Articles | Volume 26, issue 22
https://doi.org/10.5194/hess-26-5933-2022
© 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-26-5933-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2022
Research article |
| 25 Nov 2022
| 25 Nov 2022
Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data
Jingkai Xie
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Hongjie Yu
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Yan Huang
Changjiang Water Resources Commission of the Ministry of Water
Resources, Wuhan, 43000, China
Yuxue Guo
Institute of Hydrology and Water Resources, Zhejiang University,
Hangzhou, 310058, China
Related authors
Yuxue Guo, Xinting Yu, Yue-Ping Xu, Hao Chen, Haiting Gu, and Jingkai Xie
Hydrol. Earth Syst. Sci., 25, 5951–5979, https://doi.org/10.5194/hess-25-5951-2021, https://doi.org/10.5194/hess-25-5951-2021, 2021
Short summary
Short summary
We developed an AI-based management methodology to assess forecast quality and forecast-informed reservoir operation performance together due to uncertain inflow forecasts. Results showed that higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts. Moreover, the relationship between the forecast horizon and reservoir operation was complex and depended on operating configurations and performance measures.
Siwei Chen, Yuxue Guo, Yue-Ping Xu, and Lu Wang
Hydrol. Earth Syst. Sci., 28, 4989–5009, https://doi.org/10.5194/hess-28-4989-2024, https://doi.org/10.5194/hess-28-4989-2024, 2024
Short summary
Short summary
Our research explores how increased CO2 levels affect water use efficiency in the Yellow River basin. Using updated climate models, we found that future climate change significantly impacts water use efficiency, leading to improved plant resilience against moderate droughts. These findings help predict how ecosystems might adapt to environmental changes, providing essential insights into ways of managing water resources under varying climate conditions.
Xinting Yu, Yuxue Guo, Siwei Chen, Haiting Gu, and Yue-Ping Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2266, https://doi.org/10.5194/egusphere-2024-2266, 2024
Short summary
Short summary
This study introduces RDV-Copula, a new method to simplify complex vine copula structures by reducing dimensionality while retaining essential data. Applied to Shifeng Creek in China, RDV-Copula captured critical spatial-temporal relationships, demonstrating high synchronization probabilities and significant flood risks. Notably, it was found that increasing structure complexity does not always improve accuracy. This method offers an efficient tool for analyzing and simulating multisite flows.
Lu Wang, Yue-Ping Xu, Haiting Gu, Li Liu, Xiao Liang, and Siwei Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-226, https://doi.org/10.5194/hess-2024-226, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
To understand how eco-hydrological variables evolve jointly and why, this study develops a framework using correlation and causality to construct complex relationships between variables at the system level. Causality provides more detailed information that the compound causes of evolutions regarding any variable can be traced. Joint evolution is controlled by the combination of external drivers and direct causality. Overall, the study facilitates the comprehension of eco-hydrological processes.
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024, https://doi.org/10.5194/hess-28-1325-2024, 2024
Short summary
Short summary
Applying optimal water allocation models to simultaneously enable economic benefits, water preferences, and environmental demands at different decision levels, timescales, and regions is a challenge. In this study, a process-based three-layer synergistic optimal-allocation model (PTSOA) is established to achieve these goals. Reused, reclaimed water is also coupled to capture environmentally friendly solutions. Network analysis was introduced to reduce competition among different stakeholders.
Yuxue Guo, Xinting Yu, Yue-Ping Xu, Hao Chen, Haiting Gu, and Jingkai Xie
Hydrol. Earth Syst. Sci., 25, 5951–5979, https://doi.org/10.5194/hess-25-5951-2021, https://doi.org/10.5194/hess-25-5951-2021, 2021
Short summary
Short summary
We developed an AI-based management methodology to assess forecast quality and forecast-informed reservoir operation performance together due to uncertain inflow forecasts. Results showed that higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts. Moreover, the relationship between the forecast horizon and reservoir operation was complex and depended on operating configurations and performance measures.
Zhixu Bai, Yao Wu, Di Ma, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 25, 3675–3690, https://doi.org/10.5194/hess-25-3675-2021, https://doi.org/10.5194/hess-25-3675-2021, 2021
Short summary
Short summary
To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.
Chao Gao, Martijn J. Booij, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, https://doi.org/10.5194/hess-24-3251-2020, 2020
Short summary
Short summary
This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.
Li Liu, Yue Ping Xu, Su Li Pan, and Zhi Xu Bai
Hydrol. Earth Syst. Sci., 23, 3335–3352, https://doi.org/10.5194/hess-23-3335-2019, https://doi.org/10.5194/hess-23-3335-2019, 2019
Short summary
Short summary
The ensemble flood forecasting system can skillfully predict annual maximum floods with a lead time of more than 10 d and has skill in forecasting the snowmelt-related components about 7 d ahead. The accuracy of forecasts for the annual first floods is inferior, with a lead time of only 5 d. The snowmelt-induced surface runoff is the most poorly captured component by the system, and the well-predicted rainfall-related components are the major contributor to good performance.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Remote Sensing and GIS
Sediment transport in South Asian rivers high enough to impact satellite gravimetry
On the timescale of drought indices for monitoring streamflow drought considering catchment hydrological regimes
Pairing remote sensing and clustering in landscape hydrology for large-scale change identification: an application to the subarctic watershed of the George River (Nunavik, Canada)
Uncertainty assessment of satellite remote-sensing-based evapotranspiration estimates: a systematic review of methods and gaps
Predicting soil moisture conditions across a heterogeneous boreal catchment using terrain indices
A combined use of in situ and satellite-derived observations to characterize surface hydrology and its variability in the Congo River basin
Monitoring surface water dynamics in the Prairie Pothole Region of North Dakota using dual-polarised Sentinel-1 synthetic aperture radar (SAR) time series
Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions
Climatic and anthropogenic drivers of a drying Himalayan river
On the selection of precipitation products for the regionalisation of hydrological model parameters
Discharge of groundwater flow to Potter Cove on King George Island, Antarctic Peninsula
The value of ASCAT soil moisture and MODIS snow cover data for calibrating a conceptual hydrologic model
Systematic comparison of five machine-learning models in classification and interpolation of soil particle size fractions using different transformed data
Using hydrological and climatic catchment clusters to explore drivers of catchment behavior
Using MODIS estimates of fractional snow cover area to improve streamflow forecasts in interior Alaska
Informing a hydrological model of the Ogooué with multi-mission remote sensing data
Spatial characterization of long-term hydrological change in the Arkavathy watershed adjacent to Bangalore, India
Spatial pattern evaluation of a calibrated national hydrological model – a remote-sensing-based diagnostic approach
A method to employ the spatial organization of catchments into semi-distributed rainfall–runoff models
Multi-source hydrological soil moisture state estimation using data fusion optimisation
Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile
Daily Landsat-scale evapotranspiration estimation over a forested landscape in North Carolina, USA, using multi-satellite data fusion
Using object-based geomorphometry for hydro-geomorphological analysis in a Mediterranean research catchment
Comparing the Normalized Difference Infrared Index (NDII) with root zone storage in a lumped conceptual model
Case-based knowledge formalization and reasoning method for digital terrain analysis – application to extracting drainage networks
Improved large-scale hydrological modelling through the assimilation of streamflow and downscaled satellite soil moisture observations
Vegetative impacts upon bedload transport capacity and channel stability for differing alluvial planforms in the Yellow River source zone
Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations
Multidecadal change in streamflow associated with anthropogenic disturbances in the tropical Andes
Integration of 2-D hydraulic model and high-resolution lidar-derived DEM for floodplain flow modeling
Relating seasonal dynamics of enhanced vegetation index to the recycling of water in two endorheic river basins in north-west China
Urbanization dramatically altered the water balances of a paddy field-dominated basin in southern China
GRACE storage-runoff hystereses reveal the dynamics of regional watersheds
Impacts of high inter-annual variability of rainfall on a century of extreme hydrologic regime of northwest Australia
Identification of catchment functional units by time series of thermal remote sensing images
Flow regime change in an endorheic basin in southern Ethiopia
Evaluating digital terrain indices for soil wetness mapping – a Swedish case study
The suitability of remotely sensed soil moisture for improving operational flood forecasting
Modelling stream flow and quantifying blue water using a modified STREAM model for a heterogeneous, highly utilized and data-scarce river basin in Africa
Operational reservoir inflow forecasting with radar altimetry: the Zambezi case study
Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances
Assessment of waterlogging in agricultural megaprojects in the closed drainage basins of the Western Desert of Egypt
Estimating water discharge from large radar altimetry datasets
Estimation of antecedent wetness conditions for flood modelling in northern Morocco
MODIS snow cover mapping accuracy in a small mountain catchment – comparison between open and forest sites
The AACES field experiments: SMOS calibration and validation across the Murrumbidgee River catchment
A soil moisture and temperature network for SMOS validation in Western Denmark
Classification and flow prediction in a data-scarce watershed of the equatorial Nile region
On the use of AMSU-based products for the description of soil water content at basin scale
Estimating flooded area and mean water level using active and passive microwaves: the example of Paraná River Delta floodplain
Alexandra Klemme, Thorsten Warneke, Heinrich Bovensmann, Matthias Weigelt, Jürgen Müller, Tim Rixen, Justus Notholt, and Claus Lämmerzahl
Hydrol. Earth Syst. Sci., 28, 1527–1538, https://doi.org/10.5194/hess-28-1527-2024, https://doi.org/10.5194/hess-28-1527-2024, 2024
Short summary
Short summary
Satellite data help estimate groundwater depletion, but earlier assessments missed mass loss from river sediment. In the Ganges–Brahmaputra–Meghna (GBM) river system, sediment accounts for 4 % of the depletion. Correcting for sediment in the GBM mountains reduces estimated depletion by 14 %. It's important to note that the Himalayas' uplift may offset some sediment-induced mass loss. This understanding is vital for accurate water storage trend assessments and sustainable groundwater management.
Oscar M. Baez-Villanueva, Mauricio Zambrano-Bigiarini, Diego G. Miralles, Hylke E. Beck, Jonatan F. Siegmund, Camila Alvarez-Garreton, Koen Verbist, René Garreaud, Juan Pablo Boisier, and Mauricio Galleguillos
Hydrol. Earth Syst. Sci., 28, 1415–1439, https://doi.org/10.5194/hess-28-1415-2024, https://doi.org/10.5194/hess-28-1415-2024, 2024
Short summary
Short summary
Various drought indices exist, but there is no consensus on which index to use to assess streamflow droughts. This study addresses meteorological, soil moisture, and snow indices along with their temporal scales to assess streamflow drought across hydrologically diverse catchments. Using data from 100 Chilean catchments, findings suggest that there is not a single drought index that can be used for all catchments and that snow-influenced areas require drought indices with larger temporal scales.
Eliot Sicaud, Daniel Fortier, Jean-Pierre Dedieu, and Jan Franssen
Hydrol. Earth Syst. Sci., 28, 65–86, https://doi.org/10.5194/hess-28-65-2024, https://doi.org/10.5194/hess-28-65-2024, 2024
Short summary
Short summary
For vast northern watersheds, hydrological data are often sparse and incomplete. Our study used remote sensing and clustering to produce classifications of the George River watershed (GRW). Results show two types of subwatersheds with different hydrological behaviors. The GRW experienced a homogenization of subwatershed types likely due to an increase in vegetation productivity, which could explain the measured decline of 1 % (~0.16 km3 y−1) in the George River’s discharge since the mid-1970s.
Bich Ngoc Tran, Johannes van der Kwast, Solomon Seyoum, Remko Uijlenhoet, Graham Jewitt, and Marloes Mul
Hydrol. Earth Syst. Sci., 27, 4505–4528, https://doi.org/10.5194/hess-27-4505-2023, https://doi.org/10.5194/hess-27-4505-2023, 2023
Short summary
Short summary
Satellite data are increasingly used to estimate evapotranspiration (ET) or the amount of water moving from plants, soils, and water bodies into the atmosphere over large areas. Uncertainties from various sources affect the accuracy of these calculations. This study reviews the methods to assess the uncertainties of such ET estimations. It provides specific recommendations for a comprehensive assessment that assists in the potential uses of these data for research, monitoring, and management.
Johannes Larson, William Lidberg, Anneli M. Ågren, and Hjalmar Laudon
Hydrol. Earth Syst. Sci., 26, 4837–4851, https://doi.org/10.5194/hess-26-4837-2022, https://doi.org/10.5194/hess-26-4837-2022, 2022
Short summary
Short summary
Terrain indices constitute a good candidate for modelling the spatial variation of soil moisture conditions in many landscapes. In this study, we evaluate nine terrain indices on varying DEM resolution and user-defined thresholds with validation using an extensive field soil moisture class inventory. We demonstrate the importance of field validation for selecting the appropriate DEM resolution and user-defined thresholds and that failing to do so can result in ambiguous and incorrect results.
Benjamin Kitambo, Fabrice Papa, Adrien Paris, Raphael M. Tshimanga, Stephane Calmant, Ayan Santos Fleischmann, Frederic Frappart, Melanie Becker, Mohammad J. Tourian, Catherine Prigent, and Johary Andriambeloson
Hydrol. Earth Syst. Sci., 26, 1857–1882, https://doi.org/10.5194/hess-26-1857-2022, https://doi.org/10.5194/hess-26-1857-2022, 2022
Short summary
Short summary
This study presents a better characterization of surface hydrology variability in the Congo River basin, the second largest river system in the world. We jointly use a large record of in situ and satellite-derived observations to monitor the spatial distribution and different timings of the Congo River basin's annual flood dynamic, including its peculiar bimodal pattern.
Stefan Schlaffer, Marco Chini, Wouter Dorigo, and Simon Plank
Hydrol. Earth Syst. Sci., 26, 841–860, https://doi.org/10.5194/hess-26-841-2022, https://doi.org/10.5194/hess-26-841-2022, 2022
Short summary
Short summary
Prairie wetlands are important for biodiversity and water availability. Knowledge about their variability and spatial distribution is of great use in conservation and water resources management. In this study, we propose a novel approach for the classification of small water bodies from satellite radar images and apply it to our study area over 6 years. The retrieved dynamics show the different responses of small and large wetlands to dry and wet periods.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
Short summary
Short summary
This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Gopal Penny, Zubair A. Dar, and Marc F. Müller
Hydrol. Earth Syst. Sci., 26, 375–395, https://doi.org/10.5194/hess-26-375-2022, https://doi.org/10.5194/hess-26-375-2022, 2022
Short summary
Short summary
We develop an empirical approach to attribute declining streamflow in the Upper Jhelum watershed, a key subwatershed of the transboundary Indus basin. We find that a loss of streamflow since the year 2000 resulted primarily due to interactions among vegetation and groundwater in response to climate rather than local changes in land use, revealing the climate sensitivity of this Himalayan watershed.
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.
Ulrike Falk and Adrián Silva-Busso
Hydrol. Earth Syst. Sci., 25, 3227–3244, https://doi.org/10.5194/hess-25-3227-2021, https://doi.org/10.5194/hess-25-3227-2021, 2021
Short summary
Short summary
This paper focuses on the groundwater flow aspects of a small hydrological catchment at the northern tip of the Antarctic Peninsula. This region has experienced drastic climatological changes in the recent past. The basin is representative for the rugged coastline of the peninsula. It is discussed as a case study for possible future evolution of similar basins further south. Results include a quantitative analysis of glacial and groundwater contribution to total discharge into coastal waters.
Rui Tong, Juraj Parajka, Andreas Salentinig, Isabella Pfeil, Jürgen Komma, Borbála Széles, Martin Kubáň, Peter Valent, Mariette Vreugdenhil, Wolfgang Wagner, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 1389–1410, https://doi.org/10.5194/hess-25-1389-2021, https://doi.org/10.5194/hess-25-1389-2021, 2021
Short summary
Short summary
We used a new and experimental version of the Advanced Scatterometer (ASCAT) soil water index data set and Moderate Resolution Imaging Spectroradiometer (MODIS) C6 snow cover products for multiple objective calibrations of the TUWmodel in 213 catchments of Austria. Combined calibration to runoff, satellite soil moisture, and snow cover improves runoff (40 % catchments), soil moisture (80 % catchments), and snow (~ 100 % catchments) simulation compared to traditional calibration to runoff only.
Mo Zhang, Wenjiao Shi, and Ziwei Xu
Hydrol. Earth Syst. Sci., 24, 2505–2526, https://doi.org/10.5194/hess-24-2505-2020, https://doi.org/10.5194/hess-24-2505-2020, 2020
Short summary
Short summary
We systematically compared 45 models for direct and indirect soil texture classification and soil particle size fraction interpolation based on 5 machine-learning models and 3 log-ratio transformation methods. Random forest showed powerful performance in both classification of imbalanced data and regression assessment. Extreme gradient boosting is more meaningful and computationally efficient when dealing with large data sets. The indirect classification and log-ratio methods are recommended.
Florian U. Jehn, Konrad Bestian, Lutz Breuer, Philipp Kraft, and Tobias Houska
Hydrol. Earth Syst. Sci., 24, 1081–1100, https://doi.org/10.5194/hess-24-1081-2020, https://doi.org/10.5194/hess-24-1081-2020, 2020
Short summary
Short summary
We grouped 643 rivers from the United States into 10 behavioral groups based on their hydrological behavior (e.g., how much water they transport overall). Those groups are aligned with the ecoregions in the United States. Depending on the groups’ location and other characteristics, either snow, aridity or seasonality is most important for the behavior of the rivers in a group. We also find that very similar river behavior can be found in rivers far apart and with different characteristics.
Katrina E. Bennett, Jessica E. Cherry, Ben Balk, and Scott Lindsey
Hydrol. Earth Syst. Sci., 23, 2439–2459, https://doi.org/10.5194/hess-23-2439-2019, https://doi.org/10.5194/hess-23-2439-2019, 2019
Short summary
Short summary
Remotely sensed snow observations may improve operational streamflow forecasting in remote regions, such as Alaska. In this study, we insert remotely sensed observations of snow extent into the operational framework employed by the US National Weather Service’s Alaska Pacific River Forecast Center. Our work indicates that the snow observations can improve snow estimates and streamflow forecasting. This work provides direction for forecasters to implement remote sensing in their operations.
Cecile M. M. Kittel, Karina Nielsen, Christian Tøttrup, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 22, 1453–1472, https://doi.org/10.5194/hess-22-1453-2018, https://doi.org/10.5194/hess-22-1453-2018, 2018
Short summary
Short summary
In this study, we integrate free, global Earth observations in a user-friendly and flexible model to reliably characterize an otherwise unmonitored river basin. The proposed model is the best baseline characterization of the Ogooué basin in light of available observations. Furthermore, the study shows the potential of using new, publicly available Earth observations and a suitable model structure to obtain new information in poorly monitored or remote areas and to support user requirements.
Gopal Penny, Veena Srinivasan, Iryna Dronova, Sharachchandra Lele, and Sally Thompson
Hydrol. Earth Syst. Sci., 22, 595–610, https://doi.org/10.5194/hess-22-595-2018, https://doi.org/10.5194/hess-22-595-2018, 2018
Short summary
Short summary
Water resources in the Arkavathy watershed in southern India are changing due to human modification of the landscape, including changing agricultural practices and urbanization. We analyze surface water resources in man-made lakes in satellite imagery over a period of 4 decades and find drying in the northern part of the watershed (characterized by heavy agriculture) and wetting downstream of urban areas. Drying in the watershed is associated with groundwater-irrigated agriculture.
Gorka Mendiguren, Julian Koch, and Simon Stisen
Hydrol. Earth Syst. Sci., 21, 5987–6005, https://doi.org/10.5194/hess-21-5987-2017, https://doi.org/10.5194/hess-21-5987-2017, 2017
Short summary
Short summary
The present study is focused on the spatial pattern evaluation of two models and describes the similarities and dissimilarities. It also discusses the factors that generate these patterns and proposes similar new approaches to minimize the differences. The study points towards a new approach in which the spatial component of the hydrological model is also calibrated and taken into account.
Henning Oppel and Andreas Schumann
Hydrol. Earth Syst. Sci., 21, 4259–4282, https://doi.org/10.5194/hess-21-4259-2017, https://doi.org/10.5194/hess-21-4259-2017, 2017
Short summary
Short summary
How can we evaluate the heterogeneity of natural watersheds and how can we assess its spatial organization? How can we make use of this information for hydrological models and is it beneficial to our models? We propose a method display and assess the interaction of catchment characteristics with the flow path which we defined as the ordering scheme within a basin. A newly implemented algorithm brings this information to the set-up of a model and our results show an increase in model performance.
Lu Zhuo and Dawei Han
Hydrol. Earth Syst. Sci., 21, 3267–3285, https://doi.org/10.5194/hess-21-3267-2017, https://doi.org/10.5194/hess-21-3267-2017, 2017
Short summary
Short summary
Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from remote sensing and land surface modelling. The result shows a significant improvement of the soil moisture state accuracy; the method can be easily applied in other catchments.
Mauricio Zambrano-Bigiarini, Alexandra Nauditt, Christian Birkel, Koen Verbist, and Lars Ribbe
Hydrol. Earth Syst. Sci., 21, 1295–1320, https://doi.org/10.5194/hess-21-1295-2017, https://doi.org/10.5194/hess-21-1295-2017, 2017
Short summary
Short summary
This work exhaustively evaluates – for the first time – the suitability of seven state-of-the-art satellite-based rainfall estimates (SREs) over the complex topography and diverse climatic gradients of Chile.
Several indices of performance are used for different timescales and elevation zones. Our analysis reveals what SREs are in closer agreement to ground-based observations and what indices allow for understanding mismatches in shape, magnitude, variability and intensity of precipitation.
Yun Yang, Martha C. Anderson, Feng Gao, Christopher R. Hain, Kathryn A. Semmens, William P. Kustas, Asko Noormets, Randolph H. Wynne, Valerie A. Thomas, and Ge Sun
Hydrol. Earth Syst. Sci., 21, 1017–1037, https://doi.org/10.5194/hess-21-1017-2017, https://doi.org/10.5194/hess-21-1017-2017, 2017
Short summary
Short summary
This work explores the utility of a thermal remote sensing based MODIS/Landsat ET data fusion procedure over a mixed forested/agricultural landscape in North Carolina, USA. The daily ET retrieved at 30 m resolution agreed well with measured fluxes in a clear-cut and a mature pine stand. An accounting of consumptive water use by land cover classes is presented, as well as relative partitioning of ET between evaporation (E) and transpiration (T) components.
Domenico Guida, Albina Cuomo, and Vincenzo Palmieri
Hydrol. Earth Syst. Sci., 20, 3493–3509, https://doi.org/10.5194/hess-20-3493-2016, https://doi.org/10.5194/hess-20-3493-2016, 2016
Short summary
Short summary
The authors apply an object-based geomorphometric procedure to define the runoff contribution areas. The results enabled us to identify the contribution area related to the different runoff components activated during the storm events through an advanced hydro-chemical analysis. This kind of approach could be useful applied to similar, rainfall-dominated, forested and no-karst Mediterranean catchments.
Nutchanart Sriwongsitanon, Hongkai Gao, Hubert H. G. Savenije, Ekkarin Maekan, Sirikanya Saengsawang, and Sansarith Thianpopirug
Hydrol. Earth Syst. Sci., 20, 3361–3377, https://doi.org/10.5194/hess-20-3361-2016, https://doi.org/10.5194/hess-20-3361-2016, 2016
Short summary
Short summary
We demonstrated that the readily available NDII remote sensing product is a very useful proxy for moisture storage in the root zone of vegetation. We compared the temporal variation of the NDII with the root zone storage in a hydrological model of eight catchments in the Upper Ping River in Thailand, yielding very good results. Having a reliable NDII product that can help us to estimate the actual moisture storage in catchments is a major contribution to prediction in ungauged basins.
Cheng-Zhi Qin, Xue-Wei Wu, Jing-Chao Jiang, and A-Xing Zhu
Hydrol. Earth Syst. Sci., 20, 3379–3392, https://doi.org/10.5194/hess-20-3379-2016, https://doi.org/10.5194/hess-20-3379-2016, 2016
Short summary
Short summary
Application of digital terrain analysis (DTA), which is typically a modeling process involving workflow building, relies heavily on DTA domain knowledge. However, the DTA knowledge has not been formalized well to be available for inference in automatic tools. We propose a case-based methodology to solve this problem. This methodology can also be applied to other domains of geographical modeling with a similar situation.
Patricia López López, Niko Wanders, Jaap Schellekens, Luigi J. Renzullo, Edwin H. Sutanudjaja, and Marc F. P. Bierkens
Hydrol. Earth Syst. Sci., 20, 3059–3076, https://doi.org/10.5194/hess-20-3059-2016, https://doi.org/10.5194/hess-20-3059-2016, 2016
Short summary
Short summary
We perform a joint assimilation experiment of high-resolution satellite soil moisture and discharge observations in the Murrumbidgee River basin with a large-scale hydrological model. Additionally, we study the impact of high- and low-resolution meteorological forcing on the model performance. We show that the assimilation of high-resolution satellite soil moisture and discharge observations has a significant impact on discharge simulations and can bring them closer to locally calibrated models.
Zhi Wei Li, Guo An Yu, Gary Brierley, and Zhao Yin Wang
Hydrol. Earth Syst. Sci., 20, 3013–3025, https://doi.org/10.5194/hess-20-3013-2016, https://doi.org/10.5194/hess-20-3013-2016, 2016
Short summary
Short summary
Influence of vegetation upon bedload transport and channel morphodynamics is examined along a channel stability gradient ranging from meandering to anabranching to anabranching–braided to fully braided planform conditions along trunk and tributary reaches of the Yellow River source zone in western China. This innovative work reveals complex interactions between channel planform, bedload transport capacity, sediment supply in the flood season, and the hydraulic role of vegetation.
W. Qi, C. Zhang, G. Fu, C. Sweetapple, and H. Zhou
Hydrol. Earth Syst. Sci., 20, 903–920, https://doi.org/10.5194/hess-20-903-2016, https://doi.org/10.5194/hess-20-903-2016, 2016
Short summary
Short summary
Six precipitation products, including TRMM3B42, TRMM3B42RT, GLDAS/Noah, APHRODITE, PERSIANN, and GSMAP-MVK+, are investigated in the usually neglected area of NE China, and a framework is developed to quantify the contributions of uncertainties from precipitation products, hydrological models, and their interactions to uncertainty in simulated discharges. It is found that interactions between hydrological models and precipitation products contribute significantly to uncertainty in discharge.
A. Molina, V. Vanacker, E. Brisson, D. Mora, and V. Balthazar
Hydrol. Earth Syst. Sci., 19, 4201–4213, https://doi.org/10.5194/hess-19-4201-2015, https://doi.org/10.5194/hess-19-4201-2015, 2015
Short summary
Short summary
Andean catchments play a key role in the provision of freshwater resources. The development of megacities in the inter-Andean valleys raises severe concerns about growing water scarcity. This study is one of the first long-term (1970s-now) analyses of the role of land cover and climate change on provision and regulation of streamflow in the tropical Andes. Forest conversion had the largest impact on streamflow, leading to a 10 % net decrease in streamflow over the last 40 years.
D. Shen, J. Wang, X. Cheng, Y. Rui, and S. Ye
Hydrol. Earth Syst. Sci., 19, 3605–3616, https://doi.org/10.5194/hess-19-3605-2015, https://doi.org/10.5194/hess-19-3605-2015, 2015
M. A. Matin and C. P.-A. Bourque
Hydrol. Earth Syst. Sci., 19, 3387–3403, https://doi.org/10.5194/hess-19-3387-2015, https://doi.org/10.5194/hess-19-3387-2015, 2015
Short summary
Short summary
This paper describes a methodology in analysing the interdependencies between components of the hydrological cycle and vegetation characteristics at different elevation zones of two endorheic river basins in an arid-mountainous region of NW China. The analysis shows that oasis vegetation has an important function in sustaining the water cycle in the river basins and oasis vegetation is dependent on surface and shallow subsurface water flow from mountain sources.
L. Hao, G. Sun, Y. Liu, J. Wan, M. Qin, H. Qian, C. Liu, J. Zheng, R. John, P. Fan, and J. Chen
Hydrol. Earth Syst. Sci., 19, 3319–3331, https://doi.org/10.5194/hess-19-3319-2015, https://doi.org/10.5194/hess-19-3319-2015, 2015
Short summary
Short summary
The role of land cover in affecting hydrologic and environmental changes in the humid region in southern China is not well studied. We found that high flows and low flows increased and evapotranspiration decreased due to urbanization in the Qinhuai River basin. Urbanization masked climate warming effects in a rice-paddy-dominated watershed in altering long-term hydrology. Flooding risks and heat island effects are expected to rise due to urbanization.
E. A. Sproles, S. G. Leibowitz, J. T. Reager, P. J. Wigington Jr, J. S. Famiglietti, and S. D. Patil
Hydrol. Earth Syst. Sci., 19, 3253–3272, https://doi.org/10.5194/hess-19-3253-2015, https://doi.org/10.5194/hess-19-3253-2015, 2015
Short summary
Short summary
The paper demonstrates how data from the Gravity Recovery and Climate Experiment (GRACE) can be used to describe the relationship between water stored at the regional scale and stream flow. Additionally, we employ GRACE as a regional-scale indicator to successfully predict stream flow later in the water year. Our work focuses on the Columbia River Basin (North America), but is widely applicable across the globe, and could prove to be particularly useful in regions with limited hydrological data.
A. Rouillard, G. Skrzypek, S. Dogramaci, C. Turney, and P. F. Grierson
Hydrol. Earth Syst. Sci., 19, 2057–2078, https://doi.org/10.5194/hess-19-2057-2015, https://doi.org/10.5194/hess-19-2057-2015, 2015
Short summary
Short summary
We reconstructed a 100-year monthly history of flooding and drought of a large wetland in arid northwest Australia, using hydroclimatic data calibrated against 25 years of satellite images. Severe and intense regional rainfall, as well as the sequence of events, determined surface water expression on the floodplain. While inter-annual variability was high, changes to the flood regime over the last 20 years suggest the wetland may become more persistent in response to the observed rainfall trend.
B. Müller, M. Bernhardt, and K. Schulz
Hydrol. Earth Syst. Sci., 18, 5345–5359, https://doi.org/10.5194/hess-18-5345-2014, https://doi.org/10.5194/hess-18-5345-2014, 2014
Short summary
Short summary
We present a method to define hydrological landscape units by a time series of thermal infrared satellite data. Land surface temperature is calculated for 28 images in 12 years for a catchment in Luxembourg. Pattern measures show spatio-temporal persistency; principle component analysis extracts relevant patterns. Functional units represent similar behaving entities based on a representative set of images. Resulting classification and patterns are discussed regarding potential applications.
F. F. Worku, M. Werner, N. Wright, P. van der Zaag, and S. S. Demissie
Hydrol. Earth Syst. Sci., 18, 3837–3853, https://doi.org/10.5194/hess-18-3837-2014, https://doi.org/10.5194/hess-18-3837-2014, 2014
A. M. Ågren, W. Lidberg, M. Strömgren, J. Ogilvie, and P. A. Arp
Hydrol. Earth Syst. Sci., 18, 3623–3634, https://doi.org/10.5194/hess-18-3623-2014, https://doi.org/10.5194/hess-18-3623-2014, 2014
N. Wanders, D. Karssenberg, A. de Roo, S. M. de Jong, and M. F. P. Bierkens
Hydrol. Earth Syst. Sci., 18, 2343–2357, https://doi.org/10.5194/hess-18-2343-2014, https://doi.org/10.5194/hess-18-2343-2014, 2014
J. K. Kiptala, M. L. Mul, Y. A. Mohamed, and P. van der Zaag
Hydrol. Earth Syst. Sci., 18, 2287–2303, https://doi.org/10.5194/hess-18-2287-2014, https://doi.org/10.5194/hess-18-2287-2014, 2014
C. I. Michailovsky and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 18, 997–1007, https://doi.org/10.5194/hess-18-997-2014, https://doi.org/10.5194/hess-18-997-2014, 2014
T. Conradt, F. Wechsung, and A. Bronstert
Hydrol. Earth Syst. Sci., 17, 2947–2966, https://doi.org/10.5194/hess-17-2947-2013, https://doi.org/10.5194/hess-17-2947-2013, 2013
M. El Bastawesy, R. Ramadan Ali, A. Faid, and M. El Osta
Hydrol. Earth Syst. Sci., 17, 1493–1501, https://doi.org/10.5194/hess-17-1493-2013, https://doi.org/10.5194/hess-17-1493-2013, 2013
A. C. V. Getirana and C. Peters-Lidard
Hydrol. Earth Syst. Sci., 17, 923–933, https://doi.org/10.5194/hess-17-923-2013, https://doi.org/10.5194/hess-17-923-2013, 2013
Y. Tramblay, R. Bouaicha, L. Brocca, W. Dorigo, C. Bouvier, S. Camici, and E. Servat
Hydrol. Earth Syst. Sci., 16, 4375–4386, https://doi.org/10.5194/hess-16-4375-2012, https://doi.org/10.5194/hess-16-4375-2012, 2012
J. Parajka, L. Holko, Z. Kostka, and G. Blöschl
Hydrol. Earth Syst. Sci., 16, 2365–2377, https://doi.org/10.5194/hess-16-2365-2012, https://doi.org/10.5194/hess-16-2365-2012, 2012
S. Peischl, J. P. Walker, C. Rüdiger, N. Ye, Y. H. Kerr, E. Kim, R. Bandara, and M. Allahmoradi
Hydrol. Earth Syst. Sci., 16, 1697–1708, https://doi.org/10.5194/hess-16-1697-2012, https://doi.org/10.5194/hess-16-1697-2012, 2012
S. Bircher, N. Skou, K. H. Jensen, J. P. Walker, and L. Rasmussen
Hydrol. Earth Syst. Sci., 16, 1445–1463, https://doi.org/10.5194/hess-16-1445-2012, https://doi.org/10.5194/hess-16-1445-2012, 2012
J.-M. Kileshye Onema, A. E. Taigbenu, and J. Ndiritu
Hydrol. Earth Syst. Sci., 16, 1435–1443, https://doi.org/10.5194/hess-16-1435-2012, https://doi.org/10.5194/hess-16-1435-2012, 2012
S. Manfreda, T. Lacava, B. Onorati, N. Pergola, M. Di Leo, M. R. Margiotta, and V. Tramutoli
Hydrol. Earth Syst. Sci., 15, 2839–2852, https://doi.org/10.5194/hess-15-2839-2011, https://doi.org/10.5194/hess-15-2839-2011, 2011
M. Salvia, F. Grings, P. Ferrazzoli, V. Barraza, V. Douna, P. Perna, C. Bruscantini, and H. Karszenbaum
Hydrol. Earth Syst. Sci., 15, 2679–2692, https://doi.org/10.5194/hess-15-2679-2011, https://doi.org/10.5194/hess-15-2679-2011, 2011
Cited articles
Abhishek, Kinouchi, T., and Sayama, T.: A comprehensive assessment of water
storage dynamics and hydroclimatic extremes in the Chao Phraya River Basin
during 2002–2020, J. Hydrol., 603, 126868, https://doi.org/10.1016/j.jhydrol.2021.126868, 2021.
Abhishek, Kinouchi, T., Abolafia-Rosenzweig, R., and Ito, M.: Water Budget
Closure in the Upper Chao Phraya River Basin, Thailand Using Multisource
Data, Remote Sens., 14, 173, https://doi.org/10.3390/rs14010173, 2022.
Ahmed, M., Aqnouy, M., and Messari, J. S. E.: Sustainability of Morocco's
groundwater resources in response to natural and anthropogenic forces, J.
Hydrol., 603, 126866, https://doi.org/10.1016/j.jhydrol.2021.126866, 2021.
Bai, P., Liu, X., and Xie, J.: Simulating runoff under changing climatic
conditions: A comparison of the long short-term memory network with two
conceptual hydrologic models, J. Hydrol., 592, 125779, https://doi.org/10.1016/j.jhydrol.2020.125779, 2021.
Beaudoing, H. and Rodell, M.: NASA/GSFC/HSL, GLDAS Noah Land Surface Model L4 3 hourly 0.25 × 0.25 degree V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC) [data set], https://doi.org/10.5067/E7TYRXPJKWOQ, 2020.
Bomers, A., van der Meulen, B., Schielen, R. M. J., and Hulscher, S. J. M.
H.: Historic flood reconstruction with the use of an Artificial Neural
Network, Water Resour. Res., 55, 9673–9688,
https://doi.org/10.1029/2019WR025656, 2019.
Boucher, M. A., Quilty, J., and Adamowski, J.: Data assimilation for
streamflow forecasting using extreme learning machines and multilayer
perceptrons, Water Resour. Res., 56, e2019WR026226, https://doi.org/10.1029/2019WR026226, 2020.
Chao, N., Jin, T., Cai, Z., Chen, G., Liu, X., Wang, Z., and Yeh, P. J. F.:
Estimation of component contributions to total terrestrial water storage
change in the Yangtze river basin, J. Hydrol., 595, 125661,
https://doi.org/10.1016/j.jhydrol.2020.125661, 2021.
Chen, J. L., Wilson, C. R., and Tapley, B. D.: The 2009 exceptional Amazon
flood and interannual terrestrial water storage change observed by GRACE,
Water Resour. Res., 46, W12526, https://doi.org/10.1029/2010WR009383, 2010.
Chen, X., Jiang, J., and Li, H.: Drought and flood monitoring of the Liao
River Basin in northeast China using extended GRACE Data, Remote Sens.,
10, 1168, https://doi.org/10.3390/rs10081168, 2018.
Dottori, F., Szewczyk, W., Ciscar, J., Zhao, F., Alfieri, L., Hirabayashi,
Y., Bianchi, A., Mongelli, I., Frieler, K., Betts, R. A., and Feyen, L.:
Increased human and economic losses from river flooding with anthropogenic
warming, Nat. Clim. Change, 8, 781–786,
https://doi.org/10.1038/s41558-018-0257-z, 2018.
Döll, P., Hoffmann-Dobrev, H., Portmann, F. T., Siebert, S., Eicker, A.,
Rodell, M., Strassberg, G., and Scanlon, B. R.: Impact of water withdrawals
from groundwater and surface water on continental water storage variations,
J. Geodyn., 59–60, 143–156, https://doi.org/10.1016/j.jog.2011.05.001, 2012.
Fang, H., Han, D., He, G., and Chen, M.: Flood management selections for the
Yangtze River midstream after the Three Gorges Project operation, J.
Hydrol., 432-433, 1–11, https://doi.org/10.1016/j.jhydrol.2012.01.042, 2012.
Fatolazadeh, F. and Goïta, K.: Reconstructing groundwater storage
variations from GRACE observations using a new Gaussian-Han-Fan (GHF)
smoothing approach, J. Hydrol., 604, 127234, https://doi.org/10.1016/j.jhydrol.2021.127234, 2022.
Felfelani, F., Wada, Y., Longuevergne, L., and Pokhrel, Y. N.: Natural and
human-induced terrestrial water storage change: A global analysis using
hydrological models and GRACE, J. Hydrol., 553, 105–118,
https://doi.org/10.1016/j.jhydrol.2017.07.048, 2017.
Fischer, S., Schumann, A., and Bühler, P.: A statistics-based automated
flood event separation, J. Hydrol. X, 10, 100070, https://doi.org/10.1016/j.hydroa.2020.100070, 2021.
Giani, G., Tarasova, L., Woods, R. A., and Rico-Ramirez, M. A.: An objective
time-series-analysis method for rainfall-runoff event identification, Water
Resour. Res., 58, e2021WR031283, https://doi.org/10.1029/2021WR031283, 2022.
Gouweleeuw, B. T., Kvas, A., Gruber, C., Gain, A. K., Mayer-Gürr, T., Flechtner, F., and Güntner, A.: Daily GRACE gravity field solutions track major flood events in the Ganges–Brahmaputra Delta, Hydrol. Earth Syst. Sci., 22, 2867–2880, https://doi.org/10.5194/hess-22-2867-2018, 2018.
GRACE: CSR GRACE/GRACE-FO RL06 Mascon Solutions (version 02), GRACE [data set], https://www2.csr.utexas.edu/grace/RL06_mascons.html, last access: 17 November 2022.
Guo, Y., Yu, X., Xu, Y.-P., Chen, H., Gu, H., and Xie, J.: AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment, Hydrol. Earth Syst. Sci., 25, 5951–5979, https://doi.org/10.5194/hess-25-5951-2021, 2021.
Herath, S. M., Sarukkalige, P. R., and Nguyen, V. T. V.: A spatial temporal
downscaling approach to development of IDF relations for Perth airport
region in the context of climate change, Hydrolog. Sci. J.,
61, 2061–2070, https://doi.org/10.1080/02626667.2015.1083103, 2016.
Hochreiter, S. and Schmidhuber, J.: Long short-term memory, Neural Comput.,
9, 1735–1780, https://doi.org/10.1162/neco.1997.9.8.1735,
1997.
Huang, S., Zhang, X., Chen, N., Li, B., Ma, H., Xu, L., Li, R., and Niyogi,
D.: Drought propagation modification after the construction of the Three
Gorges Dam in the Yangtze River Basin, J. Hydrol., 603, 127138,
https://doi.org/10.1016/j.jhydrol.2021.127138, 2021.
Huang, Y., Salama, M. S., Krol, M. S., Su, Z., Hoekstra, A. Y., Zeng, Y.,
and Zhou, Y.: Estimation of human-induced changes in terrestrial water
storage through integration of GRACE satellite detection and hydrological
modeling: A case study of the Yangtze River basin, Water Resour. Res., 51, 8494–8516, https://doi.org/10.1002/2015WR016923, 2015.
Humphrey, V. and Gudmundsson, L.: GRACE-REC: a reconstruction of climate-driven water storage changes over the last century, Earth Syst. Sci. Data, 11, 1153–1170, https://doi.org/10.5194/essd-11-1153-2019, 2019.
Jia, H., Chen, F., Pan, D., Du, E., Wang, L., Wang, N., and Yang, A.: Flood
risk management in the Yangtze River basin – Comparison of 1998 and 2020
events, Int. J. Disast. Risk Re., 68, 102724,
https://doi.org/10.1016/j.ijdrr.2021.102724, 2021.
Jing, W., Di, L., Zhao, X., Yao, L., Xia, X., Liu, Y., Yang, J., Li, Y., and
Zhou, C.: A data-driven approach to generate past GRACE-like terrestrial
water storage solution by calibrating the land surface model simulations,
Adv. Water Resour. Res., 143, 103683,
https://doi.org/10.1016/j.advwatres.2020.103683, 2020.
Khorrami, B. and Gunduz, O.: An enhanced water storage deficit index (EWSDI)
for drought detection using GRACE gravity estimates, J. Hydrol., 603,
126812, https://doi.org/10.1016/j.jhydrol.2021.126812, 2021.
Kong, R., Zhang, Z., Zhang, F., Tian, J., Chang, J., Jiang, S., Zhu, B., and
Chen, X.: Increasing carbon storage in subtropical forests over the Yangtze
River basin and its relations to the major ecological projects, Sci. Total
Environ., 709, 136163, https://doi.org/10.1016/j.scitotenv.2019.136163,
2020.
Kumar, J., Brooks, B.-G. J., Thornton, P. E., and Dietze, M. C.: Sub-daily
statistical downscaling of meteorological variables using neural networks,
Proc. Comput. Sci., 9, 887–896,
https://doi.org/10.1016/j.procs.2012.04.095, 2012.
Landerer, F. W. and Swenson, S. C.: Accuracy of scaled GRACE terrestrial
water storage estimates, Water Resour. Res., 48, W04531, https://doi.org/10.1029/2011WR011453, 2012.
Landerer, F. W., Flechtner, F. M., Save, H., Webb, F. H., Bandikova, T.,
Bertiger, W. I., Bettadpur, S. V., Byun, S. H., Dahle, C., Dobslaw, H.,
Fahnestock, E., Harvey, N., Kang, Z., Kruizinga, G. L. H., Loomis, B. D.,
McCullough, C., Murböck, M., Nagel, P., Paik, M., Pie, N., Poole, S.,
Strekalov, D., Tamisiea, M. E., Wang, F., Watkins, M. M., Wen, H. Y., Wiese,
D. N., and Yuan, D. N.: Extending the Global Mass Change Data Record: GRACE
Follow-On Instrument and Science Data Performance, Geophys. Res. Lett., 47,
1–10, https://doi.org/10.1029/2020GL088306, 2020.
LeCun, Y., Bengio, Y., and Hinton, G.: Deep learning, Nature, 521,
436–444, https://doi.org/10.1038/nature14539, 2015.
Li, X., Scanlon, B. R., Mann, M. E., Li, X., Tian, F., Sun, Z., and Wang, G.:
Climate change threatens terrestrial water storage over the Tibetan Plateau,
Nat. Clim. Change, 12, 801–807, https://doi.org/10.1038/s41558-022-01443-0, 2022.
Liu, B., Zou, X., Yi, S., Sneeuw, N., Cai, J., and Li, J.: Identifying and
separating climate- and human-driven water storage anomalies using GRACE
satellite data, Remote Sens. Environ., 263, 112559,
https://doi.org/10.1016/j.rse.2021.112559, 2021.
Liu, L., Jiang, L., Wang, H., Ding, X., and Xu, H.: Estimation of glacier
mass loss and its contribution to river runoff in the source region of the
Yangtze River during 2000–2018, J. Hydrol., 589, 125207,
https://doi.org/10.1016/j.jhydrol.2020.125207, 2020.
Liu, X. J., Min, F. Y., and Kettner, A. J.: The impact of large to extreme
flood events on floodplain evolution of the middle and lower reaches of the
Yangtze River, China, Catena, 176, 394–409,
https://doi.org/10.1016/j.catena.2019.01.027, 2019.
Long, D., Shen, Y., Sun, A., Hong, Y., Longuevergne, L., Yang, Y., Li, B.,
and Chen, L.: Drought and flood monitoring for a large karst plateau in
Southwest China using extended GRACE data, Remote Sens. Environ., 155,
145–160, https://doi.org/10.1016/j.rse.2014.08.006, 2014.
Long, D., Yang, Y., Wada, Y., Hong, Y., Liang, W., Chen, Y., Yong, B., Hou,
A., Wei, J., and Chen, L.: Deriving scaling factors using a global
hydrological model to restore GRACE total water storage changes for China's
Yangtze River Basin, Remote Sens. Environ., 168, 177–193,
https://doi.org/10.1016/j.rse.2015.07.003, 2015.
Long, D., Yang, W., Scanlon, B.R., Zhao, J., Liu, D., Burek, P., Pan, Y.,
You, L., and Wada, Y.: South-to-North Water Diversion stabilizing Beijing's
groundwater levels, Nat. Commun., 11, 3665,
https://doi.org/10.1038/s41467-020-17428-6, 2020.
Loomis, B. D., Luthcke, S. B., and Sabaka, T. J.: Regularization and error
characterization of GRACE mascons, J. Geodesy, 93, 1381–1398, https://doi.org/10.1007/s00190-019-01252-y, 2019.
Lu, W., Lei, H., Yang, W., Yang, J., and Yang, D.: Comparison of floods
driven by tropical cyclones and monsoons in the Southeastern Coastal Region
of China, J. Hydrometeorol., 21, 1589–1603,
https://doi.org/10.1175/JHM-D-20-0002.1, 2020.
Lv, M., Ma, Z., Yuan, X., Lv, M., Li, M., and Zheng, Z.: Water budget
closure based on GRACE measurements and reconstructed evapotranspiration
using GLDAS and water use data for two large densely-populated mid-latitude
basins, J. Hydrol., 547, 585–599, https://doi.org/10.1016/j.jhydrol.2017.02.027, 2017.
Lyu, K., Zhang, X., and Church, J. A.: Projected ocean warming constrained
by the ocean observational record, Nat. Clim. Change, 11, 834–839,
https://doi.org/10.1038/s41558-021-01151-1, 2021.
Mulder, G., Olsthoorn, T. N., Al-Manmi, D. A. M. A., Schrama, E. J. O., and Smidt, E. H.: Identifying water mass depletion in northern Iraq observed by GRACE, Hydrol. Earth Syst. Sci., 19, 1487–1500, https://doi.org/10.5194/hess-19-1487-2015, 2015.
Mohanasundaram, S., Mekonen, M. M., Haacker, E., Ray, C., Lim, S., and
Shrestha, S.: An application of GRACE mission datasets for streamflow and
baseflow estimation in the Conterminous United States basins, J. Hydrol.,
601, 126622, https://doi.org/10.1016/j.jhydrol.2021.126622,
2021.
Mo, S., Zhong, Y., Forootan, E., Mehrnegar, N., Yin, X., Wu, J., Feng, W.,
and Shi, X.: Bayesian convolutional neural networks for predicting the
terrestrial water storage anomalies during GRACE and GRACE-FO gap, J.
Hydrol., 604, 127244, https://doi.org/10.1016/j.jhydrol.2021.127244, 2022.
NASA: Gravity Recovery and Climate Experiment (GRACE), NASA [data set], https://podaac.jpl.nasa.gov/GRACE?tab=mission-objectives§ions=about+data, last access: 17 November 2022.
Nourani, V., Baghanam, A. H., and Gokcekus, H.: Data-driven ensemble model
to statistically downscale rainfall using nonlinear predictor screening
approach, J. Hydrol., 565, 538–551, https://doi.org/10.1016/j.jhydrol.2018.08.049, 2018.
Ramesh, K., Smith, A. K., Garcia, R. R., Marsh, D. R., Sridharan, S., and
Kumar, K. K.: Long-term variability and tendencies in middle atmosphere
temperature and zonal wind from WACCM6 simulations during 1850–2014, J.
Geophys. Res.-Atmos., 125, e2020JD033579, https://doi.org/10.1029/2020JD033579, 2020.
Reager, J. T. and Famiglietti, J. S.: Global terrestrial water storage
capacity and flood potential using GRACE, Geophys. Res. Lett., 36, L23402,
https://doi.org/10.1029/2009GL040826, 2009.
Reager, J. T., Thomas, B. F., and Famiglietti, J. S.: River basin flood
potential inferred using GRACE gravity observations at several months lead
time, Nat. Geosci., 7, 588–592, https://doi.org/10.1038/ngeo2203, 2014.
Requena, A. I., Nguyen, T. H., Burn, D. H., and Coulibaly, P.: A temporal
downscaling approach for sub-daily gridded extreme rainfall intensity
estimation under climate change, J. Hydrol. Reg. Stud., 35, 100811,
https://doi.org/10.1016/j.ejrh.2021.100811, 2021.
Rodell, M., Famiglietti, J. S., Wiese, D. N., Reager, J. T., Beaudoing, H.
K., Landerer, F. W., and Lo, M. H.: Emerging trends in global freshwater
availability, Nature, 557, 6510659,
https://doi.org/10.1038/s41586-018-0123-1, 2018.
Rumelhart, D. E., Hinton, G. E., and Williams, R. J.: Learning
representations by backpropagating errors, Nature, 323, 533–536, 1986.
Save, H., Bettadpur, S., and Tapley, B. D.: High-resolution CSR GRACE RL05
mascons, J. Geophys. Res.-Sol. Ea., 121, 7547–7569,
https://doi.org/10.1002/2016JB013007, 2016.
Scanlon, B. R., Zhang, Z., Save, H., Wiese, D. N., Landerer, F. W., Long,
D., Longuevergne, L., and Chen, J. L.: Global evaluation of new GRACE mascon
products for hydrologic applications, Water Resour. Res., 52,
9412–9429, https://doi.org/10.1002/2016WR019494, 2016.
Shah, D. and Mishra, V.: Strong influence of changes in terrestrial water
storage on flood potential in India, J. Geophys. Res.-Atmos., 126,
e2020JD033566, https://doi.org/10.1029/2020JD033566, 2021.
Sharifi, E., Saghafian, B., and Steinacker, R.: Downscaling satellite
precipitation estimates with multiple linear regression, artificial neural
networks, and spline interpolation techniques, J. Geophys. Res.-Atmos., 124,
789–805, https://doi.org/10.1029/2018JD028795, 2019.
Shi, R., Yang, H., and Yang, D.: Spatiotemporal variations in frozen ground
and their impacts on hydrological components in the source region of the
Yangtze River, J. Hydrol., 590, 125237, https://doi.org/10.1016/j.jhydrol.2020.125237, 2020.
Shu, C. and Ouarda, T. B.: Flood frequency analysis at ungauged sites using
artificial neural networks in canonical correlation analysis physiographic
space, Water Resour. Res., 43, W07438, https://doi.org/10.1029/2006WR005142,
2007.
Sinha, D., Syed, T. H., and Reager, J. T.: Utilizing combined deviations of
precipitation and GRACE-based terrestrial water storage as a metric for
drought characterization: A case study over major Indian river basins, J.
Hydrol., 572, 294–307, https://doi.org/10.1016/j.jhydrol.2019.02.053, 2019.
Slater, L. J. and Villarini, G.: Recent trends in U.S. flood risk, Geophys.
Res. Lett., 43, 12428–12436, https://doi.org/10.1002/2016GL071199, 2016.
Sousa, S. I. V., Martins, F. G., Alvim-Ferraz, M. C. M., and Pereira, M. C.:
Multiple linear regression and artificial neural networks based on principal
components to predict ozone concentrations, Environ. Modell. Softw., 22, 97–103, https://doi.org/10.1016/j.envsoft.2005.12.002,
2007.
Sun, A. Y., Scanlon, B. R., Zhang, Z., Walling, D., Bhanja, S. N.,
Mukherjee, A., and Zhong, Z.: Combining physically based modeling and deep
learning for fusing GRACE satellite data: can we learn from mismatch?, Water
Resour. Res., 55, 1179–1195, https://doi.org/10.1029/2018WR023333, 2019.
Sun, Z., Long, D., Yang, W., Li, X., and Pan, Y.: Reconstruction of GRACE
data on changes in total water storage over the global land surface and 60
basins, Water Resour. Res., 56, e2019WR026250, https://doi.org/10.1029/2019WR026250, 2020.
Syed, T. H., Famiglietti, J. S., Rodell, M., Chen, J., and Wilson, C. R.:
Analysis of Terrestrial Water Storage Changes from GRACE and GLDAS, Water
Resour. Res., 44, W02433, https://doi.org/10.1029/2006WR005779, 2008.
Tangdamrongsub, N., Ditmar, P. G., Steele-Dunne, S. C., Gunter, B. C., and
Sutanudjaja, E. H.: Assessing total water storage and identifying flood
events over Tonlé Sap basin in Cambodia using GRACE and MODIS satellite
observations combined with hydrological models, Remote Sens. Environ., 181,
162–173, https://doi.org/10.1016/j.rse.2016.03.030, 2016.
Tanoue, M., Taguchi, R., Nakata, S., Watanabe, S., Fujimori, S., and
Hirabayashi, Y.: Estimation of direct and indirect economic losses caused by
a flood with long-lasting inundation: Application to the 2011 Thailand
flood, Water Resour. Res., 56, e2019WR026092, https://doi.org/10.1029/2019WR026092, 2020.
Tapley, B. D., Bettadpur, S., Ries, J. C., Thompson, P. F., and Watkins, M.
M.: GRACE measurements of mass variability in the earth system, Science,
305, 503, https://doi.org/10.1126/science.1099192, 2004.
Tarasova, L., Basso, S., Zink, M., and Merz, R.: Exploring controls on
rainfall-runoff events: 1. Time series-based event separation and temporal
dynamics of event runoff response in Germany, Water Resour. Res., 54,
7711–7732, https://doi.org/10.1029/2018WR022588, 2018.
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.
Velicogna, I., Tong, J., Zhang, T., and Kimball, J. S.: Increasing subsurface
water storage in discontinuous permafrost areas of the Lena River basin,
Eurasia, detected from GRACE, Geophys. Res. Lett., 39, L09403, https://doi.org/10.1029/2012GL051623, 2012.
Vu, M. T., Jarhani, A., Massei, N., and Fournier, M.: Reconstruction of
missing groundwater level data by using Long Short-Term Memory (LSTM) deep
neural network, J. Hydrol., 597, 125776,
https://doi.org/10.1016/j.jhydrol.2020.125776, 2021.
Wang, L., Chen, C., Na, X., Fu, Z., Zheng, Y., and Peng, Z.: Evaluation of
GRACE mascon solutions using in-situ geodetic data: The case of
hydrologic-induced crust displacement in the Yangtze River Basin, Sci. Total
Environ., 707, 135606, https://doi.org/10.1016/j.scitotenv.2019.135606, 2020.
Wang, M., Zheng, H., Xie, X., Fan, D., Yang, S., Zhao, Q., and Wang, K.: A
600-year flood history in the Yangtze River drainage: comparison between a
subaqueous delta and historical records, Chin. Sci. Bull., 58, 188–195,
https://doi.org/10.1007/s11434-010-4212-2, 2011.
Wang, Q., Huang, J., Liu, R., Men, C., Guo, L., Miao, Y., Jiao, L., Wang,
Y., Shoaib, M., and Xia, X.: Sequence-based statistical downscaling and its
application to hydrologic simulations based on machine learning and big
data, J. Hydrol., 586, 124875, https://doi.org/10.1016/j.jhydrol.2020.124875, 2020.
Wasko, C. and Natthan, R.: Influence of changes in rainfall and soil
moisture on trends in flooding, J. Hydrol., 575, 432–441, https://doi.org/10.1016/j.jhydrol.2019.05.054, 2019.
Wei, L., Jiang, S., Ren, L., Tan, H., Ta, W., Liu, Y., Yang, X., Zhang, L.,
and Duan, Z.: Spatiotemporal changes of terrestrial water storage and
possible causes in the closed Qaidam Basin, China using GRACE and GRACE
Follow-On data, J. Hydrol., 598, 126274, https://doi.org/10.1016/j.jhydrol.2021.126274, 2021.
Winter, C., Tarasova, L., Lutz, S. R., Musolff, A., Kumar, R., and
Fleckenstein, J. H.: Explaining the Variability in High-Frequency Nitrate
Export Patterns Using Long-Term Hydrological Event Classification, Water
Resour. Res., 58, e2021WR030938, https://doi.org/10.1029/2021WR030938, 2022.
Wu, H., Yang, Q., Liu, J., and Wang, G.: A spatiotemporal deep fusion model
for merging satellite and gauge precipitation in China, J. Hydrol., 584,
124664, https://doi.org/10.1016/j.jhydrol.2020.124664, 2020.
Wu, Y., Long, D., Lall, U., Scanlon, B. R., Tian, F., Fu, X., Zhao, J.,
Zhang, J., Wang, H., and Hu, C.: Reconstructed eight-century streamflow in
the Tibetan Plateau reveals contrasting regional variability and strong
nonstationarity, Nat. Commun., 13, 6416, https://doi.org/10.1038/s41467-022-34221-9, 2022.
Xie, J., Xu, Y. P., Wang, Y., Gu, H., Wang, F., and Pan, S.: Influences of
climatic variability and human activities on terrestrial water storage
variations across the Yellow River basin in the recent decade, J. Hydrol.,
579, 124218, https://doi.org/10.1016/j.jhydrol.2019.124218,
2019a.
Xie, J., Xu, Y. P., Gao, C., Xuan, W., and Bai, Z.: Total basin discharge
from GRACE and Water balance method for the Yarlung Tsangpo River basin,
Southwestern China, J. Geophys. Res.-Atmos., 124, 7617–7632,
https://doi.org/10.1029/2018JD030025, 2019b.
Xie, J., Xu, Y. P., Guo, Y., and Wang, Y.: Detecting the dominant
contributions of runoff variance across the source region of the Yellow
River using a new decomposition framework, Hydrol. Res., 52, 1015–1032,
https://doi.org/10.2166/nh.2021.179, 2021.
Xie, J., Xu, Y. P., Guo, Y., Wang, Y., and Chen, H.: Understanding the
impact of climatic variability on terrestrial water storage in the
Qinghai-Tibet Plateau of China, Hydrolog. Sci. J., 67, 1–16,
https://doi.org/10.1080/02626667.2022.2044482, 2022.
Xiong, J., Yin, J., Guo, S., Gu, L., Xiong, F., and Li, N.: Integrated flood
potential index for flood monitoring in the GRACE era, J. Hydrol., 603,
127115, https://doi.org/10.1016/j.jhydrol.2021.127115, 2021a.
Xiong, J., Guo, S., and Yin, J.: Discharge Estimation Using Integrated
Satellite Data and Hybrid Model in the Midstream Yangtze River, Remote
Sens., 13, 2272, https://doi.org/10.3390/rs13122272, 2021b.
Yan, X., Zhang, B., Yao, Y., Yang, Y., Li, J., and Ran, Q.: GRACE and land
surface models reveal severe drought in eastern China in 2019, J. Hydrol.,
601, 126640, https://doi.org/10.1016/j.jhydrol.2021.126640,
2021.
Yang, L., Zeng, S., Xia, J., Wang, Y., Huang, R., and Chen, M.: Effects of
the Three Gorges Dam on the downstream streamflow based on a large-scale
hydrological and hydrodynamics coupled model, J. Hydrol. Reg. Stud., 40, 101039, https://doi.org/10.1016/j.ejrh.2022.101039, 2022.
Yang, P., Xia, J., Luo, X., Meng, L., Zhang, S., Cai, W., and Wang, W.:
Impacts of climate change-related flood events in the Yangtze River Basin
based on multi-source data, Atmos. Res, 263, 105819, https://doi.org/10.1016/j.atmosres.2021.105819, 2021.
Yang, S., Liu, Z., Dai, S., Gao, Z., Zhang, J., Wang, H., Luo, X., Wu, C.,
and Zhang, Z.: Temporal variations in water resources in the yangtze river
(Changjiang) over the industrial period based on reconstruction of missing
monthly discharges, Water Resour. Res., 46, W10516, https://doi.org/10.1029/2009WR008589, 2010.
Yao, L., Li, Y., and Chen, X.: A robust water-food-land nexus optimization
model for sustainable agricultural development in the Yangtze River Basin,
Agr. Water Manage., 256, 107103,
https://doi.org/10.1016/j.agwat.2021.107103, 2021.
Yin, G. and Park, J.: The use of triple collocation approach to merge
satellite- and model-based terrestrial water storage for flood potential
analysis, J. Hydrol., 603, 127197, https://doi.org/10.1016/j.jhydrol.2021.127197, 2021.
Yin, H., Wang, F., Zhang, X., Zhang, Y., Chen, J., Xia, R., and Jin, J.:
Rainfall-runoff modeling using long short-term memory based step-sequence
framework, J. Hydrol., 610, 127901,
https://doi.org/10.1016/j.jhydrol.2022.127901, 2022.
Yue, Y., Yan, D., Yue, Q., Ji, G., and Wang, Z.: Future changes in
precipitation and temperature over the Yangtze River Basin in China based on
CMIP6 GCMs, Atmos. Res., 264, 105828,
https://doi.org/10.1016/j.atmosres.2021.105828, 2021.
Zhang, D., Lindholm, G., and Ratnaweera, H.: Use long short-term memory to
enhance Internet of Things for combined sewer overflow monitoring, J.
Hydrol., 556, 409–418, https://doi.org/10.1016/j.jhydrol.2017.11.018, 2018.
Zhang, Q., Xu, C. Y., Zhang, Z. X., Chen, Y. D., Liu, C. L., and Lin, H.:
Spatial and temporal variability of precipitation maxima during 1960–2005 in
the Yangtze River basin and possible association with large-scale
circulation, J. Hydrol., 353, 215–227,
https://doi.org/10.1016/j.jhydrol.2007.11.023, 2008.
Zhang, X., Zhang, G., Long, X., Zhang, Q., Liu, D., Wu, H., and Li, S.:
Identifying the drivers of water yield ecosystem service: A case study in
the Yangtze River Basin, China, Ecol. Indicat., 132, 108304, https://doi.org/10.1016/j.ecolind.2021.108304, 2021.
Short summary
Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers around the world. In this study, we propose a new index incorporating satellite observations combined with meteorological data to monitor extreme flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The conclusions drawn from this study provide important implications for flood hazard prevention and water resource management over this region.
Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers...
