Articles | Volume 20, issue 7
https://doi.org/10.5194/hess-20-2987-2016
© Author(s) 2016. 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-20-2987-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Insights into the water mean transit time in a high-elevation tropical ecosystem
Giovanny M. Mosquera
CORRESPONDING AUTHOR
Departamento de Recursos Hídricos y Ciencias Ambientales &
Facultad de Ciencias Agropecuarias, Universidad de Cuenca, Av. 12 de Abril,
Cuenca, 010150, Ecuador
Department of Biological and Ecological Engineering, Oregon State
University, Corvallis, 97331, USA
Catalina Segura
Department of Forestry Engineering, Resources, and Management, Oregon
State University, Corvallis, 97331, USA
Kellie B. Vaché
Department of Biological and Ecological Engineering, Oregon State
University, Corvallis, 97331, USA
David Windhorst
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for Biosystems, Land Use and Nutrition (IFZ), Justus Liebig
University Gießen, Gießen, 35392, Germany
Lutz Breuer
Institute for Landscape Ecology and Resources Management (ILR),
Research Centre for Biosystems, Land Use and Nutrition (IFZ), Justus Liebig
University Gießen, Gießen, 35392, Germany
Centre for International Development and Environmental Research,
Justus Liebig University Gießen, Gießen, 35392, Germany
Patricio Crespo
Departamento de Recursos Hídricos y Ciencias Ambientales &
Facultad de Ciencias Agropecuarias, Universidad de Cuenca, Av. 12 de Abril,
Cuenca, 010150, Ecuador
Related authors
No articles found.
Max Weißenborn, Lutz Breuer, and Tobias Houska
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-183, https://doi.org/10.5194/hess-2024-183, 2024
Revised manuscript under review for HESS
Short summary
Short summary
Our study compares neural network models for predicting discharge in ungauged basins. We evaluated Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) and Gated Recurrent Units (GRU) using 28 years of weather data. CNN showed the best accuracy, while GRU were faster and nearly as accurate. Adding static features improved all models. The research enhances flood forecasting and water management in regions lacking direct measurements, offering efficient and accurate predictive tools.
Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl
Biogeosciences, 20, 5029–5067, https://doi.org/10.5194/bg-20-5029-2023, https://doi.org/10.5194/bg-20-5029-2023, 2023
Short summary
Short summary
Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
Ricky Mwangada Mwanake, Gretchen Maria Gettel, Elizabeth Gachibu Wangari, Clarissa Glaser, Tobias Houska, Lutz Breuer, Klaus Butterbach-Bahl, and Ralf Kiese
Biogeosciences, 20, 3395–3422, https://doi.org/10.5194/bg-20-3395-2023, https://doi.org/10.5194/bg-20-3395-2023, 2023
Short summary
Short summary
Despite occupying <1 %; of the globe, streams are significant sources of greenhouse gas (GHG) emissions. In this study, we determined anthropogenic effects on GHG emissions from streams. We found that anthropogenic-influenced streams had up to 20 times more annual GHG emissions than natural ones and were also responsible for seasonal peaks. Anthropogenic influences also altered declining GHG flux trends with stream size, with potential impacts on stream-size-based spatial upscaling techniques.
Jaqueline Stenfert Kroese, John N. Quinton, Suzanne R. Jacobs, Lutz Breuer, and Mariana C. Rufino
SOIL, 7, 53–70, https://doi.org/10.5194/soil-7-53-2021, https://doi.org/10.5194/soil-7-53-2021, 2021
Short summary
Short summary
Particulate macronutrient concentrations were up to 3-fold higher in a natural forest catchment compared to fertilized agricultural catchments. Although the particulate macronutrient concentrations were lower in the smallholder agriculture catchment, because of higher sediment loads from that catchment, the total particulate macronutrient loads were higher. Land management practices should be focused on agricultural land to reduce the loss of soil carbon and nutrients to the stream.
Angel Monsalve, Catalina Segura, Nicole Hucke, and Scott Katz
Earth Surf. Dynam., 8, 825–839, https://doi.org/10.5194/esurf-8-825-2020, https://doi.org/10.5194/esurf-8-825-2020, 2020
Short summary
Short summary
Part of the inaccuracies when estimating bed load transport in
gravel-bed rivers is because we are not considering the wide distributions of shear stress in these systems. We modified a subsurface-based bed load transport equation to include these distributions. By doing so, our approach accurately predicts bed load transport rates when the pavement layer is still present, while the original one predicts zero transport. For high flows, our method had similar performance to the original equation.
Amani Mahindawansha, Christoph Külls, Philipp Kraft, and Lutz Breuer
Hydrol. Earth Syst. Sci., 24, 3627–3642, https://doi.org/10.5194/hess-24-3627-2020, https://doi.org/10.5194/hess-24-3627-2020, 2020
Short summary
Short summary
Stable isotopes of soil water are an effective tool to reveal soil hydrological processes in irrigated agricultural fields. Flow mechanisms and isotopic patterns of soil water in the soil matrix differ, depending on the crop and irrigation practices. Isotope data supported the fact that unproductive water losses via evaporation can be reduced by introducing dry seasonal crops to the crop rotation system.
Michael C. Thrun, Alfred Ultsch, and Lutz Breuer
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2020-87, https://doi.org/10.5194/gmd-2020-87, 2020
Revised manuscript not accepted
Short summary
Short summary
We propose an explainable AI (XAI) framework for times series describing water quality & environmental parameters. The relationship between parameters is investigated by swarm based cluster analysis designed to find similar days within & dissimilar days between clusters. Resulting clusters define three states of water bodies & are visualized by a topographic map of high-dimensional structures. Rules generated by the XAI system explain clusters & improve the understanding of aquatic environments.
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.
Sebastian Multsch, Maarten S. Krol, Markus Pahlow, André L. C. Assunção, Alberto G. O. P. Barretto, Quirijn de Jong van Lier, and Lutz Breuer
Hydrol. Earth Syst. Sci., 24, 307–324, https://doi.org/10.5194/hess-24-307-2020, https://doi.org/10.5194/hess-24-307-2020, 2020
Short summary
Short summary
Expanding irrigation in agriculture is one of Brazil's strategies to increase production. In this study the amount of water required to grow the main crops has been calculated and compared to the water that is available in rivers at least 95 % of the time. Future decisions regarding expanding irrigated cropping areas must, while intensifying production practices, consider the likely regional effects on water scarcity levels, in order to reach sustainable agricultural production.
Adam S. Ward, Steven M. Wondzell, Noah M. Schmadel, Skuyler Herzog, Jay P. Zarnetske, Viktor Baranov, Phillip J. Blaen, Nicolai Brekenfeld, Rosalie Chu, Romain Derelle, Jennifer Drummond, Jan H. Fleckenstein, Vanessa Garayburu-Caruso, Emily Graham, David Hannah, Ciaran J. Harman, Jase Hixson, Julia L. A. Knapp, Stefan Krause, Marie J. Kurz, Jörg Lewandowski, Angang Li, Eugènia Martí, Melinda Miller, Alexander M. Milner, Kerry Neil, Luisa Orsini, Aaron I. Packman, Stephen Plont, Lupita Renteria, Kevin Roche, Todd Royer, Catalina Segura, James Stegen, Jason Toyoda, Jacqueline Hager, and Nathan I. Wisnoski
Hydrol. Earth Syst. Sci., 23, 5199–5225, https://doi.org/10.5194/hess-23-5199-2019, https://doi.org/10.5194/hess-23-5199-2019, 2019
Short summary
Short summary
The movement of water and solutes between streams and their shallow, connected subsurface is important to many ecosystem functions. These exchanges are widely expected to vary with stream flow across space and time, but these assumptions are seldom tested across basin scales. We completed more than 60 experiments across a 5th-order river basin to document these changes, finding patterns in space but not time. We conclude space-for-time and time-for-space substitutions are not good assumptions.
Adam S. Ward, Jay P. Zarnetske, Viktor Baranov, Phillip J. Blaen, Nicolai Brekenfeld, Rosalie Chu, Romain Derelle, Jennifer Drummond, Jan H. Fleckenstein, Vanessa Garayburu-Caruso, Emily Graham, David Hannah, Ciaran J. Harman, Skuyler Herzog, Jase Hixson, Julia L. A. Knapp, Stefan Krause, Marie J. Kurz, Jörg Lewandowski, Angang Li, Eugènia Martí, Melinda Miller, Alexander M. Milner, Kerry Neil, Luisa Orsini, Aaron I. Packman, Stephen Plont, Lupita Renteria, Kevin Roche, Todd Royer, Noah M. Schmadel, Catalina Segura, James Stegen, Jason Toyoda, Jacqueline Hager, Nathan I. Wisnoski, and Steven M. Wondzell
Earth Syst. Sci. Data, 11, 1567–1581, https://doi.org/10.5194/essd-11-1567-2019, https://doi.org/10.5194/essd-11-1567-2019, 2019
Short summary
Short summary
Studies of river corridor exchange commonly focus on characterization of the physical, chemical, or biological system. As a result, complimentary systems and context are often lacking, which may limit interpretation. Here, we present a characterization of all three systems at 62 sites in a 5th-order river basin, including samples of surface water, hyporheic water, and sediment. These data will allow assessment of interacting processes in the river corridor.
Russell T. Bair, Catalina Segura, and Christopher M. Lorion
Earth Surf. Dynam., 7, 841–857, https://doi.org/10.5194/esurf-7-841-2019, https://doi.org/10.5194/esurf-7-841-2019, 2019
Short summary
Short summary
Large wood (LW) pieces are often part of fish habitat restoration projects. We investigated reach-scale changes after the addition of LW that are relevant to juvenile coho salmon. A survivable habitat for juvenile coho was characterized in terms of critical swim speed and bed stability. Model predictions showed that survivable habitat increased by 86–128 % in terms of flow velocity and bed stability. Our findings are applicable to stream restoration efforts throughout the Pacific Northwest.
Suzanne R. Jacobs, Edison Timbe, Björn Weeser, Mariana C. Rufino, Klaus Butterbach-Bahl, and Lutz Breuer
Hydrol. Earth Syst. Sci., 22, 4981–5000, https://doi.org/10.5194/hess-22-4981-2018, https://doi.org/10.5194/hess-22-4981-2018, 2018
Short summary
Short summary
This study investigated how land use affects stream water sources and flow paths in an East African tropical montane area. Rainfall was identified as an important stream water source in the forest and smallholder agriculture sub-catchments, while springs were more important in the commercial tea plantation sub-catchment. However, 15 % or less of the stream water consisted of water with an age of less than 3 months, indicating that groundwater plays an important role in all land use types.
Florian U. Jehn, Lutz Breuer, Tobias Houska, Konrad Bestian, and Philipp Kraft
Hydrol. Earth Syst. Sci., 22, 4565–4581, https://doi.org/10.5194/hess-22-4565-2018, https://doi.org/10.5194/hess-22-4565-2018, 2018
Short summary
Short summary
By realizing that hydrological models are not one single hypothesis, but an assemblage of many hypotheses, new ways to scrutinize hydrological models are needed. Up until now, studies concentrate on comparing existing models or built models incrementally. This approach here tries to tackle the problem the other way around. We construct a complex model, containing all processes important for the catchment, and deconstruct it step by step to understand the influence of single processes.
Natalie Orlowski, Lutz Breuer, Nicolas Angeli, Pascal Boeckx, Christophe Brumbt, Craig S. Cook, Maren Dubbert, Jens Dyckmans, Barbora Gallagher, Benjamin Gralher, Barbara Herbstritt, Pedro Hervé-Fernández, Christophe Hissler, Paul Koeniger, Arnaud Legout, Chandelle Joan Macdonald, Carlos Oyarzún, Regine Redelstein, Christof Seidler, Rolf Siegwolf, Christine Stumpp, Simon Thomsen, Markus Weiler, Christiane Werner, and Jeffrey J. McDonnell
Hydrol. Earth Syst. Sci., 22, 3619–3637, https://doi.org/10.5194/hess-22-3619-2018, https://doi.org/10.5194/hess-22-3619-2018, 2018
Short summary
Short summary
To extract water from soils for isotopic analysis, cryogenic water extraction is the most widely used removal technique. This work presents results from a worldwide laboratory intercomparison test of cryogenic extraction systems. Our results showed large differences in retrieved isotopic signatures among participating laboratories linked to interactions between soil type and properties, system setup, extraction efficiency, extraction system leaks, and each lab’s internal accuracy.
Tobias Houska, David Kraus, Ralf Kiese, and Lutz Breuer
Biogeosciences, 14, 3487–3508, https://doi.org/10.5194/bg-14-3487-2017, https://doi.org/10.5194/bg-14-3487-2017, 2017
Short summary
Short summary
CO2 and N2O are two prominent GHGs contributing to global warming. We combined measurement and modelling to quantify GHG emissions from adjacent arable, forest and grassland sites in Germany. Measured emissions reveal seasonal patterns and management effects like fertilizer application, tillage, harvest and grazing. Modelling helps to estimate the magnitude and uncertainty of not measurable C and N fluxes and indicates missing input source, e.g. nitrate uptake from groundwater.
Natalie Orlowski, Philipp Kraft, Jakob Pferdmenges, and Lutz Breuer
Hydrol. Earth Syst. Sci., 20, 3873–3894, https://doi.org/10.5194/hess-20-3873-2016, https://doi.org/10.5194/hess-20-3873-2016, 2016
Short summary
Short summary
The 2-year measurements of δ2H and δ18O in rainfall, stream, soil, and groundwater revealed that surface and groundwater are isotopically disconnected from the annual precipitation cycle but showed bidirectional interactions in the Schwingbach catchment. We established a hydrological model to estimate spatially distributed groundwater ages and flow directions. Our model revealed complex age dynamics and showed that runoff must have been stored in the catchment for much longer than event water.
A. H. Aubert, O. Schnepel, P. Kraft, T. Houska, I. Plesca, N. Orlowski, and L. Breuer
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-12-11591-2015, https://doi.org/10.5194/hessd-12-11591-2015, 2015
Revised manuscript not accepted
Short summary
Short summary
Studienlandschaft Schwingbachtal is an out-door full-scale study site since 2008. It deals with hydrology in an interdisciplinary approach and enhances active learning by various means (field monitoring, education trails and geocache). In order to adapt to the change in students habits and to suit better as a communication tool for the locals, it is newly equipped with augmented reality which adds virtual objects on the real landscape, making learning pleasant.
S. Multsch, J.-F. Exbrayat, M. Kirby, N. R. Viney, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 8, 1233–1244, https://doi.org/10.5194/gmd-8-1233-2015, https://doi.org/10.5194/gmd-8-1233-2015, 2015
Short summary
Short summary
Irrigation agriculture is required to sustain yields that allow feeding the world population. A robust assessment of irrigation requirement (IRR) relies on a sound quantification of evapotranspiration (ET). We prepared a multi-model ensemble considering several ET methods and investigate uncertainties in simulating IRR. More generally, we provide an example of the value of investigating the uncertainty in models that may be used to inform policy-making and to elaborate best management practices.
E. Timbe, D. Windhorst, R. Celleri, L. Timbe, P. Crespo, H.-G. Frede, J. Feyen, and L. Breuer
Hydrol. Earth Syst. Sci., 19, 1153–1168, https://doi.org/10.5194/hess-19-1153-2015, https://doi.org/10.5194/hess-19-1153-2015, 2015
Short summary
Short summary
Stream, soil and precipitation waters were collected in a tropical montane cloud forest catchment for 2 years and analyzed for stable water isotopes in order to infer transit time distribution functions and mean transit times for semi-steady-state conditions. Samples were aggregated to diverse sampling resolutions for checking the sensitivity of sampling frequency on lumped-model predictions. Results provide valuable information for the planning of future fieldwork in similar catchments.
D. Windhorst, P. Kraft, E. Timbe, H.-G. Frede, and L. Breuer
Hydrol. Earth Syst. Sci., 18, 4113–4127, https://doi.org/10.5194/hess-18-4113-2014, https://doi.org/10.5194/hess-18-4113-2014, 2014
E. Timbe, D. Windhorst, P. Crespo, H.-G. Frede, J. Feyen, and L. Breuer
Hydrol. Earth Syst. Sci., 18, 1503–1523, https://doi.org/10.5194/hess-18-1503-2014, https://doi.org/10.5194/hess-18-1503-2014, 2014
N. Orlowski, H.-G. Frede, N. Brüggemann, and L. Breuer
J. Sens. Sens. Syst., 2, 179–193, https://doi.org/10.5194/jsss-2-179-2013, https://doi.org/10.5194/jsss-2-179-2013, 2013
S. Multsch, Y. A. Al-Rumaikhani, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 6, 1043–1059, https://doi.org/10.5194/gmd-6-1043-2013, https://doi.org/10.5194/gmd-6-1043-2013, 2013
D. Windhorst, T. Waltz, E. Timbe, H.-G. Frede, and L. Breuer
Hydrol. Earth Syst. Sci., 17, 409–419, https://doi.org/10.5194/hess-17-409-2013, https://doi.org/10.5194/hess-17-409-2013, 2013
J.-F. Exbrayat, N. R. Viney, H.-G. Frede, and L. Breuer
Geosci. Model Dev., 6, 117–125, https://doi.org/10.5194/gmd-6-117-2013, https://doi.org/10.5194/gmd-6-117-2013, 2013
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Learning Landscape Features from Streamflow with Autoencoders
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Simulation-Based Inference for Parameter Estimation of Complex Watershed Simulators
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
Short summary
Short summary
We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
Short summary
A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary
Short summary
Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
Short summary
Short summary
Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
Short summary
Short summary
In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
Short summary
Short summary
It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
Short summary
Short summary
Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
Short summary
Short summary
This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
Short summary
Short summary
To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
Short summary
Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
Short summary
Short summary
In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-47, https://doi.org/10.5194/hess-2024-47, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature needed for challenging cases, associated with aridity and intermittent flow. Baseflow index, aridity, and soil/vegetation attributes strongly correlate with learned features, indicating their importance for streamflow prediction.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
Short summary
Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
Short summary
Short summary
This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
Short summary
Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
Short summary
Short summary
We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Short summary
Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
Short summary
How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Laia Estrada, Xavier Garcia, Joan Saló, Rafael Marcé, Antoni Munné, and Vicenç Acuña
EGUsphere, https://doi.org/10.5194/egusphere-2023-3007, https://doi.org/10.5194/egusphere-2023-3007, 2024
Short summary
Short summary
Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological modelling integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
Short summary
Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary
Short summary
Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Cited articles
Akaike, H.: A new look at the statistical model identification, IEEE T. Automat. Contr., 19, 716–723, https://doi.org/10.1109/TAC.1974.1100705, 1974.
Amin, I. E. and Campana, M. E.: A general lumped parameter model for the interpretation of tracer data and transit time calculation in hydrologic systems, J. Hydrol., 179, 1–21, https://doi.org/10.1016/0022-1694(95)02880-3, 1996.
Bethke, C. M. and Johnson, T. M.: Paradox of groundwater age: Correction, Geology, 30, 385–388, https://doi.org/10.1130/0091-7613(2002)030<0386:POGAC>2.0.CO;2, 2002.
Beven, K. and Binley, A.: The future of distributed models: Model calibration and uncertainty prediction, Hydrol. Process., 6, 279–298, https://doi.org/10.1002/hyp.3360060305, 1992.
Beven, K. and Freer, J.: Equifinality, data assimilation, and uncertainty estimation in mechanistic modelling of complex environmental systems using the GLUE methodology, J. Hydrol., 249, 11–29, https://doi.org/10.1016/S0022-1694(01)00421-8, 2001.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing area model of basin hydrology, Hydrol. Sci. Bull., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Birkel, C., Soulsby, C., and Tetzlaff, D.: Conceptual modelling to assess how the interplay of hydrological connectivity, catchment storage and tracer dynamics controls nonstationary water age estimates, Hydrol. Process., 29, 2956–2969, https://doi.org/10.1002/hyp.10414, 2015.
Broxton, P. D., Troch, P. A., and Lyon, S. W.: On the role of aspect to quantify water transit times in small mountainous catchments, Water Resour. Res., 45, https://doi.org/10.1029/2008WR007438, 2009.
Buytaert, W. and Beven, K.: Models as multiple working hypotheses: hydrological simulation of tropical alpine wetlands, Hydrol. Process., 25, 1784–1799, https://doi.org/10.1002/hyp.7936, 2011.
Buytaert, W., Célleri, R., De Bièvre, B., Cisneros, F., Wyseure, G., Deckers, J., and Hofstede, R.: Human impact on the hydrology of the Andean páramos, Earth-Sci. Rev., 79, 53–72, https://doi.org/10.1016/j.earscirev.2006.06.002, 2006.
Célleri, R. and Feyen, J.: The Hydrology of Tropical Andean Ecosystems: Importance, Knowledge Status, and Perspectives, Mt. Res. Dev., 29, 350–355, https://doi.org/10.1659/mrd.00007, 2009.
Coltorti, M. and Ollier, C.: Geomorphic and tectonic evolution of the Ecuadorian Andes, Geomorphology, 32, 1–19, https://doi.org/10.1016/S0169-555X(99)00036-7, 2000.
Córdova, M., Carrillo-Rojas, G., Crespo, P., Wilcox, B., and Célleri, R.: Evaluation of the Penman-Monteith (FAO 56 PM) Method for Calculating Reference Evapotranspiration Using Limited Data, Mt. Res. Dev., 35, 230–239, https://doi.org/10.1659/MRD-JOURNAL-D-14-0024.1, 2015.
Craig, H.: Standard for Reporting Concentrations of Deuterium and Oxygen-18 in Natural Waters, Science, 133, 1833–1834, https://doi.org/10.1126/science.133.3467.1833, 1961.
Crespo, P., Bücker, A., Feyen, J., Vaché, K. B., Frede, H.-G., and Breuer, L.: Preliminary evaluation of the runoff processes in a remote montane cloud forest basin using Mixing Model Analysis and Mean Transit Time, Hydrol. Process., 26, 3896–3910, https://doi.org/10.1002/hyp.8382, 2012.
Crespo, P. J., Feyen, J., Buytaert, W., Bücker, A., Breuer, L., Frede, H.-G., and Ramírez, M.: Identifying controls of the rainfall–runoff response of small catchments in the tropical Andes (Ecuador), J. Hydrol., 407, 164–174, https://doi.org/10.1016/j.jhydrol.2011.07.021, 2011.
Davies, J., Beven, K., Rodhe, A., Nyberg, L., and Bishop, K.: Integrated modeling of flow and residence times at the catchment scale with multiple interacting pathways, Water Resour. Res., 49, 4738–4750, https://doi.org/10.1002/wrcr.20377, 2013.
De Bièvre, B. and Calle, T.: Mountain Forum Bulletin 2011: Mountains and Green Economy, The Andean Páramo Project: Conserving biodiversity and hydrological services on the roof of the Andes, 2011.
Duvert, C., Stewart, M. K., Cendón, D. I., and Raiber, M.: Time series of tritium, stable isotopes and chloride reveal short-term variations in groundwater contribution to a stream, Hydrol. Earth Syst. Sci., 20, 257–277, https://doi.org/10.5194/hess-20-257-2016, 2016.
Etcheverry, D. and Perrochet, P.: Direct simulation of groundwater transit-time distributions using the reservoir theory, Hydrogeol. J., 8, 200–208, https://doi.org/10.1007/s100400050006, 2000.
Farrick, K. K. and Branfireun, B. A.: Flowpaths, source water contributions and water residence times in a Mexican tropical dry forest catchment, J. Hydrol., 529, 854–865, https://doi.org/10.1016/j.jhydrol.2015.08.059, 2015.
Freeze, R. A.: Role of subsurface flow in generating surface runoff: 2. Upstream source areas, Water Resour. Res., 8, 1272–1283, https://doi.org/10.1029/WR008i005p01272, 1972.
Goldsmith, G. R., Muñoz-Villers, L. E., Holwerda, F., McDonnell, J. J., Asbjornsen, H., and Dawson, T. E.: Stable isotopes reveal linkages among ecohydrological processes in a seasonally dry tropical montane cloud forest, Ecohydrology, 5, 779–790, https://doi.org/10.1002/eco.268, 2012.
Goller, R., Wilcke, W., Leng, M. J., Tobschall, H. J., Wagner, K., Valarezo, C., and Zech, W.: Tracing water paths through small catchments under a tropical montane rain forest in south Ecuador by an oxygen isotope approach, J. Hydrol., 308, 67–80, https://doi.org/10.1016/j.jhydrol.2004.10.022, 2005.
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.
Hale, V. C. and McDonnell, J. J.: Effect of bedrock permeability on stream base flow mean transit time scaling relations: 1. A multiscale catchment intercomparison, Water Resour. Res., 52, 1358–1374, https://doi.org/10.1002/2014WR016124, 2016.
Hale, V. C., McDonnell, J. J., Stewart, M. K., Solomon, D. K., Doolitte, J., Ice, G. G., and Pack, R. T.: Effect of bedrock permeability on stream base flow mean transit time scaling relationships: 2. Process study of storage and release, Water Resour. Res., 52, 1375–1397, https://doi.org/10.1002/2015WR017660, 2016.
Harman, C. J.: Time-variable transit time distributions and transport: Theory and application to storage-dependent transport of chloride in a watershed, Water Resour. Res., 51, 1–30, https://doi.org/10.1002/2014WR015707, 2015.
Heidbüchel, I., Troch, P. A., Lyon, S. W., and Weiler, M.: The master transit time distribution of variable flow systems, Water Resour. Res., 48, W06520, https://doi.org/10.1029/2011WR011293, 2012.
Hewlett, J. D.: Soil moisture as a source of base flow from steep mountain watersheds, US Dept of Agriculture, Forest Service, Southeastern Forest Experiment Station, Asheville, N.C., 1961.
Hrachowitz, M., Soulsby, C., Tetzlaff, D., Dawson, J. J. C., and Malcolm, I. A.: Regionalization of transit time estimates in montane catchments by integrating landscape controls, Water Resour. Res., 45, https://doi.org/10.1029/2008WR007496, 2009a.
Hrachowitz, M., Soulsby, C., Tetzlaff, D., Dawson, J. J. C., Dunn, S. M., and Malcolm, I. A.: Using long-term data sets to understand transit times in contrasting headwater catchments, J. Hydrol., 367, 237–248, https://doi.org/10.1016/j.jhydrol.2009.01.001, 2009b.
Hrachowitz, M., Soulsby, C., Tetzlaff, D., Malcolm, I. A., and Schoups, G.: Gamma distribution models for transit time estimation in catchments: Physical interpretation of parameters and implications for time-variant transit time assessment, Water Resour. Res., 46, https://doi.org/10.1029/2010WR009148, 2010.
Hrachowitz, M., Soulsby, C., Tetzlaff, D., and Malcolm, I. A.: Sensitivity of mean transit time estimates to model conditioning and data availability, Hydrol. Process., 25, 980–990, https://doi.org/10.1002/hyp.7922, 2011.
Hrachowitz, M., Savenije, H., Bogaard, T. A., Tetzlaff, D., and Soulsby, C.: What can flux tracking teach us about water age distribution patterns and their temporal dynamics?, Hydrol. Earth Syst. Sci., 17, 533–564, https://doi.org/10.5194/hess-17-533-2013, 2013.
Hu, K., Chen, H., Nie, Y., and Wang, K.: Seasonal recharge and mean residence times of soil and epikarst water in a small karst catchment of southwest China., Sci. Rep., 5, 10215, https://doi.org/10.1038/srep10215, 2015.
IUCN: High Andean wetlands, Technical report, IUCN, Gland, Switzerland, 2002.
Kirchner, J. W.: Aggregation in environmental systems – Part 1: Seasonal tracer cycles quantify young water fractions, but not mean transit times, in spatially heterogeneous catchments, Hydrol. Earth Syst. Sci., 20, 279–297, https://doi.org/10.5194/hess-20-279-2016, 2016a.
Kirchner, J. W.: Aggregation in environmental systems – Part 2: Catchment mean transit times and young water fractions under hydrologic nonstationarity, Hydrol. Earth Syst. Sci., 20, 299–328, https://doi.org/10.5194/hess-20-299-2016, 2016b.
Kirchner, J. W., Feng, X., and Neal, C.: Fractal stream chemistry and its implications for contaminant transportin catchments, Nature, 403, 524–527, https://doi.org/10.1038/35000537, 2000.
Klaus, J., Chun, K. P., McGuire, K. J., and McDonnell, J. J.: Temporal dynamics of catchment transit times from stable isotope data, Water Resour. Res., 51, 4208–4223, https://doi.org/10.1002/2014WR016247, 2015.
Kreft, A., and Zuber, A.: On the physical meaning of the dispersion equation and its solutions for different initial and boundary conditions, Chem. Eng. Sci., 33, 1471–1480, https://doi.org/10.1016/0009-2509(78)85196-3, 1978.
Lyon, S. W., Laudon, H., Seibert, J., Mörth, M., Tetzlaff, D., and Bishop, K. H.: Controls on snowmelt water mean transit times in northern boreal catchments, Hydrol. Process., 24, 1672–1684, https://doi.org/10.1002/hyp.7577, 2010.
Małoszewski, P. and Zuber, A.: Determining the turnover time of groundwater systems with the aid of environmental tracers, J. Hydrol., 57, 207–231, https://doi.org/10.1016/0022-1694(82)90147-0, 1982.
Maloszewski, P. and Zuber, A.: Lumped parameter models for the interpretation of environmental tracer data, in: Manual on Mathematical Models in Isotope Hydrogeology, TECDOC-910, 1996.
McDonnell, J. J., McGuire, K., Aggarwal, P., Beven, K. J., Biondi, D., Destouni, G., Dunn, S., James, A., Kirchner, J., Kraft, P., Lyon, S., Maloszewski, P., Newman, B., Pfister, L., Rinaldo, A., Rodhe, A., Sayama, T., Seibert, J., Solomon, K., Soulsby, C., Stewart, M., Tetzlaff, D., Tobin, C., Troch, P., Weiler, M., Western, A., Wörman, A., and Wrede, S.: How old is streamwater? Open questions in catchment transit time conceptualization, modelling and analysis, Hydrol. Process., 24, 1745–1754, https://doi.org/10.1002/hyp.7796, 2010.
McGlynn, B. L. and McDonnell, J. J.: Quantifying the relative contributions of riparian and hillslope zones to catchment runoff, Water Resour. Res., 39, https://doi.org/10.1029/2003WR002091, 2003.
McGuire, K. J. and McDonnell, J. J.: A review and evaluation of catchment transit time modeling, J. Hydrol., 330, 543–563, https://doi.org/10.1016/j.jhydrol.2006.04.020, 2006.
McGuire, K. J., DeWalle, D. R., and Gburek, W. J.: Evaluation of mean residence time in subsurface waters using oxygen-18 fluctuations during drought conditions in the mid-Appalachians, J. Hydrol., 261, 132–149, https://doi.org/10.1016/S0022-1694(02)00006-9, 2002.
McGuire, K. J., McDonnell, J. J., Weiler, M., Kendall, C., McGlynn, B. L., Welker, J. M., and Seibert, J.: The role of topography on catchment-scale water residence time, Water Resour. Res., 41, https://doi.org/10.1029/2004WR003657, 2005.
McMillan, H., Tetzlaff, D., Clark, M., and Soulsby, C.: Do time-variable tracers aid the evaluation of hydrological model structure? A multimodel approach, Water Resour. Res., 48, https://doi.org/10.1029/2011WR011688, 2012.
Mook, W. G.: Introduction: Theory, methods, review, in Environmental Isotopes in the Hydrological Cycle: Principles and Applications, edited by: Mook, W. G., IAEA and UNESCO, Paris/Vienna, 2000.
Moore, R. D.: Introduction to salt dilution gauging for streamflow measurement Part 2: Constant-rate injection, Streamline Watershed Manag. Bull., 8, 11–15, 2004.
Mosquera, G. M., Lazo, P. X., Célleri, R., Wilcox, B. P., and Crespo, P.: Runoff from tropical alpine grasslands increases with areal extent of wetlands, CATENA, 125, 120–128, https://doi.org/10.1016/j.catena.2014.10.010, 2015.
Mosquera, G. M., Célleri, R., Lazo, P. X., Vaché, K. B., Perakis, S. S., and Crespo, P.: Combined Use of Isotopic and Hydrometric Data to Conceptualize Ecohydrological Processes in a High-Elevation Tropical Ecosystem, Hydrol. Process., https://doi.org/10.1002/hyp.10927, 2016.
Muñoz-Villers, L. E. and McDonnell, J. J.: Runoff generation in a steep, tropical montane cloud forest catchment on permeable volcanic substrate, Water Resour. Res., 48, https://doi.org/10.1029/2011WR011316, 2012.
Muñoz-Villers, L. E., Geissert, D. R., Holwerda, F., and McDonnell, J. J.: Factors influencing stream baseflow transit times in tropical montane watersheds, Hydrol. Earth Syst. Sci., 20, 1621–1635, https://doi.org/10.5194/hess-20-1621-2016, 2016.
Padrón, R. S., Wilcox, B. P., Crespo, P., and Célleri, R.: Rainfall in the Andean Páramo: New Insights from High-Resolution Monitoring in Southern Ecuador, J. Hydrometeorol., 16, 985–996, https://doi.org/10.1175/JHM-D-14-0135.1, 2015.
Penna, D., Tromp-van Meerveld, H. J., Gobbi, A., Borga, M., and Dalla Fontana, G.: The influence of soil moisture on threshold runoff generation processes in an alpine headwater catchment, Hydrol. Earth Syst. Sci., 15, 689–702, https://doi.org/10.5194/hess-15-689-2011, 2011.
Pratt, W. T., Figueroa, J. F., and Flores, B. G.: Geology and Mineralization of the Area between 3 and 48S. Western Cordillera, Ecuador, Open File Report, WCr97r28, British Geological Survey, 1997.
Quichimbo, P., Tenorio, G., Borja, P., Cárdenas, I., Crespo, P., and Célleri, R.: Efectos sobre las propiedades físicas y químicas de los suelos por el cambio de la cobertura vegetal y uso del suelo: páramo de Quimsacocha al sur del Ecuador, Suelos Ecuatoriales, 42, 138–153, 2012.
Ramsay, P. M. and Oxley, E. R. B.: The growth form composition of plant communities in the ecuadorian páramos, Plant Ecol., 131, 173–192, https://doi.org/10.1023/A:1009796224479, 1997.
Roa-García, M. C. and Weiler, M.: Integrated response and transit time distributions of watersheds by combining hydrograph separation and long-term transit time modeling, Hydrol. Earth Syst. Sci., 14, 1537–1549, https://doi.org/10.5194/hess-14-1537-2010, 2010.
Roa-García, M. C., Brown, S., Schreier, H., and Lavkulich, L. M.: The role of land use and soils in regulating water flow in small headwater catchments of the Andes, Water Resour. Res., 47, W05510, https://doi.org/10.1029/2010WR009582, 2011.
Rodhe, A., Nyberg, L., and Bishop, K.: Transit Times for Water in a Small Till Catchment from a Step Shift in the Oxygen 18 Content of the Water Input, Water Resour. Res., 32, 3497–3511, https://doi.org/10.1029/95WR01806, 1996.
Seeger, S. and Weiler, M.: Reevaluation of transit time distributions, mean transit times and their relation to catchment topography, Hydrol. Earth Syst. Sci., 18, 4751–4771, https://doi.org/10.5194/hess-18-4751-2014, 2014.
Sklenar, P. and Jorgensen, P. M.: Distribution patterns of paramo plants in Ecuador, J. Biogeogr., 26, 681–691, https://doi.org/10.1046/j.1365-2699.1999.00324.x, 1999.
Soulsby, C., Tetzlaff, D., Rodgers, P., Dunn, S., and Waldron, S.: Runoff processes, stream water residence times and controlling landscape characteristics in a mesoscale catchment: An initial evaluation, J. Hydrol., 325, 197–221, https://doi.org/10.1016/j.jhydrol.2005.10.024, 2006.
Tetzlaff, D., Seibert, J., McGuire, K. J., Laudon, H., Burns, D. A., Dunn, S. M., and Soulsby, C.: How does landscape structure influence catchment transit time across different geomorphic provinces?, Hydrol. Process., 23, 945–953, https://doi.org/10.1002/hyp.7240, 2009.
Tetzlaff, D., Carey, S. K., Laudon, H., and McGuire, K.: Catchment processes and heterogeneity at multiple scales-benchmarking observations, conceptualization and prediction, Hydrol. Process., 24, 2203–2208, https://doi.org/10.1002/hyp.7784, 2010.
Tetzlaff, D., Al-Rawas, G., Blöschl, G., Carey, S. K., Fan, Y., Hrachowitz, M., Kirnbauer, R., Jewitt, G., Laudon, H., McGuire, K. J., Sayama, T., Soulsby, C., Zehe, E., and Wagener, T.: Process realism: Flow paths and storage., in Runoff prediction in ungauged basins: Synthesis across processes, places and scales, edited by: Blösch, G., Sivapalan, M., Wagener, T., Viglione, A., and Savenije, H., Cambridge University Press, Cambridge, UK, 53–69, 2013.
Tetzlaff, D., Birkel, C., Dick, J., Geris, J., and Soulsby, C.: Storage dynamics in hydropedological units control hillslope connectivity, runoff generation, and the evolution of catchment transit time distributions, Water Resour. Res., 50, 969–985, https://doi.org/10.1002/2013WR014147, 2014.
Timbe, E., Windhorst, D., Crespo, P., Frede, H.-G., Feyen, J., and Breuer, L.: Understanding uncertainties when inferring mean transit times of water trough tracer-based lumped-parameter models in Andean tropical montane cloud forest catchments, Hydrol. Earth Syst. Sci., 18, 1503–1523, https://doi.org/10.5194/hess-18-1503-2014, 2014.
US Bureau of Reclamation: Water Measurement Manual, Washington DC, 2001.
van der Velde, Y., Heidbüchel, I., Lyon, S. W., Nyberg, L., Rodhe, A., Bishop, K., and Troch, P. A.: Consequences of mixing assumptions for time-variable travel time distributions, Hydrol. Process., 29, 3460–3474, https://doi.org/10.1002/hyp.10372, 2015.
Vimeux, F., Tremoy, G., Risi, C., and Gallaire, R.: A strong control of the South American SeeSaw on the intra-seasonal variability of the isotopic composition of precipitation in the Bolivian Andes, Earth Planet. Sci. Lett., 307, 47–58 available at: http://www.documentation.ird.fr/hor/fdi:010053700 (last access: 3 December 2015), 2011.
Weiler, M., McGlynn, B. L., McGuire, K. J., and McDonnell, J. J.: How does rainfall become runoff? A combined tracer and runoff transfer function approach, Water Resour. Res., 39, https://doi.org/10.1029/2003WR002331, 2003.
Windhorst, D., Waltz, T., Timbe, E., Frede, H.-G., and Breuer, L.: Impact of elevation and weather patterns on the isotopic composition of precipitation in a tropical montane rainforest, Hydrol. Earth Syst. Sci., 17, 409–419, https://doi.org/10.5194/hess-17-409-2013, 2013.
Short summary
This study focuses on the investigation of baseflow mean transit times (MTTs) in a high-elevation tropical ecosystem (páramo) using stable water isotopes. Results showed short MTTs (< 9 months) and topographic controls on their spatial variability. We conclude that (1) the hydrology of the ecosystem is dominated by shallow subsurface flow and (2) the interplay between the high storage capacity of the páramo soils and the catchments' slopes provides the ecosystem with high regulation capacity.
This study focuses on the investigation of baseflow mean transit times (MTTs) in a...