Articles | Volume 21, issue 12
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-21-5987-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
30 Nov 2017
Research article |
| 30 Nov 2017
Spatial pattern evaluation of a calibrated national hydrological model – a remote-sensing-based diagnostic approach
Department of hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, Denmark
Julian Koch
Department of hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, Denmark
Simon Stisen
Department of hydrology, Geological Survey of Denmark and Greenland,
Copenhagen, Denmark
Related authors
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
Short summary
Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
G. Mendiguren, M. Pilar Martín, H. Nieto, J. Pacheco-Labrador, and S. Jurdao
Biogeosciences, 12, 5523–5535, https://doi.org/10.5194/bg-12-5523-2015, https://doi.org/10.5194/bg-12-5523-2015, 2015
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, Anker Lajer Højberg, Hans Thodsen, Mark F. T. Hansen, and Raphael J. M. Schneider
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-292, https://doi.org/10.5194/essd-2024-292, 2024
Preprint under review for ESSD
Short summary
Short summary
We developed a CAMELS-style dataset in Denmark, which contains hydrometeorological time series and landscape attributes for 3,330 catchments. Many of the catchments in CAMELS-DK are small and located at low elevations. The dataset provides information on groundwater characteristics and dynamics, as well as quantities related to human impact on the hydrological system in Denmark. The dataset is especially relevant for developing data-driven and hybrid physically-informed modeling frameworks.
Jun Liu, Julian Koch, Simon Stisen, Lars Troldborg, and Raphael J. M. Schneider
Hydrol. Earth Syst. Sci., 28, 2871–2893, https://doi.org/10.5194/hess-28-2871-2024, https://doi.org/10.5194/hess-28-2871-2024, 2024
Short summary
Short summary
We developed hybrid schemes to enhance national-scale streamflow predictions, combining long short-term memory (LSTM) with a physically based hydrological model (PBM). A comprehensive evaluation of hybrid setups across Denmark indicates that LSTM models forced by climate data and catchment attributes perform well in many regions but face challenges in groundwater-dependent basins. The hybrid schemes supported by PBMs perform better in reproducing long-term streamflow behavior and extreme events.
Kristian Svennevig, Julian Koch, Marie Keiding, and Gregor Luetzenburg
Nat. Hazards Earth Syst. Sci., 24, 1897–1911, https://doi.org/10.5194/nhess-24-1897-2024, https://doi.org/10.5194/nhess-24-1897-2024, 2024
Short summary
Short summary
In our study, we analysed publicly available data in order to investigate the impact of climate change on landslides in Denmark. Our research indicates that the rising groundwater table due to climate change will result in an increase in landslide activity. Previous incidents of extremely wet winters have caused damage to infrastructure and buildings due to landslides. This study is the first of its kind to exclusively rely on public data and examine landslides in Denmark.
Raoul Alexander Collenteur, Ezra Haaf, Mark Bakker, Tanja Liesch, Andreas Wunsch, Jenny Soonthornrangsan, Jeremy White, Nick Martin, Rui Hugman, Michael Fienen, Ed de Sousa, Didier Vanden Berghe, Xinyang Fan, Tim Peterson, Janis Bikše, Antoine Di Ciacca, Xinyue Wang, Yang Zheng, Maximilian Nölscher, Julian Koch, Raphael Schneider, Nikolas Benavides Höglund, Sivarama Krishna Reddy Chidepudi, Abel Henriot, Nicolas Massei, Abderrahim Jardani, Max Gustav Rudolph, Amir Rouhani, Jaime Gómez-Hernández, Seifeddine Jomaa, Anna Pölz, Tim Franken, Morteza Behbooei, Jimmy Lin, Bryan Tolson, and Rojin Meysami
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-111, https://doi.org/10.5194/hess-2024-111, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
We present the results of the 2022 groundwater modeling challenge, where 15 teams applied data-driven models to simulate hydraulic heads. 3 groups of models were identified: lumped models, machine learning models, and deep learning models. For all wells, reasonable performance was obtained by at least 1 team from group. There was not 1 team that performed best for all wells. In conclusion, the challenge was a successful initiative to compare different models and learn from each other.
Søren Julsgaard Kragh, Jacopo Dari, Sara Modanesi, Christian Massari, Luca Brocca, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 28, 441–457, https://doi.org/10.5194/hess-28-441-2024, https://doi.org/10.5194/hess-28-441-2024, 2024
Short summary
Short summary
This study provides a comparison of methodologies to quantify irrigation to enhance regional irrigation estimates. To evaluate the methodologies, we compared various approaches to quantify irrigation using soil moisture, evapotranspiration, or both within a novel baseline framework, together with irrigation estimates from other studies. We show that the synergy from using two equally important components in a joint approach within a baseline framework yields better irrigation estimates.
Hafsa Mahmood, Ty P. A. Ferré, Raphael J. M. Schneider, Simon Stisen, Rasmus R. Frederiksen, and Anders V. Christiansen
EGUsphere, https://doi.org/10.5194/egusphere-2023-1872, https://doi.org/10.5194/egusphere-2023-1872, 2023
Preprint withdrawn
Short summary
Short summary
Temporal drain flow dynamics and understanding of their underlying controlling factors are important for water resource management in tile-drained agricultural areas. This study examine whether simpler, more efficient machine learning (ML) models can provide acceptable solutions compared to traditional physics based models. We predicted drain flow time series in multiple catchments subject to a range of climatic and landscape conditions.
Søren J. Kragh, Rasmus Fensholt, Simon Stisen, and Julian Koch
Hydrol. Earth Syst. Sci., 27, 2463–2478, https://doi.org/10.5194/hess-27-2463-2023, https://doi.org/10.5194/hess-27-2463-2023, 2023
Short summary
Short summary
This study investigates the precision of irrigation estimates from a global hotspot of unsustainable irrigation practice, the Indus and Ganges basins. We show that irrigation water use can be estimated with high precision by comparing satellite and rainfed hydrological model estimates of evapotranspiration. We believe that our work can support sustainable water resource management, as it addresses the uncertainty of a key component of the water balance that remains challenging to quantify.
Julian Koch, Lars Elsgaard, Mogens H. Greve, Steen Gyldenkærne, Cecilie Hermansen, Gregor Levin, Shubiao Wu, and Simon Stisen
Biogeosciences, 20, 2387–2403, https://doi.org/10.5194/bg-20-2387-2023, https://doi.org/10.5194/bg-20-2387-2023, 2023
Short summary
Short summary
Utilizing peatlands for agriculture leads to large emissions of greenhouse gases worldwide. The emissions are triggered by lowering the water table, which is a necessary step in order to make peatlands arable. Many countries aim at reducing their emissions by restoring peatlands, which can be achieved by stopping agricultural activities and thereby raising the water table. We estimate a total emission of 2.6 Mt CO2-eq for organic-rich peatlands in Denmark and a potential reduction of 77 %.
Raphael Schneider, Julian Koch, Lars Troldborg, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci., 26, 5859–5877, https://doi.org/10.5194/hess-26-5859-2022, https://doi.org/10.5194/hess-26-5859-2022, 2022
Short summary
Short summary
Hydrological models at high spatial resolution are computationally expensive. However, outputs from such models, such as the depth of the groundwater table, are often desired in high resolution. We developed a downscaling algorithm based on machine learning that allows us to increase spatial resolution of hydrological model outputs, alleviating computational burden. We successfully applied the downscaling algorithm to the climate-change-induced impacts on the groundwater table across Denmark.
Eva Sebok, Hans Jørgen Henriksen, Ernesto Pastén-Zapata, Peter Berg, Guillaume Thirel, Anthony Lemoine, Andrea Lira-Loarca, Christiana Photiadou, Rafael Pimentel, Paul Royer-Gaspard, Erik Kjellström, Jens Hesselbjerg Christensen, Jean Philippe Vidal, Philippe Lucas-Picher, Markus G. Donat, Giovanni Besio, María José Polo, Simon Stisen, Yvan Caballero, Ilias G. Pechlivanidis, Lars Troldborg, and Jens Christian Refsgaard
Hydrol. Earth Syst. Sci., 26, 5605–5625, https://doi.org/10.5194/hess-26-5605-2022, https://doi.org/10.5194/hess-26-5605-2022, 2022
Short summary
Short summary
Hydrological models projecting the impact of changing climate carry a lot of uncertainty. Thus, these models usually have a multitude of simulations using different future climate data. This study used the subjective opinion of experts to assess which climate and hydrological models are the most likely to correctly predict climate impacts, thereby easing the computational burden. The experts could select more likely hydrological models, while the climate models were deemed equally probable.
Rena Meyer, Wenmin Zhang, Søren Julsgaard Kragh, Mie Andreasen, Karsten Høgh Jensen, Rasmus Fensholt, Simon Stisen, and Majken C. Looms
Hydrol. Earth Syst. Sci., 26, 3337–3357, https://doi.org/10.5194/hess-26-3337-2022, https://doi.org/10.5194/hess-26-3337-2022, 2022
Short summary
Short summary
The amount and spatio-temporal distribution of soil moisture, the water in the upper soil, is of great relevance for agriculture and water management. Here, we investigate whether the established downscaling algorithm combining different satellite products to estimate medium-scale soil moisture is applicable to higher resolutions and whether results can be improved by accounting for land cover types. Original satellite data and downscaled soil moisture are compared with ground observations.
Raphael Schneider, Hans Jørgen Henriksen, and Simon Stisen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2019-685, https://doi.org/10.5194/hess-2019-685, 2020
Revised manuscript not accepted
Short summary
Short summary
For groundwater models to deliver reliable results, their parameters often have to be estimated in an optimization process guided by some measure of model performance. In this context, we suggest the use of a novel performance metric, which is less prone to a fit to inadequate observations than the most frequently used metrics based on squared errors. Hence, calibration is more robust to deficiencies in model and observational data, which are common especially in larger scale models.
Julian Koch, Helen Berger, Hans Jørgen Henriksen, and Torben Obel Sonnenborg
Hydrol. Earth Syst. Sci., 23, 4603–4619, https://doi.org/10.5194/hess-23-4603-2019, https://doi.org/10.5194/hess-23-4603-2019, 2019
Short summary
Short summary
This study explores novel modelling avenues using machine learning in combination with process-based models to predict the shallow water table at high spatial resolution. Due to climate change and anthropogenic impacts, the shallow groundwater is rising in many parts of the world. In order to adapt to risks induced by groundwater flooding, new modelling tools need to emerge. In this study, we found that machine learning is capable of reaching the required accuracy and resolution.
Julian Koch, Mehmet Cüneyd Demirel, and Simon Stisen
Geosci. Model Dev., 11, 1873–1886, https://doi.org/10.5194/gmd-11-1873-2018, https://doi.org/10.5194/gmd-11-1873-2018, 2018
Short summary
Short summary
Our work addresses a key challenge in earth system modelling: how to optimally exploit the information contained in satellite remote sensing observations in the calibration of such models. For this we thoroughly test a number of measures that quantify the fit between an observed and a simulated spatial pattern. We acknowledge the difficulties associated with such a comparison and suggest using measures that regard multiple aspects of spatial information, i.e. magnitude and variability.
Mehmet C. Demirel, Juliane Mai, Gorka Mendiguren, Julian Koch, Luis Samaniego, and Simon Stisen
Hydrol. Earth Syst. Sci., 22, 1299–1315, https://doi.org/10.5194/hess-22-1299-2018, https://doi.org/10.5194/hess-22-1299-2018, 2018
Short summary
Short summary
Satellite data offer great opportunities to improve spatial model predictions by means of spatially oriented model evaluations. In this study, satellite images are used to observe spatial patterns of evapotranspiration at the land surface. These spatial patterns are utilized in combination with streamflow observations in a model calibration framework including a novel spatial performance metric tailored to target the spatial pattern performance of a catchment-scale hydrological model.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
Short summary
Short summary
Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
G. Mendiguren, M. Pilar Martín, H. Nieto, J. Pacheco-Labrador, and S. Jurdao
Biogeosciences, 12, 5523–5535, https://doi.org/10.5194/bg-12-5523-2015, https://doi.org/10.5194/bg-12-5523-2015, 2015
R. Guzinski, H. Nieto, S. Stisen, and R. Fensholt
Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, https://doi.org/10.5194/hess-19-2017-2015, 2015
Short summary
Short summary
The study compared evapotranspiration (ET) modelled by two remote sensing models and one hydrological model in a river catchment in Denmark. The results show that the spatial patterns of ET produced by the remote sensing models are more similar to each other than to the fluxes produced by the hydrological model. This indicates potential benefits to the hydrological modelling community from integrating spatial information derived through remote sensing methodology into the hydrological models.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
Short summary
Short summary
A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
J. Koch, X. He, K. H. Jensen, and J. C. Refsgaard
Hydrol. Earth Syst. Sci., 18, 2907–2923, https://doi.org/10.5194/hess-18-2907-2014, https://doi.org/10.5194/hess-18-2907-2014, 2014
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
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
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.
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
Short summary
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.
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.
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
Abbott, M. B., Bathurst, J. C., Cunge, J. A., O'Connell, P. E., and Rasmussen, J.: An introduction to the European Hydrological System – Systeme Hydrologique Europeen, “SHE”, 1: History and philosophy of a physically-based, distributed modelling system, J. Hydrol., 87, 45–59, https://doi.org/10.1016/0022-1694(86)90114-9, 1986.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration-Guidelines for computing crop water requirements-FAO Irrigation and drainage paper 56, FAO, Rome, 300, D05109, 1998.
Berrisford, P., Dee, D. P., Poli, P., Brugge, R., Fielding, K., Fuentes, M., Kållberg, P. W., Kobayashi, S., Uppala, S., and Simmons, A.: The ERA-Interim archive Version 2.0, in: ERA Report Series, ECMWF, Shinfield Park, Reading, 23, 2011.
Bertoldi, G., Notarnicola, C., Leitinger, G., Endrizzi, S., Zebisch, M., Della Chiesa, S., and Tappeiner, U.: Topographical and ecohydrological controls on land surface temperature in an alpine catchment, Ecohydrology, 3, 189–204, https://doi.org/10.1002/eco.129, 2010.
Boegh, E., Thorsen, M., Butts, M. B., Hansen, S., Christiansen, J. S., Abrahamsen, P., Hasager, C. B., Jensen, N. O., van der Keur, P., Refsgaard, J. C., Schelde, K., Soegaard, H., and Thomsen, A.: Incorporating remote sensing data in physically based distributed agro-hydrological modelling, J. Hydrol., 287, 279–299, https://doi.org/10.1016/j.jhydrol.2003.10.018, 2004.
Bowen, I. S.: The ratio of heat losses by conduction and by evaporation from any water surface, Phys. Rev., 27, 779–787, https://doi.org/10.1103/PhysRev.27.779, 1926.
Breuning Madsen, H. and Platou, S. W.: Land Use Planning in Denmark, The Use of Soil Physical Data in Irrigation Planning, 14, 267–276, 1983.
Brutsaert, W. and Sugita, M.: Application of self-preservation in the diurnal evolution of the surface energy budget to determine daily evaporation, J. Geophys. Res.-Atmos., 97, 18377–18382, https://doi.org/10.1029/92JD00255, 1992.
Campbell, G. S. A. and Norman, J. M.: An Introduction to Environmental BIophysics: 2nd Edn., Springer London, Limited, 1998.
Chen, J., Famigliett, J. S., Scanlon, B. R., and Rodell, M.: Groundwater Storage Changes: Present Status from GRACE Observations, Surv. Geophys., 37, 397–417, https://doi.org/10.1007/s10712-015-9332-4, 2016.
Clark, M. P., Nijssen, B., Lundquist, J. D., Kavetski, D., Rupp, D. E., Woods, R. A., Freer, J. E., Gutmann, E. D., Wood, A. W., Brekke, L. D., Arnold, J. R., Gochis, D. J., and Rasmussen, R. M.: A unified approach for process-based hydrologic modeling: 1. Modeling concept, Water Resour. Res., 51, 2498–2514, https://doi.org/10.1002/2015WR017198, 2015.
Cong, N., Piao, S., Chen, A., Wang, X., Lin, X., Chen, S., Han, S., Zhou, G., and Zhang, X.: Spring vegetation green-up date in China inferred from SPOT NDVI data: A multiple model analysis, Agr. Forest Meteorol., 165, 104–113, https://doi.org/10.1016/j.agrformet.2012.06.009, 2012.
Conradt, T., Wechsung, F., and Bronstert, A.: Three perceptions of the evapotranspiration landscape: comparing spatial patterns from a distributed hydrological model, remotely sensed surface temperatures, and sub-basin water balances, Hydrol. Earth Syst. Sci., 17, 2947–2966, https://doi.org/10.5194/hess-17-2947-2013, 2013.
Corbari, C. and Mancini, M.: Calibration and validation of a distributed energy-water balance model using satellite data of land surface temperature and ground discharge measurements, J. Hydrometeorol., 15, 376–392, 10.1175/JHM-D-12-0173.1, 2014.
Corbari, C., Mancini, M., Li, J., and Su, Z.: Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration?, Hydrolog. Sci. J., 60, 202–217, https://doi.org/10.1080/02626667.2013.866709, 2015.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J. J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J. N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011.
Fang, Z., Bogena, H., Kollet, S., Koch, J., and Vereecken, H.: Spatio-temporal validation of long-term 3D hydrological simulations of a forested catchment using empirical orthogonal functions and wavelet coherence analysis, J. Hydrol., 529, 1754–1767, https://doi.org/10.1016/j.jhydrol.2015.08.011, 2015.
Freeze, R. A. and Harlan, R. L.: Blueprint for a physically-based, digitally-simulated hydrologic response model, J. Hydrol., 9, 237–258, 1969.
Gentine, P., Entekhabi, D., Chehbouni, A., Boulet, G., and Duchemin, B.: Analysis of evaporative fraction diurnal behaviour, Agr. Forest Meteorol., 143, 13–29, https://doi.org/10.1016/j.agrformet.2006.11.002, 2007.
Githui, F., Selle, B., and Thayalakumaran, T.: Recharge estimation using remotely sensed evapotranspiration in an irrigated catchment in southeast Australia, Hydrol. Process., 26, 1379–1389, https://doi.org/10.1002/hyp.8274, 2012.
Graf, A., Bogena, H. R., Drüe, C., Hardelauf, H., Pütz, T., Heinemann, G., and Vereecken, H.: Spatiotemporal relations between water budget components and soil water content in a forested tributary catchment, Water Resour. Res., 50, 4837–4857, https://doi.org/10.1002/2013WR014516, 2014.
Grayson, R. B. and Blöschl, G.: Spatial modelling of catchment dynamics, in: Spatial Patterns in Catchment Hydrology: Observations and Modelling, edited by: Grayson, R. B. and Blöschl, G., Cambridge University Press, 51–81, 2000.
Gutman, G. and Ignatov, A.: The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models, Int. J. Remote Sens., 19, 1533–1543, https://doi.org/10.1080/014311698215333, 1998.
Guzinski, R., Anderson, M. C., Kustas, W. P., Nieto, H., and Sandholt, I.: Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day-night MODIS observations, Hydrol. Earth Syst. Sci., 17, 2809–2825, https://doi.org/10.5194/hess-17-2809-2013, 2013.
Guzinski, R., Nieto, H., Stisen, S., and Fensholt, R.: Inter-comparison of energy balance and hydrological models for land surface energy flux estimation over a whole river catchment, Hydrol. Earth Syst. Sci., 19, 2017–2036, https://doi.org/10.5194/hess-19-2017-2015, 2015.
Hansen, J. R., Refsgaard, J. C., Ernstsen, V., Hansen, S., Styczen, M., and Poulsen, R. N.: An integrated and physically based nitrogen cycle catchment model, Hydrol. Res., 40, 347–363, https://doi.org/10.2166/nh.2009.035, 2009.
Hendricks Franssen, H. J., Brunner, P., Makobo, P., and Kinzelbach, W.: Equally likely inverse solutions to a groundwater flow problem including pattern information from remote sensing images, Water Resour. Res., 44, W01419, https://doi.org/10.1029/2007WR006097, 2008.
Henriksen, H. J., Troldborg, L., Nyegaard, P., Sonnenborg, T. O., Refsgaard, J. C., and Madsen, B.: Methodology for construction, calibration and validation of a national hydrological model for Denmark, J. Hydrol., 280, 52–71, https://doi.org/10.1016/S0022-1694(03)00186-0, 2003.
Henriksen, H. J., Troldborg, L., Højberg, A. L., and Refsgaard, J. C.: Assessment of exploitable groundwater resources of Denmark by use of ensemble resource indicators and a numerical groundwater–surface water model, J. Hydrol., 348, 224–240, https://doi.org/10.1016/j.jhydrol.2007.09.056, 2008.
Højberg, A. L., Troldborg, L., Stisen, S., Christensen, B. B. S., and Henriksen, H. J.: Stakeholder driven update and improvement of a national water resources model, Environ. Modell. Softw., 40, 202–213, https://doi.org/10.1016/j.envsoft.2012.09.010, 2013.
Immerzeel, W. W. and Droogers, P.: Calibration of a distributed hydrological model based on satellite evapotranspiration, J. Hydrol., 349, 411–424, https://doi.org/10.1016/j.jhydrol.2007.11.017, 2008.
Immerzeel, W. W., Droogers, P., de Jong, S. M., and Bierkens, M. F. P.: Large-scale monitoring of snow cover and runoff simulation in Himalayan river basins using remote sensing, Remote Sens. Environ., 113, 40–49, https://doi.org/10.1016/j.rse.2008.08.010, 2009.
Jönsson, P. and Eklundh, L.: Seasonality extraction by function fitting to time-series of satellite sensor data, IEEE T. Geosci. Remote, 40, 1824–1832, https://doi.org/10.1109/TGRS.2002.802519, 2002.
Jönsson, P. and Eklundh, L.: TIMESAT – a program for analyzing time-series of satellite sensor data, Comput. Geosci., 30, 833–845, https://doi.org/10.1016/j.cageo.2004.05.006, 2004.
Kalma, J. D., McVicar, T. R., and McCabe, M. F.: Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data, Surv. Geophys., 29, 421–469, https://doi.org/10.1007/s10712-008-9037-z, 2008.
Karlsson, I. B., Sonnenborg, T. O., Refsgaard, J. C., Trolle, D., Børgesen, C. D., Olesen, J. E., Jeppesen, E., and Jensen, K. H.: Combined effects of climate models, hydrological model structures and land use scenarios on hydrological impacts of climate change, J. Hydrol., 535, 301–317, https://doi.org/10.1016/j.jhydrol.2016.01.069, 2016.
Koch, J., Jensen, K. H., and Stisen, S.: Toward a true spatial model evaluation in distributed hydrological modeling: Kappa statistics, Fuzzy theory, and EOF-analysis benchmarked by the human perception and evaluated against a modeling case study, Water Resour. Res., 51, 1225–1246, https://doi.org/10.1002/2014WR016607, 2015.
Koch, J., Siemann, A., Stisen, S., and Sheffield, J.: Spatial validation of large-scale land surface models against monthly land surface temperature patterns using innovative performance metrics, J. Geophys. Res.-Atmos., 121, 5430–5452, https://doi.org/10.1002/2015JD024482, 2016.
Koch, J., Mendiguren, G., Mariethoz, G., and Stisen, S.: Spatial Sensitivity Analysis of Simulated Land Surface Patterns in a Catchment Model Using a Set of Innovative Spatial Performance Metrics, J. Hydrometeorol., 18, 1121–1142, https://doi.org/10.1175/jhm-d-16-0148.1, 2017.
Komatsu, H.: Forest categorization according to dry-canopy evaporation rates in the growing season: comparison of the Priestley–Taylor coefficient values from various observation sites, Hydrol. Process., 19, 3873–3896, https://doi.org/10.1002/hyp.5987, 2005.
Kustas, W. P. and Norman, J. M.: Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover, Agr. Forest Meteorol., 94, 13–29, https://doi.org/10.1016/S0168-1923(99)00005-2, 1999.
Lettenmaier, D. P., Alsdorf, D., Dozier, J., Huffman, G. J., Pan, M., and Wood, E. F.: Inroads of remote sensing into hydrologic science during the WRR era, Water Resour. Res., 51, 7309–7342, https://doi.org/10.1002/2015WR017616, 2015.
Li, H. T., Brunner, P., Kinzelbach, W., Li, W. P., and Dong, X. G.: Calibration of a groundwater model using pattern information from remote sensing data, J. Hydrol., 377, 120–130, https://doi.org/10.1016/j.jhydrol.2009.08.012, 2009.
Mascaro, G., Vivoni, E. R., and Méndez-Barroso, L. A.: Hyperresolution hydrologic modeling in a regional watershed and its interpretation using empirical orthogonal functions, Adv. Water Resour., 83, 190–206, https://doi.org/10.1016/j.advwatres.2015.05.023, 2015.
Maxwell, R. M. and Kollet, S. J.: Interdependence of groundwater dynamics and land-energy feedbacks under climate change, Nat. Geosci., 1, 665–669, 2008.
Mendiguren, G., Pilar Martín, M., Nieto, H., Pacheco-Labrador, J., and Jurdao, S.: Seasonal variation in grass water content estimated from proximal sensing and MODIS time series in a Mediterranean Fluxnet site, Biogeosciences, 12, 5523–5535, https://doi.org/10.5194/bg-12-5523-2015, 2015.
Miralles, D. G., Holmes, T. R. H., De Jeu, R. A. M., Gash, J. H., Meesters, A. G. C. A., and Dolman, A. J.: Global land-surface evaporation estimated from satellite-based observations, Hydrol. Earth Syst. Sci., 15, 453–469, https://doi.org/10.5194/hess-15-453-2011, 2011.
Mu, Q., Heinsch, F. A., Zhao, M., and Running, S. W.: Development of a global evapotranspiration algorithm based on MODIS and global meteorology data, Remote Sens. Environ., 111, 519–536, https://doi.org/10.1016/j.rse.2007.04.015, 2007.
Norman, J. M., Kustas, W. P., and Humes, K. S.: Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature, Agr. Forest Meteorol., 77, 263–293, https://doi.org/10.1016/0168-1923(95)02265-Y, 1995.
Perry, M. A. and Niemann, J. D.: Analysis and estimation of soil moisture at the catchment scale using EOFs, J. Hydrol., 334, 388–404, https://doi.org/10.1016/j.jhydrol.2006.10.014, 2007.
Priestley, C. H. B. and Taylor, R. J.: On the Assessment of Surface Heat Flux and Evaporation Using Large-Scale Parameters, Mon. Weather Rev., 100, 81–92, https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2, 1972.
Rajib, M. A., Merwade, V., and Yu, Z.: Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture, J. Hydrol., 536, 192–207, https://doi.org/10.1016/j.jhydrol.2016.02.037, 2016.
Refsgaard, J. C.: Parameterisation, calibration and validation of distributed hydrological models, J. Hydrol., 198, 69–97, https://doi.org/10.1016/S0022-1694(96)03329-X, 1997.
Refsgaard, J. C., Stisen, S., Højberg, A. L., Olsen, M., Henriksen, H. J., Børgesen, C. D., Vejen, F., Kern-Hansen, C., and Blicher-Mathiesen, G.: Danmarks og grønlands geologiske undersøgelse rapport 2011/77, Geological Survey of Danmark and Greenland (GEUS), 2011.
Richey, A. S., Thomas, B. F., Lo, M.-H., Reager, J. T., Famiglietti, J. S., Voss, K., Swenson, S., and Rodell, M.: Quantifying renewable groundwater stress with GRACE, Water Resour. Res., 51, 5217–5238, https://doi.org/10.1002/2015WR017349, 2015.
Ridler, M.-E., Madsen, H., Stisen, S., Bircher, S., and Fensholt, R.: Assimilation of SMOS-derived soil moisture in a fully integrated hydrological and soil-vegetation-atmosphere transfer model in Western Denmark, Water Resour. Res., 50, 8962–8981, https://doi.org/10.1002/2014WR015392, 2014.
Rientjes, T. H. M., Muthuwatta, L. P., Bos, M. G., Booij, M. J., and Bhatti, H. A.: Multi-variable calibration of a semi-distributed hydrological model using streamflow data and satellite-based evapotranspiration, J. Hydrol., 505, 276–290, https://doi.org/10.1016/j.jhydrol.2013.10.006, 2013.
Ringgaard, R., Herbst, M., Friborg, T., Schelde, K., Thomsen, A. G., and Soegaard, H.: Energy Fluxes above Three Disparate Surfaces in a Temperate Mesoscale Coastal Catchment, Vadose Zone J., 10, 54–66, https://doi.org/10.2136/vzj2009.0181, 2011.
Rodell, M., Velicogna, I., and Famiglietti, J. S.: Satellite-based estimates of groundwater depletion in India, Nature, 460, 999–1002, 2009.
Rouse, J. W., Haas, R. H., Deering, D. W., and Schell, J. A.: Monitoring the vernal advancement and retrogradation (green wave effect) of natural vegetation, Goddard Space Flight Center, Greenbelt, MD, 87, 1973.
Ruiz-Pérez, G., Koch, J., Manfreda, S., Caylor, K., and Francés, F.: Calibration of a parsimonious distributed ecohydrological daily model in a data scarce basin using exclusively the spatio-temporal variation of NDVI, Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-573, in review, 2016.
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.
Savitzky, A. and Golay, M. J. E.: Smoothing and Differentiation of Data by Simplified Least Squares Procedures, Anal. Chem., 36, 1627–1639, https://doi.org/10.1021/ac60214a047, 1964.
Schuurmans, J. M., Troch, P. A., Veldhuizen, A. A., Bastiaanssen, W. G. M., and Bierkens, M. F. P.: Assimilation of remotely sensed latent heat flux in a distributed hydrological model, Adv. Water Resour., 26, 151–159, https://doi.org/10.1016/S0309-1708(02)00089-1, 2003.
Stisen, S., Jensen, K. H., Sandholt, I., and Grimes, D. I. F.: A remote sensing driven distributed hydrological model of the Senegal River basin, J. Hydrol., 354, 131–148, https://doi.org/10.1016/j.jhydrol.2008.03.006, 2008.
Stisen, S., McCabe, M. F., Refsgaard, J. C., Lerer, S., and Butts, M. B.: Model parameter analysis using remotely sensed pattern information in a multi-constraint framework, J. Hydrol., 409, 337–349, https://doi.org/10.1016/j.jhydrol.2011.08.030, 2011.
Stisen, S., Højberg, A. L., Troldborg, L., Refsgaard, J. C., Christensen, B. S. B., Olsen, M., and Henriksen, H. J.: On the importance of appropriate precipitation gauge catch correction for hydrological modelling at mid to high latitudes, Hydrol. Earth Syst. Sci., 16, 4157–4176, https://doi.org/10.5194/hess-16-4157-2012, 2012.
Sugita, M. and Brutsaert, W.: Daily evaporation over a region from lower boundary layer profiles measured with radiosondes, Water Resour. Res., 27, 747–752, https://doi.org/10.1029/90WR02706, 1991.
Sutanudjaja, E. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time, Remote Sens. Environ., 138, 172–188, https://doi.org/10.1016/j.rse.2013.07.022, 2013.
van der Keur, P., Hansen, J. R., Hansen, S., and Refsgaard, J. C.: Uncertainty in Simulation of Nitrate Leaching at Field and Catchment Scale within the Odense River Basin, Vadose Zone J., 7, 10–21, https://doi.org/10.2136/vzj2006.0186, 2008.
Vansteenkiste, T., Tavakoli, M., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., and Willems, P.: Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation, J. Hydrol., 511, 335–349, https://doi.org/10.1016/j.jhydrol.2014.01.050, 2014.
Vereecken, H., Pachepsky, Y., Simmer, C., Rihani, J., Kunoth, A., Korres, W., Graf, A., Franssen, H. J. H., Thiele-Eich, I., and Shao, Y.: On the role of patterns in understanding the functioning of soil-vegetation-atmosphere systems, J. Hydrol., 542, 63–86, https://doi.org/10.1016/j.jhydrol.2016.08.053, 2016.
Wanders, N., Bierkens, M. F. P., de Jong, S. M., de Roo, A., and Karssenberg, D.: The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models, Water Resour. Res., 50, 6874–6891, https://doi.org/10.1002/2013WR014639, 2014.
Wang, D.-C., Zhang, G.-L., Zhao, M.-S., Pan, X.-Z., Zhao, Y.-G., Li, D.-C., and Macmillan, B.: Retrieval and Mapping of Soil Texture Based on Land Surface Diurnal Temperature Range Data from MODIS, PLOS ONE, 10, e0129977, https://doi.org/10.1371/journal.pone.0129977, 2015.
Wang, L., Koike, T., Yang, K., and Yeh, P. J.-F.: Assessment of a distributed biosphere hydrological model against streamflow and MODIS land surface temperature in the upper Tone River Basin, J. Hydrol., 377, 21–34, https://doi.org/10.1016/j.jhydrol.2009.08.005, 2009.
Windolf, J., Thodsen, H., Troldborg, L., Larsen, S. E., Bøgestrand, J., Ovesen, N. B., and Kronvang, B.: A distributed modelling system for simulation of monthly runoff and nitrogen sources, loads and sinks for ungauged catchments in Denmark, J. Environ. Monitor., 13, 2645–2658, https://doi.org/10.1039/c1em10139k, 2011.
Yan, J. and Smith, K. R.: Simulation of integrated surface water and ground water systems – model formulation1, J. Am. Water Resour. As., 30, 879–890, https://doi.org/10.1111/j.1752-1688.1994.tb03336.x, 1994.
Zhang, D., Madsen, H., Ridler, M. E., Kidmose, J., Jensen, K. H., and Refsgaard, J. C.: Multivariate hydrological data assimilation of soil moisture and groundwater head, Hydrol. Earth Syst. Sci., 20, 4341–4357, https://doi.org/10.5194/hess-20-4341-2016, 2016.
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.
The present study is focused on the spatial pattern evaluation of two models and describes the...
