Articles | Volume 19, issue 6
https://doi.org/10.5194/hess-19-2821-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-19-2821-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
19 Jun 2015
Research article |
| 19 Jun 2015
Including the dynamic relationship between climatic variables and leaf area index in a hydrological model to improve streamflow prediction under a changing climate
Z. K. Tesemma
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia
Y. Wei
CORRESPONDING AUTHOR
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia
M. C. Peel
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia
A. W. Western
Department of Infrastructure Engineering, The University of Melbourne, Parkville, Victoria, 3010, Australia
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Z. K. Tesemma, Y. Wei, M. C. Peel, and A. W. Western
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-10515-2014, https://doi.org/10.5194/hessd-11-10515-2014, 2014
Revised manuscript not accepted
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Keirnan Fowler, Murray Peel, Margarita Saft, Tim J. Peterson, Andrew Western, Lawrence Band, Cuan Petheram, Sandra Dharmadi, Kim Seong Tan, Lu Zhang, Patrick Lane, Anthony Kiem, Lucy Marshall, Anne Griebel, Belinda E. Medlyn, Dongryeol Ryu, Giancarlo Bonotto, Conrad Wasko, Anna Ukkola, Clare Stephens, Andrew Frost, Hansini Gardiya Weligamage, Patricia Saco, Hongxing Zheng, Francis Chiew, Edoardo Daly, Glen Walker, R. Willem Vervoort, Justin Hughes, Luca Trotter, Brad Neal, Ian Cartwright, and Rory Nathan
Hydrol. Earth Syst. Sci., 26, 6073–6120, https://doi.org/10.5194/hess-26-6073-2022, https://doi.org/10.5194/hess-26-6073-2022, 2022
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Luca Trotter, Wouter J. M. Knoben, Keirnan J. A. Fowler, Margarita Saft, and Murray C. Peel
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MARRMoT is a piece of software that emulates 47 common models for hydrological simulations. It can be used to run and calibrate these models within a common environment as well as to easily modify them. We restructured and recoded MARRMoT in order to make the models run faster and to simplify their use, while also providing some new features. This new MARRMoT version runs models on average 3.6 times faster while maintaining very strong consistency in their outputs to the previous version.
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Hydrol. Earth Syst. Sci., 26, 941–954, https://doi.org/10.5194/hess-26-941-2022, https://doi.org/10.5194/hess-26-941-2022, 2022
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Hydrol. Earth Syst. Sci., 25, 2663–2683, https://doi.org/10.5194/hess-25-2663-2021, https://doi.org/10.5194/hess-25-2663-2021, 2021
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Wouter J. M. Knoben, Jim E. Freer, Keirnan J. A. Fowler, Murray C. Peel, and Ross A. Woods
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Computer models are used to predict river flows. A good model should represent the river basin to which it is applied so that flow predictions are as realistic as possible. However, many different computer models exist, and selecting the most appropriate model for a given river basin is not always easy. This study combines computer code for 46 different hydrological models into a single coding framework so that models can be compared in an objective way and we can learn about model differences.
Chinchu Mohan, Andrew W. Western, Yongping Wei, and Margarita Saft
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To ensure a sustainable supply of groundwater, scientific information about what is going into the system as recharge and what is taken out of the system via pumping is essential. This study identified the most influential factors in groundwater recharge and developed an empirical global recharge model. The meteorological and vegetation factors were the most important factors, and the long-term global average recharge was 134 mm per year. This model will aid in groundwater policy-making.
Shabnam Saffarpour, Andrew W. Western, Russell Adams, and Jeffrey J. McDonnell
Hydrol. Earth Syst. Sci., 20, 4525–4545, https://doi.org/10.5194/hess-20-4525-2016, https://doi.org/10.5194/hess-20-4525-2016, 2016
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A variety of threshold mechanisms influence the transfer of rainfall to runoff from catchments. Some of these mechanisms depend on the occurrence of intense rainfall and others depend on the catchment being wet. This article first provides a framework for considering which mechanisms are important in different situations and then uses that framework to examine the behaviour of a catchment in Australia that exhibits a mix of both rainfall intensity and catchment wetness dependent thresholds.
Z. Lu, Y. Wei, H. Xiao, S. Zou, J. Xie, J. Ren, and A. Western
Hydrol. Earth Syst. Sci., 19, 2261–2273, https://doi.org/10.5194/hess-19-2261-2015, https://doi.org/10.5194/hess-19-2261-2015, 2015
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This paper quantitatively analyzed the evolution of human-water relationships in the Heihe River basin over the past 2000 years by reconstructing the catchment water balance. The results provided the basis for investigating the impacts of human societies on hydrological systems. The evolutionary processes of human-water relationships can be divided into four stages: predevelopment, take-off, acceleration, and rebalancing. And the transition of the human-water relationship had no fixed pattern.
M. C. Peel, R. Srikanthan, T. A. McMahon, and D. J. Karoly
Hydrol. Earth Syst. Sci., 19, 1615–1639, https://doi.org/10.5194/hess-19-1615-2015, https://doi.org/10.5194/hess-19-1615-2015, 2015
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We present a proof-of-concept approximation of within-GCM uncertainty using non-stationary stochastic replicates of monthly precipitation and temperature projections and investigate the impact of within-GCM uncertainty on projected runoff and reservoir yield. Amplification of within-GCM variability from precipitation to runoff to reservoir yield suggests climate change impact assessments ignoring within-GCM uncertainty would provide water resources managers with an unjustified sense of certainty
J. F. Costelloe, T. J. Peterson, K. Halbert, A. W. Western, and J. J. McDonnell
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Groundwater surface mapping is used as an independent data set to better estimate groundwater discharge to streamflow. The groundwater surfaces indicated when other techniques likely overestimated the groundwater discharge component of baseflow. Groundwater surfaces also identified areas where regional groundwater could not be contributing to tributary streamflow. This method adds significant value to water resource management where sufficient groundwater monitoring data are available.
T. A. McMahon, M. C. Peel, and D. J. Karoly
Hydrol. Earth Syst. Sci., 19, 361–377, https://doi.org/10.5194/hess-19-361-2015, https://doi.org/10.5194/hess-19-361-2015, 2015
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Here we assess GCM performance from a hydrologic perspective. We identify five better performing CMIP3 GCMs that reproduce grid-scale climatological statistics of observed precipitation and temperature over global land regions for future hydrologic simulation. GCM performance in reproducing observed mean and standard deviation of annual precipitation, mean annual temperature and mean monthly precipitation and temperature was assessed and ranked, and five better performing GCMs were identified.
Z. K. Tesemma, Y. Wei, M. C. Peel, and A. W. Western
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-10515-2014, https://doi.org/10.5194/hessd-11-10515-2014, 2014
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T. A. McMahon, M. C. Peel, and J. Szilagyi
Hydrol. Earth Syst. Sci., 17, 4865–4867, https://doi.org/10.5194/hess-17-4865-2013, https://doi.org/10.5194/hess-17-4865-2013, 2013
T. A. McMahon, M. C. Peel, L. Lowe, R. Srikanthan, and T. R. McVicar
Hydrol. Earth Syst. Sci., 17, 1331–1363, https://doi.org/10.5194/hess-17-1331-2013, https://doi.org/10.5194/hess-17-1331-2013, 2013
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Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
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Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
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
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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
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The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
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
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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
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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
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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
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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
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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
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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
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Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
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Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
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A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
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Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
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Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
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Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
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We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
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In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
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Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Léonard Santos, Vazken Andréassian, Torben O. Sonnenborg, Göran Lindström, Alban de Lavenne, Charles Perrin, Lila Collet, and Guillaume Thirel
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-80, https://doi.org/10.5194/hess-2024-80, 2024
Revised manuscript accepted for HESS
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This work aims at investigating how hydrological models can be transferred to a period in which climatic conditions are different to the ones of the period in which it was set up. The RAT method, built to detect dependencies between model error and climatic drivers, was applied to 3 different hydrological models on 352 catchments in Denmark, France and Sweden. Potential issues are detected for a significant number of catchments for the 3 models even though these catchments differ for each model.
Fabian Merk, Timo Schaffhauser, Faizan Anwar, Ye Tuo, Jean-Martial Cohard, and Markus Disse
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-131, https://doi.org/10.5194/hess-2024-131, 2024
Revised manuscript accepted for HESS
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ET is computed from vegetation (plant transpiration) and soil (soil evaporation). In Western Africa, plant transpiration correlates with vegetation growth. Vegetation is often represented with the leaf-area-index (LAI). In this study, we evaluate the importance of LAI for the ET calculation. We take a close look at the LAI-ET interaction and show the relevance to consider both, LAI and ET. Our work contributes to the understanding of the processes of the terrestrial water cycle.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
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It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
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Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
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Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
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We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
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Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
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We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
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Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
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This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
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To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Patricio Yeste, Matilde García-Valdecasas Ojeda, Sonia R. Gámiz-Fortis, Yolanda Castro-Díez, Axel Bronstert, and María Jesús Esteban-Parra
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-57, https://doi.org/10.5194/hess-2024-57, 2024
Revised manuscript accepted for HESS
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Integrating streamflow and evaporation data can help improve the physical realism of hydrologic models. In this work we investigate the capabilities of the Variable Infiltration Capacity (VIC) to reproduce both hydrologic variables for 189 headwater located in Spain. Results from sensitivity analysis indicate that adding two vegetation is enough to improve the representation of evaporation, and the performance of VIC exceeded that of the largest modelling effort currently available in Spain.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
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Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
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Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
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Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
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In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-47, https://doi.org/10.5194/hess-2024-47, 2024
Revised manuscript accepted for HESS
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The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature needed for challenging cases, associated with aridity and intermittent flow. Baseflow index, aridity, and soil/vegetation attributes strongly correlate with learned features, indicating their importance for streamflow prediction.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
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In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
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This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
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Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
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We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
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Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
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How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Cited articles
Ainsworth, E. A. and Rogers, A.: The response of photosynthesis and stomatal conductance to rising [CO2]: mechanisms and environmental interactions, Plant Cell Environ., 30, 258–270, https://doi.org/10.1111/j.1365-3040.2007.01641.x, 2007.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration Guidelines for computing crop water requirements, FAO Irrigation and Drainage Paper 56, Food and Agriculture Organization of the United Nations, 1998.
Bunce, J. A.: Carbon dioxide effects on stomatal responses to the environment and water use by crops under field conditions, Oecologia, 140, 1–10, https://doi.org/10.1007/s00442-003-1401-6, 2004.
Cai, W. and Cowan, T.: Evidence of impacts from rising temperature on inflows to the Murray–Darling Basin, Geophys. Res. Lett., 35, L07701, https://doi.org/10.1029/2008GL033390, 2008.
Chiew, F. H. S., Teng, J., Vaze, J., Post, D. A., Perraud, J. M., Kirono, D. G. C., and Viney, N. R.: Estimating climate change impact on runoff across southeast Australia: method, results, and implications of the modeling method, Water Resour. Res., 45, W10414, https://doi.org/10.1029/2008WR007338, 2009.
Chiew, F. H. S., Young, W. J., Cai, W., and Teng, J.: Current drought and future hydroclimate projections in southeast Australia and implications for water resources management, Stoch. Environ. Res. Risk A., 25, 601–612, https://doi.org/10.1007/s00477-010-0424-x, 2011.
Chiew, F. H. S., Potter, N. J., Vaze, J., Petheram, C., Zhang, L., Teng, J., and Post, D. A.: Observed hydrologic non-stationarity in far south-eastern Australia: implications for modelling and prediction, Stoch. Environ. Res. Risk A., 28, 3–15, 2014.
Cornish, P. M. and Vertessy, R. A.: Forest age-induced changes in evapotranspiration and water yield in a eucalypt forest, J. Hydrol., 242, 43–63, https://doi.org/10.1016/S0022-1694(00)00384-X, 2001.
Crimmins, S. M., Dobrowski, S. Z., Greenberg, J. A., Abatzoglou, J. T., and Mynsberge, A. R.: Changes in climatic water balance drive downhill shifts in plant species' optimum elevations, Science, 331, 324–327, 2011.
Cuo, L., Zhang, Y., Gao, Y., Hao, Z., and Cairang, L.: The impacts of climate change and land cover/use transition on the hydrology in the upper Yellow River Basin, China, J. Hydrol., 502, 37–52, https://doi.org/10.1016/j.jhydrol.2013.08.003, 2013.
Demaria, E. M., Nijssen, B., and Wagener, T.: Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model, J. Geophys. Res., 112, D11113, https://doi.org/10.1029/2006JD007534, 2007.
Ellis, T. W. and Hatton, T. J.: Relating leaf area index of natural eucalypt vegetation to climate variables in southern Australia, Agr. Water Manage., 95, 743–747, https://doi.org/10.1016/j.agwat.2008.02.007, 2008.
Ewert, F.: Modelling plant responses to elevated CO2: how important is leaf area index?, Ann. Bot., 93, 619–627, https://doi.org/10.1093/aob/mch101, 2004.
Food and Agriculture Organization of the United Nations (FAO): Digital soil map of the world, Version 3.5. FAO, Rome, Italy, 1995.
Fernández-Martínez, M., Vicca, S., Janssens, I., Sardans, J., Luyssaert, S., Campioli, M., Chapin III, F., Ciais, P., Malhi, Y., and Obersteiner, M.: Nutrient availability as the key regulator of global forest carbon balance, Nature Climate Change, 4, 471–476, 2014.
Fowler, H. J., Blenkinsop, S., and Tebaldi, C.: Linking climate change modelling to impacts studies: recent advances in downscaling techniques for hydrological modelling, Int. J. Climatol., 27, 1547–1578, https://doi.org/10.1002/joc.1556, 2007.
Ford, T. W. and Quiring, S. M.: Influence of MODIS-Derived Dynamic Vegetation on VIC-Simulated Soil Moisture in Oklahoma, J. Hydrometeorol., 14, 1910–1921, https://doi.org/10.1175/JHM-D-13-037.1, 2013.
Geoscience Australia: GEODATA 9 Second Digital Elevation Model (DEM-9S) Version 3, avaialble at: http://www.ga.gov.au/metadata-gateway/metadata/record/gcat_66006, last access: 20 December 2013, 2008.
Gerten, D., Rost, S., von Bloh, W., and Lucht, W.: Causes of change in 20th century global river discharge, Geophys. Res. Lett., 35, L20405, https://doi.org/10.1029/2008GL035258, 2008.
Harrold, T. I., Jones, R. N, and Watterson, I. G.: Applying climate changes simulated by GCMs to the generation of fine-scale rainfall scenarios, Hydro 2005, 29th Hydrology and Water Resources Symposium, Canberra, 2005.
Heath, J. T., Chafer, C. J., van Ogtrop, F. F., and Bishop, T. F. A.: Post-wildfire recovery of water yield in the Sydney Basin water supply catchments: An assessment of the 2001/2002 wildfires, J. Hydrol., 519, 1428–1440, https://doi.org/10.1016/j.jhydrol.2014.09.033, 2014.
Hikosaka, K., Onoda, Y., Kinugasa, T., Nagashima, H., Anten, N. P. R., and Hirose, T.: Plant responses to elevated CO2 concentration at different scales: leaf, whole plant, canopy, and population, Ecol. Res., 20, 243–253, https://doi.org/10.1007/s11284-005-0041-1, 2005.
Hughes, J. D., Petrone, K. C., and Silberstein, R. P.: Drought, groundwater storage and stream flow decline in southwestern Australia, Geophys. Res. Lett., 39, L03408, https://doi.org/10.1029/2011GL050797, 2012.
Huntington, T. G.: CO2-induced suppression of transpiration cannot explain increasing runoff, Hydrol. Process., 22, 311–314, https://doi.org/10.1002/hyp.6925, 2008.
Jahan, N. and Gan, T. Y.: Modelling the vegetation–climate relationship in a boreal mixedwood forest of Alberta using normalized difference and enhanced vegetation indices, Int. J. Remote Sens., 32, 313–335, https://doi.org/10.1080/01431160903464146, 2011.
Jones, D. A., Wang, W., and Fawcett, R.: High-quality spatial climate data-sets for Australia, Australian Meteorological and Oceanographic Journal, 58, 233–248, 2009.
Kalma, J. D., Bates, B. C., and Woods, R. A.: Predicting catchment-scale soil moisture status with limited field measurements, Hydrol. Process., 9, 445–467, https://doi.org/10.1002/hyp.3360090315, 1995.
Kimball, J. S., Running, S. W., and Nemani, R. R.: An improved method for estimating surface humidity from daily minimum temperature, Agr. Forest Meteorol., 85, 87–98, 1997.
Körner, C.: Plant CO2 responses: an issue of definition, time and resource supply, New Phytol., 172, 393–411, https://doi.org/10.1111/j.1469-8137.2006.01886.x, 2006.
Lenihan, J. M., Drapek, R., Bachelet, D., and Neilson, R. P.: Climate change effects on vegetation distribution, carbon, and fire in California, Ecol. Appl., 13, 1667–1681, 2003.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A Simple hydrologically based model of land surface water and energy fluxes of general circulation models, J. Geophys. Res., 99, 14415–14428, https://doi.org/10.1029/94jd00483, 1994.
Liang, X., Wood, E. F., and Lettenmaier, D. P.: Surface soil moisture parameterization of the VIC-2L model: Evaluation and modification, Global Planet. Change, 13, 195–206, https://doi.org/10.1016/0921-8181(95)00046-1, 1996.
Lockart, N., Kavetski, D., and Franks, S. W.: On the recent warming in the Murray–Darling Basin: land surface interactions misunderstood, Geophys. Res. Lett., 36, L24405, https://doi.org/10.1029/2009GL040598, 2009.
Lockart, N., Kavetski, D., and Franks, S. W.: On the recent warming in the Murray-Darling Basin: Land surface interactions misunderstood, Geophys. Res. Lett., 36, L24405, https://doi.org/10.1029/2009GL040598, 2009.
McMahon, T. A., Peel, M. C., and Karoly, D. J.: Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation, Hydrol. Earth Syst. Sci., 19, 361–377, https://doi.org/10.5194/hess-19-361-2015, 2015.
McVicar, T. R., Van Niel, T. G., Li, L. T., Roderick, M. L., Rayner, D. P., Ricciardulli, L., and Donohue, R. J.: Wind speed climatology and trends for Australia, 1975–2006: Capturing the stilling phenomenon and comparison with near-surface reanalysis output, Geophys. Res. Lett., 35, L20403, https://doi.org/10.1029/2008GL035627, 2008.
Meinshausen, M., Smith, S. J., Calvin, K., Daniel, J. S., Kainuma, M. L. T., Lamarque, J. F., Matsumoto, K., Montzka, S. A., Raper, S. C. B., Riahi, K., Thomson, A., Velders, G. J. M., and van Vuuren, D. P. P.: The RCP greenhouse gas concentrations and their extensions from 1765 to 2300, Climatic Change, 109, 213–241, https://doi.org/10.1007/s10584-011-0156-z, 2011.
Milly, P. C. D., Dunne, K. A., and Vecchia, A. V.: Global pattern of trends in streamflow and water availability in a changing climate, Nature, 438, 347–350, 2005.
Moriasi, D. N., Arnold, J. G., Van Liew, M. W., Bingner, R. L., Harmel, R. D., and Veith, T. L.: Model evaluation guidelines for systematic quantification of accuracy in watershed simulations, T. ASABE, 50, 885–900, 2007.
Moss, R. H., Edmonds, J. A., Hibbard, K. A., Manning, M. R., Rose, S. K., van Vuuren, D. P., Carter, T. R., Emori, S., Kainuma, M., Kram, T., Meehl, G. A., Mitchell, J. F. B., Nakicenovic, N., Riahi, K., Smith, S. J., Stouffer, R. J., Thomson, A. M., Weyant, J. P., and Wilbanks, T. J.: The next generation of scenarios for climate change research and assessment, Nature, 463, 747–756, https://doi.org/10.1038/nature08823, 2010.
Murray, S. J., Foster, P. N., and Prentice, I. C.: Evaluation of global continental hydrology as simulated by the Land-surface Processes and eXchanges Dynamic Global Vegetation Model, Hydrol. Earth Syst. Sci., 15, 91–105, https://doi.org/10.5194/hess-15-91-2011, 2011.
Murray, S. J., Foster, P. N., and Prentice, I. C.: Future global water resources with respect to climate change and water withdrawals as estimated by a dynamic global vegetation model, J. Hydrol., 448–449, 14–29, https://doi.org/10.1016/j.jhydrol.2012.02.044, 2012.
Murray, S. J., Watson, I. M., and Prentice, I. C.: The use of dynamic global vegetation models for simulating hydrology and the potential integration of satellite observations, Prog. Phys. Geog., https://doi.org/10.1177/0309133312460072, 2013.
Nemani, R. R., Keeling C. D., Hashimoto, H., Jolly, W. M., Piper, S. C., Tucker, C. J., Myneni, R. B., and Running, S. W.: Climate-driven increases in global terrestrial net primary production from 1982 to 1999, Science, 300, 1560–1563, 2003.
O'Grady, A. P., Carter, J. L., and Bruce, J.: Can we predict groundwater discharge from terrestrial ecosystems using existing eco-hydrological concepts?, Hydrol. Earth Syst. Sci., 15, 3731–3739, https://doi.org/10.5194/hess-15-3731-2011, 2011.
Obrist, D. and Arnone, J. A.: Increasing CO2 accelerates root growth and enhances water acquisition during early stages of development in Larrea tridentate, New Phytol., 159, 175–184, https://doi.org/10.1046/j.1469-8137.2003.00791.x, 2003.
Palmer, A. R., Fuentes, S., Taylor, D., Macinnis-Ng, C., Zeppel, M., Yunusa, I., and Eamus, D.: Towards a spatial understanding of water use of several land-cover classes: an examination of relationships amongst pre-dawn leaf water potential, vegetation water use, aridity and MODIS LAI, Ecohydrology, 3, 1–10, https://doi.org/10.1002/eco.63, 2010.
Peel, M. C. and Blöschl, G.: Hydrological modelling in a changing world, Prog. Phys. Geogr., 35, 249–261, https://doi.org/10.1177/0309133311402550, 2011.
Piao, S., Friedlingstein, P., Ciais, P., de Noblet-Ducoudré, N., Labat, D., and Zaehle, S.: Changes in climate and land use have a larger direct impact than rising CO2 on global river runoff trends, P. Natl. Acad. Sci. USA, 104, 15242–15247, https://doi.org/10.1073/pnas.0707213104, 2007.
Potter, N. J. and Chiew, F. H. S.: An investigation into changes in climate characteristics causing the recent very low runoff in the southern Murray–Darling Basin using rainfall–runoff models, Water Resour. Res., 47, W00G10, https://doi.org/10.1029/2010WR010333, 2011.
Roderick, M. L. and Farquhar, G. D.: A simple framework for relating variations in runoff to variations in climatic conditions and catchment properties, Water Resour. Res., 47, W00G07, https://doi.org/10.1029/2010WR009826, 2011.
Scheiter, S., Langan, L., and Higgins, S. I.: Next-generation dynamic global vegetation models: learning from community ecology, New Phytol., 198, 957–969, 2013.
Schenk, H. J. and Jackson, R. B.: The global biogeography of roots, Ecol. Monogr., 72, 311–328, 2002.
Taylor, K. E., Stouffer, R. J., and Meehl, G. A.: An overview of CMIP5 and the experiment design, B. Am. Meteorol. Soc., 93, 485–498, https://doi.org/10.1175/BAMS-D-11-00094.1, 2012.
Teng, J., Chiew, F. H. S., Vaze, J., Marvanek, S., and Kirono, D. G. C.: Estimation of climate change impact on mean annual runoff across Continental Australia using Budyko and Fu equations and hydrological models, J. Hydrometeorol., 13, 1094–1106, 2012a.
Teng, J., Vaze, J., Chiew, F. H. S., Wang, B., and Perraud, J.-M.: Estimating the relative uncertainties sourced from GCMs and hydrological models in modeling climate change impact on runoff, J. Hydrometeorol., 13, 122–139, https://doi.org/10.1175/JHM-D-11-058.1, 2012b.
Tesemma, Z. K., Wei, Y., Western, A. W., and Peel, M. C.: Leaf area index variation for cropland, pasture and tree in response to climatic variation in the Goulburn–Broken catchment, Australia, J. Hydrometeorol., 15, 1592–1606, https://doi.org/10.1175/JHM-D-13-0108.1, 2014.
Thornton, P. E. and Running, S. W.: An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation, Agr. Forest Meteorol., 93, 211–228, 1999.
Uddling, J., Teclaw, R. M., Kubiske, M. E., Pregitzer, K. S., and Ellsworth, D. S.: Sap flux in pure aspen and mixed aspen-birch forests exposed to elevated concentrations of carbon dioxide and ozone, Tree Physiol., 28, 1231–1243, 2008.
Vaze, J. and Teng, J.: Future climate and runoff projections across New South Wales, Australia: results and practical applications, Hydrol. Process., 25, 18–35, https://doi.org/10.1002/hyp.7812, 2011.
Vaze, J., Post, D. A., Chiew, F. H. S., Perraud, J. M., Viney, N. R., and Teng, J.: Climate non-stationarity – validity of calibrated rainfall–runoff models for use in climate change studies, J. Hydrol., 394, 447–457, https://doi.org/10.1016/j.jhydrol.2010.09.018, 2010.
Verdon-Kidd, D. C. and Kiem, A. S.: Nature and causes of protracted droughts in southeast Australia: comparison between the Federation, WWII, and Big Dry droughts, Geophys. Res. Lett., 36, L22707, https://doi.org/10.1029/2009GL041067, 2009.
Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., Masui, T., Meinshausen, M., Nakicenovic, N., Smith, S. J., and Rose, S. K.: The representative concentration pathways: an overview, Climatic Change, 109, 5–31, 2011.
Warren, J. M., Norby, R. J., and Wullschleger, S. D.: Elevated CO2 enhances leaf senescence during extreme drought in a temperate forest, Tree Physiol., 31, 117–130, https://doi.org/10.1093/treephys/tpr002, 2011.
Western, A. W., Grayson, R. B., and Green, T. R.: The Tarrawarra project: high resolution spatial measurement, modelling and analysis of soil moisture and hydrological response, Hydrol. Process., 13, 633–652, 1999.
White, D. A., Battaglia, M., Mendham, D. S., Crombie, D. S., Kinal, J. O. E., and McGrath, J. F.: Observed and modelled leaf area index in Eucalyptus globulus plantations: tests of optimality and equilibrium hypotheses, Tree Physiol., 30, 831–844, https://doi.org/10.1093/treephys/tpq037, 2010.
Wullschleger, S. D., Epstein, H. E., Box, E. O., Euskirchen, E. S., Goswami, S., Iversen, C. M., Kattge, J., Norby, R. J., van Bodegom, P. M., and Xu, X.: Plant functional types in Earth System Models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems, Ann. Bot.-London, 114, 1–16, 2014.
Yapo, P. O., Gupta, H. V., and Sorooshian, S.: Multi-objective global optimization for hydrologic models, J. Hydrol., 204, 83–97, https://doi.org/10.1016/S0022-1694(97)00107-8, 1998.
Yu, M., Wang, G., Parr, D., and Ahmed, K.: Future changes of the terrestrial ecosystem based on a dynamic vegetation model driven with RCP8.5 climate projections from 19 GCMs, Clim. Change, 127, 257–271, https://doi.org/10.1007/s10584-014-1249-2, 2014.
Zhao, F., Chiew, F. H. S., Zhang, L., Vaze, J., Perraud, J.-M., and Li, M.: Application of a macroscale hydrologic model to estimate streamflow across southeast Australia, J. Hydrometeorol., 13, 1233–1250, https://doi.org/10.1175/jhm-d-11-0114.1, 2012a.
Zhao, F. F., Xu, Z. X., and Zhang, L.: Changes in streamflow regime following vegetation changes from paired catchments, Hydrol. Process., 26, 1561–1573, https://doi.org/10.1002/hyp.8266, 2012b.
Zhao, R. J., Zhuang, Y. L., Fang, L. R., Liu, X. R., and Zhang, Q. S.: The Xinanjiang Model, Hydrological Forecasting Proceedings Oxford Symposium, IAHS Press, 571 pp., 1980.
