Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5805-2021
© Author(s) 2021. 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-25-5805-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
11 Nov 2021
Research article |
| 11 Nov 2021
| 11 Nov 2021
On the selection of precipitation products for the regionalisation of hydrological model parameters
Oscar M. Baez-Villanueva
Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, Cologne, Germany
Faculty of Spatial Planning, TU Dortmund University, Dortmund, Germany
Mauricio Zambrano-Bigiarini
CORRESPONDING AUTHOR
Department of Civil Engineering, Universidad de la Frontera, Temuco, Chile
Center for Climate and Resilience Research, Universidad de Chile, Santiago, Chile
Pablo A. Mendoza
Department of Civil Engineering, Universidad de Chile, Santiago, Chile
Advanced Mining Technology Center (AMTC), Universidad de Chile, Santiago, Chile
Ian McNamara
Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, Cologne, Germany
Hylke E. Beck
GloH2O, Almere, the Netherlands
Joschka Thurner
Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, Cologne, Germany
Alexandra Nauditt
Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, Cologne, Germany
Lars Ribbe
Institute for Technology and Resources Management in the Tropics and Subtropics (ITT), TH Köln, Cologne, Germany
Nguyen Xuan Thinh
Faculty of Spatial Planning, TU Dortmund University, Dortmund, Germany
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René D. Garreaud, Camila Alvarez-Garreton, Jonathan Barichivich, Juan Pablo Boisier, Duncan Christie, Mauricio Galleguillos, Carlos LeQuesne, James McPhee, and Mauricio Zambrano-Bigiarini
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Hylke E. Beck, Noemi Vergopolan, Ming Pan, Vincenzo Levizzani, Albert I. J. M. van Dijk, Graham P. Weedon, Luca Brocca, Florian Pappenberger, George J. Huffman, and Eric F. Wood
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Pablo A. Mendoza, Andrew W. Wood, Elizabeth Clark, Eric Rothwell, Martyn P. Clark, Bart Nijssen, Levi D. Brekke, and Jeffrey R. Arnold
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Jaap Schellekens, Emanuel Dutra, Alberto Martínez-de la Torre, Gianpaolo Balsamo, Albert van Dijk, Frederiek Sperna Weiland, Marie Minvielle, Jean-Christophe Calvet, Bertrand Decharme, Stephanie Eisner, Gabriel Fink, Martina Flörke, Stefanie Peßenteiner, Rens van Beek, Jan Polcher, Hylke Beck, René Orth, Ben Calton, Sophia Burke, Wouter Dorigo, and Graham P. Weedon
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The dataset combines the results of 10 global models that describe the global continental water cycle. The data can be used as input for water resources studies, flood frequency studies etc. at different scales from continental to medium-scale catchments. We compared the results with earth observation data and conclude that most uncertainties are found in snow-dominated regions and tropical rainforest and monsoon regions.
Hylke E. Beck, Albert I. J. M. van Dijk, Ad de Roo, Emanuel Dutra, Gabriel Fink, Rene Orth, and Jaap Schellekens
Hydrol. Earth Syst. Sci., 21, 2881–2903, https://doi.org/10.5194/hess-21-2881-2017, https://doi.org/10.5194/hess-21-2881-2017, 2017
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Runoff measurements for 966 catchments around the globe were used to assess the quality of the daily runoff estimates of 10 hydrological models run as part of tier-1 of the eartH2Observe project. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty.
Brecht Martens, Diego G. Miralles, Hans Lievens, Robin van der Schalie, Richard A. M. de Jeu, Diego Fernández-Prieto, Hylke E. Beck, Wouter A. Dorigo, and Niko E. C. Verhoest
Geosci. Model Dev., 10, 1903–1925, https://doi.org/10.5194/gmd-10-1903-2017, https://doi.org/10.5194/gmd-10-1903-2017, 2017
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Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.
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
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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.
Hylke E. Beck, Albert I. J. M. van Dijk, Vincenzo Levizzani, Jaap Schellekens, Diego G. Miralles, Brecht Martens, and Ad de Roo
Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, https://doi.org/10.5194/hess-21-589-2017, 2017
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MSWEP (Multi-Source Weighted-Ensemble Precipitation) is a new global terrestrial precipitation dataset with a high 3-hourly temporal and 0.25° spatial resolution. The dataset is unique in that it takes advantage of a wide range of data sources, including gauge, satellite, and reanalysis data, to obtain the best possible precipitation estimates at global scale. The dataset outperforms existing gauge-adjusted precipitation datasets.
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
Monitoring the extreme flood events in the Yangtze River basin based on GRACE and GRACE-FO satellite data
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
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
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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
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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
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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
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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.
Jingkai Xie, Yue-Ping Xu, Hongjie Yu, Yan Huang, and Yuxue Guo
Hydrol. Earth Syst. Sci., 26, 5933–5954, https://doi.org/10.5194/hess-26-5933-2022, https://doi.org/10.5194/hess-26-5933-2022, 2022
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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.
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
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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
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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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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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
Abdelaziz, R., Merkel, B. J., Zambrano-Bigiarini, M., and Nair, S.: Particle swarm optimization for the estimation of surface complexation constants with the geochemical model PHREEQC-3.1.2, Geosci. Model Dev., 12, 167–177, https://doi.org/10.5194/gmd-12-167-2019, 2019. a
Addor, N., Jaun, S., Fundel, F., and Zappa, M.: An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios, Hydrol. Earth Syst. Sci., 15, 2327–2347, https://doi.org/10.5194/hess-15-2327-2011, 2011. a
Addor, N., Nearing, G., Prieto, C., Newman, A., Le Vine, N., and Clark, M. P.:
A ranking of hydrological signatures based on their predictability in space,
Water Resour. Res., 54, 8792–8812, 2018. a
Adhikary, S. K., Yilmaz, A. G., and Muttil, N.: Optimal design of rain gauge
network in the Middle Yarra River catchment, Australia, Hydrol.
Process., 29, 2582–2599, 2015. a
Alvarez-Garreton, C., Mendoza, P. A., Boisier, J. P., Addor, N., Galleguillos, M., Zambrano-Bigiarini, M., Lara, A., Puelma, C., Cortes, G., Garreaud, R., McPhee, J., and Ayala, A.: The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset, Hydrol. Earth Syst. Sci., 22, 5817–5846, https://doi.org/10.5194/hess-22-5817-2018, 2018. a, b, c, d
Arsenault, R. and Brissette, F. P.: Continuous streamflow prediction in
ungauged basins: The effects of equifinality and parameter set selection on
uncertainty in regionalization approaches, Water Resour. Res., 50,
6135–6153, 2014. a
Artan, G., Gadain, H., Smith, J. L., Asante, K., Bandaragoda, C. J., and
Verdin, J. P.: Adequacy of satellite derived rainfall data for stream flow
modeling, Nat. Hazards, 43, 167, https://doi.org/10.1007/s11069-007-9121-6, 2007. a
Astagneau, P. C., Thirel, G., Delaigue, O., Guillaume, J. H. A., Parajka, J., Brauer, C. C., Viglione, A., Buytaert, W., and Beven, K. J.: Technical note: Hydrology modelling R packages – a unified analysis of models and practicalities from a user perspective, Hydrol. Earth Syst. Sci., 25, 3937–3973, https://doi.org/10.5194/hess-25-3937-2021, 2021. a
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Ribbe, L., Nauditt, A.,
Giraldo-Osorio, J. D., and Thinh, N. X.: Temporal and spatial evaluation of
satellite rainfall estimates over different regions in Latin-America,
Atmos. Res., 213, 34–50, https://doi.org/10.1016/j.atmosres.2018.05.011,
2018. a, b
Baez-Villanueva, O. M., Zambrano-Bigiarini, M., Beck, H. E., McNamara, I.,
Ribbe, L., Nauditt, A., Birkel, C., Verbist, K., Giraldo-Osorio, J. D., and
Thinh, N. X.: RF-MEP: A novel Random Forest method for merging gridded
precipitation products and ground-based measurements, Remote Sens. Environ., 239, 111606, https://doi.org/10.1016/j.rse.2019.111606, 2020. a, b, c, d, e, f, g
Bambach, N., Bustos, E., Meza, F., Morales, D., Suarez, F., and Na, V.:
Aplicación de La Metodología de Actualización del Balance
Hídrico Nacional en las Cuencas de la Macrozona Norte y Centro, Dirección General de Aguas (DGA), Santiago, 2018. a
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017a. a
Beck, H. E., Vergopolan, N., Pan, M., Levizzani, V., van Dijk, A. I. J. M., Weedon, G. P., Brocca, L., Pappenberger, F., Huffman, G. J., and Wood, E. F.: Global-scale evaluation of 22 precipitation datasets using gauge observations and hydrological modeling, Hydrol. Earth Syst. Sci., 21, 6201–6217, https://doi.org/10.5194/hess-21-6201-2017, 2017b. a, b
Beck, H. E., Zimmermann, N. E., McVicar, T. R., Vergopolan, N., Berg, A., and
Wood, E. F.: Present and future Köppen-Geiger climate classification
maps at 1-km resolution, Sci. Data, 5, 180214, https://doi.org/10.1038/sdata.2018.214, 2018. a, b
Beck, H. E., Wood, E. F., McVicar, T. R., Zambrano-Bigiarini, M.,
Alvarez-Garreton, C., Baez-Villanueva, O. M., Sheffield, J., and Karger,
D. N.: Bias correction of global high-resolution precipitation climatologies
using streamflow observations from 9372 catchments, J. Climate, 33,
1299–1315, 2020b. a
Bergström, S.: Development and application of a conceptual runoff model for
Scandinavian catchments, Sveriges Meteorologiska Och Hydrologiska Institut, Norrköping, 1976. a
Bergström, S.: The HBV model, Computer models of watershed hydrology, Water Resources Publications, Highlands Ranch, CO, 1995. a
Beven, K. J.: Changing ideas in hydrology - The case of physically-based
models, J. Hydrol., 105, 157–172,
https://doi.org/10.1016/0022-1694(89)90101-7, 1989. a
Beven, K. J.: Uniqueness of place and process representations in hydrological modelling, Hydrol. Earth Syst. Sci., 4, 203–213, https://doi.org/10.5194/hess-4-203-2000, 2000. a
Beven, K. J.: A manifesto for the equifinality thesis, J. Hydrol.,
320, 18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006. a
Biau, G. and Scornet, E.: A random forest guided tour, TEST, 25, 197,
https://doi.org/10.1007/s11749-016-0481-7, 2016. a, b, c, d
Bisselink, B., Zambrano-Bigiarini, M., Burek, P., and de Roo, A.: Assessing the
role of uncertain precipitation estimates on the robustness of hydrological
model parameters under highly variable climate conditions, J. Hydrol.-Regional Studies, 8, 112–129, https://doi.org/10.1016/j.ejrh.2016.09.003,
2016. a, b
Bitew, M. M., Gebremichael, M., Ghebremichael, L. T., and Bayissa, Y. A.:
Evaluation of High-Resolution Satellite Rainfall Products through Streamflow
Simulation in a Hydrological Modeling of a Small Mountainous Watershed in
Ethiopia, J. Hydrometeorol., 13, 338–350,
https://doi.org/10.1175/2011JHM1292.1, 2012. a
Bivand, R. and Rundel, C.: rgeos: Interface to Geometry Engine – Open
Source (“GEOS”),
available at: https://CRAN.R-project.org/package=rgeos (last access: 10 December 2020), r package version
0.5-3, 2020. a
Bivand, R., Keitt, T., and Rowlingson, B.: rgdal: Bindings for the
“Geospatial” Data Abstraction Library,
available at: https://CRAN.R-project.org/package=rgdal (last access: 10 December 2020), r package version
1.5-12, 2020. a
Boisier, J. P., Rondanelli, R., Garreaud, R. D., and Muñoz, F.:
Anthropogenic and natural contributions to the Southeast Pacific
precipitation decline and recent megadrought in central Chile, Geophys.
Res. Lett., 43, 413–421, https://doi.org/10.1002/2015GL067265, 2016. a
Brauer, C. C., Torfs, P. J. J. F., Teuling, A. J., and Uijlenhoet, R.: The Wageningen Lowland Runoff Simulator (WALRUS): application to the Hupsel Brook catchment and the Cabauw polder, Hydrol. Earth Syst. Sci., 18, 4007–4028, https://doi.org/10.5194/hess-18-4007-2014, 2014. a
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32,
https://doi.org/10.1023/A:1010933404324, 2001. a
Carrillo, G., Troch, P. A., Sivapalan, M., Wagener, T., Harman, C., and Sawicz, K.: Catchment classification: hydrological analysis of catchment behavior through process-based modeling along a climate gradient, Hydrol. Earth Syst. Sci., 15, 3411–3430, https://doi.org/10.5194/hess-15-3411-2011, 2011. a, b
Ceola, S., Arheimer, B., Baratti, E., Blöschl, G., Capell, R., Castellarin, A., Freer, J., Han, D., Hrachowitz, M., Hundecha, Y., Hutton, C., Lindström, G., Montanari, A., Nijzink, R., Parajka, J., Toth, E., Viglione, A., and Wagener, T.: Virtual laboratories: new opportunities for collaborative water science, Hydrol. Earth Syst. Sci., 19, 2101–2117, https://doi.org/10.5194/hess-19-2101-2015, 2015. a
Ciabatta, L., Brocca, L., Massari, C., Moramarco, T., Gabellani, S., Puca, S.,
and Wagner, W.: Rainfall-runoff modelling by using SM2RAIN-derived and
state-of-the-art satellite rainfall products over Italy, Int. J. Appl. Earth Obs., 48, 163–173, 2016. a
Clark, M. P. and Hay, L. E.: Use of medium-range numerical weather prediction
model output to produce forecasts of streamflow, J. Hydrometeorol.,
5, 15–32, 2004. a
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. a
Clerc, M.: From theory to practice in particle swarm optimization, in: Handbook
of Swarm Intelligence, 3–36, Springer, Berlin, Germany, 2011a. a
Clerc, M.: Standard particle swarm optimisation from 2006 to 2011, Particle
Swarm Central, France, 253, 1–15, 2011b. a
Coughlan de Perez, E., van den Hurk, B., van Aalst, M. K., Amuron, I., Bamanya, D., Hauser, T., Jongma, B., Lopez, A., Mason, S., Mendler de Suarez, J., Pappenberger, F., Rueth, A., Stephens, E., Suarez, P., Wagemaker, J., and Zsoter, E.: Action-based flood forecasting for triggering humanitarian action, Hydrol. Earth Syst. Sci., 20, 3549–3560, https://doi.org/10.5194/hess-20-3549-2016, 2016. a
Dallery, D., Squividant, H., De Lavenne, A., Launay, J., and Cudennec, C.: An
end-user-friendly hydrological Web Service for hydrograph prediction in
ungauged basins, Hydrol. Sci. J., 0, 1–9, https://doi.org/10.1080/02626667.2020.1797045, 2020. a
Dembélé, M., Hrachowitz, M., Savenije, H. H., Mariéthoz, G., and
Schaefli, B.: Improving the predictive skill of a distributed hydrological
model by calibration on spatial patterns with multiple satellite data sets,
Water Resour. Res., 56, e2019WR026085, https://doi.org/10.1029/2019WR026085, 2020. a
DGA: Plan director para la gestión de los recursos hídricos en
la cuenca del río San José, Tech. rep., Dirección General
de Aguas, Santiago, available at: https://snia.mop.gob.cl/sad/ADM600v1.pdf (last access: 9 June 2021),
1998. a
DGA: Recursos hídricos compartidos con la República Argentina :
ficha temática de la cuenca del río Grande de Tierra del Fuego,
Tech. rep., Dirección General de Aguas, Santiago,
available at: https://snia.mop.gob.cl/sad/CUH2087.pdf (last access: 9 June 2021), 1999. a
DGA: Cuenca Quebrada de Tarapacá, Tech. rep., Dirección General
de Aguas, Santiago,
available at: https://mma.gob.cl/wp-content/uploads/2017/12/Tarapaca.pdf (last access: 9 June 2021),
2004a. a
DGA: Cuenca Río Loa, Tech. rep., Dirección General de Aguas,
Santiago,
available at: https://mma.gob.cl/wp-content/uploads/2017/12/Loa.pdf (last access: 9 June 2021),
2004b. a
DGA: Cuenca del Río Elqui, Tech. rep., Dirección General de
Aguas, Santiago,
available at: https://mma.gob.cl/wp-content/uploads/2017/12/Elqui.pdf (last access: 9 June 2021),
2004c. a
DGA: Evaluación de los recursos hídricos superficales de las
cuencas de los ríos Petorca y La Ligua V Región, Tech. rep.,
Dirección General de Aguas, Santiago,
available at: https://snia.mop.gob.cl/sad/SUP4496.pdf (last access: 9 June 2021), 2006. a
DGA: Análisis integral de soluciones a la escasez hídrica,
región de Arica y Parinacota: informe final, Tech. rep.,
Dirección General de Aguas, Santiago,
available at: https://snia.mop.gob.cl/sad/REH5720.pdf (last access: 9 June 2021), 2016a. a
DGA: Actualización de Información y Modelación
Hidrológica Acuíferos de la XII Región, de Magallanes y la
Antártica Chilena : Informe definitivo etapa II, Tech. rep.,
Dirección General de Aguas, Santiago,
available at: https://snia.mop.gob.cl/sad/SUB5698.pdf (last access: 9 June 2021), 2016b. a
DGA: Herramientas de gestión y actualización de los modelos
numéricos del acuífero de Copiapó: informe final, Tech.
rep., Dirección General de Aguas, Santiago,
available at: https://snia.mop.gob.cl/sad/SUB5851v1.pdf (last access: 9 June 2021), 2018. a
Díaz-Uriarte, R. and Alvarez de Andrés, S.: Gene selection and
classification of microarray data using random forest., BMC Bioinformatics,
7, 3, https://doi.org/10.1186/1471-2105-7-3, 2006. a
Ding, J., Wallner, M., Müller, H., and Haberlandt, U.: Estimation of
instantaneous peak flows from maximum mean daily flows using the HBV
hydrological model, Hydrol. Process., 30, 1431–1448, 2016. a
Eberhart, R. and Kennedy, J.: A new optimizer using particle swarm theory, in:
Micro Machine and Human Science, 1995. MHS '95, Proceedings of the Sixth
International Symposium on, 39–43, https://doi.org/10.1109/MHS.1995.494215, 1995. a
Fernandez, W., Vogel, R., and Sankarasubramanian, A.: Regional calibration of a
watershed model, Hydrol. Sci. J., 45, 689–707, 2000. a
Galleguillos, M., Gimeno, F., Puelma, C., Zambrano-Bigiarini, M., Lara, A., and
Rojas, M.: Disentangling the effect of future land use strategies and climate
change on streamflow in a Mediterranean catchment dominated by tree
plantations, J. Hydrol., 595, 126047,
https://doi.org/10.1016/j.jhydrol.2021.126047, 2021. a
Garcia, F., Folton, N., and Oudin, L.: Which objective function to calibrate
rainfall–runoff models for low-flow index simulations?, Hydrol. Sci. J., 62, 1149–1166, 2017. a
Garreaud, R. D., Alvarez-Garreton, C., Barichivich, J., Boisier, J. P., Christie, D., Galleguillos, M., LeQuesne, C., McPhee, J., and Zambrano-Bigiarini, M.: The 2010–2015 megadrought in central Chile: impacts on regional hydroclimate and vegetation, Hydrol. Earth Syst. Sci., 21, 6307–6327, https://doi.org/10.5194/hess-21-6307-2017, 2017. a, b
Garreaud, R. D., Boisier, J. P., Rondanelli, R., Montecinos, A., Sepúlveda,
H. H., and Veloso-Aguila, D.: The Central Chile Mega Drought (2010–2018): A
climate dynamics perspective, International J. Climatol., 40,
421–439, 2020. a
Guo, Y., Zhang, Y., Zhang, L., and Wang, Z.: Regionalization of hydrological
modeling for predicting streamflow in ungauged catchments: A comprehensive
review, Wiley Interdisciplinary Reviews: Water, e1487, https://doi.org/10.1002/wat2.1487, 2021. a, b
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of
the mean squared error and NSE performance criteria: Implications for
improving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009. a
Hann, H., Nauditt, A., Zambrano-Bigiarini, M., Thurner, J., McNamara, I., and
Ribbe, L.: Combining satellite-based rainfall data with rainfall-runoff
modelling to simulate low flows in a Southern Andean catchment, J. Nat. Res. Dev., 11, 1–19,
https://doi.org/10.18716/ojs/jnrd/2021.11.02, 2021. a
Hargreaves, G. H. and Samani, Z. A.: Reference crop evapotranspiration from
ambient air temperature, American Society of Agricultural Engineers, (fiche
no. 85-2517), (Microfiche collection), USA, 1985. a
Hengl, T., Nussbaum, M., Wright, M. N., Heuvelink, G. B., and Gräler, B.:
Random Forest as a generic framework for predictive modeling of spatial and
spatio-temporal variables, PeerJ, 6, e5518, https://doi.org/10.7717/peerj.5518, 2018. a
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., De Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., de Rosnay, P., Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy.
Meteor. Soc., 146, 1999–2049, 2020. a, b, c, d
Hijmans, R. J.: raster: Geographic Data Analysis and Modeling,
available at: https://CRAN.R-project.org/package=raster (last access: 12 December 2021), r package version
3.3-13, 2020. a
Hofstra, N., New, M., and McSweeney, C.: The influence of interpolation and
station network density on the distributions and trends of climate variables
in gridded daily data, Clim. Dynam., 35, 841–858, 2010. a
Hrachowitz, M., Savenije, H., Blöschl, G., McDonnell, J., Sivapalan, M.,
Pomeroy, J., Arheimer, B., Blume, T., Clark, M., Ehret, U., et al.: A decade
of Predictions in Ungauged Basins (PUB) – a review, Hydrol. Sci. J., 58, 1198–1255, 2013. a
Huang, S., Eisner, S., Magnusson, J. O., Lussana, C., Yang, X., and Beldring,
S.: Improvements of the spatially distributed hydrological modelling using
the HBV model at 1 km resolution for Norway, J. Hydrol., 577,
123585, https://doi.org/10.1016/j.jhydrol.2019.03.051, 2019. a
Jansen, K. F., Teuling, A. J., Craig, J. R., Dal Molin, M., Knoben, W. J.,
Parajka, J., Vis, M., and Melsen, L. A.: Mimicry of a Conceptual Hydrological
Model (HBV): What's in a Name?, Water Resour. Res., 57,
e2020WR029143, https://doi.org/10.1029/2020WR029143, 2021. a
Jehn, F. U., Bestian, K., Breuer, L., Kraft, P., and Houska, T.: Using hydrological and climatic catchment clusters to explore drivers of catchment behavior, Hydrol. Earth Syst. Sci., 24, 1081–1100, https://doi.org/10.5194/hess-24-1081-2020, 2020. a
Karl, T. R., Nicholls, N., and Ghazi, A.: Clivar/GCOS/WMO workshop on indices
and indicators for climate extremes workshop summary, in: Weather and climate
extremes, 3–7, Springer, Dordrecht, the Netherlands, 1999. a
Kearney, M. R. and Maino, J. L.: Can next-generation soil data products improve
soil moisture modelling at the continental scale? An assessment using a new
microclimate package for the R programming environment, J. Hydrol., 561, 662–673, https://doi.org/10.1016/j.jhydrol.2018.04.040, 2018. a
Kennedy, J. and Eberhart, R.: Particle swarm optimization, in: Neural Networks,
1995. Proceedings., IEEE International Conference on, 4, 1942–1948,
https://doi.org/10.1109/ICNN.1995.488968, 1995. a
Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube
basin under an ensemble of climate change scenarios, J. Hydrol.,
424, 264–277, https://doi.org/10.1016/j.jhydrol.2012.01.011, 2012. a, b, c, d
Knoben, W. J. M., Freer, J. E., and Woods, R. A.: Technical note: Inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores, Hydrol. Earth Syst. Sci., 23, 4323–4331, https://doi.org/10.5194/hess-23-4323-2019, 2019. a
Koffler, D., Gauster, T., and Laaha, G.: lfstat: Calculation of Low Flow
Statistics for Daily Stream Flow Data,
available at: https://CRAN.R-project.org/package=lfstat (last access: 12 December 2020), r package version
0.9.4, 2016. a
Kuentz, A., Arheimer, B., Hundecha, Y., and Wagener, T.: Understanding hydrologic variability across Europe through catchment classification, Hydrol. Earth Syst. Sci., 21, 2863–2879, https://doi.org/10.5194/hess-21-2863-2017, 2017. a
Kundu, D., Vervoort, R. W., and van Ogtrop, F. F.: The value of remotely sensed
surface soil moisture for model calibration using SWAT, Hydrol.
Process., 31, 2764–2780, https://doi.org/10.1002/hyp.11219, 2017. a
Lagos, M., Mendoza, P., Rondanellu, R., Daniele, D., and Tomaás, G.:
Aplicación de La metodología de actualización del balance
hídrico nacional en las cuencas de la Macrozona Sur y parte de la
Macrozona Austral, Dirección General de Aguas (DGA), Santiago, Chile, 2019. a
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for
general circulation models, J. Geophys. Res.-Atmos., 99,
14415–14428, 1994. a
Liaw, A. and Wiener, M.: Classification and Regression by randomForest, R
News, 2, 18–22, 2002. a
Lindström, G.: A simple automatic calibration routine for the HBV model,
Hydrol. Res., 28, 153–168, 1997. a
Melsen, L. A., Addor, N., Mizukami, N., Newman, A. J., Torfs, P. J. J. F., Clark, M. P., Uijlenhoet, R., and Teuling, A. J.: Mapping (dis)agreement in hydrologic projections, Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, 2018. a
Mendoza, P. A., Clark, M. P., Mizukami, N., Gutmann, E. D., Arnold, J. R.,
Brekke, L. D., and Rajagopalan, B.: How do hydrologic modeling decisions
affect the portrayal of climate change impacts?, Hydrol. Process., 30,
1071–1095, 2016. a
Merz, R. and Blöschl, G.: Regionalisation of catchment model parameters,
J. Hydrol., 287, 95–123, 2004. a
Mizukami, N., Rakovec, O., Newman, A. J., Clark, M. P., Wood, A. W., Gupta, H. V., and Kumar, R.: On the choice of calibration metrics for “high-flow” estimation using hydrologic models, Hydrol. Earth Syst. Sci., 23, 2601–2614, https://doi.org/10.5194/hess-23-2601-2019, 2019. a
Neri, M., Parajka, J., and Toth, E.: Importance of the informative content in the study area when regionalising rainfall-runoff model parameters: the role of nested catchments and gauging station density, Hydrol. Earth Syst. Sci., 24, 5149–5171, https://doi.org/10.5194/hess-24-5149-2020, 2020. a, b, c, d, e, f, g, h, i, j, k, l, m
Nikolopoulos, E. I., Anagnostou, E. N., and Borga, M.: Using high-resolution
satellite rainfall products to simulate a major flash flood event in northern
Italy, J. Hydrometeorol., 14, 171–185, 2013. a
Ollivier, C., Mazzilli, N., Olioso, A., Chalikakis, K., Carrière, S. D.,
Danquigny, C., and Emblanch, C.: Karst recharge-discharge semi distributed
model to assess spatial variability of flows, Sci. Total
Environ., 703, 134368, https://doi.org/10.1016/j.scitotenv.2019.134368, 2020. a
Oudin, L., Andréassian, V., Perrin, C., Michel, C., and Le Moine, N.:
Spatial proximity, physical similarity, regression and ungaged catchments:
A comparison of regionalization approaches based on 913 French
catchments, Water Resour. Res., 44, W03413, https://doi.org/10.1029/2007WR006240, 2008. a, b, c, d, e, f, g, h, i, j, k, l, m
Parajka, J., Viglione, A., Rogger, M., Salinas, J. L., Sivapalan, M., and Blöschl, G.: Comparative assessment of predictions in ungauged basins – Part 1: Runoff-hydrograph studies, Hydrol. Earth Syst. Sci., 17, 1783–1795, https://doi.org/10.5194/hess-17-1783-2013, 2013. a, b
Parajka, J., Blaschke, A. P., Blöschl, G., Haslinger, K., Hepp, G., Laaha, G., Schöner, W., Trautvetter, H., Viglione, A., and Zessner, M.: Uncertainty contributions to low-flow projections in Austria, Hydrol. Earth Syst. Sci., 20, 2085–2101, https://doi.org/10.5194/hess-20-2085-2016, 2016. a
Perpiñán, O. and Hijmans, R.: rasterVis,
available at: https://oscarperpinan.github.io/rastervis/ (last access: 12 December 2020), r package version
0.49, 2020. a
Pokhrel, P., Yilmaz, K. K., and Gupta, H. V.: Multiple-criteria calibration of
a distributed watershed model using spatial regularization and response
signatures, J. Hydrol., 418, 49–60, 2012. a
Pool, S., Vis, M. J. P., Knight, R. R., and Seibert, J.: Streamflow characteristics from modeled runoff time series – importance of calibration criteria selection, Hydrol. Earth Syst. Sci., 21, 5443–5457, https://doi.org/10.5194/hess-21-5443-2017, 2017. a, b
Prasad, A. M., Iverson, L. R., and Liaw, A.: Newer Classification and
Regression Tree Techniques: Bagging and Random Forests for Ecological
Prediction, Ecosystems, 9, 181, https://doi.org/10.1007/s10021-005-0054-1, 2006. a, b
R Core Team: R: A Language and Environment for Statistical
Computing, R Foundation for Statistical Computing, Vienna, Austria,
available at: https://www.R-project.org/ (last access: 12 December 2020), 2020. a
Ren, Z. and Li, M.: Errors and correction of precipitation measurements in
China, Adv. Atmos. Sci., 24, 449–458, https://doi.org/10.1007/s00376-007-0449-3, 2007. a
Robertson, A. W., Baethgen, W., Block, P., Lall, U., Sankarasubramanian, A.,
de Souza Filho, F. d. A., and Verbist, K. M.: Climate risk management for
water in semi–arid regions, Earth Perspectives, 1, 12, https://doi.org/10.1186/2194-6434-1-12, 2014. a
Rojas, R., Feyen, L., and Watkiss, P.: Climate change and river floods in the
European Union: Socio-economic consequences and the costs and benefits
of adaptation, Global Environ. Change, 23, 1737–1751,
https://doi.org/10.1016/j.gloenvcha.2013.08.006, 2013. a
Saadi, M., Oudin, L., and Ribstein, P.: Random forest ability in regionalizing
hourly hydrological model parameters, Water, 11, 1540, https://doi.org/10.3390/w11081540, 2019. a, b
Samaniego, L., Kumar, R., and Attinger, S.: Multiscale parameter
regionalization of a grid-based hydrologic model at the mesoscale, Water Resour. Res., 46, W05523, https://doi.org/10.1029/2008WR007327, 2010. a, b, c
Sawicz, K., Wagener, T., Sivapalan, M., Troch, P. A., and Carrillo, G.: Catchment classification: empirical analysis of hydrologic similarity based on catchment function in the eastern USA, Hydrol. Earth Syst. Sci., 15, 2895–2911, https://doi.org/10.5194/hess-15-2895-2011, 2011. a
Sevruk, B., Ondrás, M., and Chvíla, B.: The WMO precipitation
measurement intercomparisons, Atmos. Res., 92, 376–380,
https://doi.org/10.1016/j.atmosres.2009.01.016, 2009. a
Shafii, M. and Tolson, B. A.: Optimizing hydrological consistency by
incorporating hydrological signatures into model calibration objectives,
Water Resour. Res., 51, 3796–3814, 2015. a
Sharma, S., Siddique, R., Reed, S., Ahnert, P., Mendoza, P., and Mejia, A.: Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system, Hydrol. Earth Syst. Sci., 22, 1831–1849, https://doi.org/10.5194/hess-22-1831-2018, 2018. a
Silal, S. P., Little, F., Barnes, K. I., and White, L. J.: Predicting the
impact of border control on malaria transmission: a simulated focal screen
and treat campaign, Malar J., 14, 268, https://doi.org/10.1186/s12936-015-0776-2, 2015. a
Sleziak, P., Szolgay, J., Hlavčová, K., Danko, M., and Parajka, J.:
The effect of the snow weighting on the temporal stability of hydrologic
model efficiency and parameters, J. Hydrol., 583, 124639, https://doi.org/10.1016/j.jhydrol.2020.124639, 2020. a
Stisen, S. and Sandholt, I.: Evaluation of remote-sensing-based rainfall
products through predictive capability in hydrological runoff modelling,
Hydrol. Process., 24, 879–891, https://doi.org/10.1002/hyp.7529, 2010. a
Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., and Hsu, K.-L.: A
Review of Global Precipitation Data Sets: Data Sources, Estimation, and
Intercomparisons, Rev. Geophys., 56, 79–107,
https://doi.org/10.1002/2017RG000574, 2018. a
Swain, J. B. and Patra, K. C.: Streamflow estimation in ungauged catchments
using regional flow duration curve: comparative study, J. Hydrol.
Eng., 22, 04017010, https://doi.org/10.1061/(ASCE)HE.1943-5584.0001509, 2017. a, b, c
Széles, B., Parajka, J., Hogan, P., Silasari, R., Pavlin, L., Strauss, P.,
and Blöschl, G.: The added value of different data types for calibrating
and testing a hydrologic model in a small catchment, Water Resour. Res., 56, e2019WR026153, https://doi.org/10.1029/2019WR026153, 2020. a, b, c, d
Tarek, M., Brissette, F. P., and Arsenault, R.: Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America, Hydrol. Earth Syst. Sci., 24, 2527–2544, https://doi.org/10.5194/hess-24-2527-2020, 2020. a
Thiemig, V., Rojas, R., Zambrano-Bigiarini, M., and De Roo, A.: Hydrological
evaluation of satellite-based rainfall estimates over the Volta and
Baro-Akobo Basin, J. Hydrol., 499, 324–338,
https://doi.org/10.1016/j.jhydrol.2013.07.012, 2013. a
Uhlenbrook, S., Seibert, J., Leibundgut, C., and Rohde, A.: Prediction
uncertainty of conceptual rainfall-runoff models caused by problems to
identify model parameters and structure, Hydrol. Sci. J., 44,
779–797, 1999. a
Unduche, F., Tolossa, H., Senbeta, D., and Zhu, E.: Evaluation of four
hydrological models for operational flood forecasting in a Canadian
Prairie watershed, Hydrol. Sci. J., 63, 1133–1149, 2018. a
Vandewiele, G. and Elias, A.: Monthly water balance of ungauged catchments
obtained by geographical regionalization, J. Hydrol., 170,
277–291, 1995. a
Vásquez, N., Cepeda, J., Gómez, T., Mendoza, P. A., Lagos, M., Boisier,
J. P., Álvarez-Garretón, C., and Vargas, X.: Catchment-Scale
Natural Water Balance in Chile, in: Water Resources of Chile,
189–208, Springer, Switzerland, 2021. a
Verbist, K., Robertson, A. W., Cornelis, W. M., and Gabriels, D.: Seasonal
predictability of daily rainfall characteristics in central northern Chile
for dry-land management, J. Appl. Meteorol. Climatol., 49,
1938–1955, 2010. a
Vetter, T., Huang, S., Aich, V., Yang, T., Wang, X., Krysanova, V., and Hattermann, F.: Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents, Earth Syst. Dynam., 6, 17–43, https://doi.org/10.5194/esd-6-17-2015, 2015. a
Viglione, A. and Parajka, J.: TUWmodel: Lumped/Semi-Distributed
Hydrological Model for Education Purposes,
available at: https://CRAN.R-project.org/package=TUWmodel (last access: 12 December 2020), r package
version 1.1-1, 2020. a
Vrugt, J. A., Gupta, H. V., Bouten, W., and Sorooshian, S.: A Shuffled
Complex Evolution Metropolis algorithm for optimization and uncertainty
assessment of hydrological model parameters, Water Resour. Res., 39,
1201, https://doi.org/10.1029/2002WR001642, 2003. a
Vrugt, J. A., ter Braak, C. J. F., Gupta, H. V., and Robinson, B. A.: Response
to comment by Keith Beven on “Equifinality of formal (DREAM) and
informal (GLUE) Bayesian approaches in hydrologic modeling?”, Stoch.
Env. Res. Risk A., 23, 1061–1062,
https://doi.org/10.1007/s00477-008-0284-9, 2009. a
Wagener, T., Boyle, D. P., Lees, M. J., Wheater, H. S., Gupta, H. V., and Sorooshian, S.: A framework for development and application of hydrological models, Hydrol. Earth Syst. Sci., 5, 13–26, https://doi.org/10.5194/hess-5-13-2001, 2001. a
Wagener, T., Sivapalan, M., Troch, P., and Woods, R.: Catchment Classification
and Hydrologic Similarity, Geography Compass, 1, 901–931,
https://doi.org/10.1111/j.1749-8198.2007.00039.x, 2007. a
Woldemeskel, F. M., Sivakumar, B., and Sharma, A.: Merging gauge and satellite
rainfall with specification of associated uncertainty across Australia,
J. Hydrol., 499, 167–176, https://doi.org/10.1016/j.jhydrol.2013.06.039,
2013. a
Xavier, A. C., King, C. W., and Scanlon, B. R.: Daily gridded meteorological
variables in Brazil (1980–2013), Int. J. Climatol., 36,
2644–2659, 2016. a
Xue, X., Hong, Y., Limaye, A. S., Gourley, J. J., Huffman, G. J., Khan, S. I.,
Dorji, 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, 2013. a
Yang, Y., Pan, M., Beck, H. E., Fisher, C. K., Beighley, R. E., Kao, S.-C.,
Hong, Y., and Wood, E. F.: In quest of calibration density and consistency in
hydrologic modeling: distributed parameter calibration against streamflow
characteristics, Water Resour. Res., 55, 7784–7803, 2019. a
Yapo, P. O., Gupta, H. V., and Sorooshian, S.: Multi-objective global
optimization for hydrologic models, J. Hydrol., 204, 83–97,
https://doi.org/10.1016/S0022-1694(97)00107-8, 1998. a
Young, A. R.: Stream flow simulation within UK ungauged catchments using a
daily rainfall-runoff model, J. Hydrol., 320, 155–172, 2006. a
Zambrano-Bigiarini, M.: hydroGOF: Goodness-of-fit functions for comparison
of simulated and observed hydrological time series, r package version 0.4-0,
https://doi.org/10.5281/zenodo.839854, 2020a. a
Zambrano-Bigiarini, M.: hydroTSM: Time Series Management, Analysis
and Interpolation for Hydrological Modelling, r package version 0.6-0, https://doi.org/10.5281/zenodo.839864, 2020b. a
Zambrano-Bigiarini, M. and Baez-Villanueva, O.: Tutorial for using hydroPSO to
calibrate TUWmodel, https://doi.org/10.5281/zenodo.3772176, 2020. a
Zambrano-Bigiarini, M. and Rojas, R.: A model-independent Particle Swarm
Optimisation software for model calibration, Environ. Model.
Softw., 43, 5–25, https://doi.org/10.1016/j.envsoft.2013.01.004, 2013. a, b
Zambrano-Bigiarini, M., Nauditt, A., Birkel, C., Verbist, K., and Ribbe, L.: Temporal and spatial evaluation of satellite-based rainfall estimates across the complex topographical and climatic gradients of Chile, Hydrol. Earth Syst. Sci., 21, 1295–1320, https://doi.org/10.5194/hess-21-1295-2017, 2017. a, b, c, d
Zambrano-Bigiarini, M., Baez-Villanueva, O. M., and Giraldo-Osorio, J.:
RFmerge: Merging of Satellite Datasets with Ground Observations using Random
Forests, r
package version 0.1-10, https://doi.org/10.5281/zenodo.3581515, 2020. a
Zessner, M., Schönhart, M., Parajka, J., Trautvetter, H., Mitter, H.,
Kirchner, M., Hepp, G., Blaschke, A. P., Strenn, B., and Schmid, E.: A novel
integrated modelling framework to assess the impacts of climate and
socio-economic drivers on land use and water quality, Sci. Total
Environ., 579, 1137–1151, 2017. a
Zhang, L., Li, X., Zheng, D., Zhang, K., Ma, Q., Zhao, Y., and Ge, Y.: Merging
multiple satellite-based precipitation products and gauge observations using
a novel double machine learning approach, J. Hydrol., 594,
125969, https://doi.org/10.1016/j.jhydrol.2021.125969, 2021. a, b
Zhang, Y. and Chiew, F. H.: Relative merits of different methods for runoff
predictions in ungauged catchments, Water Resour. Res., 45, W07412, https://doi.org/10.1029/2008WR007504, 2009. a
Zhang, Y. and Wang, K.: Global precipitation system size, Environ.
Res. Lett., 16, 054005, https://doi.org/10.1088/1748-9326/abf394, 2021. a, b
Zhang, Y., Vaze, J., Chiew, F. H., and Li, M.: Comparing flow duration curve
and rainfall–runoff modelling for predicting daily runoff in ungauged
catchments, J. Hydrol., 525, 72–86, 2015. a
Zhao, Y., Feng, D., Yu, L., Wang, X., Chen, Y., Bai, Y., Hernández, H. J.,
Galleguillos, M., Estades, C., Biging, G. S., Radke, J. D., and Gong, P.:
Detailed dynamic land cover mapping of Chile: Accuracy improvement by
integrating multi-temporal data, Remote Sens. Environ., 183,
170–185, https://doi.org/10.1016/j.rse.2016.05.016, 2016. a, b
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.
Most rivers worldwide are ungauged, which hinders the sustainable management of water resources....
