Articles | Volume 26, issue 4
https://doi.org/10.5194/hess-26-1145-2022
© 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-26-1145-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
28 Feb 2022
Research article |
| 28 Feb 2022
| 28 Feb 2022
Combined impacts of uncertainty in precipitation and air temperature on simulated mountain system recharge from an integrated hydrologic model
Adam P. Schreiner-McGraw
CORRESPONDING AUTHOR
Department of Environmental Sciences, University of California,
Riverside, 92521, USA
Hoori Ajami
Department of Environmental Sciences, University of California,
Riverside, 92521, USA
Related authors
No articles found.
Kachinga Silwimba, Alejandro N. Flores, Irene Cionni, Sharon A. Billings, Pamela L. Sullivan, Hoori Ajami, Daniel R. Hirmas, and Li Li
EGUsphere, https://doi.org/10.5194/egusphere-2025-713, https://doi.org/10.5194/egusphere-2025-713, 2025
This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
This study evaluates the influence of soil hydraulic parameterizations on soil moisture simulations in CLM5 across the CONUS (1980–2010) using Empirical Orthogonal Function (EOF) analysis. Results reveal significant regional discrepancies, particularly in the Great Plains, where parameter uncertainty drives biases in soil moisture variability. Comparisons with ERA5-Land highlight seasonal mismatches, underscoring the need for improved soil parameterization to enhance land surface model accuracy.
Lena Wang, Sharon Billings, Li Li, Daniel Hirmas, Keira Johnson, Devon Kerins, Julio Pachon, Curtis Beutler, Karla Jarecke, Vaishnavi Varikuti, Micah Unruh, Hoori Ajami, Holly Barnard, Alejandro Flores, Kenneth Williams, and Pamela Sullivan
EGUsphere, https://doi.org/10.5194/egusphere-2025-70, https://doi.org/10.5194/egusphere-2025-70, 2025
Short summary
Short summary
Our study looked at how different forest types and conditions affected soil microbes, and soil carbon and stability. Aspen organic matter led to higher microbial activity, smaller soil aggregates, and more stable soil carbon, possibly reducing dissolved organic carbon movement from hillslopes to streams. This shows the importance of models like the Microbial Efficiency – Matrix Stabilization framework for predicting CO2 release, soil carbon stability, and carbon movement.
Hoori Ajami, Ashish Sharma, Lawrence E. Band, Jason P. Evans, Narendra K. Tuteja, Gnanathikkam E. Amirthanathan, and Mohammed A. Bari
Hydrol. Earth Syst. Sci., 21, 281–294, https://doi.org/10.5194/hess-21-281-2017, https://doi.org/10.5194/hess-21-281-2017, 2017
Short summary
Short summary
We present the first data-based framework for explaining why catchments behave in a non-stationary manner, even when they are unaffected by deforestation or urbanization. The role of vegetation dynamics in streamflow is indicated by similar or greater sensitivity of annual runoff ratio to annual fractional vegetation cover. We formulated a novel ecohydrologic catchment classification framework that incorporates the role of vegetation dynamics in catchment-scale water partitioning.
H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen
Hydrol. Earth Syst. Sci., 18, 5169–5179, https://doi.org/10.5194/hess-18-5169-2014, https://doi.org/10.5194/hess-18-5169-2014, 2014
Short summary
Short summary
A new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical depth-to-water table function. Results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater--surface water--land surface model (ParFlow.CLM) by up to 50%. The methodology is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Extended-range forecasting of stream water temperature with deep-learning models
Technical note: An approach for handling multiple temporal frequencies with different input dimensions using a single LSTM cell
Projections of streamflow intermittence under climate change in European drying river networks
Economic valuation of subsurface water contributions to watershed ecosystem services using a fully integrated groundwater–surface-water model
Analyzing the generalization capabilities of a hybrid hydrological model for extrapolation to extreme events
CH-RUN: a deep-learning-based spatially contiguous runoff reconstruction for Switzerland
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric–hydrological model
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
A diversity-centric strategy for the selection of spatio-temporal training data for LSTM-based streamflow forecasting
Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago
Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers
Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study
Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?
State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models
Improving the hydrological consistency of a process-based solute-transport model by simultaneous calibration of streamflow and stream concentrations
Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments
The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa
Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model
Spatio-temporal patterns and trends of streamflow in water-scarce Mediterranean basins
A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments
Seasonal variation in land cover estimates reveals sensitivities and opportunities for environmental models
Estimating response times, flow velocities, and roughness coefficients of Canadian Prairie basins
Learning landscape features from streamflow with autoencoders
Hydrological regime index for non-perennial rivers
On the use of streamflow transformations for hydrological model calibration
Simulation-based inference for parameter estimation of complex watershed simulators
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
CONCN: A high-resolution, integrated surface water-groundwater ParFlow modeling platform of continental China
Catchment response to climatic variability: implications for root zone storage and streamflow predictions
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Technical note: What does the Standardized Streamflow Index actually reflect? Insights and implications for hydrological drought analysis
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Assessing the adequacy of traditional hydrological models for climate change impact studies: A case for long-short-term memory (LSTM) neural networks
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025, https://doi.org/10.5194/hess-29-1919-2025, 2025
Short summary
Short summary
Common intuition holds that higher input data resolution leads to better results. To assess the benefits of high-resolution data, we conduct simulation experiments using data with various temporal resolutions across multiple catchments and find that higher-resolution data do not always improve model performance, challenging the necessity of pursuing such data. In catchments with small areas or significant flow variability, high-resolution data is more valuable.
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
Short summary
Short summary
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.
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025, https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary
Short summary
In this article, we show that by taking the optimal parameters calibrated with a semi-lumped model for the discharge at a catchment's outlet, we can accurately simulate runoff at various points within the study area, including three nested and three neighboring catchments. In addition, we demonstrate that employing more intricate melt models, which better represent physical processes, enhances the transfer of parameters in the simulation, until we observe overparameterization.
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025, https://doi.org/10.5194/hess-29-1685-2025, 2025
Short summary
Short summary
We generate operational forecasts of daily maximum stream water temperature for 32 consecutive days at 54 stations in Switzerland with our best-performing data-driven model. The average forecast error is 0.38 °C for 1 d ahead and increases to 0.90 °C for 32 d ahead given the uncertainty in the meteorological variables influencing water temperature. Here we compare the skill of several models, how well they can forecast at new and ungauged stations, and the importance of different model inputs.
Eduardo Acuña Espinoza, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, Ralf Loritz, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1749–1758, https://doi.org/10.5194/hess-29-1749-2025, https://doi.org/10.5194/hess-29-1749-2025, 2025
Short summary
Short summary
Long short-term memory (LSTM) networks have demonstrated state-of-the-art performance for rainfall-runoff hydrological modelling. However, most studies focus on predictions at a daily scale, limiting the benefits of sub-daily (e.g. hourly) predictions in applications like flood forecasting. In this study, we introduce a new architecture, multi-frequency LSTM (MF-LSTM), designed to use inputs of various temporal frequencies to produce sub-daily (e.g. hourly) predictions at a moderate computational cost.
Louise Mimeau, Annika Künne, Alexandre Devers, Flora Branger, Sven Kralisch, Claire Lauvernet, Jean-Philippe Vidal, Núria Bonada, Zoltán Csabai, Heikki Mykrä, Petr Pařil, Luka Polović, and Thibault Datry
Hydrol. Earth Syst. Sci., 29, 1615–1636, https://doi.org/10.5194/hess-29-1615-2025, https://doi.org/10.5194/hess-29-1615-2025, 2025
Short summary
Short summary
Our study projects how climate change will affect the drying of river segments and stream networks in Europe, using advanced modelling techniques to assess changes in six river networks across diverse ecoregions. We found that drying events will become more frequent and intense and will start earlier or last longer, potentially turning some river sections from perennial to intermittent. The results are valuable for river ecologists for evaluating the ecological health of river ecosystem.
Tariq Aziz, Steven K. Frey, David R. Lapen, Susan Preston, Hazen A. J. Russell, Omar Khader, Andre R. Erler, and Edward A. Sudicky
Hydrol. Earth Syst. Sci., 29, 1549–1568, https://doi.org/10.5194/hess-29-1549-2025, https://doi.org/10.5194/hess-29-1549-2025, 2025
Short summary
Short summary
This study determines the value of subsurface water for ecosystem services' supply in an agricultural watershed in Ontario, Canada. Using a fully integrated water model and an economic valuation approach, the research highlights subsurface water's critical role in maintaining watershed ecosystem services. The study informs on the sustainable use of subsurface water and introduces a new method for managing watershed ecosystem services.
Eduardo Acuña Espinoza, Ralf Loritz, Frederik Kratzert, Daniel Klotz, Martin Gauch, Manuel Álvarez Chaves, and Uwe Ehret
Hydrol. Earth Syst. Sci., 29, 1277–1294, https://doi.org/10.5194/hess-29-1277-2025, https://doi.org/10.5194/hess-29-1277-2025, 2025
Short summary
Short summary
Data-driven techniques have shown the potential to outperform process-based models in rainfall–runoff simulations. Hybrid models, combining both approaches, aim to enhance accuracy and maintain interpretability. Expanding the set of test cases to evaluate hybrid models under different conditions, we test their generalization capabilities for extreme hydrological events.
Basil Kraft, Michael Schirmer, William H. Aeberhard, Massimiliano Zappa, Sonia I. Seneviratne, and Lukas Gudmundsson
Hydrol. Earth Syst. Sci., 29, 1061–1082, https://doi.org/10.5194/hess-29-1061-2025, https://doi.org/10.5194/hess-29-1061-2025, 2025
Short summary
Short summary
This study reconstructs daily runoff in Switzerland (1962–2023) using a deep-learning model, providing a spatially contiguous dataset on a medium-sized catchment grid. The model outperforms traditional hydrological methods, revealing shifts in Swiss water resources, including more frequent dry years and declining summer runoff. The reconstruction is publicly available.
Mengjiao Zhang, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1033–1060, https://doi.org/10.5194/hess-29-1033-2025, https://doi.org/10.5194/hess-29-1033-2025, 2025
Short summary
Short summary
Owing to differences in the existing published results, we conducted a detailed analysis of the runoff components and future trends in the Yarlung Tsangpo River basin and found that the contributions of snowmelt and glacier melt runoff to streamflow (both ~5 %) are limited and much lower than previous results. The streamflow in this area will continuously increase in the future, but the overestimated contribution of glacier melt could lead to an underestimation of this increasing trend.
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025, https://doi.org/10.5194/hess-29-903-2025, 2025
Short summary
Short summary
This study develops an integrated framework based on the novel Driving index for changes in Precipitation–Runoff Relationships (DPRR) to explore the controlling changes in precipitation–runoff relationships in non-stationary environments. According to the quantitative results of the candidate driving factors, the possible process explanations for changes in the precipitation–runoff relationships are deduced. The main contribution offers a comprehensive understanding of hydrological processes.
Everett Snieder and Usman T. Khan
Hydrol. Earth Syst. Sci., 29, 785–798, https://doi.org/10.5194/hess-29-785-2025, https://doi.org/10.5194/hess-29-785-2025, 2025
Short summary
Short summary
Improving the accuracy of flood forecasts is paramount to minimising flood damage. Machine learning (ML) models are increasingly being applied for flood forecasting. Such models are typically trained on large historic hydrometeorological datasets. In this work, we evaluate methods for selecting training datasets that maximise the spatio-temporal diversity of the represented hydrological processes. Empirical results showcase the importance of hydrological diversity in training ML models.
Joško Trošelj and Naota Hanasaki
Hydrol. Earth Syst. Sci., 29, 753–766, https://doi.org/10.5194/hess-29-753-2025, https://doi.org/10.5194/hess-29-753-2025, 2025
Short summary
Short summary
This study presents the first distributed hydrological simulation which confirms claims raised by historians that the eastward diversion project of the Tone River in Japan was conducted 4 centuries ago to increase low flows and subsequent travelling possibilities surrounding the capital, Edo (Tokyo), using inland navigation. We showed that great steps forward can be made for improving quality of life with small human engineering waterworks and small interventions in the regime of natural flows.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci., 29, 683–700, https://doi.org/10.5194/hess-29-683-2025, https://doi.org/10.5194/hess-29-683-2025, 2025
Short summary
Short summary
This work investigates how hydrological models are transferred to a period in which climate conditions are different to the ones of the period in which they were set up. The robustness assessment test built to detect dependencies between model error and climatic drivers was applied to three hydrological models in 352 catchments in Denmark, France and Sweden. Potential issues are seen in a significant number of catchments for the models, even though the catchments differ for each model.
Xudong Zheng, Dengfeng Liu, Shengzhi Huang, Hao Wang, and Xianmeng Meng
Hydrol. Earth Syst. Sci., 29, 627–653, https://doi.org/10.5194/hess-29-627-2025, https://doi.org/10.5194/hess-29-627-2025, 2025
Short summary
Short summary
Water budget non-closure is a widespread phenomenon among multisource datasets which undermines the robustness of hydrological inferences. This study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed PHPM-MDCF. We examined the efficiency and robustness of the framework using the CAMELS dataset and achieved an average reduction of 49 % in total water budget residuals across 475 CONUS basins.
Elena Macdonald, Bruno Merz, Viet Dung Nguyen, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 29, 447–463, https://doi.org/10.5194/hess-29-447-2025, https://doi.org/10.5194/hess-29-447-2025, 2025
Short summary
Short summary
Flood peak distributions indicate how likely the occurrence of an extreme flood is at a certain river. If the distribution has a so-called heavy tail, extreme floods are more likely than might be anticipated. We find heavier tails in small catchments compared to large catchments, and spatially variable rainfall leads to a lower occurrence probability of extreme floods. Spatially variable runoff does not show effects. The results can improve estimations of probabilities of extreme floods.
Junfu Gong, Xingwen Liu, Cheng Yao, Zhijia Li, Albrecht H. Weerts, Qiaoling Li, Satish Bastola, Yingchun Huang, and Junzeng Xu
Hydrol. Earth Syst. Sci., 29, 335–360, https://doi.org/10.5194/hess-29-335-2025, https://doi.org/10.5194/hess-29-335-2025, 2025
Short summary
Short summary
Our study introduces a new method to improve flood forecasting by combining soil moisture and streamflow data using an advanced data assimilation technique. By integrating field and reanalysis soil moisture data and assimilating this with streamflow measurements, we aim to enhance the accuracy of flood predictions. This approach reduces the accumulation of past errors in the initial conditions at the start of the forecast, helping to better prepare for and respond to floods.
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
Short summary
Short summary
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.
Haley A. Canham, Belize Lane, Colin B. Phillips, and Brendan P. Murphy
Hydrol. Earth Syst. Sci., 29, 27–43, https://doi.org/10.5194/hess-29-27-2025, https://doi.org/10.5194/hess-29-27-2025, 2025
Short summary
Short summary
The influence of watershed disturbances has proved challenging to disentangle from natural streamflow variability. This study evaluates the influence of time-varying hydrologic controls on rainfall–runoff in undisturbed and wildfire-disturbed watersheds using a novel time-series event separation method. Across watersheds, water year type and season influenced rainfall–runoff patterns. Accounting for these controls enabled clearer isolation of wildfire effects.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci., 28, 5511–5539, https://doi.org/10.5194/hess-28-5511-2024, https://doi.org/10.5194/hess-28-5511-2024, 2024
Short summary
Short summary
Evapotranspiration (ET) is computed from the vegetation (plant transpiration) and soil (soil evaporation). In western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented using the leaf area index (LAI). In this study, we evaluate the importance of the LAI for ET calculation. We take a close look at this interaction and highlight its relevance. Our work contributes to the understanding of terrestrial water cycle processes .
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
Short summary
Short summary
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.
Laia Estrada, Xavier Garcia, Joan Saló-Grau, Rafael Marcé, Antoni Munné, and Vicenç Acuña
Hydrol. Earth Syst. Sci., 28, 5353–5373, https://doi.org/10.5194/hess-28-5353-2024, https://doi.org/10.5194/hess-28-5353-2024, 2024
Short summary
Short summary
Hydrological modelling is a powerful tool to support decision-making. We assessed spatio-temporal patterns and trends of streamflow for 2001–2022 with a hydrological model, integrating stakeholder expert knowledge on management operations. The results provide insight into how climate change and anthropogenic pressures affect water resources availability in regions vulnerable to water scarcity, thus raising the need for sustainable management practices and integrated hydrological modelling.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, https://doi.org/10.5194/hess-28-5331-2024, 2024
Short summary
Short summary
Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. We investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analyses indicate that adding two vegetation parameters is enough to improve the representation of evaporation and that the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Daniel T. Myers, David Jones, Diana Oviedo-Vargas, John Paul Schmit, Darren L. Ficklin, and Xuesong Zhang
Hydrol. Earth Syst. Sci., 28, 5295–5310, https://doi.org/10.5194/hess-28-5295-2024, https://doi.org/10.5194/hess-28-5295-2024, 2024
Short summary
Short summary
We studied how streamflow and water quality models respond to land cover data collected by satellites during the growing season versus the non-growing season. The land cover data showed more trees during the growing season and more built areas during the non-growing season. We next found that the use of non-growing season data resulted in a higher modeled nutrient export to streams. Knowledge of these sensitivities would be particularly important when models inform water resource management.
Kevin R. Shook, Paul H. Whitfield, Christopher Spence, and John W. Pomeroy
Hydrol. Earth Syst. Sci., 28, 5173–5192, https://doi.org/10.5194/hess-28-5173-2024, https://doi.org/10.5194/hess-28-5173-2024, 2024
Short summary
Short summary
Recent studies suggest that the velocities of water running off landscapes in the Canadian Prairies may be much smaller than generally assumed. Analyses of historical flows for 23 basins in central Alberta show that many of the rivers responded more slowly and that the flows are much slower than would be estimated from equations developed elsewhere. The effects of slow flow velocities on the development of hydrological models of the region are discussed, as are the possible causes.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci., 28, 4971–4988, https://doi.org/10.5194/hess-28-4971-2024, https://doi.org/10.5194/hess-28-4971-2024, 2024
Short summary
Short summary
The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature associated with aridity and intermittent flow that is needed for challenging cases. Baseflow index, aridity, and soil or vegetation attributes strongly correlate with learnt features, indicating their importance for streamflow prediction.
Pablo Fernando Dornes and Rocío Noelia Comas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-338, https://doi.org/10.5194/hess-2024-338, 2024
Preprint under review for HESS
Short summary
Short summary
The Desaguadero-Salado-Chadiluevú-Curacó (DSCC) River is a semiarid river which is severely dammed in its tributaries which collect the snowmelt runoff. This runoff feeds mostly gravitational irrigation systems of very low efficiency. As a result, the DSCC River does not have natural runoff. The proposed Hydrological Regime Index (HRI) is able to discriminate and quantify regime alterations under permanent and non-permanent flow conditions and with low and high impoundment conditions.
Guillaume Thirel, Léonard Santos, Olivier Delaigue, and Charles Perrin
Hydrol. Earth Syst. Sci., 28, 4837–4860, https://doi.org/10.5194/hess-28-4837-2024, https://doi.org/10.5194/hess-28-4837-2024, 2024
Short summary
Short summary
We discuss how mathematical transformations impact calibrated hydrological model simulations. We assess how 11 transformations behave over the complete range of streamflows. Extreme transformations lead to models that are specialized for extreme streamflows but show poor performance outside the range of targeted streamflows and are less robust. We show that no a priori assumption about transformations can be taken as warranted.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 4685–4713, https://doi.org/10.5194/hess-28-4685-2024, https://doi.org/10.5194/hess-28-4685-2024, 2024
Short summary
Short summary
Large-scale hydrologic simulators are a needed tool to explore complex watershed processes and how they may evolve with a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration using neural networks with a set of experiments based on streamflow in the upper Colorado River basin.
Jari-Pekka Nousu, Kersti Leppä, Hannu Marttila, Pertti Ala-aho, Giulia Mazzotti, Terhikki Manninen, Mika Korkiakoski, Mika Aurela, Annalea Lohila, and Samuli Launiainen
Hydrol. Earth Syst. Sci., 28, 4643–4666, https://doi.org/10.5194/hess-28-4643-2024, https://doi.org/10.5194/hess-28-4643-2024, 2024
Short summary
Short summary
We used hydrological models, field measurements, and satellite-based data to study the soil moisture dynamics in a subarctic catchment. The role of groundwater was studied with different ways to model the groundwater dynamics and via comparisons to the observational data. The choice of groundwater model was shown to have a strong impact, and representation of lateral flow was important to capture wet soil conditions. Our results provide insights for ecohydrological studies in boreal regions.
Chen Yang, Zitong Jia, Wenjie Xu, Zhongwang Wei, Xiaolang Zhang, Yiguang Zou, Jeffrey McDonnell, Laura Condon, Yongjiu Dai, and Reed Maxwell
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-292, https://doi.org/10.5194/hess-2024-292, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
We developed the first high-resolution, integrated surface water-groundwater hydrologic model of the entire continental China using ParFlow. The model shows good performance of streamflow and water table depth when compared to global data products and observations. It is essential for water resources management and decision making in China within a consistent framework in the changing world. It also has significant implications for similar modeling in other places in the world.
Nienke Tempel, Laurène Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 28, 4577–4597, https://doi.org/10.5194/hess-28-4577-2024, https://doi.org/10.5194/hess-28-4577-2024, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities and, thus, on hydrological predictions. Analysing data from 286 areas in Europe and the US, we found that, despite some variations in root zone storage capacity due to changing climatic conditions over multiple decades, these changes are generally minor and have a limited effect on water storage and river flow predictions.
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Wouter J. M. Knoben, Ashwin Raman, Gaby J. Gründemann, Mukesh Kumar, Alain Pietroniro, Chaopeng Shen, Yalan Song, Cyril Thébault, Katie van Werkhoven, Andrew W. Wood, and Martyn P. Clark
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-279, https://doi.org/10.5194/hess-2024-279, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Hydrologic models are needed to provide simulations of water availability, floods and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models, and thus cannot easily be used to select an appropriate model for a specific place.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Fabián Lema, Pablo A. Mendoza, Nicolás A. Vásquez, Naoki Mizukami, Mauricio Zambrano-Bigiarini, and Ximena Vargas
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-221, https://doi.org/10.5194/hess-2024-221, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Hydrological droughts affect ecosystems and socioeconomic activities worldwide. Despite they are commonly described with the Standardized Streamflow Index (SSI), there is limited understanding of what it truly reflects in terms of water cycle processes. Here, we used state-of-the-art hydrological models in Andean basins to examine drivers of SSI fluctuations. The results highlight the importance of careful selection of indices and time scales for accurate drought characterization and monitoring.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Jean-Luc Martel, François Brissette, Richard Arsenault, Richard Turcotte, Mariana Castañeda-Gonzalez, William Armstrong, Edouard Mailhot, Jasmine Pelletier-Dumont, Gabriel Rondeau-Genesse, and Louis-Philippe Caron
EGUsphere, https://doi.org/10.5194/egusphere-2024-2133, https://doi.org/10.5194/egusphere-2024-2133, 2024
Short summary
Short summary
This study compares Long Short-Term Memory (LSTM) neural networks with traditional hydrological models to predict future streamflow under climate change. Using data from 148 catchments, it finds that LSTM models, which learn from extensive data sequences, perform differently and often better than traditional hydrolgical models. The continental LSTM model, which includes data from diverse climate zones, is particularly effective for understanding climate impacts on water resources.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Cited articles
Abatzoglou, J. T.: Development of gridded surface meteorological data for
ecological applications and modelling, Int. J. Climatol., 33, 121–131,
https://doi.org/10.1002/joc.3413, 2013.
Ajami, H., Troch, P. A., Maddock, T., Meixner, T., and Eastoe, C.:
Quantifying mountain block recharge by means of catchment-scale
storage-discharge relationships, Water Resour. Res., 47, 1–14,
https://doi.org/10.1029/2010WR009598, 2011.
Ajami, H., Meixner, T., Dominguez, F., Hogan, J., and Maddock, T.:
Seasonalizing Mountain System Recharge in Semi-Arid Basins-Climate Change
Impacts, Hydrol. Process., 50, 585–597, https://doi.org/10.1111/j.1745-6584.2011.00881.x,
2012.
Ajami, H., McCabe, M. F., Evans, J. P., and Stisen, S.: Assessing the impact
of model spin-up on surface water-groundwater interactions using an
integrated hydrologic model, Water Resour. Res., 50, 2636–2656,
https://doi.org/10.1002/2013WR014258, 2014.
Ajami, H., McCabe, M. F., and Evans, J. P.: Impacts of model initialization
on an integrated surface water-groundwater model, Ground Water, 29, 3790–3801,
https://doi.org/10.1002/hyp.10478, 2015.
Anon: Tulare Lake basin hydrology and hydrography: A summary of the movement
of water and aquatic species, 136 pp., 2007.
Beck, H. E., Pan, M., Roy, T., Weedon, G. P., Pappenberger, F., van Dijk, A. I. J. M., Huffman, G. J., Adler, R. F., and Wood, E. F.: Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS, Hydrol. Earth Syst. Sci., 23, 207–224, https://doi.org/10.5194/hess-23-207-2019, 2019.
Beven, K.: 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, Hydrol. Sci. Bull., 24, 43–69,
https://doi.org/10.1080/02626667909491834, 1979.
Bridget, R. S., Richard, W. H., and Peter, G. C.: Choosing
appropriate techniques for quantifying groundwater recharge, Hydrogeol. J., 10, 18–39,
https://doi.org/10.1007/s10040-0010176-2, 2002.
Brush, C. F., Dogrul, E. C., and Kadir, T. N.: Development and calibration
of the California Central Valley groundwater-surface water simulation model
(C2VSim), Version 3.02-CG, Sacramento, 196 pp., 2013.
Chaney, N. W., Wood, E. F., McBratney, A. B., Hempel, J. W., Nauman, T. W.,
Brungard, C. W., and Odgers, N. P.: POLARIS: A 30-meter probabilistic soil
series map of the contiguous United States, Geoderma, 274, 54–67,
https://doi.org/10.1016/j.geoderma.2016.03.025, 2016.
Chow, V. T.: Open-Channel Hydraulics, The Blackburn Press, Caldwell, NJ, ISBN: 1932846182,
2009.
Crosbie, R. S., Dawes, W. R., Charles, S. P., Mpelasoka, F. S., Aryal, S.,
Barron, O., and Summerell, G. K.: Differences in future recharge estimates
due to GCMs, downscaling methods and hydrological models, Geophys. Res. Lett., 38, 1–5,
https://doi.org/10.1029/2011GL047657, 2011.
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, 1013–1023,
https://doi.org/10.1175/BAMS-84-8-1013, 2003.
Daly, C., Neilson, R., and Phillips, D. L.: A statistical-topographic model
for mapping climatological precipitation over mountainous terrain, J. Appl. Meteorol., 33, 140–158, https://doi.org/10.1175/1520-0450(1994)033<0140:ASTMFM>2.0.CO;2, 1994.
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. Clim., 28, 2031–2064, https://doi.org/10.1002/joc.1688, 2008.
Erler, A. R., Frey, S. K., Khader, O., d'Orgeville, M., Park, Y. J., Hwang,
H. T., Lapen, D. R., Peltier, W. R., and Sudicky, E. A.: Evaluating Climate
Change Impacts on Soil Moisture and Groundwater Resources Within a
Lake-Affected Region, Water Resour. Res., 55, 8142–8163, https://doi.org/10.1029/2018WR023822,
2019.
Fatichi, S., Vivoni, E. R., Ogden, F. L., Ivanov, V. Y., Mirus, B., Gochis,
D., Downer, C. W., Camporese, M., Davison, J. H., Ebel, B., Jones, N., Kim,
J., Mascaro, G., Niswonger, R., Restrepo, P., Rigon, R., Shen, C., Sulis,
M., and Tarboton, D.: An overview of current applications, challenges, and
future trends in distributed process-based models in hydrology, J. Hydrol., 537, 45–60,
https://doi.org/10.1016/j.jhydrol.2016.03.026, 2016.
Faunt, C. C.: Groundwater Availability of the Central Valley Aquifer,
California, United States Geological Survey, http://pubs.usgs.gov/pp/1766/, 2009.
Gesch, D. B., Evans, G. A., Oimoen, M. J., and Arundel, S.: The National
Elevation Dataset, American Society for Photogrammetry and Remote Sensing,
83–110, 2018.
Hall, W. H.: Physical data and statistics of California – Tables and
memoranda relating to rainfall, temperature, winds, evaporation, and other
atmospheric phenomena; drainage areas and basins, flows of streams,
descriptions and flows of artesian wells, and other fact, State Printing,
Sacramento, CA, 560 pp., 1886.
Hartmann, A., Gleeson, T., Wada, Y., and Wagener, T.: Enhanced groundwater
recharge rates and altered recharge sensitivity to climate variability
through subsurface heterogeneity, P. Natl. Acad. Sci. USA, 114, 2842–2847,
https://doi.org/10.1073/pnas.1614941114, 2017.
Henn, B., Newman, A. J., Livneh, B., Daly, C., and Lundquist, J. D.: An
assessment of differences in gridded precipitation datasets in complex
terrain, J. Hydrol., 556, 1205–1219, https://doi.org/10.1016/j.jhydrol.2017.03.008,
2018.
Holbrook, W. S., Riebe, C. S., Elwaseif, M., Hayes, J. L., Basler-Reeder,
K., Harry, D. L., Malazian, A., Dosseto, A., Hartsough, P. C., and Hopmans,
J. W.: Geophysical constraints on deep weathering and water storage
potential in the Southern Sierra Critical Zone Observatory, Earth Surf. Proc. Land., 39, 366–380,
https://doi.org/10.1002/esp.3502, 2014.
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 plot-scale understanding to the catchment
scale, Water Resour. Res., 45, 1–16, https://doi.org/10.1029/2008WR007225, 2009.
Jennings, C. W.: Geologic map of California:, Sacramento, 1 pp., 1977.
Kollet, S. J. and Maxwell, R. M.: Integrated surface-groundwater flow
modeling: A free-surface overland flow boundary condition in a parallel
groundwater flow model, Adv. Water Res., 29, 945–958,
https://doi.org/10.1016/j.advwatres.2005.08.006, 2006.
Kollet, S. J., Cvijanovic, I., Schüttemeyer, D., Maxwell, R. M., Moene,
A. F., and Bayer, P.: The Influence of Rain Sensible Heat and Subsurface
Energy Transport on the Energy Balance at the Land Surface, Vadose Zone J., 8, 846–857,
https://doi.org/10.2136/vzj2009.0005, 2009.
Livneh, B., Rosenberg, E. A., Lin, C., Nijssen, B., Mishra, V., Andreadis,
K. M., Maurer, E. P., and Lettenmaier, D. P.: A long-term hydrologically
based dataset of land surface fluxes and states for the conterminous United
States: Update and extensions, J. Climate, 26, 9384–9392,
https://doi.org/10.1175/JCLI-D-12-00508.1, 2013.
Lundquist, J. D., Cayan, D. R., and Dettinger, M. D.: Meteorology and
Hydrology in Yosemite National Park: A Sensor Network Application BT –
Information Processing in Sensor Networks, 518–528, 2003.
Lundquist, J. D., Hughes, M., Henn, B., Gutmann, E. D., Livneh, B., Dozier,
J., and Neiman, P.: High-elevation precipitation patterns: Using snow
measurements to assess daily gridded datasets across the Sierra Nevada,
California, J. Hydrometeorol., 16, 1773–1792, https://doi.org/10.1175/JHM-D-15-0019.1, 2015.
Mailloux, B. J., Person, M., Kelley, S., Dunbar, N., Cather, S., Strayer,
L., and Hudleston, P.: Tectonic controls on the hydrogeology of the Rio
Grande Rift, New Mexico, Water Resour. Res., 35, 2641–2659,
https://doi.org/10.1029/1999WR900110, 1999.
Manning, A. H. and Solomon, D. K.: Using noble gases to investigate
mountain-front recharge, J. Hydrol., 275, 194–207,
https://doi.org/10.1016/S0022-1694(03)00043-X, 2003.
Margulis, S. A., Cortés, G., Girotto, M., and Durand, M.: A landsat-era
Sierra Nevada snow reanalysis (1985–2015), J. Hydrometeorol., 17, 1203–1221,
https://doi.org/10.1175/JHM-D-15-0177.1, 2016.
Maxwell, R. M.: A terrain-following grid transform and preconditioner for
parallel, large-scale, integrated hydrologic modeling, Adv. Water Res., 53, 109–117,
https://doi.org/10.1016/j.advwatres.2012.10.001, 2013.
Maxwell, R. M. and Kollet, S. J.: Interdependence of groundwater dynamics
and land-energy feedbacks under climate change, Nat. Geosci., 1, 665–669,
https://doi.org/10.1038/ngeo315, 2008.
Maxwell, R. M. and Miller, N. L.: On the development of a coupled land
surface and groundwater model, J. Hydrometeorol., 6, 233–247, 2005.
Meixner, T., Manning, A. H., Stonestrom, D. A., Allen, D. M., Ajami, H.,
Blasch, K. W., Brookfield, A. E., Castro, C. L., Clark, J. F., Gochis, D.
J., Flint, A. L., Neff, K. L., Niraula, R., Rodell, M., Scanlon, B. R.,
Singha, K., and Walvoord, M. A.: Implications of projected climate change
for groundwater recharge in the western United States, J. Hydrol., 534, 124–138,
https://doi.org/10.1016/j.jhydrol.2015.12.027, 2016.
Newman, B. D., Wilcox, B. P., Archer, S. R., Breshears, D. D., Dahm, C. N.,
Duffy, C. J., McDowell, N. G., Phillips, F. M., Scanlon, B. R., and Vivoni,
E. R.: Ecohydrology of water-limited environments: A scientific vision, Water Resour. Res., 42,
1–15, https://doi.org/10.1029/2005WR004141, 2006.
Olmsted, F. H. and Davis, G. H.: Geologic features and ground-water storage
capacity of the Sacramento Valley, California, 241 pp., 1961.
Oyler, J. W., Ballantyne, A., Jencso, K., Sweet, M., and Running, S. W.:
Creating a topoclimatic daily air temperature dataset for the conterminous
United States using homogenized station data and remotely sensed land skin
temperature, Int. J. Climatol., 35, 2258–2279, https://doi.org/10.1002/joc.4127, 2015.
Pan, M., Cai, X., Chaney, N. W., Entekhabi, D., and Wood, E. F.: An initial
assessment of SMAP soil moisture retrievals using high-resolution model
simulations and in situ observations, Geophys. Res. Lett., 43, 9662–9668,
https://doi.org/10.1002/2016GL069964, 2016.
Pfister, L., Martínez-Carreras, N., Hissler, C., Klaus, J., Carrer, G.
E., Stewart, M. K., and McDonnell, J. J.: Bedrock geology controls on
catchment storage, mixing, and release: A comparative analysis of 16 nested
catchments, Hydrol. Proc., 31, 1828–1845, https://doi.org/10.1002/hyp.11134, 2017.
Rasmussen, R., Baker, B., Kochendorfer, J., Meyers, T., Landolt, S.,
Fischer, A. P., Black, J., Thériault, J. M., Kucera, P., Gochis, D.,
Smith, C., Nitu, R., Hall, M., Ikeda, K., and Gutmann, E.: How well are we
measuring snow: The NOAA/FAA/NCAR winter precipitation test bed, B. Am. Meteorol. Soc., 93,
811–829, https://doi.org/10.1175/BAMS-D-11-00052.1, 2012.
Schreiner-McGraw, A. P. and Vivoni, E. R.: Percolation observations in an
arid piedmont watershed and linkages to historical conditions in the
Chihuahuan Desert, Ecosphere, 8, https://doi.org/10.1002/ecs2.2000, 2017.
Schreiner-McGraw, A. P. and Vivoni, E. R.: On the Sensitivity of Hillslope
Runoff and Channel Transmission Losses in Arid Piedmont Slopes, Water Resour. Res., 54,
https://doi.org/10.1029/2018WR022842, 2018.
Schreiner-McGraw, A. P. and Ajami, H.: Impact of Uncertainty in
Precipitation Forcing Data Sets on the Hydrologic Budget of an Integrated
Hydrologic Model in Mountainous Terrain, Water Resour. Res., 56, e2020WR027639,
https://doi.org/10.1029/2020WR027639, 2020.
Schreiner-McGraw, A. P. and Ajami, H.: Combined impacts of uncertainty in precipitation and air
temperature on simulated mountain system recharge
from an integrated hydrologic model, [data set], 2022.
Schreiner-Mcgraw, A. P., Ajami, H., and Vivoni, E. R.: Extreme weather
events and transmission losses in arid streams, Environ. Res. Lett., 14,
https://doi.org/10.1088/1748-9326/ab2949, 2019.
Smith, S., reedmaxwell, i-ferguson, Gasper, F., Engdahl, N., Hokkanen, J., Avery, P., Jourdain, S., grapp1, Condon, L., Kulkarni, K., xy124, basileh, Thompson, D., Swilley, J., Bansal, V., Chennault, C., Coon, E., Ian Bertolacci M. S., Beisman, J., Fonseca, J. A., Lührsarezai, S., icswoodward, alanquits: parflow/parflow: ParFlow Version 3.8.0, Zenodo [code], https://doi.org/10.5281/zenodo.4816885, 2021.
Spencer, S. A., Silins, U., and Anderson, A. E.: Precipitation-Runoff and
Storage Dynamics in Watersheds Underlain by Till and Permeable Bedrock in
Alberta's Rocky Mountains, Water Resour. Res., 55, 10690–10706,
https://doi.org/10.1029/2019WR025313, 2019.
Taylor, R. G., Scanlon, B., Döll, P., Rodell, M., Van Beek, R., Wada,
Y., Longuevergne, L., Leblanc, M., Famiglietti, J. S., Edmunds, M., Konikow,
L., Green, T. R., Chen, J., Taniguchi, M., Bierkens, M. F. P., Macdonald,
A., Fan, Y., Maxwell, R. M., Yechieli, Y., Gurdak, J. J., Allen, D. M.,
Shamsudduha, M., Hiscock, K., Yeh, P. J. F., Holman, I., and Treidel, H.:
Ground water and climate change, Nat. Clim. Change, 3, 322–329,
https://doi.org/10.1038/nclimate1744, 2013.
Thayer, D., Parsekian, A. D., Hyde, K., Speckman, H., Beverly, D., Ewers,
B., Covalt, M., Fantello, N., Kelleners, T., Ohara, N., Rogers, T., and
Holbrook, W. S.: Geophysical Measurements to Determine the Hydrologic
Partitioning of Snowmelt on a Snow-Dominated Subalpine Hillslope, Water Resour. Res., 54,
3788–3808, https://doi.org/10.1029/2017WR021324, 2018.
Thornton, P. E., Running, S. W., and White, M. A.: Generating surfaces of
daily meteorological variables over large regions of complex terrain, J. Hydrol., 190,
214–251, https://doi.org/10.1016/S0022-1694(96)03128-9, 1997.
Udall, B. and Overpeck, J.: The twenty-first century Colorado River hot
drought and implications for the future, Water Resour. Res., 53, 2404–2418,
https://doi.org/10.1002/2016WR019638, 2017.
Vano, J. A., Das, T., and Lettenmaier, D. P.: Hydrologic sensitivities of
Colorado River runoff to changes in precipitation and temperature, J. Hydrometeorol., 13,
932–949, https://doi.org/10.1175/JHM-D-11-069.1, 2012.
Visser, A., Moran, J. E., Singleton, M. J., and Esser, B. K.: Importance of
river water recharge to the San Joaquin Valley groundwater system, Hydrol. Proc., 32,
1202–1213, https://doi.org/10.1002/hyp.11468, 2018.
Viviroli, D. and Weingartner, R.: The hydrological significance of mountains: from regional to global scale, Hydrol. Earth Syst. Sci., 8, 1017–1030, https://doi.org/10.5194/hess-8-1017-2004, 2004.
Viviroli, D., Dürr, H. H., Messerli, B., Meybeck, M., and Weingartner,
R.: Mountains of the world, water towers for humanity: Typology, mapping,
and global significance, Water Resour. Res., 43, 1–13, https://doi.org/10.1029/2006WR005653,
2007.
Welch, L. A. and Allen, D. M.: Hydraulic conductivity characteristics in
mountains and implications for conceptualizing bedrock groundwater flow, Hydrogeol. J., 22, 1003–1026, https://doi.org/10.1007/s10040-014-1121-5, 2014.
Woldemeskel, F. M., Sharma, A., Sivakumar, B., and Mehrotra, R.: An error
estimation method for precipitation and temperature projections for future
climates, J. Geophys. Res.-Atmos., 117, 1–13, https://doi.org/10.1029/2012JD018062, 2012.
Short summary
We assess the impact of uncertainty in measurements of precipitation and air temperature on simulated groundwater processes in a mountainous watershed. We illustrate the role of topography in controlling how uncertainty in the input datasets propagates through the soil and into the groundwater. While the focus of previous investigations has been on the impact of precipitation uncertainty, we show that air temperature uncertainty is equally important in controlling the groundwater recharge.
We assess the impact of uncertainty in measurements of precipitation and air temperature on...
