simulations
Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) v2.1: an object-oriented implementation of 47 established hydrological models for improved speed and readability
Rad-cGAN v1.0: Radar-based precipitation nowcasting model with conditional generative adversarial networks for multiple dam domains
The eWaterCycle platform for open and FAIR hydrological collaboration
Evaluating the Atibaia River hydrology using JULES6.1
A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector
CLIMFILL v0.9: a framework for intelligently gap filling Earth observations
Modeling subgrid lake energy balance in ORCHIDEE terrestrial scheme using the FLake lake model
Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling
Improved runoff simulations for a highly varying soil depth and complex terrain watershed in the Loess Plateau with the Community Land Model version 5
GSTools v1.3: a toolbox for geostatistical modelling in Python
AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods
Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x
Tree hydrodynamic modelling of the soil–plant–atmosphere continuum using FETCH3
Effects of dimensionality on the performance of hydrodynamic models for stratified lakes and reservoirs
Computation of backwater effects in surface waters of lowland catchments including control structures – an efficient and re-usable method implemented in the hydrological open-source model Kalypso-NA (4.0)
Inishell 2.0: semantically driven automatic GUI generation for scientific models
Irrigation quality and management determine salinization in Israeli olive orchards
Javier Diez-Sierra, Salvador Navas, and Manuel del Jesus
Geosci. Model Dev., 16, 5035–5048, https://doi.org/10.5194/gmd-16-5035-2023, https://doi.org/10.5194/gmd-16-5035-2023, 2023
Short summary
Short summary
NEOPRENE is an open-source, freely available library allowing scientists and practitioners to generate synthetic time series and maps of rainfall. These outputs will help to explore plausible events that were never observed in the past but may occur in the near future and to generate possible future events under climate change conditions. The paper shows how to use the library to downscale daily precipitation and how to use synthetic generation to improve our characterization of extreme events.
Adam Pasik, Alexander Gruber, Wolfgang Preimesberger, Domenico De Santis, and Wouter Dorigo
Geosci. Model Dev., 16, 4957–4976, https://doi.org/10.5194/gmd-16-4957-2023, https://doi.org/10.5194/gmd-16-4957-2023, 2023
Short summary
Short summary
We apply the exponential filter (EF) method to satellite soil moisture retrievals to estimate the water content in the unobserved root zone globally from 2002–2020. Quality assessment against an independent dataset shows satisfactory results. Error characterization is carried out using the standard uncertainty propagation law and empirically estimated values of EF model structural uncertainty and parameter uncertainty. This is followed by analysis of temporal uncertainty variations.
Po-Wei Huang, Bernd Flemisch, Chao-Zhong Qin, Martin O. Saar, and Anozie Ebigbo
Geosci. Model Dev., 16, 4767–4791, https://doi.org/10.5194/gmd-16-4767-2023, https://doi.org/10.5194/gmd-16-4767-2023, 2023
Short summary
Short summary
Water in natural environments consists of many ions. Ions are electrically charged and exert electric forces on each other. We discuss whether the electric forces are relevant in describing mixing and reaction processes in natural environments. By comparing our computer simulations to lab experiments in literature, we show that the electric interactions between ions can play an essential role in mixing and reaction processes, in which case they should not be neglected in numerical modeling.
Edward R. Jones, Marc F. P. Bierkens, Niko Wanders, Edwin H. Sutanudjaja, Ludovicus P. H. van Beek, and Michelle T. H. van Vliet
Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, https://doi.org/10.5194/gmd-16-4481-2023, 2023
Short summary
Short summary
DynQual is a new high-resolution global water quality model for simulating total dissolved solids, biological oxygen demand and fecal coliform as indicators of salinity, organic pollution and pathogen pollution, respectively. Output data from DynQual can supplement the observational record of water quality data, which is highly fragmented across space and time, and has the potential to inform assessments in a broad range of fields including ecological, human health and water scarcity studies.
Hugo Delottier, John Doherty, and Philip Brunner
Geosci. Model Dev., 16, 4213–4231, https://doi.org/10.5194/gmd-16-4213-2023, https://doi.org/10.5194/gmd-16-4213-2023, 2023
Short summary
Short summary
Long run times are usually a barrier to the quantification and reduction of predictive uncertainty with complex hydrological models. Data space inversion (DSI) provides an alternative and highly model-run-efficient method for uncertainty quantification. This paper demonstrates DSI's ability to robustly quantify predictive uncertainty and extend the methodology to provide practical metrics that can guide data acquisition and analysis to achieve goals of decision-support modelling.
Zhipin Ai and Naota Hanasaki
Geosci. Model Dev., 16, 3275–3290, https://doi.org/10.5194/gmd-16-3275-2023, https://doi.org/10.5194/gmd-16-3275-2023, 2023
Short summary
Short summary
Simultaneously simulating food production and the requirements and availability of water resources in a spatially explicit manner within a single framework remains challenging on a global scale. Here, we successfully enhanced the global hydrological model H08 that considers human water use and management to simulate the yields of four major staple crops: maize, wheat, rice, and soybean. Our improved model will be beneficial for advancing global food–water nexus studies in the future.
Emilie Rouzies, Claire Lauvernet, Bruno Sudret, and Arthur Vidard
Geosci. Model Dev., 16, 3137–3163, https://doi.org/10.5194/gmd-16-3137-2023, https://doi.org/10.5194/gmd-16-3137-2023, 2023
Short summary
Short summary
Water and pesticide transfer models are complex and should be simplified to be used in decision support. Indeed, these models simulate many spatial processes in interaction, involving a large number of parameters. Sensitivity analysis allows us to select the most influential input parameters, but it has to be adapted to spatial modelling. This study will identify relevant methods that can be transposed to any hydrological and water quality model and improve the fate of pesticide knowledge.
Guoding Chen, Ke Zhang, Sheng Wang, Yi Xia, and Lijun Chao
Geosci. Model Dev., 16, 2915–2937, https://doi.org/10.5194/gmd-16-2915-2023, https://doi.org/10.5194/gmd-16-2915-2023, 2023
Short summary
Short summary
In this study, we developed a novel modeling system called iHydroSlide3D v1.0 by coupling a modified a 3D landslide model with a distributed hydrology model. The model is able to apply flexibly different simulating resolutions for hydrological and slope stability submodules and gain a high computational efficiency through parallel computation. The test results in the Yuehe River basin, China, show a good predicative capability for cascading flood–landslide events.
Jens A. de Bruijn, Mikhail Smilovic, Peter Burek, Luca Guillaumot, Yoshihide Wada, and Jeroen C. J. H. Aerts
Geosci. Model Dev., 16, 2437–2454, https://doi.org/10.5194/gmd-16-2437-2023, https://doi.org/10.5194/gmd-16-2437-2023, 2023
Short summary
Short summary
We present a computer simulation model of the hydrological system and human system, which can simulate the behaviour of individual farmers and their interactions with the water system at basin scale to assess how the systems have evolved and are projected to evolve in the future. For example, we can simulate the effect of subsidies provided on investment in adaptation measures and subsequent effects in the hydrological system, such as a lowering of the groundwater table or reservoir level.
Matthew D. Wilson and Thomas J. Coulthard
Geosci. Model Dev., 16, 2415–2436, https://doi.org/10.5194/gmd-16-2415-2023, https://doi.org/10.5194/gmd-16-2415-2023, 2023
Short summary
Short summary
During flooding, the sources of water that inundate a location can influence impacts such as pollution. However, methods to trace water sources in flood events are currently only available in complex, computationally expensive hydraulic models. We propose a simplified method which can be added to efficient, reduced-complexity model codes, enabling an improved understanding of flood dynamics and its impacts. We demonstrate its application for three sites at a range of spatial and temporal scales.
Bibi S. Naz, Wendy Sharples, Yueling Ma, Klaus Goergen, and Stefan Kollet
Geosci. Model Dev., 16, 1617–1639, https://doi.org/10.5194/gmd-16-1617-2023, https://doi.org/10.5194/gmd-16-1617-2023, 2023
Short summary
Short summary
It is challenging to apply a high-resolution integrated land surface and groundwater model over large spatial scales. In this paper, we demonstrate the application of such a model over a pan-European domain at 3 km resolution and perform an extensive evaluation of simulated water states and fluxes by comparing with in situ and satellite data. This study can serve as a benchmark and baseline for future studies of climate change impact projections and for hydrological forecasting.
Jiangtao Liu, David Hughes, Farshid Rahmani, Kathryn Lawson, and Chaopeng Shen
Geosci. Model Dev., 16, 1553–1567, https://doi.org/10.5194/gmd-16-1553-2023, https://doi.org/10.5194/gmd-16-1553-2023, 2023
Short summary
Short summary
Under-monitored regions like Africa need high-quality soil moisture predictions to help with food production, but it is not clear if soil moisture processes are similar enough around the world for data-driven models to maintain accuracy. We present a deep-learning-based soil moisture model that learns from both in situ data and satellite data and performs better than satellite products at the global scale. These results help us apply our model globally while better understanding its limitations.
Daniel Caviedes-Voullième, Mario Morales-Hernández, Matthew R. Norman, and Ilhan Özgen-Xian
Geosci. Model Dev., 16, 977–1008, https://doi.org/10.5194/gmd-16-977-2023, https://doi.org/10.5194/gmd-16-977-2023, 2023
Short summary
Short summary
This paper introduces the SERGHEI framework and a solver for shallow-water problems. Such models, often used for surface flow and flood modelling, are computationally intense. In recent years the trends to increase computational power have changed, requiring models to adapt to new hardware and new software paradigms. SERGHEI addresses these challenges, allowing surface flow simulation to be enabled on the newest and upcoming consumer hardware and supercomputers very efficiently.
Guta Wakbulcho Abeshu, Fuqiang Tian, Thomas Wild, Mengqi Zhao, Sean Turner, A F M Kamal Chowdhury, Chris R. Vernon, Hongchang Hu, Yuan Zhuang, Mohamad Hejazi, and Hong-Yi Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-12, https://doi.org/10.5194/gmd-2023-12, 2023
Revised manuscript accepted for GMD
Short summary
Short summary
Most existing global hydrologic models do not explicitly represent hydropower reservoirs. We are introducing a new water management module to Xanthos that distinguishes between the operational characteristics of irrigation, hydropower, and flood control reservoirs. We show that this explicit representation of hydropower reservoirs can lead to a significantly more realistic simulation of reservoir storage and releases in over 44 % of the hydropower reservoirs included in this study.
Andrew M. Ireson, Raymond J. Spiteri, Martyn P. Clark, and Simon A. Mathias
Geosci. Model Dev., 16, 659–677, https://doi.org/10.5194/gmd-16-659-2023, https://doi.org/10.5194/gmd-16-659-2023, 2023
Short summary
Short summary
Richards' equation (RE) is used to describe the movement and storage of water in a soil profile and is a component of many hydrological and earth-system models. Solving RE numerically is challenging due to the non-linearities in the properties. Here, we present a simple but effective and mass-conservative solution to solving RE, which is ideal for teaching/learning purposes but also useful in prototype models that are used to explore alternative process representations.
Fang Wang, Di Tian, and Mark Carroll
Geosci. Model Dev., 16, 535–556, https://doi.org/10.5194/gmd-16-535-2023, https://doi.org/10.5194/gmd-16-535-2023, 2023
Short summary
Short summary
Gridded precipitation datasets suffer from biases and coarse resolutions. We developed a customized deep learning (DL) model to bias-correct and downscale gridded precipitation data using radar observations. The results showed that the customized DL model can generate improved precipitation at fine resolutions where regular DL and statistical methods experience challenges. The new model can be used to improve precipitation estimates, especially for capturing extremes at smaller scales.
Malak Sadki, Simon Munier, Aaron Boone, and Sophie Ricci
Geosci. Model Dev., 16, 427–448, https://doi.org/10.5194/gmd-16-427-2023, https://doi.org/10.5194/gmd-16-427-2023, 2023
Short summary
Short summary
Predicting water resource evolution is a key challenge for the coming century.
Anthropogenic impacts on water resources, and particularly the effects of dams and reservoirs on river flows, are still poorly known and generally neglected in global hydrological studies. A parameterized reservoir model is reproduced to compute monthly releases in Spanish anthropized river basins. For global application, an exhaustive sensitivity analysis of the model parameters is performed on flows and volumes.
Nicolas Flipo, Nicolas Gallois, and Jonathan Schuite
Geosci. Model Dev., 16, 353–381, https://doi.org/10.5194/gmd-16-353-2023, https://doi.org/10.5194/gmd-16-353-2023, 2023
Short summary
Short summary
A new approach is proposed to fit hydrological or land surface models, which suffer from large uncertainties in terms of water partitioning between fast runoff and slow infiltration from small watersheds to regional or continental river basins. It is based on the analysis of hydrosystem behavior in the frequency domain, which serves as a basis for estimating water flows in the time domain with a physically based model. It opens the way to significant breakthroughs in hydrological modeling.
Masaya Yoshikai, Takashi Nakamura, Eugene C. Herrera, Rempei Suwa, Rene Rollon, Raghab Ray, Keita Furukawa, and Kazuo Nadaoka
EGUsphere, https://doi.org/10.5194/egusphere-2022-1350, https://doi.org/10.5194/egusphere-2022-1350, 2023
Short summary
Short summary
Due to complex root system structures, representing the impacts of Rhizophora mangroves on flow and sediment transport in hydrodynamic models has been challenging. This study presents a new drag and turbulence model that leverages an empirical model for root systems. The model can be applied without rigorous measurements of root structures and showed high performance in flow simulations, which may provide a better understanding of sedimentary processes in Rhizophora mangrove forests.
Joachim Meyer, John Horel, Patrick Kormos, Andrew Hedrick, Ernesto Trujillo, and S. McKenzie Skiles
Geosci. Model Dev., 16, 233–250, https://doi.org/10.5194/gmd-16-233-2023, https://doi.org/10.5194/gmd-16-233-2023, 2023
Short summary
Short summary
Freshwater resupply from seasonal snow in the mountains is changing. Current water prediction methods from snow rely on historical data excluding the change and can lead to errors. This work presented and evaluated an alternative snow-physics-based approach. The results in a test watershed were promising, and future improvements were identified. Adaptation to current forecast environments would improve resilience to the seasonal snow changes and helps ensure the accuracy of resupply forecasts.
Hao Chen, Tiejun Wang, Yonggen Zhang, Yun Bai, and Xi Chen
EGUsphere, https://doi.org/10.5194/egusphere-2022-1326, https://doi.org/10.5194/egusphere-2022-1326, 2023
Short summary
Short summary
Effectively assembling multiple models for approaching a benchmark solution remains a long-standing issue for various geoscience domains. We here proposed an automated machine learning-assisted ensemble framework (AutoML-Ens) that attempts to resolve this challenge. Results demonstrated the great potential of AutoML-Ens for improving estimations due to its two unique features, i.e., assigning dynamic weights for candidate models and taking full advantage of AutoML-assisted workflow.
Shuqi Lin, Donald C. Pierson, and Jorrit P. Mesman
Geosci. Model Dev., 16, 35–46, https://doi.org/10.5194/gmd-16-35-2023, https://doi.org/10.5194/gmd-16-35-2023, 2023
Short summary
Short summary
The risks brought by the proliferation of algal blooms motivate the improvement of bloom forecasting tools, but algal blooms are complexly controlled and difficult to predict. Given rapid growth of monitoring data and advances in computation, machine learning offers an alternative prediction methodology. This study tested various machine learning workflows in a dimictic mesotrophic lake and gave promising predictions of the seasonal variations and the timing of algal blooms.
Thibault Hallouin, Richard J. Ellis, Douglas B. Clark, Simon J. Dadson, Andrew G. Hughes, Bryan N. Lawrence, Grenville M. S. Lister, and Jan Polcher
Geosci. Model Dev., 15, 9177–9196, https://doi.org/10.5194/gmd-15-9177-2022, https://doi.org/10.5194/gmd-15-9177-2022, 2022
Short summary
Short summary
A new framework for modelling the water cycle in the land system has been implemented. It considers the hydrological cycle as three interconnected components, bringing flexibility in the choice of the physical processes and their spatio-temporal resolutions. It is designed to foster collaborations between land surface, hydrological, and groundwater modelling communities to develop the next-generation of land system models for integration in Earth system models.
Ciaran Harman and Esther Xu Fei
EGUsphere, https://doi.org/10.5194/egusphere-2022-1262, https://doi.org/10.5194/egusphere-2022-1262, 2022
Short summary
Short summary
Over the last 10 years scientists have developed a new way of modeling how material is transported through complex systems, called StorAge Selection. Here we present some new code implementing this method that is easy to use, but also flexible and very accurate. We show that for cases where we know exactly what the answer should be, our code gets the right answer. We also show that our code is closer than some other people's code to the right answer in an important way: it conserves mass.
Seyed Mahmood Hamze-Ziabari, Ulrich Lemmin, Frédéric Soulignac, Mehrshad Foroughan, and David Andrew Barry
Geosci. Model Dev., 15, 8785–8807, https://doi.org/10.5194/gmd-15-8785-2022, https://doi.org/10.5194/gmd-15-8785-2022, 2022
Short summary
Short summary
A procedure combining numerical simulations, remote sensing, and statistical analyses is developed to detect large-scale current systems in large lakes. By applying this novel procedure in Lake Geneva, strategies for detailed transect field studies of the gyres and eddies were developed. Unambiguous field evidence of 3D gyre/eddy structures in full agreement with predictions confirmed the robustness of the proposed procedure.
Kristina Šarović, Melita Burić, and Zvjezdana B. Klaić
Geosci. Model Dev., 15, 8349–8375, https://doi.org/10.5194/gmd-15-8349-2022, https://doi.org/10.5194/gmd-15-8349-2022, 2022
Short summary
Short summary
We develop a simple 1-D model for the prediction of the vertical temperature profiles in small, warm lakes. The model uses routinely measured meteorological variables as well as UVB radiation and yearly mean temperature data. It can be used for the assessment of the onset and duration of lake stratification periods when water temperature data are unavailable, which can be useful for various lake studies performed in other scientific fields, such as biology, geochemistry, and sedimentology.
Jason A. Clark, Elchin E. Jafarov, Ken D. Tape, Benjamin M. Jones, and Victor Stepanenko
Geosci. Model Dev., 15, 7421–7448, https://doi.org/10.5194/gmd-15-7421-2022, https://doi.org/10.5194/gmd-15-7421-2022, 2022
Short summary
Short summary
Lakes in the Arctic are important reservoirs of heat. Under climate warming scenarios, we expect Arctic lakes to warm the surrounding frozen ground. We simulate water temperatures in three Arctic lakes in northern Alaska over several years. Our results show that snow depth and lake ice strongly affect water temperatures during the frozen season and that more heat storage by lakes would enhance thawing of frozen ground.
Danielle S. Grogan, Shan Zuidema, Alex Prusevich, Wilfred M. Wollheim, Stanley Glidden, and Richard B. Lammers
Geosci. Model Dev., 15, 7287–7323, https://doi.org/10.5194/gmd-15-7287-2022, https://doi.org/10.5194/gmd-15-7287-2022, 2022
Short summary
Short summary
This paper describes the University of New Hampshire's water balance model (WBM). This model simulates the land surface components of the global water cycle and includes water extractions for use by humans for agricultural, domestic, and industrial purposes. A new feature is described that permits water source tracking through the water cycle, which has implications for water resource management. This paper was written to describe a long-used model and presents its first open-source version.
Luca Guillaumot, Mikhail Smilovic, Peter Burek, Jens de Bruijn, Peter Greve, Taher Kahil, and Yoshihide Wada
Geosci. Model Dev., 15, 7099–7120, https://doi.org/10.5194/gmd-15-7099-2022, https://doi.org/10.5194/gmd-15-7099-2022, 2022
Short summary
Short summary
We develop and test the first large-scale hydrological model at regional scale with a very high spatial resolution that includes a water management and groundwater flow model. This study infers the impact of surface and groundwater-based irrigation on groundwater recharge and on evapotranspiration in both irrigated and non-irrigated areas. We argue that water table recorded in boreholes can be used as validation data if water management is well implemented and spatial resolution is ≤ 100 m.
Robert Chlumsky, James R. Craig, Simon G. M. Lin, Sarah Grass, Leland Scantlebury, Genevieve Brown, and Rezgar Arabzadeh
Geosci. Model Dev., 15, 7017–7030, https://doi.org/10.5194/gmd-15-7017-2022, https://doi.org/10.5194/gmd-15-7017-2022, 2022
Short summary
Short summary
We introduce the open-source RavenR package, which has been built to support the use of the hydrologic modelling framework Raven. The R package contains many functions that may be useful in each step of the model-building process, including preparing model input files, running the model, and analyzing the outputs. We present six reproducible use cases of the RavenR package for the Liard River basin in Canada to demonstrate how it may be deployed.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
Short summary
Short summary
Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Stefania Camici, Gabriele Giuliani, Luca Brocca, Christian Massari, Angelica Tarpanelli, Hassan Hashemi Farahani, Nico Sneeuw, Marco Restano, and Jérôme Benveniste
Geosci. Model Dev., 15, 6935–6956, https://doi.org/10.5194/gmd-15-6935-2022, https://doi.org/10.5194/gmd-15-6935-2022, 2022
Short summary
Short summary
This paper presents an innovative approach, STREAM (SaTellite-based Runoff Evaluation And Mapping), to derive daily river discharge and runoff estimates from satellite observations of soil moisture, precipitation, and terrestrial total water storage anomalies. Potentially useful for multiple operational and scientific applications, the added value of the STREAM approach is the ability to increase knowledge on the natural processes, human activities, and their interactions on the land.
Ji Li, Daoxian Yuan, Fuxi Zhang, Jiao Liu, and Mingguo Ma
Geosci. Model Dev., 15, 6581–6600, https://doi.org/10.5194/gmd-15-6581-2022, https://doi.org/10.5194/gmd-15-6581-2022, 2022
Short summary
Short summary
A new karst hydrological model (the QMG model) is developed to simulate and predict the floods in karst trough valley basins. Unlike the complex structure and parameters of current karst groundwater models, this model has a simple double-layered structure with few parameters and decreases the demand for modeling data in karst areas. The flood simulation results based on the QMG model of the Qingmuguan karst trough valley basin are satisfactory, indicating the suitability of the model simulation.
Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
Geosci. Model Dev., 15, 6359–6369, https://doi.org/10.5194/gmd-15-6359-2022, https://doi.org/10.5194/gmd-15-6359-2022, 2022
Short summary
Short summary
MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
Suyeon Choi and Yeonjoo Kim
Geosci. Model Dev., 15, 5967–5985, https://doi.org/10.5194/gmd-15-5967-2022, https://doi.org/10.5194/gmd-15-5967-2022, 2022
Short summary
Short summary
Here we present the cGAN-based precipitation nowcasting model, named Rad-cGAN, trained to predict a radar reflectivity map with a lead time of 10 min. Rad-cGAN showed superior performance at a lead time of up to 90 min compared with the reference models. Furthermore, we demonstrate the successful implementation of the transfer learning strategies using pre-trained Rad-cGAN to develop the models for different dam domains.
Rolf Hut, Niels Drost, Nick van de Giesen, Ben van Werkhoven, Banafsheh Abdollahi, Jerom Aerts, Thomas Albers, Fakhereh Alidoost, Bouwe Andela, Jaro Camphuijsen, Yifat Dzigan, Ronald van Haren, Eric Hutton, Peter Kalverla, Maarten van Meersbergen, Gijs van den Oord, Inti Pelupessy, Stef Smeets, Stefan Verhoeven, Martine de Vos, and Berend Weel
Geosci. Model Dev., 15, 5371–5390, https://doi.org/10.5194/gmd-15-5371-2022, https://doi.org/10.5194/gmd-15-5371-2022, 2022
Short summary
Short summary
With the eWaterCycle platform, we are providing the hydrological community with a platform to conduct their research that is fully compatible with the principles of both open science and FAIR science. The eWatercyle platform gives easy access to well-known hydrological models, big datasets and example experiments. Using eWaterCycle hydrologists can easily compare the results from different models, couple models and do more complex hydrological computational research.
Hsi-Kai Chou, Ana Maria Heuminski de Avila, and Michaela Bray
Geosci. Model Dev., 15, 5233–5240, https://doi.org/10.5194/gmd-15-5233-2022, https://doi.org/10.5194/gmd-15-5233-2022, 2022
Short summary
Short summary
Land surface models allow us to understand and investigate the cause and effect of environmental process changes. Therefore, this type of model is increasingly used for hydrological assessments. Here we explore the possibility of this approach using a case study in the Atibaia River basin, which serves as a major water supply for the metropolitan regions of Campinas and São Paulo, Brazil. We evaluated the model performance and use the model to simulate the basin hydrology.
Malgorzata Golub, Wim Thiery, Rafael Marcé, Don Pierson, Inne Vanderkelen, Daniel Mercado-Bettin, R. Iestyn Woolway, Luke Grant, Eleanor Jennings, Benjamin M. Kraemer, Jacob Schewe, Fang Zhao, Katja Frieler, Matthias Mengel, Vasiliy Y. Bogomolov, Damien Bouffard, Marianne Côté, Raoul-Marie Couture, Andrey V. Debolskiy, Bram Droppers, Gideon Gal, Mingyang Guo, Annette B. G. Janssen, Georgiy Kirillin, Robert Ladwig, Madeline Magee, Tadhg Moore, Marjorie Perroud, Sebastiano Piccolroaz, Love Raaman Vinnaa, Martin Schmid, Tom Shatwell, Victor M. Stepanenko, Zeli Tan, Bronwyn Woodward, Huaxia Yao, Rita Adrian, Mathew Allan, Orlane Anneville, Lauri Arvola, Karen Atkins, Leon Boegman, Cayelan Carey, Kyle Christianson, Elvira de Eyto, Curtis DeGasperi, Maria Grechushnikova, Josef Hejzlar, Klaus Joehnk, Ian D. Jones, Alo Laas, Eleanor B. Mackay, Ivan Mammarella, Hampus Markensten, Chris McBride, Deniz Özkundakci, Miguel Potes, Karsten Rinke, Dale Robertson, James A. Rusak, Rui Salgado, Leon van der Linden, Piet Verburg, Danielle Wain, Nicole K. Ward, Sabine Wollrab, and Galina Zdorovennova
Geosci. Model Dev., 15, 4597–4623, https://doi.org/10.5194/gmd-15-4597-2022, https://doi.org/10.5194/gmd-15-4597-2022, 2022
Short summary
Short summary
Lakes and reservoirs are warming across the globe. To better understand how lakes are changing and to project their future behavior amidst various sources of uncertainty, simulations with a range of lake models are required. This in turn requires international coordination across different lake modelling teams worldwide. Here we present a protocol for and results from coordinated simulations of climate change impacts on lakes worldwide.
Verena Bessenbacher, Sonia Isabelle Seneviratne, and Lukas Gudmundsson
Geosci. Model Dev., 15, 4569–4596, https://doi.org/10.5194/gmd-15-4569-2022, https://doi.org/10.5194/gmd-15-4569-2022, 2022
Short summary
Short summary
Earth observations have many missing values. They are often filled using information from spatial and temporal contexts that mostly ignore information from related observed variables. We propose the gap-filling method CLIMFILL that additionally uses information from related variables. We test CLIMFILL using gap-free reanalysis data of variables related to soil–moisture climate interactions. CLIMFILL creates estimates for the missing values that recover the original dependence structure.
Anthony Bernus and Catherine Ottlé
Geosci. Model Dev., 15, 4275–4295, https://doi.org/10.5194/gmd-15-4275-2022, https://doi.org/10.5194/gmd-15-4275-2022, 2022
Short summary
Short summary
The lake model FLake was coupled to the ORCHIDEE land surface model to simulate lake energy balance at global scale with a multi-tile approach. Several simulations were performed with various atmospheric reanalyses and different lake depth parameterizations. The simulated lake surface temperature showed good agreement with observations (RMSEs of the order of 3 °C). We showed the large impact of the atmospheric forcing on lake temperature. We highlighted systematic errors on ice cover phenology.
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.
Jiming Jin, Lei Wang, Jie Yang, Bingcheng Si, and Guo-Yue Niu
Geosci. Model Dev., 15, 3405–3416, https://doi.org/10.5194/gmd-15-3405-2022, https://doi.org/10.5194/gmd-15-3405-2022, 2022
Short summary
Short summary
This study aimed to improve runoff simulations and explore deep soil hydrological processes for a highly varying soil depth and complex terrain watershed in the Loess Plateau, China. The actual soil depths and river channels were incorporated into the model to better simulate the runoff in this watershed. The soil evaporation scheme was modified to better describe the evaporation processes. Our results showed that the model significantly improved the runoff simulations.
Sebastian Müller, Lennart Schüler, Alraune Zech, and Falk Heße
Geosci. Model Dev., 15, 3161–3182, https://doi.org/10.5194/gmd-15-3161-2022, https://doi.org/10.5194/gmd-15-3161-2022, 2022
Short summary
Short summary
The GSTools package provides a Python-based platform for geoostatistical applications. Salient features of GSTools are its random field generation, its kriging capabilities and its versatile covariance model. It is furthermore integrated with other Python packages, like PyKrige, ogs5py or scikit-gstat, and provides interfaces to meshio and PyVista. Four presented workflows showcase the abilities of GSTools.
Ather Abbas, Laurie Boithias, Yakov Pachepsky, Kyunghyun Kim, Jong Ahn Chun, and Kyung Hwa Cho
Geosci. Model Dev., 15, 3021–3039, https://doi.org/10.5194/gmd-15-3021-2022, https://doi.org/10.5194/gmd-15-3021-2022, 2022
Short summary
Short summary
The field of artificial intelligence has shown promising results in a wide variety of fields including hydrological modeling. However, developing and testing hydrological models with artificial intelligence techniques require expertise from diverse fields. In this study, we developed an open-source framework based upon the python programming language to simplify the process of the development of hydrological models of time series data using machine learning.
Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe
Geosci. Model Dev., 15, 2917–2947, https://doi.org/10.5194/gmd-15-2917-2022, https://doi.org/10.5194/gmd-15-2917-2022, 2022
Short summary
Short summary
Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.
Marcela Silva, Ashley M. Matheny, Valentijn R. N. Pauwels, Dimetre Triadis, Justine E. Missik, Gil Bohrer, and Edoardo Daly
Geosci. Model Dev., 15, 2619–2634, https://doi.org/10.5194/gmd-15-2619-2022, https://doi.org/10.5194/gmd-15-2619-2022, 2022
Short summary
Short summary
Our study introduces FETCH3, a ready-to-use, open-access model that simulates the water fluxes across the soil, roots, and stem. To test the model capabilities, we tested it against exact solutions and a case study. The model presented considerably small errors when compared to the exact solutions and was able to correctly represent transpiration patterns when compared to experimental data. The results show that FETCH3 can correctly simulate above- and below-ground water transport.
Mayra Ishikawa, Wendy Gonzalez, Orides Golyjeswski, Gabriela Sales, J. Andreza Rigotti, Tobias Bleninger, Michael Mannich, and Andreas Lorke
Geosci. Model Dev., 15, 2197–2220, https://doi.org/10.5194/gmd-15-2197-2022, https://doi.org/10.5194/gmd-15-2197-2022, 2022
Short summary
Short summary
Reservoir hydrodynamics is often described in numerical models differing in dimensionality. 1D and 2D models assume homogeneity along the unresolved dimension. We compare the performance of models with 1 to 3 dimensions. All models presented reasonable results for seasonal temperature dynamics. Neglecting longitudinal transport resulted in the largest deviations in temperature. Flow velocity could only be reproduced by the 3D model. Results support the selection of models and their assessment.
Sandra Hellmers and Peter Fröhle
Geosci. Model Dev., 15, 1061–1077, https://doi.org/10.5194/gmd-15-1061-2022, https://doi.org/10.5194/gmd-15-1061-2022, 2022
Short summary
Short summary
A hydrological method to compute backwater effects in surface water streams and on adjacent lowlands caused by mostly complex flow control systems is presented. It enables transfer of discharges to water levels and calculation of backwater volume routing along streams and lowland areas by balancing water level slopes. The developed, implemented and evaluated method extends the application range of hydrological models significantly for flood-routing simulation in backwater-affected catchments.
Mathias Bavay, Michael Reisecker, Thomas Egger, and Daniela Korhammer
Geosci. Model Dev., 15, 365–378, https://doi.org/10.5194/gmd-15-365-2022, https://doi.org/10.5194/gmd-15-365-2022, 2022
Short summary
Short summary
Most users struggle with the configuration of numerical models. This can be improved by relying on a GUI, but this requires a significant investment and a specific skill set and does not fit with the daily duties of model developers, leading to major maintenance burdens. Inishell generates a GUI on the fly based on an XML description of the required configuration elements, making maintenance very simple. This concept has been shown to work very well in our context.
Vladimir Mirlas, Yaakov Anker, Asher Aizenkod, and Naftali Goldshleger
Geosci. Model Dev., 15, 129–143, https://doi.org/10.5194/gmd-15-129-2022, https://doi.org/10.5194/gmd-15-129-2022, 2022
Short summary
Short summary
Salinization owing to irrigation water quality causes soil degradation and soil fertility reduction that with poor drainage conditions impede plant development and manifest in economic damage. This study provided a soil salting process evaluation procedure through a combination of soil salinity monitoring, field experiments, remote sensing, and unsaturated soil profile saline water movement modeling. The modeling results validated the soil salinization danger from using brackish irrigation.
Cited articles
Allen, R. G., Pereira, L., Raes, D., and Smith, M.: Crop Evapotranspiration,
Food and Agriculture Organization of the United Nations, Rome, Italy, FAO
publication 56, 290 pp., ISBN 92-5-104219-5, 1998.
Anderson, E. A.: Snow accumulation and ablation model – SNOW-17, US National
Weather Service, Silver Spring, MD, 61, 2006.
Bartholmes, J. C., Thielen, J., Ramos, M. H., and Gentilini, S.: The european flood alert system EFAS – Part 2: Statistical skill assessment of probabilistic and deterministic operational forecasts, Hydrol. Earth Syst. Sci., 13, 141–153, https://doi.org/10.5194/hess-13-141-2009, 2009.
Beven, K.: A manifesto for the equifinality thesis, J. Hydrol., 320, 18–36,
https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Burek, P., Satoh, Y., Kahil, T., Tang, T., Greve, P., Smilovic, M., Guillaumot, L., Zhao, F., and Wada, Y.: Development of the Community Water Model (CWatM v1.04) – a high-resolution hydrological model for global and regional assessment of integrated water resources management, Geosci. Model Dev., 13, 3267–3298, https://doi.org/10.5194/gmd-13-3267-2020, 2020.
Chen, M., Li, Z., and Gao, S.: Multisensor Remote Sensing and the
Multidimensional Modeling of Extreme Flood Events, in: Remote Sensing of
Water-Related Hazards, edited by: Zhang, K., Hong, Y., and AghaKouchak, A., https://doi.org/10.1002/9781119159131.ch5, 2022.
Chow, V. T., Maidment, D. R., and Mays, L. W.: Applied Hydrology:
McGraw-Hill Series in Water Resources and Environmental Engineering,
McGraw-Hill, Inc., New York, 1988.
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta,
H. V., Wagener, T., and Hay, L. E.: Framework for Understanding Structural
Errors (FUSE): A modular framework to diagnose differences between
hydrological models, Water Resour. Res., 44, W00B02,
https://doi.org/10.1029/2007WR006735, 2008.
Clark, M. P., Fan, Y., Lawrence, D. M., Adam, J. C., Bolster, D., Gochis, D.
J., Hooper, R. P., Kumar, M., Leung, L. R., Mackay, D. S., Maxwell, R. M.,
Shen, C., Swenson, S. C., and Zeng, X.: Improving the representation of
hydrologic processes in Earth System Models, Water Resour. Res., 51, 5929–5956, https://doi.org/10.1002/2015WR017096, 2015a.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski D., Rupp, D. E.,
Woods, R. A., Freeer, J. E., Gutmann, E. D., Wood, A. W., Gochis, D. J.,
Rasmussen, R. M., Tarboton, D. G., Mahat, V., Flerchinger G. N., and Marks,
D. G.: A unified approach for process-based hydrologic modeling: 1. Modeling
concept, Water Resour. Res., 51, 2498–2514,
https://doi.org/10.1002/2015WR017198, 2015b.
Clark, M. P., Vogel, R. M., Lamontagne, J. R., Mizukami, N., Knoben, W. J.
M., Tang, G., Shervan, G., Freer J. E., Whitfield, P. H., Shook, K. R., and
Papalexiou, S. M.: The abuse of popular performance metrics in hydrologic
modeling, Water Resour. Res., 57, e2020WR029001, https://doi.org/10.1029/2020WR029001, 2021.
Cloke, E. and Pappenberger, F.: Ensemble flood forecasting: A review, J.
Hydrol., 375, 613–626, https://doi.org/10.1016/j.jhydrol.2009.06.005, 2009.
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor,
G. H., Curtis, J., and Pasteris, P. A.: Physiographically-sensitive mapping
of temperature and precipitation across the conterminous United States, Int.
J. Climatol., 28, 2031–2064, 2008.
David, C. H., Maidment, D. R., Niu, G., Yang, Z., Habets, F., and Eijkhout,
V.: River Network Routing on the NHDPlus Dataset, J. Hydrometeorol., 12,
913–934, 2011.
de Almeida, G. A. M. and Bates, P.: Applicability of the local inertial
approximation of the shallow water equations to flood modeling, Water
Resour. Res., 49, 4833–4844, https://doi.org/10.1002/wrcr.20366, 2013.
Döll, P., Kaspar, F., and Lehner, B.: A global hydrological model for
deriving water availability indicators: model tuning and validation, J.
Hydrol., 270, 105–134, https://doi.org/10.1016/S0022-1694(02)00283-4, 2003.
Fenicia, F., Kavetski, D., and Savenije, H. H. G.: Elements of a flexible
approach for conceptual hydrological modeling: 1. Motivation and theoretical
development, Water Resour. Res., 47, W11510,
https://doi.org/10.1029/2010WR010174, 2011.
Flamig, Z. L., Vergara, H., and Gourley, J. J.: The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case study, Geosci. Model Dev., 13, 4943–4958, https://doi.org/10.5194/gmd-13-4943-2020, 2020.
Franz, K. J., Hogue, T. S., and Sorooshian, S.: Operational snow modeling:
Addressing the challenges of an energy balance model for National Weather
Service forecasts, J. Hydrol., 360, 48–66, 2008.
Freeze, R. A.: Role of subsurface flow in generating surface runoff: 2.
Upstream source areas, Water Resour. Res., 8, 1272–1283,
https://doi.org/10.1029/WR008i005p01272, 1972.
Gao, S., Chen, M., Li, Z., Cook, S., Allen, D., Neeson, T., Yang, T., Yami,
T., and Hong, Y.: Mapping dynamic non-perennial stream networks using
high-resolution distributed hydrologic simulation: A case study in the upper
blue river basin, J. Hydrol., 600, 126522, https://doi.org/10.1016/j.jhydrol.2021.126522, 2021.
Gharari, S., Clark, M. P., Mizukami, N., Knoben, W. J. M., Wong, J. S., and Pietroniro, A.: Flexible vector-based spatial configurations in land models, Hydrol. Earth Syst. Sci., 24, 5953–5971, https://doi.org/10.5194/hess-24-5953-2020, 2020.
Gharari, S., Vanderkelen, I., Tefs, A., Mizukami, N., Stadnyk, T. A.,
Lawrence, D., and Clark, M. P.: A Flexible Multi-Scale Framework to Simulate
Lakes and Reservoirs in Earth System Models, Earth and Space Science Open
Archive, https://doi.org/10.1002/essoar.10510902.1, 2022.
Gourley, J. J., Flamig, Z. L., Vergara, H., Kirstetter, P., Clark, R. A.,
III, Argyle, E., Arthur, A., Martinaitis, S., Terti, G., Erlingis, J. M.,
Hong, Y., and Howard, K. W.: The FLASH Project: Improving the Tools for
Flash Flood Monitoring and Prediction across the United States, B. Am.
Meteorol. Soc., 98, 361–372, https://doi.org/10.1175/BAMS-D-15-00247.1, 2017.
Hanasaki, N, Kanae, S., and Oki, T.: A reservoir operation scheme for global
river routing models, J. Hydrol., 327, 22–41, 2006.
Horton, P., Schaefli, B., and Kauzlaric, M.: Why do we have so many
different hydrological models? A review based on the case of Switzerland,
Wiley Interdiscip. Rev., Water, e1574, https://doi.org/10.1002/wat2.1574, 2021.
Knoben, W. J. M., Freer, J. E., Peel, M. C., Fowler, K. J. A., and Woods, R.
A.: A brief analysis of conceptual model structure uncertainty using 36
models and 559 catchments, Water Resour. Res., 56, e2019WR025975, https://doi.org/10.1029/2019WR025975, 2020.
Knoben, W. J. M., Clark, M., Bates, J., Bennet, A., Gharari, S., Marsh, C.,
Nijssen, B., Pietroniro, A., Spiteri, R., Tarboton, D. J., and Wood, A. J.:
Community Workflows to Advance Reproducibility in Hydrologic Modeling:
Separating model-agnostic and model-specific configuration steps in
applications of large-domain hydrologic models, Earth and Space Science Open
Archive, https://doi.org/10.1002/essoar.10509195.1, 2021.
Lehner, B. and Grill, G.: Global river hydrography and network routing:
baseline data and new approaches to study the world's large river systems,
Hydrol. Process., 27, 2171–2186, https://doi.org/10.1002/hyp.9740, 2013.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B.,
Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson,
C., Robertson, J. C., Rödel, R., Sindorf, N., and Wisser, D.:
High-resolution mapping of the world's reservoirs and dams for sustainable
river-flow management, Front. Ecol. Environ., 9, 494–502, https://doi.org/10.1890/100125, 2011.
Li, Z.: CREST-VEC: A framework towards more accurate and realistic flood
simulation across scales (v1.0), Zenodo [code], https://doi.org/10.5281/zenodo.6305817, 2022.
Li, Z., Chen, M., Gao, S., Hong, Z., Tang, G., Wen, Y., Gourley, J. J., and
Hong, Y.: Cross-examination of similarity, difference and deficiency of
gauge, radar and satellite precipitation measuring uncertainties for extreme
events using conventional metrics and multiplicative triple collocation,
Remote Sens., 12, 1258, https://doi.org/10.3390/rs12081258, 2020.
Li, Z., Chen, M., Gao, S., Luo, X., Gourley, J. J., Kirstetter, P., Yang,
T., Kolar, R., McGovern, A., Wen, Y., Rao, B., Yami, T., and Hong, Y.:
CREST-iMAP v1. 0: A fully coupled hydrologic-hydraulic modeling framework
dedicated to flood inundation mapping and prediction, Environ. Model. Softw.,
141, 105051, https://doi.org/10.1016/j.envsoft.2021.105051, 2021.
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.
Lighthill, M. J. and Whitham, G. B.: On kinematic waves I. Flood movement in
long rivers, Proc. R. Soc. Lond., 229, A229281–316, https://doi.org/10.1098/rspa.1955.0088, 1955.
Lin, P., Rajib, M. A., Yang, Z., Somos-Valenzuela, M., Merwade, V.,
Maidment, D. R., Wang, Y., and Chen, L.: Spatiotemporal Evaluation of
Simulated Evapotranspiration and Streamflo over Texas Using the
WRF-Hydro-RAPID Modeling Framework, J. Am. Water Resour. Assoc., 54,
40–54, https://doi.org/10.1111/1752-1688.12585, 2018.
Lin, P., Pan, M., Beck, H. E., Yang, Y., Yamazaki, D., Frasson, R., David,
C. G., Durand, M., Pavelsky, T. M., Allen, G. H., Gleason, C. J., and Wood,
E. F.: Global reconstruction of naturalized river flows at 2.94 million
reaches, Water Resour. Res., 55, 6499–6516, https://doi.org/10.1029/2019WR025287, 2019.
Lin, P., Pan, M., Wood, E.F. Yamazaki, D., and Allen, G. H.: A new vector-based
global river network dataset accounting for variable drainage density, Sci
Data, 8, 28, https://doi.org/10.1038/s41597-021-00819-9, 2021.
Liston, G. E., Sud, Y. C., and Wood, E. F.: Evaluating GCM land surface
hydrology parameterizations by computing river discharges using a runoff
routing model, J. Appl. Met., 33, 394–405, 1994.
Lohman, D., Nolte-holube, R., and Raschke, E.: A large-scale horizontal
routing model to be coupled to land surface parametrization schemes, Tellus
A, 48, 708–721, https://doi.org/10.1034/j.1600-0870.1996.t01-3-00009.x, 1996.
Martinaitis, S. M., Gourley, J. J., Flamig, Z. L., Argyle, E. M., Clark, R.
A., III, Arthur, A., Smith, B. R., Erlingis, J. M., Perfater, S., and
Albright, B.: The HMT Multi-Radar Multi-Sensor Hydro Experiment, B. Am.
Meterorol. Soc., 98, 347–359, 2017.
Messager, M. L., Lehner, B., Grill, G., Nedeva, I., and Schmitt, O.:
Estimating the volume and age of water stored in global lakes using a
geo-statistical approach, Nat. Comm., 13603,
https://doi.org/10.1038/ncomms13603, 2016.
Mizukami, N., Clark, M. P., Sampson, K., Nijssen, B., Mao, Y., McMillan, H., Viger, R. J., Markstrom, S. L., Hay, L. E., Woods, R., Arnold, J. R., and Brekke, L. D.: mizuRoute version 1: a river network routing tool for a continental domain water resources applications, Geosci. Model Dev., 9, 2223–2238, https://doi.org/10.5194/gmd-9-2223-2016, 2016.
Mizukami, N., Clark, M. P., Newman, A. J., Wood, A. W., Gutmann, E. D.,
Nijssen, B., Rakovec, O., and Samaniego, L.: Towards seamless large-domain
parameter estimation for hydrologic models, Water Resour. Res., 53, 8020–8040, https://doi.org/10.1002/2017WR020401, 2017.
Mizukami, N., Clark, M. P., Gharari, S., Kluzek, E., Pan, M., Lin, P., Beck,
H. E., and Yamazaki, D.: A vector-based river routing model for Earth System
Models: Parallelization and global applications, J. Adv. Model. Earth Sy.,
13, e2020MS002434, https://doi.org/10.1029/2020MS002434, 2021.
Newman, A. J., Clark, M. P., Sampson, K., Wood, A., Hay, L. E., Bock, A., Viger, R. J., Blodgett, D., Brekke, L., Arnold, J. R., Hopson, T., and Duan, Q.: Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance, Hydrol. Earth Syst. Sci., 19, 209–223, https://doi.org/10.5194/hess-19-209-2015, 2015.
NOAA National Centers for Environmental Information (NCEI): U.S.
Billion-Dollar Weather and Climate Disasters,
https://doi.org/10.25921/stkw-7w73, 2022.
Ohmura, A.: Physical basis for the temperature-based melt-index method, J.
Appl. Meteorol., 40, 753–761, 2001.
Paiva, R. C. D., Collischonn, W., and Tucci, C. E. M.: Large scale hydrologic
and hydrodynamic modeling using limited data and a GIS based approach, J.
Hydrol., 406, 170–181, https://doi.org/10.1016/j.jhydrol.2011.06.007,
2011.
Ponce, V. M., Li, R.-M., and Simons, D. B.: Applicability of kinematic and
diffusion models, J. Hydraul. Div., 104, 353–360, 1978.
PRISM Climate Group, Oregon State University, https://prism.oregonstate.edu
(last access: 16 September 2020), 2014.
Quinn, P., Beven, K., Chevallier, P., and Planchon, O.: The prediction of
hillslope flow paths for distributed hydrological modelling using digital
terrain models, Hydrol. Process., 5, 59–79, https://doi.org/10.1002/hyp.3360050106, 1991.
Salas, F. R., Somos-Valenzuela, Marcelo A., Dugger, A., Maidment, D. R.,
Gochis, D. J., David, C. H., Yu, W., Ding, D., Clark, E. P., and Noman, N.:
Towards Real-Time Continental Scale Streamflow Simulation in Continuous and
Discrete Space, J. Am. Water Resour. Assoc. 54, 7–27, https://doi.org/10.1111/1752-1688.12586, 2018.
Savenije, H. H. G.: HESS Opinions “The art of hydrology”, Hydrol. Earth Syst. Sci., 13, 157–161, https://doi.org/10.5194/hess-13-157-2009, 2009.
Shaad, K.: Evolution of river-routing schemes in macro-scale models and their
potentials for watershed management, Hydrol. Sci. J., 63, 1062–1077,
https://doi.org/10.1080/02626667.2018.1473871, 2018.
Shen, X., Hong, Y., Zhang, K., and Hao, Z.: Refining a distributed linear
reservoir routing method to improve performance of the CREST model, J.
Hydrol. Eng., 22, 04016061, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001442, 2017.
Solvik, K., Bartuszevige, A. M., Bogaerts, M., and Joseph, M. B.: Predicting
playa inundation using a long short-term memory neural network, Water
Resour. Res., 57, e2020WR029009, https://doi.org/10.1029/2020WR029009, 2021.
Tang, G., Zeng, Z., Long, D., Guo, X., Yong, B., Zhang, W., and Hong, Y.:
Statistical and Hydrological Comparisons between TRMM and GPM Level-3
Products over a Midlatitude Basin: Is Day-1 IMERG a Good Successor for TMPA
3B42V7?, J. Hydrometeorol., 17, 121–137, 2016.
Tarboton, D. G.: A new method for the determination of flow directions and
upslope areas in grid digital elevation models, Water Resour. Res., 33,
309–319, https://doi.org/10.1029/96WR03137, 1997.
Tavakoly, A. A., Gutenson, J. L., Lewis, J. W., Follum, M. L., Rajib, A.,
LaHatte, W. C., and Hamilton, C. O.: Direct integration of numerous dams and
reservoirs outflow in continental scale hydrologic modeling, Water Resour.
Res., 57, e2020WR029544, https://doi.org/10.1029/2020WR029544,
2021.
Tellman, B., Sullivan, J. A., Kuhn, C. Kettner, A. J., Doyle, C. S.,
Brakenridge, G. R., Erickson, T. A., and Slayback, D. A.: Satellite imaging
reveals increased proportion of population exposed to floods, Nature, 596,
80–86, https://doi.org/10.1038/s41586-021-03695-w, 2021.
Tijerina, D., Condon, L., FitzGerald, K., Dugger, A., O'Neill, M. M.,
Sampson, K., Gochis, D., and Maxwell, R.: Continental hydrologic intercomparison
project, phase 1: A large-scale hydrologic model comparison over the
continental United States, Water Resour. Res., 57, e2020WR028931, https://doi.org/10.1029/2020WR028931, 2021.
Tokuda, D., Kim, H., Yamazaki, D., and Oki, T.: Development of a coupled simulation framework representing the lake and river continuum of mass and energy (TCHOIR v1.0), Geosci. Model Dev., 14, 5669–5693, https://doi.org/10.5194/gmd-14-5669-2021, 2021.
Vanderkelen, I., Gharari, S., Mizukami, N., Clark, M. P., Lawrence, D. M., Swenson, S., Pokhrel, Y., Hanasaki, N., van Griensven, A., and Thiery, W.: Evaluating a reservoir parametrization in the vector-based global routing model mizuRoute (v2.0.1) for Earth system model coupling, Geosci. Model Dev., 15, 4163–4192, https://doi.org/10.5194/gmd-15-4163-2022, 2022.
Vergara, H., Kirstetter, P., Gourley, J. J., Flamig, Z. L., Hong, Y., Arthur,
A., and Kolar, R.: Estimating a-priori kinematic wave model parameters based
on regionalization for flash flood forecasting in the Conterminous United
States, J. Hydrol., 541, 421–433, https://doi.org/10.1016/j.jhydrol.2016.06.011, 2016.
Vrugt, J. A., ter Braak, C., Diks, C., Robinson, B. A., Hyman, J. M., and
Higdon, D.: Accelerating Markov Chain Monte Carlo Simulation by Differential
Evolution with Self-Adaptive Randomized Subspace Sampling, Int. J. Nonlinear
Sci. Numer. Simul., 10, 273–290,
https://doi.org/10.1515/ijnsns.2009.10.3.273, 2009.
Wang, J., Hong, Y., Li, L., Gourley, J. J., Khan, S. I., Yilmaz, K. K., Adler,
R. F., Policelli, F. S., Habib, S., Irwn, D., Limaye, A. S., Korme, T., and
Okello, L.: The coupled routing and excess storage (CREST) distributed
hydrological model, Hydrol. Sci. J., 56, 84–98, 2011.
Wang, X., White-Hull, C., Dyer, S., and Yang, Y.: GIS-ROUT: A River Model
for Watershed Planning, Environ. Plann. B, 27, 231–246,
https://doi.org/10.1068/b2624, 2000.
Xue, X., Hong, Y., Limaye, A. S., Gourley, J. J., Huffman, G. J., Khan, S.
I., Doriji, C., and Chen, S.: Statistical and hydrological evaluation of
TRMM-based Multi-satellite Precipitation Analysis over the Wangchu Basin of
Bhutan: Are the latest satellite precipitation products 3B42V7 ready for use
in ungauged basins?, J. Hydrol., 499, 91–99,
https://doi.org/10.1016/j.jhydrol.2013.06.042, 2013.
Yamazaki, D., Kanae, S., Kim, H., and Oki, T.: A physically based description of
floodplain inundation dynamics in a global river routing model, Water
Resour. Res., 47, 1–21, https://doi.org/10.1029/2010WR009726, 2011.
Yamazaki, D., Sato, T., Kanae, S., Hirabayashi, Y., and Bates, P. D.:
Regional flood dynamics in a bifurcating mega delta simulated in a global
river model, Geophys. Res. Lett., 41, 3127–3135,
https://doi.org/10.1002/2014GL059744, 2014.
Yamazaki, D., Ikeshima, D., Tawatari, R., Yamaguchi, T., O'Loughlin, F.,
Neal, J. C., Sampson, C. C., Kanae, S., and Bates, P. D.: A high-accuracy
map of global terrain elevations, Geophys. Res. Lett., 44, 5844–5853,
https://doi.org/10.1002/2017GL072874, 2017.
Yamazaki, D., Ikeshima, D., Sosa, J., Bates, P. D., Allen, G. H., and
Pavelsky, T. M.: MERIT Hydro: A High-Resolution Global Hydrography Map Based
on Latest Topography Dataset, Water Resour. Res., 55, 5053–5073,
https://doi.org/10.1029/2019WR024873, 2019.
Yang, T., Zhang, L., Kim, T., Hong, Y., Zhang, D., and Peng, Q.: A
large-scale comparison of Artificial Intelligence and Data Mining (AI&DM)
techniques in simulating reservoir releases over the Upper Colorado Region,
J. Hydrol., 602, 126723, https://doi.org/10.1016/j.jhydrol.2021.126723, 2021.
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, 2021.
Zhang, J., Howard, K., Langston, C., Kaney, B., Qi, Y., Tang, L., Grams, H., Wang, Y., Cocks, S., Martinaitis, S., Arthur, A., Cooper, K., Brogden, J., and Kitzmiller, D.: Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimation: Initial Operating Capabilities, B. Am. Meteorol. Soc., 97, 621–638, https://doi.org/10.1175/BAMS-D-14-00174.1, 2016.
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.
Operational streamflow prediction at a continental scale is critical for national water...
