Articles | Volume 20, issue 3
https://doi.org/10.5194/hess-20-1151-2016
© 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-20-1151-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
17 Mar 2016
Research article |
| 17 Mar 2016
The importance of topography-controlled sub-grid process heterogeneity and semi-quantitative prior constraints in distributed hydrological models
Delft University of Technology, Stevinweg 1, 2628 CN Delft, the
Netherlands
Luis Samaniego
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
Juliane Mai
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
Rohini Kumar
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
Stephan Thober
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
Matthias Zink
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
David Schäfer
UFZ – Helmholtz Centre for Environmental Research, Permoserstraße
15, 04318 Leipzig, Germany
Hubert H. G. Savenije
Delft University of Technology, Stevinweg 1, 2628 CN Delft, the
Netherlands
Markus Hrachowitz
Delft University of Technology, Stevinweg 1, 2628 CN Delft, the
Netherlands
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Timo Houben, Thomas Müller, Peter Lünenschloss, Jens Voigtländer, Thomas Trabert, Ema Vosgerau, David Schäfer, and Jan Bumberger
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Sadaf Nasreen, Oldrich Rakovec, Rohini Kumar, Manuela I. Brunner, Ujjwal Singh, Petr Maca, Yannis Markonis, and Martin Hanel
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Hatice Türk, Christine Stumpp, Markus Hrachowitz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci., 30, 1053–1076, https://doi.org/10.5194/hess-30-1053-2026, https://doi.org/10.5194/hess-30-1053-2026, 2026
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Pia Ebeling, Alexander Hubig, Alexander Wachholz, Ulrike Scharfenberger, Sarah Haug, Tam Nguyen, Fanny Sarrazin, Masooma Batool, Andreas Musolff, and Rohini Kumar
Earth Syst. Sci. Data, 18, 691–712, https://doi.org/10.5194/essd-18-691-2026, https://doi.org/10.5194/essd-18-691-2026, 2026
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Peter Lünenschloß, Antje Claussnitzer, Thomas Schartner, Mirjam Brunner, Timo Houben, David Schäfer, and Jan Bumberger
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Robert Reinecke, Tanjila Akhter, Annemarie Bäthge, Ricarda Dietrich, Sebastian Gnann, Simon N. Gosling, Danielle Grogan, Andreas Hartmann, Stefan Kollet, Rohini Kumar, Richard Lammers, Sida Liu, Yan Liu, Nils Moosdorf, Bibi Naz, Sara Nazari, Chibuike Orazulike, Yadu Pokhrel, Jacob Schewe, Mikhail Smilovic, Maryna Strokal, Wim Thiery, Yoshihide Wada, Shan Zuidema, and Inge de Graaf
Geosci. Model Dev., 19, 523–542, https://doi.org/10.5194/gmd-19-523-2026, https://doi.org/10.5194/gmd-19-523-2026, 2026
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Thiago V. M. do Nascimento, Julia Rudlang, Sebastian Gnann, Jan Seibert, Markus Hrachowitz, and Fabrizio Fenicia
Hydrol. Earth Syst. Sci., 29, 7173–7200, https://doi.org/10.5194/hess-29-7173-2025, https://doi.org/10.5194/hess-29-7173-2025, 2025
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Nathalie Rombeek, Markus Hrachowitz, and Remko Uijlenhoet
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Maria Staudinger, Anna Herzog, Ralf Loritz, Tobias Houska, Sandra Pool, Diana Spieler, Paul D. Wagner, Juliane Mai, Jens Kiesel, Stephan Thober, Björn Guse, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 5005–5029, https://doi.org/10.5194/hess-29-5005-2025, https://doi.org/10.5194/hess-29-5005-2025, 2025
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Nathalie Rombeek, Markus Hrachowitz, Arjan Droste, and Remko Uijlenhoet
Hydrol. Earth Syst. Sci., 29, 4585–4606, https://doi.org/10.5194/hess-29-4585-2025, https://doi.org/10.5194/hess-29-4585-2025, 2025
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Rain gauge networks from personal weather stations (PWSs) have a network density 100 times higher than dedicated rain gauge networks in the Netherlands. However, PWSs are prone to several sources of error, as they are generally not installed and maintained according to international guidelines. This study systematically quantifies and describes the uncertainties arising from PWS rainfall estimates. In particular, the focus is on the highest rainfall accumulations.
Vishal Thakur, Yannis Markonis, Rohini Kumar, Johanna Ruth Thomson, Mijael Rodrigo Vargas Godoy, Martin Hanel, and Oldrich Rakovec
Hydrol. Earth Syst. Sci., 29, 4395–4416, https://doi.org/10.5194/hess-29-4395-2025, https://doi.org/10.5194/hess-29-4395-2025, 2025
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Understanding the changes in water movement in earth is crucial for everyone. To quantify this water movement there are several techniques. We examined how different methods of estimating evaporation impact predictions of various types of water movement across Europe. We found that, while these methods generally agree on whether changes are increasing or decreasing, they differ in magnitude. This means selecting the right evaporation method is crucial for accurate predictions of water movement.
Katherine Grayson, Stephan Thober, Aleksander Lacima-Nadolnik, Ivan Alsina-Ferrer, Llorenç Lledó, Ehsan Sharifi, and Francisco Doblas-Reyes
Geosci. Model Dev., 18, 5873–5890, https://doi.org/10.5194/gmd-18-5873-2025, https://doi.org/10.5194/gmd-18-5873-2025, 2025
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We present One_Pass (v0.8.0), a Python package enabling computation of statistics from streamed global climate model output using one-pass algorithms. Users often need statistics covering periods longer than the stream duration, requiring algorithms that do not store full time series. One-pass methods address this need while avoiding full data archiving, offering memory-efficient, accurate results for high-performance computing (HPC) workflows and downstream applications like bias adjustment.
Hatice Türk, Christine Stumpp, Markus Hrachowitz, Karsten Schulz, Peter Strauss, Günter Blöschl, and Michael Stockinger
Hydrol. Earth Syst. Sci., 29, 3935–3956, https://doi.org/10.5194/hess-29-3935-2025, https://doi.org/10.5194/hess-29-3935-2025, 2025
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Using advances in transit time estimation and tracer data, we tested if fast-flow transit times are controlled solely by soil moisture or if they are also controlled by precipitation intensity. We used soil-moisture-dependent and precipitation-intensity-conditional transfer functions. We showed that a significant portion of event water bypasses the soil matrix through fast flow paths (overland flow, tile drains, preferential-flow paths) in dry soil conditions for both low- and high-intensity precipitation.
Magali Ponds, Sarah Hanus, Harry Zekollari, Marie-Claire ten Veldhuis, Gerrit Schoups, Roland Kaitna, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 3545–3568, https://doi.org/10.5194/hess-29-3545-2025, https://doi.org/10.5194/hess-29-3545-2025, 2025
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This research examines how future climate changes impact root zone storage, a key hydrological model parameter. Root zone storage – the soil water accessible to plants – adapts to climate but is often kept constant in models. We estimated climate-adapted storage in six Austrian Alps catchments. While storage increased, streamflow projections showed minimal change, which suggests that dynamic root zone representation is less critical in humid regions but warrants further study in arid areas.
Jan Řehoř, Rudolf Brázdil, Oldřich Rakovec, Martin Hanel, Milan Fischer, Rohini Kumar, Jan Balek, Markéta Poděbradská, Vojtěch Moravec, Luis Samaniego, Yannis Markonis, and Miroslav Trnka
Hydrol. Earth Syst. Sci., 29, 3341–3358, https://doi.org/10.5194/hess-29-3341-2025, https://doi.org/10.5194/hess-29-3341-2025, 2025
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We present a robust method for identification and classification of global land drought events (GLDEs) based on soil moisture. Two models were used to calculate soil moisture and delimit soil drought over global land from 1980–2022, with clusters of 775 and 630 GLDEs. Using four spatiotemporal and three motion-related characteristics, we categorized GLDEs into seven severity and seven dynamic categories. The frequency of GLDEs has generally increased in recent decades.
Sebastian Müller, Martin Lange, Thomas Fischer, Sara König, Matthias Kelbling, Jeisson Javier Leal Rojas, and Stephan Thober
Geosci. Model Dev., 18, 4483–4498, https://doi.org/10.5194/gmd-18-4483-2025, https://doi.org/10.5194/gmd-18-4483-2025, 2025
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This study presents FINAM (
FINAM is not a model), a new coupling framework written in Python to dynamically connect independently developed models. Python, as the ultimate glue language, enables the use of codes from nearly any programming language like Fortran, C++, Rust, and others. FINAM is designed to simplify the integration of various models with minimal effort, as demonstrated through various examples ranging from simple to complex systems.
Pia Ebeling, Andreas Musolff, Rohini Kumar, Andreas Hartmann, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 29, 2925–2950, https://doi.org/10.5194/hess-29-2925-2025, https://doi.org/10.5194/hess-29-2925-2025, 2025
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Groundwater is a crucial resource at risk due to droughts. To understand drought effects on groundwater levels in Germany, we grouped 6626 wells into six regional and two national patterns. Weather explained half of the level variations with varied response times. Shallow groundwater responds fast and is more vulnerable to short droughts (a few months). Dampened deep heads buffer short droughts but suffer from long droughts and recoveries. Two nationwide trend patterns were linked to human water use.
Mansi Nagpal, Jasmin Heilemann, Luis Samaniego, Bernd Klauer, Erik Gawel, and Christian Klassert
Nat. Hazards Earth Syst. Sci., 25, 2115–2135, https://doi.org/10.5194/nhess-25-2115-2025, https://doi.org/10.5194/nhess-25-2115-2025, 2025
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This study measures the direct effects of droughts in association with other extreme weather events on agriculture in Germany at the district level. Using a statistical yield model, we quantify the direct damage of extremes on crop yields and farm revenue. Extreme events during drought cause an average annual damage of EUR 781 million, accounting for 45 % of reported revenue losses. The insights herein can help develop better strategies for managing and mitigating the effects of future climate extremes.
Sergiy Vorogushyn, Li Han, Heiko Apel, Viet Dung Nguyen, Björn Guse, Xiaoxiang Guan, Oldrich Rakovec, Husain Najafi, Luis Samaniego, and Bruno Merz
Nat. Hazards Earth Syst. Sci., 25, 2007–2029, https://doi.org/10.5194/nhess-25-2007-2025, https://doi.org/10.5194/nhess-25-2007-2025, 2025
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The July 2021 flood in central Europe was one of the deadliest floods in Europe in the recent decades and the most expensive flood in Germany. In this paper, we show that the hydrological impact of this event in the Ahr valley could have been even worse if the rainfall footprint trajectory had been only slightly different. The presented methodology of spatial counterfactuals generates plausible unprecedented events and helps to better prepare for future extreme floods.
Hannes Müller Schmied, Simon Newland Gosling, Marlo Garnsworthy, Laura Müller, Camelia-Eliza Telteu, Atiq Kainan Ahmed, Lauren Seaby Andersen, Julien Boulange, Peter Burek, Jinfeng Chang, He Chen, Lukas Gudmundsson, Manolis Grillakis, Luca Guillaumot, Naota Hanasaki, Aristeidis Koutroulis, Rohini Kumar, Guoyong Leng, Junguo Liu, Xingcai Liu, Inga Menke, Vimal Mishra, Yadu Pokhrel, Oldrich Rakovec, Luis Samaniego, Yusuke Satoh, Harsh Lovekumar Shah, Mikhail Smilovic, Tobias Stacke, Edwin Sutanudjaja, Wim Thiery, Athanasios Tsilimigkras, Yoshihide Wada, Niko Wanders, and Tokuta Yokohata
Geosci. Model Dev., 18, 2409–2425, https://doi.org/10.5194/gmd-18-2409-2025, https://doi.org/10.5194/gmd-18-2409-2025, 2025
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Global water models contribute to the evaluation of important natural and societal issues but are – as all models – simplified representation of reality. So, there are many ways to calculate the water fluxes and storages. This paper presents a visualization of 16 global water models using a standardized visualization and the pathway towards this common understanding. Next to academic education purposes, we envisage that these diagrams will help researchers, model developers, and data users.
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025, https://doi.org/10.5194/hess-29-1703-2025, 2025
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The quantification of precipitation into evaporation and runoff is vital for water resources management. The Budyko framework, based on aridity and evaporative indices of a catchment, can be an ideal tool for that. However, recent research highlights deviations of catchments from the expected evaporative index, casting doubt on its reliability. This study quantifies deviations of 2387 catchments, finding them minor and predictable. Integrating these into predictions upholds the framework's efficacy.
Damian N. Mingo, Remko Nijzink, Christophe Ley, and Jack S. Hale
Geosci. Model Dev., 18, 1709–1736, https://doi.org/10.5194/gmd-18-1709-2025, https://doi.org/10.5194/gmd-18-1709-2025, 2025
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Hydrologists are often faced with selecting amongst a set of competing models with different numbers of parameters and ability to fit available data. Bayes’ factor is a tool that can be used to compare models; however, it is very difficult to compute Bayes' factor numerically. In our paper, we explore and develop highly efficient algorithms for computing Bayes’ factor of hydrological systems, which will introduce this useful tool for selecting models into everyday hydrological practice.
Wouter R. Berghuijs, Ross A. Woods, Bailey J. Anderson, Anna Luisa Hemshorn de Sánchez, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1319–1333, https://doi.org/10.5194/hess-29-1319-2025, https://doi.org/10.5194/hess-29-1319-2025, 2025
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Water balances of catchments will often strongly depend on their state in the recent past, but such memory effects may persist at annual timescales. We use global data sets to show that annual memory is typically absent in precipitation but strong in terrestrial water stores and also present in evaporation and streamflow (including low flows and floods). Our experiments show that hysteretic models provide behaviour that is consistent with these observed memory behaviours.
Masooma Batool, Fanny J. Sarrazin, and Rohini Kumar
Earth Syst. Sci. Data, 17, 881–916, https://doi.org/10.5194/essd-17-881-2025, https://doi.org/10.5194/essd-17-881-2025, 2025
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Our paper presents a reconstruction and analysis of the gridded P surplus in European landscapes from 1850 to 2019 at a 5 arcmin resolution. By utilizing 48 different estimates, we account for uncertainties in major components of the P surplus. Our findings highlight substantial historical changes, with the total P surplus in the EU 27 tripling over 170 years. Our dataset enables flexible aggregation at various spatial scales, providing critical insights for land and water management strategies.
Jordy Salmon-Monviola, Ophélie Fovet, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 127–158, https://doi.org/10.5194/hess-29-127-2025, https://doi.org/10.5194/hess-29-127-2025, 2025
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To increase the predictive power of hydrological models, it is necessary to improve their consistency, i.e. their physical realism, which is measured by the ability of the model to reproduce observed system dynamics. Using a model to represent the dynamics of water and nitrate and dissolved organic carbon concentrations in an agricultural catchment, we showed that using solute-concentration data for calibration is useful to improve the hydrological consistency of the model.
Eshrat Fatima, Rohini Kumar, Sabine Attinger, Maren Kaluza, Oldrich Rakovec, Corinna Rebmann, Rafael Rosolem, Sascha E. Oswald, Luis Samaniego, Steffen Zacharias, and Martin Schrön
Hydrol. Earth Syst. Sci., 28, 5419–5441, https://doi.org/10.5194/hess-28-5419-2024, https://doi.org/10.5194/hess-28-5419-2024, 2024
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This study establishes a framework to incorporate cosmic-ray neutron measurements into the mesoscale Hydrological Model (mHM). We evaluate different approaches to estimate neutron counts within the mHM using the Desilets equation, with uniformly and non-uniformly weighted average soil moisture, and the physically based code COSMIC. The data improved not only soil moisture simulations but also the parameterisation of evapotranspiration in the model.
Sven Armin Westermann, Anke Hildebrandt, Souhail Bousetta, and Stephan Thober
Biogeosciences, 21, 5277–5303, https://doi.org/10.5194/bg-21-5277-2024, https://doi.org/10.5194/bg-21-5277-2024, 2024
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Plants at the land surface mediate between soil and the atmosphere regarding water and carbon transport. Since plant growth is a dynamic process, models need to consider these dynamics. Two models that predict water and carbon fluxes by considering plant temporal evolution were tested against observational data. Currently, dynamizing plants in these models did not enhance their representativeness, which is caused by a mismatch between implemented physical relations and observable connections.
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
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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.
Fanny J. Sarrazin, Sabine Attinger, and Rohini Kumar
Earth Syst. Sci. Data, 16, 4673–4708, https://doi.org/10.5194/essd-16-4673-2024, https://doi.org/10.5194/essd-16-4673-2024, 2024
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Nitrogen (N) and phosphorus (P) contamination of water bodies is a long-term issue due to the long history of N and P inputs to the environment and their persistence. Here, we introduce a long-term and high-resolution dataset of N and P inputs from wastewater (point sources) for Germany, combining data from different sources and conceptual understanding. We also account for uncertainties in modelling choices, thus facilitating robust long-term and large-scale water quality studies.
Hongkai Gao, Markus Hrachowitz, Lan Wang-Erlandsson, Fabrizio Fenicia, Qiaojuan Xi, Jianyang Xia, Wei Shao, Ge Sun, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 4477–4499, https://doi.org/10.5194/hess-28-4477-2024, https://doi.org/10.5194/hess-28-4477-2024, 2024
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The concept of the root zone is widely used but lacks a precise definition. Its importance in Earth system science is not well elaborated upon. Here, we clarified its definition with several similar terms to bridge the multi-disciplinary gap. We underscore the key role of the root zone in the Earth system, which links the biosphere, hydrosphere, lithosphere, atmosphere, and anthroposphere. To better represent the root zone, we advocate for a paradigm shift towards ecosystem-centred modelling.
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
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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.
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
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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.
Fransje van Oorschot, Ruud J. van der Ent, Andrea Alessandri, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 2313–2328, https://doi.org/10.5194/hess-28-2313-2024, https://doi.org/10.5194/hess-28-2313-2024, 2024
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Vegetation plays a crucial role in regulating the water cycle by transporting water from the subsurface to the atmosphere via roots; this transport depends on the extent of the root system. In this study, we quantified the effect of irrigation on roots at a global scale. Our results emphasize the importance of accounting for irrigation in estimating the vegetation root extent, which is essential to adequately represent the water cycle in hydrological and climate models.
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
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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.
Hubert H. G. Savenije
Proc. IAHS, 385, 1–4, https://doi.org/10.5194/piahs-385-1-2024, https://doi.org/10.5194/piahs-385-1-2024, 2024
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Hydrology is the bloodstream of the Earth, acting as a living organism, with the ecosystem as its active agent. The ecosystem optimises its survival within the constraints of energy, water, climate and nutrients. It is capable of adjusting the hydrological system and, through evolution, adjust its efficiency of carbon sequestration and moisture uptake. In trying to understand future functioning of hydrology, we have to take into account the adaptability of the ecosystem.
Kingsley Nnaemeka Ogbu, Oldrich Rakovec, Luis Samaniego, Gloria Chinwendu Okafor, Bernhard Tischbein, and Hadush Meresa
Proc. IAHS, 385, 211–218, https://doi.org/10.5194/piahs-385-211-2024, https://doi.org/10.5194/piahs-385-211-2024, 2024
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In this study, the MPR-mHM technique was applied in four data-scarce basins in Nigeria. Remotely sensed rainfall datasets were used as model forcings to evaluate the mHM capability in reproducing observed stream discharge under single and multivariable model calibration frameworks. Overall, model calibration performances displayed satisfactory outputs as evident in the Kling-Gupta Efficiency (KGE) scores across most basins.
Jiaxing Liang, Hongkai Gao, Fabrizio Fenicia, Qiaojuan Xi, Yahui Wang, and Hubert H. G. Savenije
EGUsphere, https://doi.org/10.5194/egusphere-2024-550, https://doi.org/10.5194/egusphere-2024-550, 2024
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The root zone storage capacity (Sumax) is a key element in hydrology and land-atmospheric interaction. In this study, we utilized a hydrological model and a dynamic parameter identification method, to quantify the temporal trends of Sumax for 497 catchments in the USA. We found that 423 catchments (85 %) showed increasing Sumax, which averagely increased from 178 to 235 mm between 1980 and 2014. The increasing trend was also validated by multi-sources data and independent methods.
Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri
Earth Syst. Dynam., 14, 1239–1259, https://doi.org/10.5194/esd-14-1239-2023, https://doi.org/10.5194/esd-14-1239-2023, 2023
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Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
Samah Larabi, Juliane Mai, Markus Schnorbus, Bryan A. Tolson, and Francis Zwiers
Hydrol. Earth Syst. Sci., 27, 3241–3263, https://doi.org/10.5194/hess-27-3241-2023, https://doi.org/10.5194/hess-27-3241-2023, 2023
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The computational cost of sensitivity analysis (SA) becomes prohibitive for large hydrologic modeling domains. Here, using a large-scale Variable Infiltration Capacity (VIC) deployment, we show that watershed classification helps identify the spatial pattern of parameter sensitivity within the domain at a reduced cost. Findings reveal the opportunity to leverage climate and land cover attributes to reduce the cost of SA and facilitate more rapid deployment of large-scale land surface models.
Siyuan Wang, Markus Hrachowitz, Gerrit Schoups, and Christine Stumpp
Hydrol. Earth Syst. Sci., 27, 3083–3114, https://doi.org/10.5194/hess-27-3083-2023, https://doi.org/10.5194/hess-27-3083-2023, 2023
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This study shows that previously reported underestimations of water ages are most likely not due to the use of seasonally variable tracers. Rather, these underestimations can be largely attributed to the choices of model approaches which rely on assumptions not frequently met in catchment hydrology. We therefore strongly advocate avoiding the use of this model type in combination with seasonally variable tracers and instead adopting StorAge Selection (SAS)-based or comparable model formulations.
Hubert T. Samboko, Sten Schurer, Hubert H. G. Savenije, Hodson Makurira, Kawawa Banda, and Hessel Winsemius
Geosci. Instrum. Method. Data Syst., 12, 155–169, https://doi.org/10.5194/gi-12-155-2023, https://doi.org/10.5194/gi-12-155-2023, 2023
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The study investigates how low-cost technology can be applied in data-scarce catchments to improve water resource management. More specifically, we investigate how drone technology can be combined with low-cost real-time kinematic positioning (RTK) global navigation satellite system (GNSS) equipment and subsequently applied to a 3D hydraulic model so as to generate more physically based rating curves.
Arianna Borriero, Rohini Kumar, Tam V. Nguyen, Jan H. Fleckenstein, and Stefanie R. Lutz
Hydrol. Earth Syst. Sci., 27, 2989–3004, https://doi.org/10.5194/hess-27-2989-2023, https://doi.org/10.5194/hess-27-2989-2023, 2023
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We analyzed the uncertainty of the water transit time distribution (TTD) arising from model input (interpolated tracer data) and structure (StorAge Selection, SAS, functions). We found that uncertainty was mainly associated with temporal interpolation, choice of SAS function, nonspatial interpolation, and low-flow conditions. It is important to characterize the specific uncertainty sources and their combined effects on TTD, as this has relevant implications for both water quantity and quality.
Hongkai Gao, Fabrizio Fenicia, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2607–2620, https://doi.org/10.5194/hess-27-2607-2023, https://doi.org/10.5194/hess-27-2607-2023, 2023
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It is a deeply rooted perception that soil is key in hydrology. In this paper, we argue that it is the ecosystem, not the soil, that is in control of hydrology. Firstly, in nature, the dominant flow mechanism is preferential, which is not particularly related to soil properties. Secondly, the ecosystem, not the soil, determines the land–surface water balance and hydrological processes. Moving from a soil- to ecosystem-centred perspective allows more realistic and simpler hydrological models.
Nutchanart Sriwongsitanon, Wasana Jandang, James Williams, Thienchart Suwawong, Ekkarin Maekan, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 2149–2171, https://doi.org/10.5194/hess-27-2149-2023, https://doi.org/10.5194/hess-27-2149-2023, 2023
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We developed predictive semi-distributed rainfall–runoff models for nested sub-catchments in the upper Ping basin, which yielded better or similar performance compared to calibrated lumped models. The normalised difference infrared index proves to be an effective proxy for distributed root zone moisture capacity over sub-catchments and is well correlated with the percentage of evergreen forest. In validation, soil moisture simulations appeared to be highly correlated with the soil wetness index.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Bart Schilperoort, Nick van de Giesen, Imasiku Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 27, 1695–1722, https://doi.org/10.5194/hess-27-1695-2023, https://doi.org/10.5194/hess-27-1695-2023, 2023
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Miombo woodland plants continue to lose water even during the driest part of the year. This appears to be facilitated by the adapted features such as deep rooting (beyond 5 m) with access to deep soil moisture, potentially even ground water. It appears the trend and amount of water that the plants lose is correlated more to the available energy. This loss of water in the dry season by miombo woodland plants appears to be incorrectly captured by satellite-based evaporation estimates.
Robert Chlumsky, Juliane Mai, James R. Craig, and Bryan A. Tolson
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-69, https://doi.org/10.5194/hess-2023-69, 2023
Revised manuscript not accepted
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A blended model allows multiple hydrologic processes to be represented in a single model, which allows for a model to achieve high performance without the need to modify its structure for different catchments. Here, we improve upon the initial blended version by testing more than 30 blended models in twelve catchments to improve the overall model performance. We validate our proposed, updated blended model version with independent catchments, and make this version available for open use.
Carolin Winter, Tam V. Nguyen, Andreas Musolff, Stefanie R. Lutz, Michael Rode, Rohini Kumar, and Jan H. Fleckenstein
Hydrol. Earth Syst. Sci., 27, 303–318, https://doi.org/10.5194/hess-27-303-2023, https://doi.org/10.5194/hess-27-303-2023, 2023
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The increasing frequency of severe and prolonged droughts threatens our freshwater resources. While we understand drought impacts on water quantity, its effects on water quality remain largely unknown. Here, we studied the impact of the unprecedented 2018–2019 drought in Central Europe on nitrate export in a heterogeneous mesoscale catchment in Germany. We show that severe drought can reduce a catchment's capacity to retain nitrogen, intensifying the internal pollution and export of nitrate.
Richard Arsenault, Jean-Luc Martel, Frédéric Brunet, François Brissette, and Juliane Mai
Hydrol. Earth Syst. Sci., 27, 139–157, https://doi.org/10.5194/hess-27-139-2023, https://doi.org/10.5194/hess-27-139-2023, 2023
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Predicting flow in rivers where no observation records are available is a daunting task. For decades, hydrological models were set up on these gauges, and their parameters were estimated based on the hydrological response of similar or nearby catchments where records exist. New developments in machine learning have now made it possible to estimate flows at ungauged locations more precisely than with hydrological models. This study confirms the performance superiority of machine learning models.
Remko C. Nijzink and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 6289–6309, https://doi.org/10.5194/hess-26-6289-2022, https://doi.org/10.5194/hess-26-6289-2022, 2022
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Most catchments plot close to the empirical Budyko curve, which allows for estimating the long-term mean annual evaporation and runoff. We found that a model that optimizes vegetation properties in response to changes in precipitation leads it to converge to a single curve. In contrast, models that assume no changes in vegetation start to deviate from a single curve. This implies that vegetation has a stabilizing role, bringing catchments back to equilibrium after changes in climate.
Pau Wiersma, Jerom Aerts, Harry Zekollari, Markus Hrachowitz, Niels Drost, Matthias Huss, Edwin H. Sutanudjaja, and Rolf Hut
Hydrol. Earth Syst. Sci., 26, 5971–5986, https://doi.org/10.5194/hess-26-5971-2022, https://doi.org/10.5194/hess-26-5971-2022, 2022
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We test whether coupling a global glacier model (GloGEM) with a global hydrological model (PCR-GLOBWB 2) leads to a more realistic glacier representation and to improved basin runoff simulations across 25 large-scale basins. The coupling does lead to improved glacier representation, mainly by accounting for glacier flow and net glacier mass loss, and to improved basin runoff simulations, mostly in strongly glacier-influenced basins, which is where the coupling has the most impact.
Judith Uwihirwe, Alessia Riveros, Hellen Wanjala, Jaap Schellekens, Frederiek Sperna Weiland, Markus Hrachowitz, and Thom A. Bogaard
Nat. Hazards Earth Syst. Sci., 22, 3641–3661, https://doi.org/10.5194/nhess-22-3641-2022, https://doi.org/10.5194/nhess-22-3641-2022, 2022
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This study compared gauge-based and satellite-based precipitation products. Similarly, satellite- and hydrological model-derived soil moisture was compared to in situ soil moisture and used in landslide hazard assessment and warning. The results reveal the cumulative 3 d rainfall from the NASA-GPM to be the most effective landslide trigger. The modelled antecedent soil moisture in the root zone was the most informative hydrological variable for landslide hazard assessment and warning in Rwanda.
Friedrich Boeing, Oldrich Rakovec, Rohini Kumar, Luis Samaniego, Martin Schrön, Anke Hildebrandt, Corinna Rebmann, Stephan Thober, Sebastian Müller, Steffen Zacharias, Heye Bogena, Katrin Schneider, Ralf Kiese, Sabine Attinger, and Andreas Marx
Hydrol. Earth Syst. Sci., 26, 5137–5161, https://doi.org/10.5194/hess-26-5137-2022, https://doi.org/10.5194/hess-26-5137-2022, 2022
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In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.
Bahar Bahrami, Anke Hildebrandt, Stephan Thober, Corinna Rebmann, Rico Fischer, Luis Samaniego, Oldrich Rakovec, and Rohini Kumar
Geosci. Model Dev., 15, 6957–6984, https://doi.org/10.5194/gmd-15-6957-2022, https://doi.org/10.5194/gmd-15-6957-2022, 2022
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Leaf area index (LAI) and gross primary productivity (GPP) are crucial components to carbon cycle, and are closely linked to water cycle in many ways. We develop a Parsimonious Canopy Model (PCM) to simulate GPP and LAI at stand scale, and show its applicability over a diverse range of deciduous broad-leaved forest biomes. With its modular structure, the PCM is able to adapt with existing data requirements, and run in either a stand-alone mode or as an interface linked to hydrologic models.
Remko C. Nijzink and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 4575–4585, https://doi.org/10.5194/hess-26-4575-2022, https://doi.org/10.5194/hess-26-4575-2022, 2022
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Most catchments plot close to the empirical Budyko curve, which allows for the estimation of the long-term mean annual evaporation and runoff. The Budyko curve can be defined as a function of a wetness index or a dryness index. We found that differences can occur and that there is an uncertainty due to the different formulations.
Sadaf Nasreen, Markéta Součková, Mijael Rodrigo Vargas Godoy, Ujjwal Singh, Yannis Markonis, Rohini Kumar, Oldrich Rakovec, and Martin Hanel
Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, https://doi.org/10.5194/essd-14-4035-2022, 2022
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This article presents a 500-year reconstructed annual runoff dataset for several European catchments. Several data-driven and hydrological models were used to derive the runoff series using reconstructed precipitation and temperature and a set of proxy data. The simulated runoff was validated using independent observed runoff data and documentary evidence. The validation revealed a good fit between the observed and reconstructed series for 14 catchments, which are available for further analysis.
Pia Ebeling, Rohini Kumar, Stefanie R. Lutz, Tam Nguyen, Fanny Sarrazin, Michael Weber, Olaf Büttner, Sabine Attinger, and Andreas Musolff
Earth Syst. Sci. Data, 14, 3715–3741, https://doi.org/10.5194/essd-14-3715-2022, https://doi.org/10.5194/essd-14-3715-2022, 2022
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Environmental data are critical for understanding and managing ecosystems, including the mitigation of water quality degradation. To increase data availability, we present the first large-sample water quality data set (QUADICA) of riverine macronutrient concentrations combined with water quantity, meteorological, and nutrient forcing data as well as catchment attributes. QUADICA covers 1386 German catchments to facilitate large-sample data-driven and modeling water quality assessments.
Hongkai Gao, Chuntan Han, Rensheng Chen, Zijing Feng, Kang Wang, Fabrizio Fenicia, and Hubert Savenije
Hydrol. Earth Syst. Sci., 26, 4187–4208, https://doi.org/10.5194/hess-26-4187-2022, https://doi.org/10.5194/hess-26-4187-2022, 2022
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Frozen soil hydrology is one of the 23 unsolved problems in hydrology (UPH). In this study, we developed a novel conceptual frozen soil hydrological model, FLEX-Topo-FS. The model successfully reproduced the soil freeze–thaw process, and its impacts on hydrologic connectivity, runoff generation, and groundwater. We believe this study is a breakthrough for the 23 UPH, giving us new insights on frozen soil hydrology, with broad implications for predicting cold region hydrology in future.
Juliane Mai, Hongren Shen, Bryan A. Tolson, Étienne Gaborit, Richard Arsenault, James R. Craig, Vincent Fortin, Lauren M. Fry, Martin Gauch, Daniel Klotz, Frederik Kratzert, Nicole O'Brien, Daniel G. Princz, Sinan Rasiya Koya, Tirthankar Roy, Frank Seglenieks, Narayan K. Shrestha, André G. T. Temgoua, Vincent Vionnet, and Jonathan W. Waddell
Hydrol. Earth Syst. Sci., 26, 3537–3572, https://doi.org/10.5194/hess-26-3537-2022, https://doi.org/10.5194/hess-26-3537-2022, 2022
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Model intercomparison studies are carried out to test various models and compare the quality of their outputs over the same domain. In this study, 13 diverse model setups using the same input data are evaluated over the Great Lakes region. Various model outputs – such as streamflow, evaporation, soil moisture, and amount of snow on the ground – are compared using standardized methods and metrics. The basin-wise model outputs and observations are made available through an interactive website.
Judith Uwihirwe, Markus Hrachowitz, and Thom Bogaard
Nat. Hazards Earth Syst. Sci., 22, 1723–1742, https://doi.org/10.5194/nhess-22-1723-2022, https://doi.org/10.5194/nhess-22-1723-2022, 2022
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This research tested the value of regional groundwater level information to improve landslide predictions with empirical models based on the concept of threshold levels. In contrast to precipitation-based thresholds, the results indicated that relying on threshold models exclusively defined using hydrological variables such as groundwater levels can lead to improved landslide predictions due to their implicit consideration of long-term antecedent conditions until the day of landslide occurrence.
Henry Zimba, Miriam Coenders-Gerrits, Kawawa Banda, Petra Hulsman, Nick van de Giesen, Imasiku Nyambe, and Hubert Savenije
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-114, https://doi.org/10.5194/hess-2022-114, 2022
Manuscript not accepted for further review
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We compare performance of evaporation models in the Luangwa Basin located in a semi-arid and complex Miombo ecosystem in Africa. Miombo plants changes colour, drop off leaves and acquire new leaves during the dry season. In addition, the plant roots go deep in the soil and appear to access groundwater. Results show that evaporation models with structure and process that do not capture this unique plant structure and behaviour appears to have difficulties to correctly estimating evaporation.
Michelle Viswanathan, Tobias K. D. Weber, Sebastian Gayler, Juliane Mai, and Thilo Streck
Biogeosciences, 19, 2187–2209, https://doi.org/10.5194/bg-19-2187-2022, https://doi.org/10.5194/bg-19-2187-2022, 2022
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We analysed the evolution of model parameter uncertainty and prediction error as we updated parameters of a maize phenology model based on yearly observations, by sequentially applying Bayesian calibration. Although parameter uncertainty was reduced, prediction quality deteriorated when calibration and prediction data were from different maize ripening groups or temperature conditions. The study highlights that Bayesian methods should account for model limitations and inherent data structures.
Elisa Ragno, Markus Hrachowitz, and Oswaldo Morales-Nápoles
Hydrol. Earth Syst. Sci., 26, 1695–1711, https://doi.org/10.5194/hess-26-1695-2022, https://doi.org/10.5194/hess-26-1695-2022, 2022
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We explore the ability of non-parametric Bayesian networks to reproduce maximum daily discharge in a given month in a catchment when the remaining hydro-meteorological and catchment attributes are known. We show that a saturated network evaluated in an individual catchment can reproduce statistical characteristics of discharge in about ~ 40 % of the cases, while challenges remain when a saturated network considering all the catchments together is evaluated.
Laurène J. E. Bouaziz, Emma E. Aalbers, Albrecht H. Weerts, Mark Hegnauer, Hendrik Buiteveld, Rita Lammersen, Jasper Stam, Eric Sprokkereef, Hubert H. G. Savenije, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 26, 1295–1318, https://doi.org/10.5194/hess-26-1295-2022, https://doi.org/10.5194/hess-26-1295-2022, 2022
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Assuming stationarity of hydrological systems is no longer appropriate when considering land use and climate change. We tested the sensitivity of hydrological predictions to changes in model parameters that reflect ecosystem adaptation to climate and potential land use change. We estimated a 34 % increase in the root zone storage parameter under +2 K global warming, resulting in up to 15 % less streamflow in autumn, due to 14 % higher summer evaporation, compared to a stationary system.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, https://doi.org/10.5194/hess-26-525-2022, 2022
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Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Geosci. Model Dev., 15, 883–900, https://doi.org/10.5194/gmd-15-883-2022, https://doi.org/10.5194/gmd-15-883-2022, 2022
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The Vegetation Optimality Model (VOM) is a coupled water–vegetation model that predicts vegetation properties rather than determines them based on observations. A range of updates to previous applications of the VOM has been made for increased generality and improved comparability with conventional models. This showed that there is a large effect on the simulated water and carbon fluxes caused by the assumption of deep groundwater tables and updated soil profiles in the model.
Robert Schweppe, Stephan Thober, Sebastian Müller, Matthias Kelbling, Rohini Kumar, Sabine Attinger, and Luis Samaniego
Geosci. Model Dev., 15, 859–882, https://doi.org/10.5194/gmd-15-859-2022, https://doi.org/10.5194/gmd-15-859-2022, 2022
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The recently released multiscale parameter regionalization (MPR) tool enables
environmental modelers to efficiently use extensive datasets for model setups.
It flexibly ingests the datasets using user-defined data–parameter relationships
and rescales parameter fields to given model resolutions. Modern
land surface models especially benefit from MPR through increased transparency and
flexibility in modeling decisions. Thus, MPR empowers more sound and robust
simulations of the Earth system.
Hubert T. Samboko, Sten Schurer, Hubert H. G. Savenije, Hodson Makurira, Kawawa Banda, and Hessel Winsemius
Geosci. Instrum. Method. Data Syst., 11, 1–23, https://doi.org/10.5194/gi-11-1-2022, https://doi.org/10.5194/gi-11-1-2022, 2022
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The study was conducted along the Luangwa River in Zambia. It combines low-cost instruments such as UAVs and GPS kits to collect data for the purposes of water management. A novel technique which seamlessly merges the dry and wet bathymetry before application in a hydraulic model was applied. Successful implementation resulted in water authorities with small budgets being able to monitor flows safely and efficiently without significant compromise on accuracy.
Michael Peichl, Stephan Thober, Luis Samaniego, Bernd Hansjürgens, and Andreas Marx
Hydrol. Earth Syst. Sci., 25, 6523–6545, https://doi.org/10.5194/hess-25-6523-2021, https://doi.org/10.5194/hess-25-6523-2021, 2021
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Using a statistical model that can also take complex systems into account, the most important factors affecting wheat yield in Germany are determined. Different spatial damage potentials are taken into account. In many parts of Germany, yield losses are caused by too much soil water in spring. Negative heat effects as well as damaging soil drought are identified especially for north-eastern Germany. The model is able to explain years with exceptionally high yields (2014) and losses (2003, 2018).
Joni Dehaspe, Fanny Sarrazin, Rohini Kumar, Jan H. Fleckenstein, and Andreas Musolff
Hydrol. Earth Syst. Sci., 25, 6437–6463, https://doi.org/10.5194/hess-25-6437-2021, https://doi.org/10.5194/hess-25-6437-2021, 2021
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Increased nitrate concentrations in surface waters can compromise river ecosystem health. As riverine nitrate uptake is hard to measure, we explore how low-frequency nitrate concentration and discharge observations (that are widely available) can help to identify (in)efficient uptake in river networks. We find that channel geometry and water velocity rather than the biological uptake capacity dominate the nitrate-discharge pattern at the outlet. The former can be used to predict uptake.
Cited articles
Abdulla, F. A. and Lettenmaier, D. P.: Development of regional parameter
estimation equations for a macroscale hydrologic model, J. Hydrol., 197,
230–257, https://doi.org/10.1016/S0022-1694(96)03262-3, 1997.
Andréassian, V., Perrin, C., Berthet, L., Le Moine, N., Lerat, J.,
Loumagne, C., Oudin, L., Mathevet, T., Ramos, M.-H., and Valéry, A.: HESS
Opinions “Crash tests for a standardized evaluation of hydrological
models”, Hydrol. Earth Syst. Sci., 13, 1757–1764,
https://doi.org/10.5194/hess-13-1757-2009, 2009.
Andréassian, V., Le Moine, N., Perrin, C., Ramos, M.-H., Oudin, L.,
Mathevet, T., Lerat, J., and Berthet, L.: All that glitters is not gold: the
case of calibrating hydrological models, Hydrol. Process., 26, 2206–2210,
https://doi.org/10.1002/hyp.9264, 2012.
Arino, O., Ramos, J., Kalogirou, V., Defourny, P., and Achard, F.: GlobCover,
ESA Living Planet Symposium, 27 June–2 July 2010, Bergen, Norway, 2009.
Bergström, S.: The HBV model: Its structure and applications, Swedish
Meteorological and Hydrological Institute, Norrköping, 1–33, 1992.
Beven, K. J.: Prophecy, reality and uncertainty in distributed hydrological
modelling, Adv. Water Resour., 16, 41–51, https://doi.org/10.1016/0309-1708(93)90028-E,
1993.
Beven, K. J.: Uniqueness of place and process representations in hydrological
modelling, Hydrol. Earth Syst. Sci., 4, 203–213,
https://doi.org/10.5194/hess-4-203-2000, 2000.
Beven, K. J.: A manifesto for the equifinality thesis, J. Hydrol., 320,
18–36, https://doi.org/10.1016/j.jhydrol.2005.07.007, 2006.
Beven, K. J. and Kirkby, M. J.: A physically based, variable contributing
area model of basin hydrology/Un modèle à base physique de zone
d'appel variable de l'hydrologie du bassin versant, Hydrol. Sci. Bull.,
24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Booij, M.: Impact of climate change on river flooding assessed with different
spatial model resolutions, J. Hydrol., 303, 176–198,
https://doi.org/10.1016/j.jhydrol.2004.07.013, 2005.
Coron, L., Andréassian, V., Perrin, C., Lerat, J., Vaze, J., Bourqui, M.,
and Hendrickx, F.: Crash testing hydrological models in contrasted climate
conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48,
W05552, https://doi.org/10.1029/2011WR011721, 2012.
Das, T., Bárdossy, A., Zehe, E., and He, Y.: Comparison of conceptual
model performance using different representations of spatial variability, J.
Hydrol., 356, 106–118, https://doi.org/10.1016/j.jhydrol.2008.04.008, 2008.
Detty, J. M. and McGuire, K. J.: Topographic controls on shallow groundwater
dynamics: implications of hydrologic connectivity between hillslopes and
riparian zones in a till mantled catchment, Hydrol. Process., 24, 2222–2236,
https://doi.org/10.1002/hyp.7656, 2010.
Duan, Q., Sorooshian, S., and Gupta, V.: Effective and efficient global
optimization for conceptual rainfall-runoff models, Water Resour. Res.,
28, 1015–1031, https://doi.org/10.1029/91WR02985, 1992.
Eder, G., Sivapalan, M., and Nachtnebel, H. P.: Modelling water balances in
an Alpine catchment through exploitation of emergent properties over changing
time scales, Hydrol. Process., 17, 2125–2149, https://doi.org/10.1002/hyp.1325, 2003.
Euser, T., Winsemius, H. C., Hrachowitz, M., Fenicia, F., Uhlenbrook, S., and
Savenije, H. H. G.: A framework to assess the realism of model structures
using hydrological signatures, Hydrol. Earth Syst. Sci., 17, 1893–1912,
https://doi.org/10.5194/hess-17-1893-2013, 2013.
Euser, T., Hrachowitz, M., Winsemius, H. C., and Savenije, H. H. G.: The
effect of forcing and landscape distribution on performance and consistency
of model structures, Hydrol. Process., 29, 3727–3743, https://doi.org/10.1002/hyp.10445,
2015.
FAO/IIASA/ISRIC/ISSCAS/JRC: Harmonized World Soil Database (version 1.2),
Rome, Laxenburg, 2012.
Fenicia, F., Savenije, H. H. G., Matgen, P., and Pfister, L.: Understanding
catchment behavior through stepwise model concept improvement, Water Resour.
Res., 44, W01402, https://doi.org/10.1029/2006WR005563, 2008
Flügel, W.-A.: Delineating hydrological response units by geographical
information system analyses for regional hydrological modelling using
PRMS/MMS in the drainage basin of the River Bröl, Germany, Hydrol.
Process., 9, 423–436, https://doi.org/10.1002/hyp.3360090313, 1995.
Fovet, O., Ruiz, L., Hrachowitz, M., Faucheux, M., and Gascuel-Odoux, C.:
Hydrological hysteresis and its value for assessing process consistency in
catchment conceptual models, Hydrol. Earth Syst. Sci., 19, 105–123,
https://doi.org/10.5194/hess-19-105-2015, 2015.
Gao, H., Hrachowitz, M., Fenicia, F., Gharari, S., and Savenije, H. H. G.:
Testing the realism of a topography-driven model (FLEX-Topo) in the nested
catchments of the Upper Heihe, China, Hydrol. Earth Syst. Sci., 18,
1895–1915, https://doi.org/10.5194/hess-18-1895-2014, 2014a.
Gao, H., Hrachowitz, M., Schymanski, S. J., Fenicia, F., Sriwongsitanon, N.,
and Savenije, H. H. G.: Climate controls how ecosystems size the root zone
storage capacity at catchment scale, Geophys. Res. Lett., 41,
7916–7923, https://doi.org/10.1002/2014GL061668, 2014b.
Gharari, S., Hrachowitz, M., Fenicia, F., and Savenije, H. H. G.:
Hydrological landscape classification: investigating the performance of HAND
based landscape classifications in a central European meso-scale catchment,
Hydrol. Earth Syst. Sci., 15, 3275–3291, https://doi.org/10.5194/hess-15-3275-2011,
2011.
Gharari, S., Hrachowitz, M., Fenicia, F., Gao, H., and Savenije, H. H. G.:
Using expert knowledge to increase realism in environmental system models can
dramatically reduce the need for calibration, Hydrol. Earth Syst. Sci., 18,
4839–4859, https://doi.org/10.5194/hess-18-4839-2014, 2014.
Götzinger, J. and Bárdossy, A.: Comparison of four regionalisation
methods for a distributed hydrological model, J. Hydrol., 333, 374–384,
https://doi.org/10.1016/j.jhydrol.2006.09.008, 2007.
Gupta, H. V., Wagener, T., and Liu, Y.: Reconciling theory with observations:
elements of a diagnostic approach to model evaluation, Hydrol. Process., 22,
3802–3813, https://doi.org/10.1002/hyp.6989, 2008.
Gupta, H. V., Clark, M. P., Vrugt, J. A., Abramowitz, G., and Ye, M.: Towards
a comprehensive assessment of model structural adequacy, Water Resour. Res.,
48, W08301, https://doi.org/10.1029/2011WR011044, 2012.
Hargreaves, G. H. and Samani, Z. A.: Reference crop evapotranspiration from
ambient air temperature, American Society of Agricultural Engineers,
Microfiche collection, USA, no. 85-2517, Chicago, 1985.
Haylock, M., Hofstra, N., Klein Tank, A., Klok, E., Jones, P., and New, M.: A
European daily high-resolution gridded data set of surface temperature and
precipitation for 1950–2006, J. Geophys. Res.-Atmos., 113,
D20119, https://doi.org/10.1029/2008JD010201, 2008.
Holländer, H. M., Blume, T., Bormann, H., Buytaert, W., Chirico, G.,
Exbrayat, J.-F., Gustafsson, D., Hölzel, H., Kraft, P., Stamm, C., Stoll,
S., Blöschl, G., and Flühler, H.: Comparative predictions of
discharge from an artificial catchment (Chicken Creek) using sparse data,
Hydrol. Earth Syst. Sci., 13, 2069–2094, https://doi.org/10.5194/hess-13-2069-2009,
2009.
Hrachowitz, M. and Weiler, M.: Uncertainty of Precipitation Estimates Caused
by Sparse Gauging Networks in a Small, Mountainous Watershed, J. Hydrol. Eng., 16, 460–471,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0000331, 2011.
Hrachowitz, M., Fovet, O., Ruiz, L., Euser, T., Gharari, S., Nijzink, R.,
Freer, J., Savenije, H. H. G., and Gascuel-Odoux, C.: Process consistency in
models: The importance of system signatures, expert knowledge, and process
complexity, Water Resour. Res., 50, 7445–7469,
https://doi.org/10.1002/2014WR015484, 2014.
Hughes, D.: A review of 40 years of hydrological science and practice in
southern Africa using the Pitman rainfall runoff model, J. Hydrol., 501,
111–124, https://doi.org/10.1016/j.jhydrol.2013.07.043, 2013.
Hundecha, Y. and Bárdossy, A.: Modeling of the effect of land use changes
on the runoff generation of a river basin through parameter regionalization
of a watershed model, J. Hydrol., 292, 281–295,
https://doi.org/10.1016/j.jhydrol.2004.01.002, 2004.
Jencso, K. G., McGlynn, B. L., Gooseff, M. N., Wondzell, S. M., Bencala, K.
E., and Marshall, L. A.: Hydrologic connectivity between landscapes and
streams: Transferring reach- and plotscale understanding to the catchment
scale, Water Resour. Res., 45, W04428, https://doi.org/10.1029/2008WR007225, 2009.
Jothityangkoon, C., Sivapalan, M., and Farmer, D.: Process controls of water
balance variability in a large semi-arid catchment: downward approach to
hydrological model development, J. Hydrol., 254, 174–198,
https://doi.org/10.1016/S0022-1694(01)00496-6, 2001.
Kapangaziwiri, E., Hughes, D., and Wagener, T.: Incorporating uncertainty in
hydrological predictions for gauged and ungauged basins in southern Africa,
Hydrol. Sci. J., 57, 1000–1019, https://doi.org/10.1080/02626667.2012.690881, 2012.
Kirchner, J. W.: Getting the right answers for the right reasons: Linking
measurements, analyses, and models to advance the science of hydrology,
Water Resour. Res., 42, W03S04, https://doi.org/10.1029/2005WR004362, 2006.
Kite, G. W. and Kouwen, N.: Watershed modeling using land classifications,
Water Resour. Res., 28, 3193–3200, https://doi.org/10.1029/92WR01819, 1992.
Knudsen, J., Thomsen, A., and Refsgaard, J. C.: WATBAL, Nord. Hydrol.,
17, 347–362, 1986.
Kouwen, N., Soulis, E., Pietroniro, A., Donald, J., and Harrington, R.:
Grouped Response Units for Distributed Hydrologic Modeling,
J. Water Resour. Plan. Manage, 119, 289–305,
https://doi.org/10.1061/(ASCE)0733-9496(1993)119:3(289), 1993.
Kumar, P.: Typology of hydrologic predictability, Water Resour. Res.,
47, W00H05, https://doi.org/10.1029/2010WR009769, 2011.
Kumar, R., Samaniego, L., and Attinger, S.: The effects of spatial
discretization and model parameterization on the prediction of extreme runoff
characteristics, J. Hydrol., 392, 54–69, https://doi.org/10.1016/j.jhydrol.2010.07.047,
2010.
Kumar, R., Livneh, B., and Samaniego, L.: Toward computationally efficient
large-scale hydrologic predictions with a multiscale regionalization scheme,
Water Resour. Res., 49, 5700–5714, https://doi.org/10.1002/wrcr.20431, 2013a.
Kumar, R., Samaniego, L., and Attinger, S.: Implications of distributed
hydrologic model parameterization on water fluxes at multiple scales and
locations, Water Resour. Res., 49, 360–379, https://doi.org/10.1029/2012WR012195,
2013b.
Kunstmann, H., Krause, J., and Mayr, S.: Inverse distributed hydrological
modelling of Alpine catchments, Hydrol. Earth Syst. Sci., 10, 395–412,
https://doi.org/10.5194/hess-10-395-2006, 2006.
Leavesley, G. and Stannard, L.: Application of remotely sensed data in a
distributed-parameter watershed model, Application of Remote Sensing in
Hydrology, Saskatoon, 47–68, 1990.
Lehner, B., Verdin, K., and Jarvis, A.: New global hydrography derived from
spaceborne elevation data, EOS, Trans. Am. Geophys. Union, 89,
93–94, 2008.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple
hydrologically based model of land surface water and energy fluxes for
general circulation models, J. Geophys. Res.-Atmos., 99,
14415–14428, https://doi.org/10.1029/94JD00483, 1994.
Lindström, G., Pers, C., Rosberg, J., Stromqvist, J., and Arheimer, B.:
Development and testing of the HYPE (Hydrological Predictions for the
Environment) water quality model for different spatial scales, Hydrol. Res.,
41, 295–319, https://doi.org/10.2166/nh.2010.007, 2010.
Livneh, B., Kumar, R., and Samaniego, L.: Influence of soil textural
properties on hydrologic fluxes in the Mississippi river basin, Hydrol.
Process., 29, 4638–4655, https://doi.org/10.1002/hyp.10601, 2015.
McGlynn, B. L., McDonnell, J. J., Seibert, J., and Kendall, C.: Scale effects
on headwater catchment runoff timing, flow sources, and
groundwater-streamflow relations, Water Resour. Res., 40, W07504,
https://doi.org/10.1029/2003WR002494, 2004.
Merz, B. and Bárdossy, A.: Effects of spatial variability on the rainfall
runoff process in a small loess catchment, J. Hydrol., 212–213, 304–317,
https://doi.org/10.1016/S0022-1694(98)00213-3, 1998.
Montanari, A. and Toth, E.: Calibration of hydrological models in the
spectral domain: An opportunity for scarcely gauged basins?, Water Resour.
Res., 43, W05434, https://doi.org/10.1029/2006WR005184, 2007.
Mou, L., Tian, F., Hu, H., and Sivapalan, M.: Extension of the Representative
Elementary Watershed approach for cold regions: constitutive relationships
and an application, Hydrol. Earth Syst. Sci., 12, 565–585,
https://doi.org/10.5194/hess-12-565-2008, 2008.
Muerth, M. J., Gauvin St-Denis, B., Ricard, S., Velázquez, J. A., Schmid,
J., Minville, M., Caya, D., Chaumont, D., Ludwig, R., and Turcotte, R.: On
the need for bias correction in regional climate scenarios to assess climate
change impacts on river runoff, Hydrol. Earth Syst. Sci., 17, 1189–1204,
https://doi.org/10.5194/hess-17-1189-2013, 2013.
Nicolle, P., Pushpalatha, R., Perrin, C., François, D., Thiéry, D.,
Mathevet, T., Le Lay, M., Besson, F., Soubeyroux, J.-M., Viel, C., Regimbeau,
F., Andréassian, V., Maugis, P., Augeard, B., and Morice, E.:
Benchmarking hydrological models for low-flow simulation and forecasting on
French catchments, Hydrol. Earth Syst. Sci., 18, 2829–2857,
https://doi.org/10.5194/hess-18-2829-2014, 2014.
Nobre, A., Cuartas, L., Hodnett, M., Rennó, C., Rodrigues, G., Silveira,
A., Waterloo, M., and Saleska, S.: Height Above the Nearest Drainage – a
hydrologically relevant new terrain model, J. Hydrol., 404, 13–29,
https://doi.org/10.1016/j.jhydrol.2011.03.051, 2011.
Obled, C., Wendling, J., and Beven, K.: The sensitivity of hydrological
models to spatial rainfall patterns: an evaluation using observed data, J.
Hydrol., 159, 305–333, https://doi.org/10.1016/0022-1694(94)90263-1, 1994.
Orth, R., Staudinger, M., Seneviratne, S. I., Seibert, J., and Zappa, M.:
Does model performance improve with complexity? A case study with three
hydrological models, J. Hydrol., 523, 147–159,
https://doi.org/10.1016/j.jhydrol.2015.01.044, 2015.
Pape, P. L., Ayrault, S., and Quantin, C.: Trace element behaviour and
partition versus urbanization gradient in an urban river (Orge River,
France), J. Hydrol., 472–473, 99–110, https://doi.org/10.1016/j.jhydrol.2012.09.042,
2012.
Perrin, C., Michel, C., and Andréassian, V.: Does a large number of
parameters enhance model performance? Comparative assessment of common
catchment model structures on 429 catchments, J. Hydrol., 242, 275–301,
https://doi.org/10.1016/S0022-1694(00)00393-0, 2001.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a
parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289,
https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Pokhrel, P., Gupta, H. V., and Wagener, T.: A spatial regularization approach
to parameter estimation for a distributed watershed model, Water Resour.
Res., 44, W12419, https://doi.org/10.1029/2007WR006615, 2008.
Pushpalatha, R., Perrin, C., Moine, N. L., Mathevet, T., and Andréassian,
V.: A downward structural sensitivity analysis of hydrological models to
improve lowflow simulation, J. Hydrol., 411, 66–76,
https://doi.org/10.1016/j.jhydrol.2011.09.034, 2011.
Rakovec, O., Kumar, R., Mai, J., Cuntz, M., Thober, S., Zink, M., Attinger,
S., Schäfer, D., Schrön, M., and Samaniego, L.: Multiscale and
multivariate evaluation of water fluxes and states over European river
basins, J. Hydrometeorol., 17, 287–307,
https://doi.org/10.1175/JHM-D-15-0054.1, 2015.
Reed, S., Koren, V., Smith, M., Zhang, Z., Moreda, F., Seo, D.-J., and
Participants, D.: Overall distributed model intercomparison project results,
J. Hydrol., 298, 27–60, https://doi.org/10.1016/j.jhydrol.2004.03.031, 2004.
Refsgaard, J. C. and Storm, B.: MIKE SHE, in: Computer models of watershed
hydrology, edited by: Singh, V. P., Water Resources Publications, Littleton,
809–846, 1995.
Refsgaard, J. C. and Knudsen, J.: Operational Validation and Intercomparison
of Different Types of Hydrological Models, Water Resour. Res., 32, 2189–2202, https://doi.org/10.1029/96WR00896,
1996.
Reggiani, P. and Rientjes, T. H. M.: Flux parameterization in
the representative elementary watershed approach: Application to a natural
basin, Water Resour. Res., 41, W04013, https://doi.org/10.1029/2004WR003693,
2005.
Reggiani, P., Sivapalan, M., and Hassanizadeh, S. M.: A unifying framework
for watershed thermodynamics: balance equations for mass, momentum, energy
and entropy, and the second law of thermodynamics, Adv. Water Resour., 22,
367–398, https://doi.org/10.1016/S0309-1708(98)00012-8, 1998.
Reichert, P. and Omlin, M.: On the usefulness of overparameterized ecological
models, Ecol. Model., 95, 289–299, https://doi.org/10.1016/S0304-3800(96)00043-9, 1997.
Rennó, C. D., Nobre, A. D., Cuartas, L. A., Soares, J. V., Hodnett, M.
G., Tomasella, J., and Waterloo, M. J.: HAND, a new terrain descriptor using
SRTM-DEM: Mapping terra-firme rainforest environments in Amazonia,
Remote Sens. Environ., 112, 3469–3481, https://doi.org/10.1016/j.rse.2008.03.018,
2008.
Rodríguez-Iturbe, I., Isham, V., Cox, D. R., Manfreda, S., and
Porporato, A.: Space-time modeling of soil moisture: Stochastic rainfall
forcing with heterogeneous vegetation, Water Resour. Res., 42, W06D05,
https://doi.org/10.1029/2005WR004497, 2006.
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, 2010a.
Samaniego, L., Bárdossy, A., and Kumar, R.: Streamflow prediction in
ungauged catchments using copula-based dissimilarity measures, Water Resour.
Res., 46, W02506, https://doi.org/10.1029/2008WR007695, 2010b.
Samaniego, L., Kumar, R., and Zink, M.: Implications of parameter uncertainty
on soil moisture drought analysis in Germany, J. Hydrometeorol.,
14, 47–68, https://doi.org/10.1175/JHM-D-12-075.1, 2013.
Savenije, H. H. G.: HESS Opinions “Topography driven conceptual modelling
(FLEX-Topo)”, Hydrol. Earth Syst. Sci., 14, 2681–2692,
https://doi.org/10.5194/hess-14-2681-2010, 2010.
Sawicz, K., Wagener, T., Sivapalan, M., Troch, P. A., and
Carrillo, G.: Catchment classification: empirical analysis
of hydrologic similarity based on catchment function in the eastern USA, Hydrol. Earth Syst. Sci., 15, 2895–2911, https://doi.org/10.5194/hess-15-2895-2011,
2011.
Schmalz, B. and Fohrer, N.: Comparing model sensitivities of different
landscapes using the ecohydrological SWAT model, Adv. Geosci., 21, 91–98,
https://doi.org/10.5194/adgeo-21-91-2009, 2009.
Schmalz, B., Tavares, F., and Fohrer, N.: Modelling hydrological processes in
mesoscale lowland river basins with SWAT – capabilities and challenges,
Hydrol. Sci. J., 53, 989–1000, https://doi.org/10.1623/hysj.53.5.989,
2008.
Schmocker-Fackel, P., Naef, F., and Scherrer, S.: Identifying runoff
processes on the plot and catchment scale, Hydrol. Earth Syst. Sci., 11,
891–906, https://doi.org/10.5194/hess-11-891-2007, 2007.
Schoups, G., Hopmans, J. W., Young, C. A., Vrugt, J. A., and Wallender, W.
W.: Multi-criteria optimization of a regional spatially-distributed
subsurface water flow model, J. Hydrol., 311, 20–48,
https://doi.org/10.1016/j.jhydrol.2005.01.001, 2005.
Seibert, J. and McDonnell, J.: Gauging the Ungauged Basin: Relative Value of
Soft and Hard Data, J. Hydrol. Eng., A4014004,
https://doi.org/10.1061/(ASCE)HE.1943-5584.0000861, 2013.
Seibert, J. and McDonnell, J. J.: On the dialog between experimentalist and
modeler in catchment hydrology: Use of soft data for multicriteria model
calibration, Water Resour. Res., 38, 23-1–23-14,
https://doi.org/10.1029/2001WR000978, 2002.
Seibert, J., Bishop, K., Rodhe, A., and McDonnell, J. J.: Groundwater
dynamics along a hillslope: A test of the steady state hypothesis,
Water Resour. Res., 39, 1014, https://doi.org/10.1029/2002WR001404, 2003a.
Seibert, J., Rodhe, A., and Bishop, K.: Simulating interactions between
saturated and unsaturated storage in a conceptual runoff model, Hydrol.
Process., 17, 379–390, https://doi.org/10.1002/hyp.1130, 2003b.
Shamir, E., Imam, B., Morin, E., Gupta, H. V., and Sorooshian, S.: The role
of hydrograph indices in parameter estimation of rainfall–runoff models,
Hydrol. Process., 19, 2187–2207, https://doi.org/10.1002/hyp.5676, 2005.
Singh, V. P.: Effect of spatial and temporal variability in rainfall and
watershed characteristics on stream flow hydrograph, Hydrol. Process., 11,
1649–1669, https://doi.org/10.1002/(SICI)1099-1085(19971015)11:12<1649::AID-HYP495>3.0.CO;2-1, 1997.
Smakhtin, V.: Low flow hydrology: a review, J. Hydrol., 240, 147–186,
https://doi.org/10.1016/S0022-1694(00)00340-1, 2001.
Spence, C., Guan, X. J., Phillips, R., Hedstrom, N., Granger, R., and Reid,
B.: Storage dynamics and streamflow in a catchment with a variable
contributing area, Hydrol. Process., 24, 2209–2221, https://doi.org/10.1002/hyp.7492,
2010.
Staudinger, M., Stahl, K., Seibert, J., Clark, M. P., and Tallaksen, L. M.:
Comparison of hydrological model structures based on recession and low flow
simulations, Hydrol. Earth Syst. Sci., 15, 3447–3459,
https://doi.org/10.5194/hess-15-3447-2011, 2011.
te Linde, A. H., Aerts, J. C. J. H., Hurkmans, R. T. W. L., and Eberle, M.:
Comparing model performance of two rainfall runoff models in the Rhine basin
using different atmospheric forcing data sets, Hydrol. Earth Syst. Sci., 12,
943–957, https://doi.org/10.5194/hess-12-943-2008, 2008.
Thober, S., Kumar, R., Sheffield, J., Mai, J., Schäfer, D., and
Samaniego, L.: Seasonal Soil Moisture Drought Prediction over Europe using
the North American Multi-Model Ensemble (NMME), J. Hydrometeorol.,
2329–2344, https://doi.org/10.1175/JHM-D-15-0053.1, 2015.
Tian, F., Hu, H., Lei, Z., and Sivapalan, M.: Extension of the Representative
Elementary Watershed approach for cold regions via explicit treatment of
energy related processes, Hydrol. Earth Syst. Sci., 10, 619–644,
https://doi.org/10.5194/hess-10-619-2006, 2006.
Tolson, B. A. and Shoemaker, C. A.: Dynamically dimensioned search algorithm
for computationally efficient watershed model calibration, Water Resour.
Res., 43, W01413, https://doi.org/10.1029/2005WR004723, 2007.
Tonkin, M. J. and Doherty, J.: A hybrid regularized inversion methodology for
highly parameterized environmental models, Water Resour. Res., 41,
W10412, https://doi.org/10.1029/2005WR003995, 2005.
Tromp-van Meerveld, H. J. and McDonnell, J. J.: Threshold relations in
subsurface stormflow: 2. The fill and spill hypothesis, Water Resour. Res.,
42, W02411, https://doi.org/10.1029/2004WR003800, 2006.
Uhlenbrook, S., Roser, S., and Tilch, N.: Hydrological process representation
at the meso-scale: the potential of a distributed, conceptual catchment
model, J. Hydrol., 291, 278–296, https://doi.org/10.1016/j.jhydrol.2003.12.038, 2004.
van Emmerik, T., Mulder, G., Eilander, D., Piet, M., and Savenije, H.:
Predicting the ungauged basin: Model validation and realism assessment,
Front. Earth Sci., 3, 62, https://doi.org/10.3389/feart.2015.00062, 2015.
van Esse, W. R., Perrin, C., Booij, M. J., Augustijn, D. C. M., Fenicia, F.,
Kavetski, D., and Lobligeois, F.: The influence of conceptual model structure
on model performance: a comparative study for 237 French catchments, Hydrol.
Earth Syst. Sci., 17, 4227–4239, https://doi.org/10.5194/hess-17-4227-2013, 2013.
Vannametee, E., Karssenberg, D., and Bierkens, M. F. P.: Towards closure relations
in the Representative Elementary Watershed (REW) framework containing
observable parameters: Relations for Hortonian overland flow, Adv. Water
Resour., 43, 52–66, https://doi.org/10.1016/j.advwatres.2012.03.029, 2012.
Velázquez, J. A., Schmid, J., Ricard, S., Muerth, M. J., Gauvin St-Denis,
B., Minville, M., Chaumont, D., Caya, D., Ludwig, R., and Turcotte, R.: An
ensemble approach to assess hydrological models' contribution to
uncertainties in the analysis of climate change impact on water resources,
Hydrol. Earth Syst. Sci., 17, 565–578, https://doi.org/10.5194/hess-17-565-2013, 2013.
Wagener, T. and Gupta, H.: Model identification for hydrological forecasting
under uncertainty, Stochastic Environmental Research and Risk Assessment, 19,
378–387, https://doi.org/10.1007/s00477-005-0006-5, 2005.
Wigmosta, M. S., Vail, L. W., and Lettenmaier, D. P.: A distributed
hydrology-vegetation model for complex terrain, Water Resour. Res., 30,
1665–1679, https://doi.org/10.1029/94WR00436, 1994.
Wilks, D. S.: Statistical methods in the atmospheric sciences, vol. 100,
Academic Press, Oxford, 351–354, 2011.
Winsemius, H. C., Savenije, H. H. G., and Bastiaanssen, W. G. M.:
Constraining model parameters on remotely sensed evaporation: justification
for distribution in ungauged basins?, Hydrol. Earth Syst. Sci., 12, 1403–1413,
https://doi.org/10.5194/hess-12-1403-2008, 2008.
Winter, T. C.: THE CONCEPT OF HYDROLOGIC LANDSCAPES1, J.
Am. W. Resour. Assoc., 37, 335–349,
https://doi.org/10.1111/j.1752-1688.2001.tb00973.x, 2001.
Yilmaz, K. K., Gupta, H. V., and Wagener, T.: A process-based diagnostic
approach to model evaluation: Application to the NWS distributed hydrologic
model, Water Resour. Res., 44, W09417, https://doi.org/10.1029/2007WR006716, 2008.
Young, P. C.: Parallel Processes in Hydrology andWater Quality: A Unified
Time-Series Approach, Water Environ. J., 6, 598–612,
https://doi.org/10.1111/j.1747-6593.1992.tb00796.x, 1992.
Zehe, E., Maurer, T., Ihringer, J., and Plate, E.: Modeling water flow and
mass transport in a loess catchment, Phys. Chem. Earth, 26, 487–507,
https://doi.org/10.1016/S1464-1909(01)00041-7, 2001.
Zehe, E., Ehret, U., Pfister, L., Blume, T., Schröder, B., Westhoff, M.,
Jackisch, C., Schymanski, S. J., Weiler, M., Schulz, K., Allroggen, N.,
Tronicke, J., van Schaik, L., Dietrich, P., Scherer, U., Eccard, J.,
Wulfmeyer, V., and Kleidon, A.: HESS Opinions: From response units to
functional units: a thermodynamic reinterpretation of the HRU concept to link
spatial organization and functioning of intermediate scale catchments,
Hydrol. Earth Syst. Sci., 18, 4635–4655, https://doi.org/10.5194/hess-18-4635-2014,
2014.
Zhang, G. P. and Savenije, H. H. G.: Rainfall-runoff modelling in a catchment
with a complex groundwater flow system: application of the Representative
Elementary Watershed (REW) approach, Hydrol. Earth Syst. Sci., 9, 243–261,
https://doi.org/10.5194/hess-9-243-2005, 2005.
Zhang, G. P., Savenije, H. H. G., Fenicia, F., and Pfister, L.: Modelling
subsurface storm flow with the Representative Elementary Watershed (REW)
approach: application to the Alzette River Basin, Hydrol. Earth Syst. Sci.,
10, 937–955, https://doi.org/10.5194/hess-10-937-2006, 2006.
Zhao, R.-J.: The Xinanjiang model applied in China, J. Hydrol., 135,
371–381, https://doi.org/10.1016/0022-1694(92)90096-E, 1992.
Short summary
The heterogeneity of landscapes in river basins strongly affects the hydrological response. In this study, the distributed mesoscale Hydrologic Model (mHM) was equipped with additional processes identified by landscapes within one modelling cell. Seven study catchments across Europe were selected to test the value of this additional sub-grid heterogeneity. In addition, the models were constrained based on expert knowledge. Generally, the modifications improved the representation of low flows.
The heterogeneity of landscapes in river basins strongly affects the hydrological response. In...
