Articles | Volume 26, issue 14
https://doi.org/10.5194/hess-26-3805-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-26-3805-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
On the similarity of hillslope hydrologic function: a clustering approach based on groundwater changes
Fadji Z. Maina
CORRESPONDING AUTHOR
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA 94704, USA
now at: NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, 8800 Greenbelt Rd, Greenbelt, 20771 MD, USA
Haruko M. Wainwright
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA 94704, USA
Peter James Dennedy-Frank
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA 94704, USA
Erica R. Siirila-Woodburn
Energy Geosciences Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, M. S. 74R-316C, Berkeley, CA 94704, USA
Related authors
Peyman Abbaszadeh, Fadji Zaouna Maina, Chen Yang, Dan Rosen, Sujay Kumar, Matthew Rodell, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-280, https://doi.org/10.5194/hess-2024-280, 2024
Preprint under review for HESS
Short summary
Short summary
To manage Earth's water resources effectively amid climate change, it's crucial to understand both surface and groundwater processes. We developed a new modeling system that combines two advanced tools, ParFlow and LIS/Noah-MP, to better simulate both land surface and groundwater interactions. By testing this integrated model in the Upper Colorado River Basin, we found it improves predictions of hydrologic processes, especially in complex terrains.
Fadji Z. Maina, Alan Rhoades, Erica R. Siirila-Woodburn, and Peter-James Dennedy-Frank
Hydrol. Earth Syst. Sci., 26, 3589–3609, https://doi.org/10.5194/hess-26-3589-2022, https://doi.org/10.5194/hess-26-3589-2022, 2022
Short summary
Short summary
In this work, we assess the effects of end-of-century extreme dry and wet conditions on the hydrology of California. Our results, derived from cutting-edge and high-resolution climate and hydrologic models, highlight that (1) water storage will be larger and increase earlier in the year, yet the summer streamflow will decrease as a result of high evapotranspiration rates, and that (2) groundwater and lower-order streams are very sensitive to decreases in snowmelt and higher evapotranspiration.
Fadji Z. Maina, Erica R. Siirila-Woodburn, and Pouya Vahmani
Hydrol. Earth Syst. Sci., 24, 3451–3474, https://doi.org/10.5194/hess-24-3451-2020, https://doi.org/10.5194/hess-24-3451-2020, 2020
Short summary
Short summary
Projecting the changes in water resources under a no-analog future climate requires integrated hydrologic models. However, these models are plagued by several sources of uncertainty. A hydrologic model was forced with various resolutions of meteorological forcing (0.5 to 40.5 km) to assess its sensitivity to these inputs. We show that most hydrologic variables reveal biases that are seasonally and spatially dependent, which can have serious implications for calibration and water management.
Peyman Abbaszadeh, Fadji Zaouna Maina, Chen Yang, Dan Rosen, Sujay Kumar, Matthew Rodell, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-280, https://doi.org/10.5194/hess-2024-280, 2024
Preprint under review for HESS
Short summary
Short summary
To manage Earth's water resources effectively amid climate change, it's crucial to understand both surface and groundwater processes. We developed a new modeling system that combines two advanced tools, ParFlow and LIS/Noah-MP, to better simulate both land surface and groundwater interactions. By testing this integrated model in the Upper Colorado River Basin, we found it improves predictions of hydrologic processes, especially in complex terrains.
Zexuan Xu, Erica R. Siirila-Woodburn, Alan M. Rhoades, and Daniel Feldman
Hydrol. Earth Syst. Sci., 27, 1771–1789, https://doi.org/10.5194/hess-27-1771-2023, https://doi.org/10.5194/hess-27-1771-2023, 2023
Short summary
Short summary
The goal of this study is to understand the uncertainties of different modeling configurations for simulating hydroclimate responses in the mountainous watershed. We run a group of climate models with various configurations and evaluate them against various reference datasets. This paper integrates a climate model and a hydrology model to have a full understanding of the atmospheric-through-bedrock hydrological processes.
Fadji Z. Maina, Alan Rhoades, Erica R. Siirila-Woodburn, and Peter-James Dennedy-Frank
Hydrol. Earth Syst. Sci., 26, 3589–3609, https://doi.org/10.5194/hess-26-3589-2022, https://doi.org/10.5194/hess-26-3589-2022, 2022
Short summary
Short summary
In this work, we assess the effects of end-of-century extreme dry and wet conditions on the hydrology of California. Our results, derived from cutting-edge and high-resolution climate and hydrologic models, highlight that (1) water storage will be larger and increase earlier in the year, yet the summer streamflow will decrease as a result of high evapotranspiration rates, and that (2) groundwater and lower-order streams are very sensitive to decreases in snowmelt and higher evapotranspiration.
Zexuan Xu, Rebecca Serata, Haruko Wainwright, Miles Denham, Sergi Molins, Hansell Gonzalez-Raymat, Konstantin Lipnikov, J. David Moulton, and Carol Eddy-Dilek
Hydrol. Earth Syst. Sci., 26, 755–773, https://doi.org/10.5194/hess-26-755-2022, https://doi.org/10.5194/hess-26-755-2022, 2022
Short summary
Short summary
Climate change could change the groundwater system and threaten water supply. To quantitatively evaluate its impact on water quality, numerical simulations with chemical and reaction processes are required. With the climate projection dataset, we used the newly developed hydrological and chemical model to investigate the movement of contaminants and assist the management of contamination sites.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
Short summary
Short summary
This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Qina Yan, Haruko Wainwright, Baptiste Dafflon, Sebastian Uhlemann, Carl I. Steefel, Nicola Falco, Jeffrey Kwang, and Susan S. Hubbard
Earth Surf. Dynam., 9, 1347–1361, https://doi.org/10.5194/esurf-9-1347-2021, https://doi.org/10.5194/esurf-9-1347-2021, 2021
Short summary
Short summary
We develop a hybrid model to estimate the spatial distribution of the thickness of the soil layer, which also provides estimations of soil transport and soil production rates. We apply this model to two examples of hillslopes in the East River watershed in Colorado and validate the model. The results show that the north-facing (NF) hillslope has a deeper soil layer than the south-facing (SF) hillslope and that the hybrid model provides better accuracy than a machine-learning model.
Fadji Z. Maina, Erica R. Siirila-Woodburn, and Pouya Vahmani
Hydrol. Earth Syst. Sci., 24, 3451–3474, https://doi.org/10.5194/hess-24-3451-2020, https://doi.org/10.5194/hess-24-3451-2020, 2020
Short summary
Short summary
Projecting the changes in water resources under a no-analog future climate requires integrated hydrologic models. However, these models are plagued by several sources of uncertainty. A hydrologic model was forced with various resolutions of meteorological forcing (0.5 to 40.5 km) to assess its sensitivity to these inputs. We show that most hydrologic variables reveal biases that are seasonally and spatially dependent, which can have serious implications for calibration and water management.
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76, https://doi.org/10.5194/gmd-11-61-2018, https://doi.org/10.5194/gmd-11-61-2018, 2018
Short summary
Short summary
The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
Haruko M. Wainwright, Anna K. Liljedahl, Baptiste Dafflon, Craig Ulrich, John E. Peterson, Alessio Gusmeroli, and Susan S. Hubbard
The Cryosphere, 11, 857–875, https://doi.org/10.5194/tc-11-857-2017, https://doi.org/10.5194/tc-11-857-2017, 2017
Short summary
Short summary
Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This paper aims to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. In addition, we develop a Bayesian geostatistical method to integrate multiscale observational platforms (a snow probe, ground penetrating radar, unmanned aerial system and airborne lidar) for estimating snow depth in high resolution over a large area.
Related subject area
Subject: Hillslope hydrology | Techniques and Approaches: Modelling approaches
Technical note: Monitoring discharge of mountain streams by retrieving image features with deep learning
Investigation of the functional relationship between antecedent rainfall and the probability of debris flow occurrence in Jiangjia Gully, China
Rapid spatio-temporal flood modelling via hydraulics-based graph neural networks
Understanding hydrologic controls of sloping soil response to precipitation through machine learning analysis applied to synthetic data
Elucidating the role of soil hydraulic properties on aspect-dependent landslide initiation
Recession discharge from compartmentalized bedrock hillslopes
Frozen soil hydrological modeling for a mountainous catchment northeast of the Qinghai–Tibet Plateau
Spatiotemporal changes in flow hydraulic characteristics and soil loss during gully headcut erosion under controlled conditions
Estimation of rainfall erosivity based on WRF-derived raindrop size distributions
Physically based model for gully simulation: application to the Brazilian semiarid region
Assessing the perturbations of the hydrogeological regime in sloping fens due to roads
A review of the (Revised) Universal Soil Loss Equation ((R)USLE): with a view to increasing its global applicability and improving soil loss estimates
Hybridizing Bayesian and variational data assimilation for high-resolution hydrologic forecasting
Multi-source data assimilation for physically based hydrological modeling of an experimental hillslope
A new method, with application, for analysis of the impacts on flood risk of widely distributed enhanced hillslope storage
Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem
Reconstructing long-term gully dynamics in Mediterranean agricultural areas
Evaluating performance of simplified physically based models for shallow landslide susceptibility
Multiresponse modeling of variably saturated flow and isotope tracer transport for a hillslope experiment at the Landscape Evolution Observatory
Determinants of modelling choices for 1-D free-surface flow and morphodynamics in hydrology and hydraulics: a review
Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale
Quantification of the influence of preferential flow on slope stability using a numerical modelling approach
Hydrological hysteresis and its value for assessing process consistency in catchment conceptual models
Derivation and evaluation of landslide-triggering thresholds by a Monte Carlo approach
Stable water isotope tracing through hydrological models for disentangling runoff generation processes at the hillslope scale
Analysis of landslide triggering conditions in the Sarno area using a physically based model
The influence of grid resolution on the prediction of natural and road-related shallow landslides
Incipient subsurface heterogeneity and its effect on overland flow generation – insight from a modeling study of the first experiment at the Biosphere 2 Landscape Evolution Observatory
Coupled prediction of flood response and debris flow initiation during warm- and cold-season events in the Southern Appalachians, USA
Predicting subsurface stormflow response of a forested hillslope – the role of connected flow paths
Interplay of riparian forest and groundwater in the hillslope hydrology of Sudanian West Africa (northern Benin)
A model-based assessment of the potential use of compound-specific stable isotope analysis in river monitoring of diffuse pesticide pollution
A paradigm shift in stormflow predictions for active tectonic regions with large-magnitude storms: generalisation of catchment observations by hydraulic sensitivity analysis and insight into soil-layer evolution
Derivation of critical rainfall thresholds for shallow landslides as a tool for debris flow early warning systems
Statistical analysis and modelling of surface runoff from arable fields in central Europe
Hydrological modelling of a slope covered with shallow pyroclastic deposits from field monitoring data
Physically based modeling of rainfall-triggered landslides: a case study in the Luquillo forest, Puerto Rico
Characterization of groundwater dynamics in landslides in varved clays
A critical assessment of simple recharge models: application to the UK Chalk
The effect of spatial throughfall patterns on soil moisture patterns at the hillslope scale
Snow accumulation/melting model (SAMM) for integrated use in regional scale landslide early warning systems
Suspended sediment concentration–discharge relationships in the (sub-) humid Ethiopian highlands
A model of hydrological and mechanical feedbacks of preferential fissure flow in a slow-moving landslide
Scale effect on overland flow connectivity at the plot scale
Physical models for classroom teaching in hydrology
Coupling the modified SCS-CN and RUSLE models to simulate hydrological effects of restoring vegetation in the Loess Plateau of China
Effects of peatland drainage management on peak flows
A conceptual model of the hydrological influence of fissures on landslide activity
A structure generator for modelling the initial sediment distribution of an artificial hydrologic catchment
A novel explicit approach to model bromide and pesticide transport in connected soil structures
Chenqi Fang, Genyu Yuan, Ziying Zheng, Qirui Zhong, and Kai Duan
Hydrol. Earth Syst. Sci., 28, 4085–4098, https://doi.org/10.5194/hess-28-4085-2024, https://doi.org/10.5194/hess-28-4085-2024, 2024
Short summary
Short summary
Measuring discharge at steep, rocky mountain streams is challenging due to the difficulties in identifying cross-section characteristics and establishing stable stage–discharge relationships. We present a novel method using only a low-cost commercial camera and deep learning algorithms. Our study shows that deep convolutional neural networks can automatically recognize and retrieve complex stream features embedded in RGB images to achieve continuous discharge monitoring.
Shaojie Zhang, Xiaohu Lei, Hongjuan Yang, Kaiheng Hu, Juan Ma, Dunlong Liu, and Fanqiang Wei
Hydrol. Earth Syst. Sci., 28, 2343–2355, https://doi.org/10.5194/hess-28-2343-2024, https://doi.org/10.5194/hess-28-2343-2024, 2024
Short summary
Short summary
Antecedent effective precipitation (AEP) plays an important role in debris flow formation, but the relationship between AEP and the debris flow occurrence (Pdf) is still not quantified. We used numerical calculation and the Monte Carlo integration method to solve this issue. The relationship between Pdf and AEP can be described by the piecewise function, and debris flow is a small-probability event comparing to rainfall frequency because the maximum Pdf in Jiangjia Gully is only 15.88 %.
Roberto Bentivoglio, Elvin Isufi, Sebastiaan Nicolas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 27, 4227–4246, https://doi.org/10.5194/hess-27-4227-2023, https://doi.org/10.5194/hess-27-4227-2023, 2023
Short summary
Short summary
To overcome the computational cost of numerical models, we propose a deep-learning approach inspired by hydraulic models that can simulate the spatio-temporal evolution of floods. We show that the model can rapidly predict dike breach floods over different topographies and breach locations, with limited use of ground-truth data.
Daniel Camilo Roman Quintero, Pasquale Marino, Giovanni Francesco Santonastaso, and Roberto Greco
Hydrol. Earth Syst. Sci., 27, 4151–4172, https://doi.org/10.5194/hess-27-4151-2023, https://doi.org/10.5194/hess-27-4151-2023, 2023
Short summary
Short summary
This study shows a methodological approach using machine learning techniques to disentangle the relationships among the variables in a synthetic dataset to identify suitable variables that control the hydrologic response of the slopes. It has been found that not only is the rainfall responsible for the water accumulation in the slope; the ground conditions (soil water content and aquifer water level) also indicate the activation of natural slope drainage mechanisms.
Yanglin Guo and Chao Ma
Hydrol. Earth Syst. Sci., 27, 1667–1682, https://doi.org/10.5194/hess-27-1667-2023, https://doi.org/10.5194/hess-27-1667-2023, 2023
Short summary
Short summary
In a localized area with the same vegetation, an overwhelming propensity of shallow landslides on the south-facing slope over the north-facing slope could not be attributed to plant roots. We provide new evidence from the pore water pressure of failing mass, unsaturated hydraulic conductivity, water storage, and drainage and the hillslope stability fluctuation to prove that the infinite slope model may be suitable for elucidating the aspect-dependent landslide distribution in the study area.
Clément Roques, David E. Rupp, Jean-Raynald de Dreuzy, Laurent Longuevergne, Elizabeth R. Jachens, Gordon Grant, Luc Aquilina, and John S. Selker
Hydrol. Earth Syst. Sci., 26, 4391–4405, https://doi.org/10.5194/hess-26-4391-2022, https://doi.org/10.5194/hess-26-4391-2022, 2022
Short summary
Short summary
Streamflow dynamics are directly dependent on contributions from groundwater, with hillslope heterogeneity being a major driver in controlling both spatial and temporal variabilities in recession discharge behaviors. By analysing new model results, this paper identifies the major structural features of aquifers driving streamflow dynamics. It provides important guidance to inform catchment-to-regional-scale models, with key geological knowledge influencing groundwater–surface water interactions.
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
Short summary
Short summary
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.
Mingming Guo, Zhuoxin Chen, Wenlong Wang, Tianchao Wang, Qianhua Shi, Hongliang Kang, Man Zhao, and Lanqian Feng
Hydrol. Earth Syst. Sci., 25, 4473–4494, https://doi.org/10.5194/hess-25-4473-2021, https://doi.org/10.5194/hess-25-4473-2021, 2021
Short summary
Short summary
Gully headcut erosion is always a difficult issue in soil erosion, which hinders the revelation of gully erosion mechanisms and the establishment of a gully erosion model. This study clarified the spatiotemporal changes in flow properties, energy consumption, and soil loss, confirming that gully head consumed the most of flow energy (78 %) and can contribute 89 % of total soil loss. Critical energy consumption initiating soil erosion of the upstream area, gully head, and gully bed is confirmed.
Qiang Dai, Jingxuan Zhu, Shuliang Zhang, Shaonan Zhu, Dawei Han, and Guonian Lv
Hydrol. Earth Syst. Sci., 24, 5407–5422, https://doi.org/10.5194/hess-24-5407-2020, https://doi.org/10.5194/hess-24-5407-2020, 2020
Short summary
Short summary
Rainfall is a driving force that accounts for a large proportion of soil loss around the world. Most previous studies used a fixed rainfall–energy relationship to estimate rainfall energy, ignoring the spatial and temporal changes of raindrop microphysical processes. This study proposes a novel method for large-scale and long-term rainfall energy and rainfall erosivity investigations based on rainfall microphysical parameterization schemes in the Weather Research and Forecasting (WRF) model.
Pedro Henrique Lima Alencar, José Carlos de Araújo, and Adunias dos Santos Teixeira
Hydrol. Earth Syst. Sci., 24, 4239–4255, https://doi.org/10.5194/hess-24-4239-2020, https://doi.org/10.5194/hess-24-4239-2020, 2020
Short summary
Short summary
Soil erosion by water has been emphasized as a key problem to be faced in the 21st century. Thus, it is critical to understand land degradation and to answer fundamental questions regarding how and why such processes occur. Here, we present a model for gully erosion (channels carved by rainwater) based on existing equations, and we identify some major variables that influence the initiation and evolution of this process. The successful model can help in planning soil conservation practices.
Fabien Cochand, Daniel Käser, Philippe Grosvernier, Daniel Hunkeler, and Philip Brunner
Hydrol. Earth Syst. Sci., 24, 213–226, https://doi.org/10.5194/hess-24-213-2020, https://doi.org/10.5194/hess-24-213-2020, 2020
Short summary
Short summary
Roads in sloping fens constitute a hydraulic barrier for surface and subsurface flow. This can lead to the drying out of downslope areas of the fen as well as gully erosion. By combining fieldwork and numerical models, this study presents an assessment of the hydrogeological impact of three road structures especially designed to limit their impact. The study shows that the impact of roads on the hydrological regime in fens can be significantly reduced by using appropriate engineering measures.
Rubianca Benavidez, Bethanna Jackson, Deborah Maxwell, and Kevin Norton
Hydrol. Earth Syst. Sci., 22, 6059–6086, https://doi.org/10.5194/hess-22-6059-2018, https://doi.org/10.5194/hess-22-6059-2018, 2018
Short summary
Short summary
Soil erosion is a global problem and models identify vulnerable areas for management. One such model is the Revised Universal Soil Loss Equation. We review its different sub-factors and compile studies and equations that modified it for local conditions. The limitations of RUSLE include its data requirements and exclusion of gullying and landslides. Future directions include accounting for these erosion types. This paper serves as a reference for others working with RUSLE and related approaches.
Felipe Hernández and Xu Liang
Hydrol. Earth Syst. Sci., 22, 5759–5779, https://doi.org/10.5194/hess-22-5759-2018, https://doi.org/10.5194/hess-22-5759-2018, 2018
Short summary
Short summary
Predicting floods requires first knowing the amount of water in the valleys, which is complicated because we cannot know for sure how much water there is in the soil. We created a unique system that combines the best methods to estimate these conditions accurately based on the observed water flow in the rivers and on detailed simulations of the valleys. Comparisons with popular methods show that our system can produce realistic predictions efficiently, even for very detailed river networks.
Anna Botto, Enrica Belluco, and Matteo Camporese
Hydrol. Earth Syst. Sci., 22, 4251–4266, https://doi.org/10.5194/hess-22-4251-2018, https://doi.org/10.5194/hess-22-4251-2018, 2018
Short summary
Short summary
We present a multivariate application of the ensemble Kalman filter (EnKF) in hydrological modeling of a real-world hillslope test case with dominant unsaturated dynamics and strong nonlinearities. Overall, the EnKF is able to correctly update system state and soil parameters. However, multivariate data assimilation may lead to significant tradeoffs between model predictions of different variables, if the observation data are not high quality or representative.
Peter Metcalfe, Keith Beven, Barry Hankin, and Rob Lamb
Hydrol. Earth Syst. Sci., 22, 2589–2605, https://doi.org/10.5194/hess-22-2589-2018, https://doi.org/10.5194/hess-22-2589-2018, 2018
Short summary
Short summary
Flooding is a significant hazard and extreme events in recent years have focused attention on effective means of reducing its risk. An approach known as natural flood management (NFM) seeks to increase flood resilience by a range of measures that work with natural processes. The paper develops a modelling approach to assess one type NFM of intervention – distributed additional hillslope storage features – and demonstrates that more strategic placement is required than has hitherto been applied.
Abraham Endalamaw, W. Robert Bolton, Jessica M. Young-Robertson, Don Morton, Larry Hinzman, and Bart Nijssen
Hydrol. Earth Syst. Sci., 21, 4663–4680, https://doi.org/10.5194/hess-21-4663-2017, https://doi.org/10.5194/hess-21-4663-2017, 2017
Short summary
Short summary
This study applies plot-scale and hill-slope knowledge to a process-based mesoscale model to improve the skill of distributed hydrological models to simulate the spatially and basin-integrated hydrological processes of complex ecosystems in the sub-arctic boreal forest. We developed a sub-grid parameterization method to parameterize the surface heterogeneity of interior Alaskan discontinuous permafrost watersheds.
Antonio Hayas, Tom Vanwalleghem, Ana Laguna, Adolfo Peña, and Juan V. Giráldez
Hydrol. Earth Syst. Sci., 21, 235–249, https://doi.org/10.5194/hess-21-235-2017, https://doi.org/10.5194/hess-21-235-2017, 2017
Short summary
Short summary
Gully erosion is one of the most important erosion processes. In this study, we provide new data on gully dynamics over long timescales with an unprecedented temporal resolution. We apply a new Monte Carlo based method for calculating gully volumes based on orthophotos and, especially, for constraining uncertainties of these estimations. Our results show that gully erosion rates are highly variable from year to year and significantly higher than other erosion processes.
Giuseppe Formetta, Giovanna Capparelli, and Pasquale Versace
Hydrol. Earth Syst. Sci., 20, 4585–4603, https://doi.org/10.5194/hess-20-4585-2016, https://doi.org/10.5194/hess-20-4585-2016, 2016
Short summary
Short summary
This paper focuses on performance evaluation of simplified, physically based landslide susceptibility models. It presents a new methodology to systemically and objectively calibrate, verify, and compare different models and models performances indicators in order to individuate and select the models whose behavior is more reliable for a certain case study. The procedure was implemented in a package for landslide susceptibility analysis and integrated the open-source hydrological model NewAge.
Carlotta Scudeler, Luke Pangle, Damiano Pasetto, Guo-Yue Niu, Till Volkmann, Claudio Paniconi, Mario Putti, and Peter Troch
Hydrol. Earth Syst. Sci., 20, 4061–4078, https://doi.org/10.5194/hess-20-4061-2016, https://doi.org/10.5194/hess-20-4061-2016, 2016
Short summary
Short summary
Very few studies have applied a physically based hydrological model with integrated and distributed multivariate observation data of both flow and transport phenomena. In this study we address this challenge for a hillslope-scale unsaturated zone isotope tracer experiment. The results show how model complexity evolves as the number and detail of simulated responses increases. Possible gaps in process representation for simulating solute transport phenomena in very dry soils are discussed.
Bruno Cheviron and Roger Moussa
Hydrol. Earth Syst. Sci., 20, 3799–3830, https://doi.org/10.5194/hess-20-3799-2016, https://doi.org/10.5194/hess-20-3799-2016, 2016
Short summary
Short summary
This review paper investigates the determinants of modelling choices for numerous applications of 1-D free-surface flow and morphodynamics in hydrology and hydraulics. Each case study has a signature composed of given contexts (spatiotemporal scales, flow typology, and phenomenology) and chosen concepts (refinement and subscales of the flow model). This review proposes a normative procedure possibly enriched by the community for a larger, comprehensive and updated image of modelling strategies.
F. Todisco, L. Brocca, L. F. Termite, and W. Wagner
Hydrol. Earth Syst. Sci., 19, 3845–3856, https://doi.org/10.5194/hess-19-3845-2015, https://doi.org/10.5194/hess-19-3845-2015, 2015
Short summary
Short summary
We developed a new formulation of USLE, named Soil Moisture for Erosion (SM4E), that directly incorporates soil moisture information. SM4E is applied here by using modeled data and satellite observations obtained from the Advanced SCATterometer (ASCAT). SM4E is found to outperform USLE and USLE-MM models in silty–clay soil in central Italy. Through satellite data, there is the potential of applying SM4E for large-scale monitoring and quantification of the soil erosion process.
W. Shao, T. A. Bogaard, M. Bakker, and R. Greco
Hydrol. Earth Syst. Sci., 19, 2197–2212, https://doi.org/10.5194/hess-19-2197-2015, https://doi.org/10.5194/hess-19-2197-2015, 2015
Short summary
Short summary
The effect of preferential flow on the stability of landslides is studied through numerical simulation of two types of rainfall events on a hypothetical hillslope. A model is developed that consists of two parts. The first part is a model for combined saturated/unsaturated subsurface flow and is used to compute the spatial and temporal water pressure response to rainfall. Preferential flow is simulated with a dual-permeability continuum model consisting of a matrix/preferential flow domain.
O. Fovet, L. Ruiz, M. Hrachowitz, M. Faucheux, and C. Gascuel-Odoux
Hydrol. Earth Syst. Sci., 19, 105–123, https://doi.org/10.5194/hess-19-105-2015, https://doi.org/10.5194/hess-19-105-2015, 2015
Short summary
Short summary
We studied the annual hysteretic patterns observed between stream flow and water storage in the saturated and unsaturated zones of a hillslope and a riparian zone. We described these signatures using a hysteresis index and then used this to assess conceptual hydrological models. This led us to identify four hydrological periods and a clearly distinct behaviour between riparian and hillslope groundwaters and to provide new information about the model performances.
D. J. Peres and A. Cancelliere
Hydrol. Earth Syst. Sci., 18, 4913–4931, https://doi.org/10.5194/hess-18-4913-2014, https://doi.org/10.5194/hess-18-4913-2014, 2014
Short summary
Short summary
A Monte Carlo approach, combining rainfall-stochastic models and hydrological and slope stability physically based models, is used to derive rainfall thresholds of landslide triggering. The uncertainty in threshold assessment related to variability of rainfall intensity within events and to past rainfall (antecedent rainfall) is analyzed and measured via ROC-based indexes, with a specific focus dedicated to the widely used power-law rainfall intensity-duration (I-D) thresholds.
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
G. Capparelli and P. Versace
Hydrol. Earth Syst. Sci., 18, 3225–3237, https://doi.org/10.5194/hess-18-3225-2014, https://doi.org/10.5194/hess-18-3225-2014, 2014
D. Penna, M. Borga, G. T. Aronica, G. Brigandì, and P. Tarolli
Hydrol. Earth Syst. Sci., 18, 2127–2139, https://doi.org/10.5194/hess-18-2127-2014, https://doi.org/10.5194/hess-18-2127-2014, 2014
G.-Y. Niu, D. Pasetto, C. Scudeler, C. Paniconi, M. Putti, P. A. Troch, S. B. DeLong, K. Dontsova, L. Pangle, D. D. Breshears, J. Chorover, T. E. Huxman, J. Pelletier, S. R. Saleska, and X. Zeng
Hydrol. Earth Syst. Sci., 18, 1873–1883, https://doi.org/10.5194/hess-18-1873-2014, https://doi.org/10.5194/hess-18-1873-2014, 2014
J. Tao and A. P. Barros
Hydrol. Earth Syst. Sci., 18, 367–388, https://doi.org/10.5194/hess-18-367-2014, https://doi.org/10.5194/hess-18-367-2014, 2014
J. Wienhöfer and E. Zehe
Hydrol. Earth Syst. Sci., 18, 121–138, https://doi.org/10.5194/hess-18-121-2014, https://doi.org/10.5194/hess-18-121-2014, 2014
A. Richard, S. Galle, M. Descloitres, J.-M. Cohard, J.-P. Vandervaere, L. Séguis, and C. Peugeot
Hydrol. Earth Syst. Sci., 17, 5079–5096, https://doi.org/10.5194/hess-17-5079-2013, https://doi.org/10.5194/hess-17-5079-2013, 2013
S. R. Lutz, H. J. van Meerveld, M. J. Waterloo, H. P. Broers, and B. M. van Breukelen
Hydrol. Earth Syst. Sci., 17, 4505–4524, https://doi.org/10.5194/hess-17-4505-2013, https://doi.org/10.5194/hess-17-4505-2013, 2013
Makoto Tani
Hydrol. Earth Syst. Sci., 17, 4453–4470, https://doi.org/10.5194/hess-17-4453-2013, https://doi.org/10.5194/hess-17-4453-2013, 2013
M. N. Papa, V. Medina, F. Ciervo, and A. Bateman
Hydrol. Earth Syst. Sci., 17, 4095–4107, https://doi.org/10.5194/hess-17-4095-2013, https://doi.org/10.5194/hess-17-4095-2013, 2013
P. Fiener, K. Auerswald, F. Winter, and M. Disse
Hydrol. Earth Syst. Sci., 17, 4121–4132, https://doi.org/10.5194/hess-17-4121-2013, https://doi.org/10.5194/hess-17-4121-2013, 2013
R. Greco, L. Comegna, E. Damiano, A. Guida, L. Olivares, and L. Picarelli
Hydrol. Earth Syst. Sci., 17, 4001–4013, https://doi.org/10.5194/hess-17-4001-2013, https://doi.org/10.5194/hess-17-4001-2013, 2013
C. Lepore, E. Arnone, L. V. Noto, G. Sivandran, and R. L. Bras
Hydrol. Earth Syst. Sci., 17, 3371–3387, https://doi.org/10.5194/hess-17-3371-2013, https://doi.org/10.5194/hess-17-3371-2013, 2013
J. E. van der Spek, T. A. Bogaard, and M. Bakker
Hydrol. Earth Syst. Sci., 17, 2171–2183, https://doi.org/10.5194/hess-17-2171-2013, https://doi.org/10.5194/hess-17-2171-2013, 2013
A. M. Ireson and A. P. Butler
Hydrol. Earth Syst. Sci., 17, 2083–2096, https://doi.org/10.5194/hess-17-2083-2013, https://doi.org/10.5194/hess-17-2083-2013, 2013
A. M. J. Coenders-Gerrits, L. Hopp, H. H. G. Savenije, and L. Pfister
Hydrol. Earth Syst. Sci., 17, 1749–1763, https://doi.org/10.5194/hess-17-1749-2013, https://doi.org/10.5194/hess-17-1749-2013, 2013
G. Martelloni, S. Segoni, D. Lagomarsino, R. Fanti, and F. Catani
Hydrol. Earth Syst. Sci., 17, 1229–1240, https://doi.org/10.5194/hess-17-1229-2013, https://doi.org/10.5194/hess-17-1229-2013, 2013
C. D. Guzman, S. A. Tilahun, A. D. Zegeye, and T. S. Steenhuis
Hydrol. Earth Syst. Sci., 17, 1067–1077, https://doi.org/10.5194/hess-17-1067-2013, https://doi.org/10.5194/hess-17-1067-2013, 2013
D. M. Krzeminska, T. A. Bogaard, J.-P. Malet, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 17, 947–959, https://doi.org/10.5194/hess-17-947-2013, https://doi.org/10.5194/hess-17-947-2013, 2013
A. Peñuela, M. Javaux, and C. L. Bielders
Hydrol. Earth Syst. Sci., 17, 87–101, https://doi.org/10.5194/hess-17-87-2013, https://doi.org/10.5194/hess-17-87-2013, 2013
A. Rodhe
Hydrol. Earth Syst. Sci., 16, 3075–3082, https://doi.org/10.5194/hess-16-3075-2012, https://doi.org/10.5194/hess-16-3075-2012, 2012
G. Y. Gao, B. J. Fu, Y. H. Lü, Y. Liu, S. Wang, and J. Zhou
Hydrol. Earth Syst. Sci., 16, 2347–2364, https://doi.org/10.5194/hess-16-2347-2012, https://doi.org/10.5194/hess-16-2347-2012, 2012
C. E. Ballard, N. McIntyre, and H. S. Wheater
Hydrol. Earth Syst. Sci., 16, 2299–2310, https://doi.org/10.5194/hess-16-2299-2012, https://doi.org/10.5194/hess-16-2299-2012, 2012
D. M. Krzeminska, T. A. Bogaard, Th. W. J. van Asch, and L. P. H. van Beek
Hydrol. Earth Syst. Sci., 16, 1561–1576, https://doi.org/10.5194/hess-16-1561-2012, https://doi.org/10.5194/hess-16-1561-2012, 2012
T. Maurer, A. Schneider, and H. H. Gerke
Hydrol. Earth Syst. Sci., 15, 3617–3638, https://doi.org/10.5194/hess-15-3617-2011, https://doi.org/10.5194/hess-15-3617-2011, 2011
J. Klaus and E. Zehe
Hydrol. Earth Syst. Sci., 15, 2127–2144, https://doi.org/10.5194/hess-15-2127-2011, https://doi.org/10.5194/hess-15-2127-2011, 2011
Cited articles
Andréassian, V., Lerat, J., Le Moine, N., and Perrin, C.:
Neighbors: Nature's own hydrological models, J. Hydrol., 414–415, 49–58, https://doi.org/10.1016/j.jhydrol.2011.10.007, 2012.
Aryal, S. K., O'Loughlin, E. M., and Mein, R. G.:
A similarity approach to predict landscape saturation in catchments, Water Resour. Res., 38, 26-1-26–16, https://doi.org/10.1029/2001WR000864, 2002.
Berghuijs, W. R., Sivapalan, M., Woods, R. A., and Savenije, H. H. G.:
Patterns of similarity of seasonal water balances: A window into streamflow variability over a range of time scales, Water Resour. Res., 50, 5638–5661, https://doi.org/10.1002/2014WR015692, 2014.
Berne, A., Uijlenhoet, R., and Troch, P. A.: Similarity analysis of subsurface flow response of hillslopes with complex geometry, Water Resour. Res., 41, W09410, https://doi.org/10.1029/2004WR003629, 2005.
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. 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. B., 24, 43–69, https://doi.org/10.1080/02626667909491834, 1979.
Bormann, H.:
Towards a hydrologically motivated soil texture classification, Geoderma, 157, 142–153, https://doi.org/10.1016/j.geoderma.2010.04.005, 2010.
Bosch, J. M. and Hewlett, J. D.:
A review of catchment experiments to determine the effect of vegetation changes on water yield and evapotranspiration, J. Hydrol., 55, 3–23, https://doi.org/10.1016/0022-1694(82)90117-2, 1982.
Brown, A. E., Zhang, L., McMahon, T. A., Western, A. W., and Vertessy, R. A.:
A review of paired catchment studies for determining changes in water yield resulting from alterations in vegetation, J. Hydrol., 310, 28–61, https://doi.org/10.1016/j.jhydrol.2004.12.010, 2005.
Brunner, P. and Simmons, C. T.:
HydroGeoSphere: A Fully Integrated, Physically Based Hydrological Model, Groundwater, 50, 170–176, https://doi.org/10.1111/j.1745-6584.2011.00882.x, 2012.
Carrillo, G., Troch, P. A., Sivapalan, M., Wagener, T., Harman, C., and Sawicz, K.:
Catchment classification: hydrological analysis of catchment behavior through process-based modeling along a climate gradient, Hydrol. Earth Syst. Sci., 15, 3411–3430, https://doi.org/10.5194/hess-15-3411-2011, 2011.
Carroll, R. W. H., Bearup, L. A., Brown, W., Dong, W., Bill, M., and Willlams, K. H.:
Factors controlling seasonal groundwater and solute flux from snow-dominated basins, Hydrol. Process., 32, 2187–2202, https://doi.org/10.1002/hyp.13151, 2018.
CGIAR-CSI:
Global Aridity Index and Potential Evapotranspiration Climate Database v2, https://cgiarcsi.community/2019/01/24/global-aridity-index-and-potential-evapotranspiration-climate-database-v2/ (last access: 22 August 2020) 2019.
Chadwick, K. D., Brodrick, P. G., Grant, K., Goulden, T., Henderson, A., Falco, N., Wainwright, H., Williams, K. H., Bill, M., Breckheimer, I., Brodie, E. L., Steltzer, H., Williams, C. F. R., Blonder, B., Chen, J., Dafflon, B., Damerow, J., Hancher, M., Khurram, A., Lamb, J., Lawrence, C. R., McCormick, M., Musinsky, J., Pierce, S., Polussa, A., Hastings Porro, M., Scott, A., Singh, H. W., Sorensen, P. O., Varadharajan, C., Whitney, B., and Maher, K.: Integrating airborne remote sensing and field campaigns for ecology and earth system science, Methods Ecol. Evol., 11, 1492–1508, https://doi.org/10.1111/2041-210x.13463, 2020.
Chaney, N. W., Van Huijgevoort, M. H. J., Shevliakova, E., Malyshev, S., Milly, P. C. D., Gauthier, P. P. G., and Sulman, B. N.:
Harnessing big data to rethink land heterogeneity in Earth system models, Hydrol. Earth Syst. Sci., 22, 3311–3330, https://doi.org/10.5194/hess-22-3311-2018, 2018.
Condon, L. E., Maxwell, R. M., and Gangopadhyay, S.:
The impact of subsurface conceptualization on land energy fluxes, Adv. Water Resour., 60, 188–203, https://doi.org/10.1016/j.advwatres.2013.08.001, 2013.
Coon, E. T., David Moulton, J., and Painter, S. L.: Managing complexity in simulations of land surface and near-surface processes, Environ. Modell. Softw., 78, 134–149, https://doi.org/10.1016/j.envsoft.2015.12.017, 2016.
Cosgrove, B. A., Lohmann, D., Mitchell, K. E., Houser, P. R., Wood, E. F., Schaake, J. C., Robock, A., Marshall, C., Sheffield, J., Duan, Q., Luo, L., Higgins, R. W., Pinker, R. T., Tarpley, J. D., and Meng, J.: Real-time and retrospective forcing in the North American Land Data Assimilation System (NLDAS) project, J. Geophys. Res.-Atmos., 108, 8842, https://doi.org/10.1029/2002JD003118, 2003.
Dai, Y., Zeng, X., Dickinson, R. E., Baker, I., Bonan, G. B., Bosilovich, M. G., Denning, A. S., Dirmeyer, P. A., Houser, P. R., Niu, G., Oleson, K. W., Schlosser, C. A., and Yang, Z.-L.: The Common Land Model, B. Am. Meteorol. Soc., 84, 1013–1024, https://doi.org/10.1175/BAMS-84-8-1013, 2003.
Daly, C., Halbleib, M., Smith, J. I., Gibson, W. P., Doggett, M. K., Taylor, G. H., Curtis, J., and Pasteris, P. P.: Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States, Int. J. Climatol., 28, 2031–2064, https://doi.org/10.1002/joc.1688, 2008.
Devadoss, J., Falco, N., Dafflon, B., Wu, Y., Franklin, M., Hermes, A., Hinckley, E.-L. S., and Wainwright, H.: Remote Sensing-Informed Zonation for Understanding Snow, Plant and Soil Moisture Dynamics within a Mountain Ecosystem, Remote Sens.-Basel, 12, 2733, https://doi.org/10.3390/rs12172733, 2020.
ESS-DIVE: About ESS-DIVE, ESS-DIVE, https://ess-dive.lbl.gov, last access: 5 July 2022.
Falco, N., Balde, A., Breckheimer, I., Brodie, E., Brodrick, P. G., Chadwick, K. D., Chen, J., Dafflon, B., Henderson, A., Lamb, J., Maher, K., Kueppers, L., Steltzer, H., Wainwright, H., Williams, K., and Hubbard, S. S.: Plant species distribution within the Upper Colorado River Basin estimated by using hyperspectral and lidar airborne data, Watershed Function SFA, ESS-DIVE repository [data set], https://doi.org/10.15485/1602034, 2020.
Fan, Y., Clark, M., Lawrence, D. M., Swenson, S., Band, L. E., Brantley, S. L., Brooks, P. D., Dietrich, W. E., Flores, A., Grant, G., Kirchner, J. W., Mackay, D. S., McDonnell, J. J., Milly, P. C. D., Sullivan, P. L., Tague, C., Ajami, H., Chaney, N., Hartmann, A., Hazenberg, P., McNamara, J., Pelletier, J., Perket, J., Rouholahnejad‐Freund, E., Wagener, T., Zeng, X., Beighley, E., Buzan, J., Huang, M., Livneh, B., Mohanty, B. P., Nijssen, B., Safeeq, M., Shen, C., Verseveld, W. van, Volk, J., and Yamazaki, D.: Hillslope Hydrology in Global Change Research and Earth System Modeling, Water Resour. Res., 55, 1737–1772, https://doi.org/10.1029/2018WR023903, 2019.
Ferguson, I. M. and Maxwell, R. M.: Role of groundwater in watershed response and land surface feedbacks under climate change, Water Resour. Res., 46, W00F02, https://doi.org/10.1029/2009WR008616, 2010.
Foster, L. M. and Maxwell, R. M.: Sensitivity analysis of hydraulic conductivity and Manning's n parameters lead to new method to scale effective hydraulic conductivity across model resolutions, Hydrol. Process., 33, 332–349, https://doi.org/10.1002/hyp.13327, 2019.
Goulden, T., Hass, B., Brodie, E., Chadwick, K. D., Falco, N., Maher, K., Wainwright, H., and Williams, K.: NEON AOP Survey of Upper East River CO Watersheds: LAZ Files, LiDAR Surface Elevation, Terrain Elevation, and Canopy Height Rasters, Watershed Function SFA, ESS-DIVE repository [data set], https://doi.org/10.15485/1617203, 2020.
Grabs, T., Seibert, J., Bishop, K., and Laudon, H.:
Modeling spatial patterns of saturated areas: A comparison of the topographic wetness index and a dynamic distributed model, J. Hydrol., 373, 15–23, https://doi.org/10.1016/j.jhydrol.2009.03.031, 2009.
Harman, C. and Sivapalan, M.: A similarity framework to assess controls on shallow subsurface flow dynamics in hillslopes, Water Resour. Res., 45, W01417, https://doi.org/10.1029/2008WR007067, 2009.
Hjerdt, K. N., McDonnell, J. J., Seibert, J., and Rodhe, A.: A new topographic index to quantify downslope controls on local drainage, Water Resour. Res., 40, W05602, https://doi.org/10.1029/2004WR003130, 2004.
Hubbard, S. S., Williams, K. H., Agarwal, D., Banfield, J., Beller, H., Bouskill, N., Brodie, E., Carroll, R., Dafflon, B., Dwivedi, D., Falco, N., Faybishenko, B., Maxwell, R., Nico, P., Steefel, C., Steltzer, H., Tokunaga, T., Tran, P. A., Wainwright, H., and Varadharajan, C.: The East River, Colorado, Watershed: A Mountainous Community Testbed for Improving Predictive Understanding of Multiscale Hydrological–Biogeochemical Dynamics, Vadose Zone J., 17, 180061, https://doi.org/10.2136/vzj2018.03.0061, 2018.
IGBP:
Global plant database published – IGBP [text], http://www.igbp.net/news/news/news/globalplantdatabasepublished.5.1b8ae20512db692f2a6800014762.html, last access: 17 October 2018.
Jefferson, J. L., Gilbert, J. M., Constantine, P. G., and Maxwell, R. M.:
Active subspaces for sensitivity analysis and dimension reduction of an integrated hydrologic model, Comput. Geosci., 83, 127–138, https://doi.org/10.1016/j.cageo.2015.07.001, 2015.
Kassambara, A.:
Practical guide to cluster analysis in R: Unsupervised machine learning, in: Vol. 1, Sthda, ISBN 13 978-1542462709, 2017.
Loritz, R., Kleidon, A., Jackisch, C., Westhoff, M., Ehret, U., Gupta, H., and Zehe, E.: A topographic index explaining hydrological similarity by accounting for the joint controls of runoff formation, Hydrol. Earth Syst. Sci., 23, 3807–3821, https://doi.org/10.5194/hess-23-3807-2019, 2019.
Lyon, S. W. and Troch, P. A.: Hillslope subsurface flow similarity: Real-world tests of the hillslope Péclet number, Water Resour. Res., 43, W07450, https://doi.org/10.1029/2006WR005323, 2007.
Lyon, S. W. and Troch, P. A.: Development and application of a catchment similarity index for subsurface flow, Water Resour. Res., 46, W03511, https://doi.org/10.1029/2009WR008500, 2010.
Maina, F. Z. and Siirila-Woodburn, E. R.:
The Role of Subsurface Flow on Evapotranspiration: A Global Sensitivity Analysis, Water Resour. Res., 56, e2019WR026612, https://doi.org/10.1029/2019WR026612, 2020.
Maina, F. Z., Siirila-Woodburn, E. R., Newcomer, M., Xu, Z., and Steefel, C.: Determining the impact of a severe dry to wet transition on watershed hydrodynamics in California, USA with an integrated hydrologic model, J. Hydrol., 580, 124358, https://doi.org/10.1016/j.jhydrol.2019.124358, 2020.
Maina, F. Z., Siirila-Woodburn, E. R., and Dennedy-Frank, P. J.: Assessing the impacts of hydrodynamic parameter uncertainties on simulated evapotranspiration in a mountainous watershed, J. Hydrol., 608, 127620, https://doi.org/10.1016/j.jhydrol.2022.127620, 2022.
Maxwell, R. M.:
A terrain-following grid transform and preconditioner for parallel, large-scale, integrated hydrologic modeling, Adv. Water Resour., 53, 109–117, https://doi.org/10.1016/j.advwatres.2012.10.001, 2013.
Maxwell, R. M. and Condon, L. E.: Connections between groundwater flow and transpiration partitioning, Science, 353, 377–380, https://doi.org/10.1126/science.aaf7891, 2016.
Maxwell, R. M. and Miller, N. L.:
Development of a Coupled Land Surface and Groundwater Model, J. Hydrometeorol., 6, 233–247, https://doi.org/10.1175/JHM422.1, 2005.
McDonnell, J. J. and Woods, R.:
On the need for catchment classification, J. Hydrol., 299, 2–3, https://doi.org/10.1016/j.jhydrol.2004.09.003, 2004.
Noël, P., Rousseau, A. N., Paniconi, C., and Nadeau, D. F.:
Algorithm for Delineating and Extracting Hillslopes and Hillslope Width Functions from Gridded Elevation Data, J. Hydrol. Eng., 19, 366–374, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000783, 2014.
Oudin, L., Kay, A., Andréassian, V., and Perrin, C.: Are seemingly physically similar catchments truly hydrologically similar?, Water Resour. Res., 46, W11558, https://doi.org/10.1029/2009WR008887, 2010.
ParFlow: ParFlow hydrologic model, ParFlow, https://parflow.org/#download, last access: 5 July 2022.
Pribulick, C. E., Foster, L. M., Bearup, L. A., Navarre-Sitchler, A. K., Williams, K. H., Carroll, R. W. H., and Maxwell, R. M.:
Contrasting the hydrologic response due to land cover and climate change in a mountain headwaters system, Ecohydrology, 9, 1431–1438, https://doi.org/10.1002/eco.1779, 2016.
Rahman, M., Sulis, M., and Kollet, S. J.:
Evaluating the dual-boundary forcing concept in subsurface–land surface interactions of the hydrological cycle, Hydrol. Process., 30, 1563–1573, https://doi.org/10.1002/hyp.10702, 2016.
Richards, L. A.:
Capillary conduction of liquids through porous medium, J. Appl. Phys., 1, 318–333, https://doi.org/10.1063/1.1745010, 1931.
Ryken, A., Bearup, L. A., Jefferson, J. L., Constantine, P., and Maxwell, R. M.:
Sensitivity and model reduction of simulated snow processes: Contrasting observational and parameter uncertainty to improve prediction, Adv. Water Resour., 135, 103473, https://doi.org/10.1016/j.advwatres.2019.103473, 2020.
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.
Schwanghart, W. and Scherler, D.:
Short Communication: TopoToolbox 2 – MATLAB-based software for topographic analysis and modeling in Earth surface sciences, Earth Surf. Dynam., 2, 1–7, https://doi.org/10.5194/esurf-2-1-2014, 2014.
Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S., and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences, Hydrolog. Sci. J., 48, 857–880, https://doi.org/10.1623/hysj.48.6.857.51421, 2003.
van Genuchten, M. T.:
A Closed-form Equation for Predicting the Hydraulic Conductivity of Unsaturated Soils1, Soil Sci. Soc. Am. J., 44, 892, https://doi.org/10.2136/sssaj1980.03615995004400050002x, 1980.
Wagener, T., Sivapalan, M., Troch, P., and Woods, R.:
CatchmentClassification and Hydrologic Similarity, Geography Compass, 1, 901–931, https://doi.org/10.1111/j.1749-8198.2007.00039.x, 2007.
Wainwright, H. M., Uhlemann, S., Franklin, M., Falco, N., Bouskill, N. J., Newcomer, M. E., Dafflon, B., Siirila-Woodburn, E. R., Minsley, B. J., Williams, K. H., and Hubbard, S. S.: Watershed zonation through hillslope clustering for tractably quantifying above- and below-ground watershed heterogeneity and functions, Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, 2022.
Winnick, M. J., Carroll, R. W. H., Williams, K. H., Maxwell, R. M., Dong, W., and Maher, K.: Snowmelt controls on concentration-discharge relationships and the balance of oxidative and acid-base weathering fluxes in an alpine catchment, East River, Colorado, Water Resour. Res., 53, 2507–2523, https://doi.org/10.1002/2016WR019724, 2017.
Short summary
We propose a hillslope clustering approach based on the seasonal changes in groundwater levels and test its performance by comparing it to several common clustering approaches (aridity index, topographic wetness index, elevation, land cover, and machine-learning clustering). The proposed approach is robust as it reasonably categorizes hillslopes with similar elevation, land cover, hydroclimate, land surface processes, and subsurface hydrodynamics, hence a similar hydrologic function.
We propose a hillslope clustering approach based on the seasonal changes in groundwater levels...