Articles | Volume 26, issue 18
https://doi.org/10.5194/hess-26-4657-2022
© 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-26-4657-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Future snow changes and their impact on the upstream runoff in Salween
Chenhao Chai
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
The University of Chinese Academy of Sciences, Beijing 100049, China
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
The University of Chinese Academy of Sciences, Beijing 100049, China
Deliang Chen
Department of Earth Sciences, University of Gothenburg, Gothenburg
40530, Sweden
Jing Zhou
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
Hu Liu
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
The University of Chinese Academy of Sciences, Beijing 100049, China
Jingtian Zhang
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
The University of Chinese Academy of Sciences, Beijing 100049, China
Yuanwei Wang
School of Geographical Sciences, Nanjing University of Information
Science and Technology, Nanjing 210044, China
School of Geography and Planning, Sun Yat-sen University, Guangzhou
510275, China
Ruishun Liu
State Key Laboratory of Tibetan Plateau Earth System, Resources and
Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy
of Sciences, Beijing 100101, China
The University of Chinese Academy of Sciences, Beijing 100049, China
Related authors
No articles found.
He Sun, Tandong Yao, Fengge Su, Wei Yang, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 4361–4381, https://doi.org/10.5194/hess-28-4361-2024, https://doi.org/10.5194/hess-28-4361-2024, 2024
Short summary
Short summary
Our findings show that runoff in the Yarlung Zangbo (YZ) basin is primarily driven by rainfall, with the largest glacier runoff contribution in the downstream sub-basin. Annual runoff increased in the upper stream but decreased downstream due to varying precipitation patterns. It is expected to rise throughout the 21st century, mainly driven by increased rainfall.
Zengyun Hu, Xi Chen, Deliang Chen, Zhuo Zhang, Qiming Zhou, and Qingxiang Li
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-82, https://doi.org/10.5194/gmd-2024-82, 2024
Preprint withdrawn
Short summary
Short summary
ERC firstly unified the evaluating, ranking, and clustering by a simple mathematic equation based on Euclidean Distance. It provides new system to solve the evaluating, ranking, and clustering tasks in SDGs. In fact, ERC system can be applied in any scientific domain.
Tao Chen, Félicien Meunier, Marc Peaucelle, Guoping Tang, Ye Yuan, and Hans Verbeeck
Biogeosciences, 21, 2253–2272, https://doi.org/10.5194/bg-21-2253-2024, https://doi.org/10.5194/bg-21-2253-2024, 2024
Short summary
Short summary
Chinese subtropical forest ecosystems are an extremely important component of global forest ecosystems and hence crucial for the global carbon cycle and regional climate change. However, there is still great uncertainty in the relationship between subtropical forest carbon sequestration and its drivers. We provide first quantitative estimates of the individual and interactive effects of different drivers on the gross primary productivity changes of various subtropical forest types in China.
Qian Lin, Jie Chen, and Deliang Chen
EGUsphere, https://doi.org/10.5194/egusphere-2024-826, https://doi.org/10.5194/egusphere-2024-826, 2024
Preprint archived
Short summary
Short summary
Glaciers of the Tibetan Plateau (TP) have experienced widespread retreat in recent decades, but impacts of glacier changes that have occurred on regional climate, including precipitation, is still unknown. Thus, this study addressed this knowledge gap, and found that glacier changes exert a more pronounced impact on summer extreme precipitation events than mean precipitation over the TP. This provides a certain theoretical reference for the further improvement of long-term glacier projection.
Fangzhong Shi, Xiaoyan Li, Shaojie Zhao, Yujun Ma, Junqi Wei, Qiwen Liao, and Deliang Chen
Hydrol. Earth Syst. Sci., 28, 163–178, https://doi.org/10.5194/hess-28-163-2024, https://doi.org/10.5194/hess-28-163-2024, 2024
Short summary
Short summary
(1) Evaporation under ice-free and sublimation under ice-covered conditions and its influencing factors were first quantified based on 6 years of eddy covariance observations. (2) Night evaporation of Qinghai Lake accounts for more than 40 % of the daily evaporation. (3) Lake ice sublimation reaches 175.22 ± 45.98 mm, accounting for 23 % of the annual evaporation. (4) Wind speed weakening may have resulted in a 7.56 % decrease in lake evaporation during the ice-covered period from 2003 to 2017.
John Erik Engström, Lennart Wern, Sverker Hellström, Erik Kjellström, Chunlüe Zhou, Deliang Chen, and Cesar Azorin-Molina
Earth Syst. Sci. Data, 15, 2259–2277, https://doi.org/10.5194/essd-15-2259-2023, https://doi.org/10.5194/essd-15-2259-2023, 2023
Short summary
Short summary
Newly digitized wind speed observations provide data from the time period from around 1920 to the present, enveloping one full century of wind measurements. The results of this work enable the investigation of the historical variability and trends in surface wind speed in Sweden for
the last century.
He Sun, Tandong Yao, Fengge Su, Wei Yang, Guifeng Huang, and Deliang Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-16, https://doi.org/10.5194/hess-2023-16, 2023
Manuscript not accepted for further review
Short summary
Short summary
Based on field research campaigns since 2017 in the Yarlung Zangbo (YZ) river basin and a well-validated model, our results reveal that large regional differences in runoff regimes and changes exist in the basin. Annual runoff shows decreasing trend in the downstream sub-basin but increasing trends in the upper and middle sub-basins, due to opposing precipitation changes. Glacier runoff plays more important role in annual total runoff in downstream basin.
Hao Li, Baoying Shan, Liu Liu, Lei Wang, Akash Koppa, Feng Zhong, Dongfeng Li, Xuanxuan Wang, Wenfeng Liu, Xiuping Li, and Zongxue Xu
Hydrol. Earth Syst. Sci., 26, 6399–6412, https://doi.org/10.5194/hess-26-6399-2022, https://doi.org/10.5194/hess-26-6399-2022, 2022
Short summary
Short summary
This study examines changes in water yield by determining turning points in the direction of yield changes and highlights that regime shifts in historical water yield occurred in the Upper Brahmaputra River basin, both the climate and cryosphere affect the magnitude of water yield increases, climate determined the declining trends in water yield, and meltwater has the potential to alleviate the water shortage. A repository for all source files is made available.
Jianting Zhao, Lin Zhao, Zhe Sun, Fujun Niu, Guojie Hu, Defu Zou, Guangyue Liu, Erji Du, Chong Wang, Lingxiao Wang, Yongping Qiao, Jianzong Shi, Yuxin Zhang, Junqiang Gao, Yuanwei Wang, Yan Li, Wenjun Yu, Huayun Zhou, Zanpin Xing, Minxuan Xiao, Luhui Yin, and Shengfeng Wang
The Cryosphere, 16, 4823–4846, https://doi.org/10.5194/tc-16-4823-2022, https://doi.org/10.5194/tc-16-4823-2022, 2022
Short summary
Short summary
Permafrost has been warming and thawing globally; this is especially true in boundary regions. We focus on the changes and variability in permafrost distribution and thermal dynamics in the northern limit of permafrost on the Qinghai–Tibet Plateau (QTP) by applying a new permafrost model. Unlike previous papers on this topic, our findings highlight a slow, decaying process in the response of permafrost in the QTP to a warming climate, especially regarding areal extent.
Changgui Lin, Erik Kjellström, Renate Anna Irma Wilcke, and Deliang Chen
Earth Syst. Dynam., 13, 1197–1214, https://doi.org/10.5194/esd-13-1197-2022, https://doi.org/10.5194/esd-13-1197-2022, 2022
Short summary
Short summary
This study endorses RCMs' added value on the driving GCMs in representing observed heat wave magnitudes. The future increase of heat wave magnitudes projected by GCMs is attenuated when downscaled by RCMs. Within the downscaling, uncertainties can be attributed almost equally to choice of RCMs and to the driving data associated with different GCMs. Uncertainties of GCMs in simulating heat wave magnitudes are transformed by RCMs in a complex manner rather than simply inherited.
Chunlüe Zhou, Cesar Azorin-Molina, Erik Engström, Lorenzo Minola, Lennart Wern, Sverker Hellström, Jessika Lönn, and Deliang Chen
Earth Syst. Sci. Data, 14, 2167–2177, https://doi.org/10.5194/essd-14-2167-2022, https://doi.org/10.5194/essd-14-2167-2022, 2022
Short summary
Short summary
To fill the key gap of short availability and inhomogeneity of wind speed (WS) in Sweden, we rescued the early paper records of WS since 1925 and built the first 10-member centennial homogenized WS dataset (HomogWS-se) for community use. An initial WS stilling and recovery before the 1990s was observed, and a strong link with North Atlantic Oscillation was found. HomogWS-se improves our knowledge of uncertainty and causes of historical WS changes.
Xiangde Xu, Chan Sun, Deliang Chen, Tianliang Zhao, Jianjun Xu, Shengjun Zhang, Juan Li, Bin Chen, Yang Zhao, Hongxiong Xu, Lili Dong, Xiaoyun Sun, and Yan Zhu
Atmos. Chem. Phys., 22, 1149–1157, https://doi.org/10.5194/acp-22-1149-2022, https://doi.org/10.5194/acp-22-1149-2022, 2022
Short summary
Short summary
A vertical transport window of tropospheric vapor exists on the Tibetan Plateau (TP). The TP's thermal forcing drives the vertical transport
windowof vapor in the troposphere. The effects of the TP's vertical transport window of vapor are of importance in global climate change.
Yuanwei Wang, Lei Wang, Xiuping Li, Jing Zhou, and Zhidan Hu
Earth Syst. Sci. Data, 12, 1789–1803, https://doi.org/10.5194/essd-12-1789-2020, https://doi.org/10.5194/essd-12-1789-2020, 2020
Short summary
Short summary
This article is to provide a better precipitation product for the largest river basin of the Tibetan Plateau, the upper Brahmaputra River basin, suitable for use in hydrological simulations and other climate change studies. We integrate gauge, satellite, and reanalysis precipitation datasets to generate a new dataset. The new product has been rigorously validated at various temporal and spatial scales with gauge precipitation observations as well as in cryosphere hydrological simulations.
Chaehyeon C. Nam, Doo-Sun R. Park, Chang-Hoi Ho, and Deliang Chen
Nat. Hazards Earth Syst. Sci., 18, 3225–3234, https://doi.org/10.5194/nhess-18-3225-2018, https://doi.org/10.5194/nhess-18-3225-2018, 2018
Short summary
Short summary
This study shows that a small deviation of the tropical cyclone (TC) track in the west–east direction (less than 250 km smaller than the average radius of the TC) has a more dominant effect on the extent and distribution of TC damage than TC intensity or size. This suggests that track information should be considered more carefully in assessments of future TC risk.
Kristina Seftigen, Hugues Goosse, Francois Klein, and Deliang Chen
Clim. Past, 13, 1831–1850, https://doi.org/10.5194/cp-13-1831-2017, https://doi.org/10.5194/cp-13-1831-2017, 2017
Short summary
Short summary
Comparisons of proxy data to GCM-simulated hydroclimate are still limited and inter-model variability remains poorly characterized. In this study, we bring together tree-ring paleoclimate evidence and CMIP5–PMIP3 model simulations of the last millennium hydroclimate variability across Scandinavia. We explore the consistency between the datasets and the role of external forcing versus internal variability in driving the hydroclimate changes regionally.
Chi Zhang, Qiuhong Tang, Deliang Chen, Laifang Li, Xingcai Liu, and Huijuan Cui
Atmos. Chem. Phys., 17, 10383–10393, https://doi.org/10.5194/acp-17-10383-2017, https://doi.org/10.5194/acp-17-10383-2017, 2017
Short summary
Short summary
Precipitation over Southwest China (SWC) has decreased significantly in recent years. By tracking precipitation moisture, we found that the reduced precipitation results from the reduced moisture supply from the extended west, which is influenced by the South Asian summer monsoon and the westerlies. Further study revealed the dynamic variations in circulation dominate the interannual variations in SWC precipitation. Changes in circulation systems may be related to the recent changes in SSTs.
Peng Zhang, Hans W. Linderholm, Björn E. Gunnarson, Jesper Björklund, and Deliang Chen
Clim. Past, 12, 1297–1312, https://doi.org/10.5194/cp-12-1297-2016, https://doi.org/10.5194/cp-12-1297-2016, 2016
Short summary
Short summary
We present C-Scan, a new Scots pine tree-ring density based reconstruction of warm-season (April-September) temperatures for central Scandinavia back to 850 CE, extending the previous reconstruction by 250 years. Our reconstruction indicates that the warm-season warmth during a relatively-warm period of last millennium is not so pronounced in central Scandinavia, which adds further detail to our knowledge about the spatial pattern of surface air temperature on the regional scale.
M. S. Johnston, G. Holl, J. Hocking, S. J. Cooper, and D. Chen
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-11753-2015, https://doi.org/10.5194/amtd-8-11753-2015, 2015
Preprint withdrawn
M. Shrestha, L. Wang, T. Koike, H. Tsutsui, Y. Xue, and Y. Hirabayashi
Hydrol. Earth Syst. Sci., 18, 747–761, https://doi.org/10.5194/hess-18-747-2014, https://doi.org/10.5194/hess-18-747-2014, 2014
Related subject area
Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Hybrid hydrological modeling for large alpine basins: a semi-distributed approach
Karst aquifer discharge response to rainfall interpreted as anomalous transport
HESS Opinions: Never train a Long Short-Term Memory (LSTM) network on a single basin
Large-sample hydrology – a few camels or a whole caravan?
Comment on “Are soils overrated in hydrology?” by Gao et al. (2023)
Multi-decadal fluctuations in root zone storage capacity through vegetation adaptation to hydro-climatic variability have minor effects on the hydrological response in the Neckar River basin, Germany
Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China
On the importance of plant phenology in the evaporative process of a semi-arid woodland: could it be why satellite-based evaporation estimates in the miombo differ?
Regionalization of GR4J model parameters for river flow prediction in Paraná, Brazil
Evolution of river regimes in the Mekong River basin over 8 decades and the role of dams in recent hydrological extremes
Skill of seasonal flow forecasts at catchment scale: an assessment across South Korea
To what extent do flood-inducing storm events change future flood hazards?
When ancient numerical demons meet physics-informed machine learning: adjoint-based gradients for implicit differentiable modeling
Assessing the impact of climate change on high return levels of peak flows in Bavaria applying the CRCM5 large ensemble
Impacts of climate and land surface change on catchment evapotranspiration and runoff from 1951 to 2020 in Saxony, Germany
Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method
Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada
To bucket or not to bucket? Analyzing the performance and interpretability of hybrid hydrological models with dynamic parameterization
Widespread flooding dynamics under climate change: characterising floods using grid-based hydrological modelling and regional climate projections
HESS Opinions: The sword of Damocles of the impossible flood
Metamorphic testing of machine learning and conceptual hydrologic models
The influence of human activities on streamflow reductions during the megadrought in central Chile
Elevational control of isotopic composition and application in understanding hydrologic processes in the mid Merced River catchment, Sierra Nevada, California, USA
Enhancing long short-term memory (LSTM)-based streamflow prediction with a spatially distributed approach
Broadleaf afforestation impacts on terrestrial hydrology insignificant compared to climate change in Great Britain
Impacts of spatiotemporal resolutions of precipitation on flood event simulation based on multimodel structures – a case study over the Xiang River basin in China
A network approach for multiscale catchment classification using traits
Multi-model approach in a variable spatial framework for streamflow simulation
Advancing understanding of lake–watershed hydrology: a fully coupled numerical model illustrated by Qinghai Lake
Technical note: Testing the connection between hillslope-scale runoff fluctuations and streamflow hydrographs at the outlet of large river basins
Empirical stream thermal sensitivity cluster on the landscape according to geology and climate
Multi-scale soil moisture data and process-based modeling reveal the importance of lateral groundwater flow in a subarctic catchment
Deep learning for monthly rainfall–runoff modelling: a large-sample comparison with conceptual models across Australia
On optimization of calibrations of a distributed hydrological model with spatially distributed information on snow
Toward interpretable LSTM-based modeling of hydrological systems
Vegetation Response to Climatic Variability: Implications for Root Zone Storage and Streamflow Predictions
Flow intermittence prediction using a hybrid hydrological modelling approach: influence of observed intermittence data on the training of a random forest model
What controls the tail behaviour of flood series: rainfall or runoff generation?
Learning Landscape Features from Streamflow with Autoencoders
Seasonal prediction of end-of-dry-season watershed behavior in a highly interconnected alluvial watershed in northern California
Glaciers determine the sensitivity of hydrological processes to perturbed climate in a large mountainous basin on the Tibetan Plateau
Leveraging gauge networks and strategic discharge measurements to aid the development of continuous streamflow records
On the need for physical constraints in deep learning rainfall–runoff projections under climate change: a sensitivity analysis to warming and shifts in potential evapotranspiration
Evaluation of hydrological models on small mountainous catchments: impact of the meteorological forcings
Projecting sediment export from two highly glacierized alpine catchments under climate change: exploring non-parametric regression as an analysis tool
Simulation-Based Inference for Parameter Estimation of Complex Watershed Simulators
A framework for parameter estimation, sensitivity analysis, and uncertainty analysis for holistic hydrologic modeling using SWAT+
On understanding mountainous carbonate basins of the Mediterranean using parsimonious modeling solutions
Comparing quantile regression forest and mixture density long short-term memory models for probabilistic post-processing of satellite precipitation-driven streamflow simulations
Recent ground thermo-hydrological changes in a southern Tibetan endorheic catchment and implications for lake level changes
Bu Li, Ting Sun, Fuqiang Tian, Mahmut Tudaji, Li Qin, and Guangheng Ni
Hydrol. Earth Syst. Sci., 28, 4521–4538, https://doi.org/10.5194/hess-28-4521-2024, https://doi.org/10.5194/hess-28-4521-2024, 2024
Short summary
Short summary
This paper developed hybrid semi-distributed hydrological models by employing a process-based model as the backbone and utilizing deep learning to parameterize and replace internal modules. The main contribution is to provide a high-performance tool enriched with explicit hydrological knowledge for hydrological prediction and to improve understanding about the hydrological sensitivities to climate change in large alpine basins.
Dan Elhanati, Nadine Goeppert, and Brian Berkowitz
Hydrol. Earth Syst. Sci., 28, 4239–4249, https://doi.org/10.5194/hess-28-4239-2024, https://doi.org/10.5194/hess-28-4239-2024, 2024
Short summary
Short summary
A continuous time random walk framework was developed to allow modeling of a karst aquifer discharge response to measured rainfall. The application of the numerical model yielded robust fits between modeled and measured discharge values, especially for the distinctive long tails found during recession times. The findings shed light on the interplay of slow and fast flow in the karst system and establish the application of the model for simulating flow and transport in such systems.
Frederik Kratzert, Martin Gauch, Daniel Klotz, and Grey Nearing
Hydrol. Earth Syst. Sci., 28, 4187–4201, https://doi.org/10.5194/hess-28-4187-2024, https://doi.org/10.5194/hess-28-4187-2024, 2024
Short summary
Short summary
Recently, a special type of neural-network architecture became increasingly popular in hydrology literature. However, in most applications, this model was applied as a one-to-one replacement for hydrology models without adapting or rethinking the experimental setup. In this opinion paper, we show how this is almost always a bad decision and how using these kinds of models requires the use of large-sample hydrology data sets.
Franziska Clerc-Schwarzenbach, Giovanni Selleri, Mattia Neri, Elena Toth, Ilja van Meerveld, and Jan Seibert
Hydrol. Earth Syst. Sci., 28, 4219–4237, https://doi.org/10.5194/hess-28-4219-2024, https://doi.org/10.5194/hess-28-4219-2024, 2024
Short summary
Short summary
We show that the differences between the forcing data included in three CAMELS datasets (US, BR, GB) and the forcing data included for the same catchments in the Caravan dataset affect model calibration considerably. The model performance dropped when the data from the Caravan dataset were used instead of the original data. Most of the model performance drop could be attributed to the differences in precipitation data. However, differences were largest for the potential evapotranspiration data.
Ying Zhao, Mehdi Rahmati, Harry Vereecken, and Dani Or
Hydrol. Earth Syst. Sci., 28, 4059–4063, https://doi.org/10.5194/hess-28-4059-2024, https://doi.org/10.5194/hess-28-4059-2024, 2024
Short summary
Short summary
Gao et al. (2023) question the importance of soil in hydrology, sparking debate. We acknowledge some valid points but critique their broad, unsubstantiated views on soil's role. Our response highlights three key areas: (1) the false divide between ecosystem-centric and soil-centric approaches, (2) the vital yet varied impact of soil properties, and (3) the call for a scale-aware framework. We aim to unify these perspectives, enhancing hydrology's comprehensive understanding.
Siyuan Wang, Markus Hrachowitz, and Gerrit Schoups
Hydrol. Earth Syst. Sci., 28, 4011–4033, https://doi.org/10.5194/hess-28-4011-2024, https://doi.org/10.5194/hess-28-4011-2024, 2024
Short summary
Short summary
Root zone storage capacity (Sumax) changes significantly over multiple decades, reflecting vegetation adaptation to climatic variability. However, this temporal evolution of Sumax cannot explain long-term fluctuations in the partitioning of water fluxes as expressed by deviations ΔIE from the parametric Budyko curve over time with different climatic conditions, and it does not have any significant effects on shorter-term hydrological response characteristics of the upper Neckar catchment.
Zehua Chang, Hongkai Gao, Leilei Yong, Kang Wang, Rensheng Chen, Chuntan Han, Otgonbayar Demberel, Batsuren Dorjsuren, Shugui Hou, and Zheng Duan
Hydrol. Earth Syst. Sci., 28, 3897–3917, https://doi.org/10.5194/hess-28-3897-2024, https://doi.org/10.5194/hess-28-3897-2024, 2024
Short summary
Short summary
An integrated cryospheric–hydrologic model, FLEX-Cryo, was developed that considers glaciers, snow cover, and frozen soil and their dynamic impacts on hydrology. We utilized it to simulate future changes in cryosphere and hydrology in the Hulu catchment. Our projections showed the two glaciers will melt completely around 2050, snow cover will reduce, and permafrost will degrade. For hydrology, runoff will decrease after the glacier has melted, and permafrost degradation will increase baseflow.
Henry M. Zimba, Miriam Coenders-Gerrits, Kawawa E. Banda, Petra Hulsman, Nick van de Giesen, Imasiku A. Nyambe, and Hubert H. G. Savenije
Hydrol. Earth Syst. Sci., 28, 3633–3663, https://doi.org/10.5194/hess-28-3633-2024, https://doi.org/10.5194/hess-28-3633-2024, 2024
Short summary
Short summary
The fall and flushing of new leaves in the miombo woodlands co-occur in the dry season before the commencement of seasonal rainfall. The miombo species are also said to have access to soil moisture in deep soils, including groundwater in the dry season. Satellite-based evaporation estimates, temporal trends, and magnitudes differ the most in the dry season, most likely due to inadequate understanding and representation of the highlighted miombo species attributes in simulations.
Louise Akemi Kuana, Arlan Scortegagna Almeida, Emílio Graciliano Ferreira Mercuri, and Steffen Manfred Noe
Hydrol. Earth Syst. Sci., 28, 3367–3390, https://doi.org/10.5194/hess-28-3367-2024, https://doi.org/10.5194/hess-28-3367-2024, 2024
Short summary
Short summary
The authors compared regionalization methods for river flow prediction in 126 catchments from the south of Brazil, a region with humid subtropical and hot temperate climate. The regionalization method based on physiographic–climatic similarity had the best performance for predicting daily and Q95 reference flow. We showed that basins without flow monitoring can have a good approximation of streamflow using machine learning and physiographic–climatic information as inputs.
Huy Dang and Yadu Pokhrel
Hydrol. Earth Syst. Sci., 28, 3347–3365, https://doi.org/10.5194/hess-28-3347-2024, https://doi.org/10.5194/hess-28-3347-2024, 2024
Short summary
Short summary
By examining basin-wide simulations of a river regime over 83 years with and without dams, we present evidence that climate variation was a key driver of hydrologic variabilities in the Mekong River basin (MRB) over the long term; however, dams have largely altered the seasonality of the Mekong’s flow regime and annual flooding patterns in major downstream areas in recent years. These findings could help us rethink the planning of future dams and water resource management in the MRB.
Yongshin Lee, Francesca Pianosi, Andres Peñuela, and Miguel Angel Rico-Ramirez
Hydrol. Earth Syst. Sci., 28, 3261–3279, https://doi.org/10.5194/hess-28-3261-2024, https://doi.org/10.5194/hess-28-3261-2024, 2024
Short summary
Short summary
Following recent advancements in weather prediction technology, we explored how seasonal weather forecasts (1 or more months ahead) could benefit practical water management in South Korea. Our findings highlight that using seasonal weather forecasts for predicting flow patterns 1 to 3 months ahead is effective, especially during dry years. This suggest that seasonal weather forecasts can be helpful in improving the management of water resources.
Mariam Khanam, Giulia Sofia, and Emmanouil N. Anagnostou
Hydrol. Earth Syst. Sci., 28, 3161–3190, https://doi.org/10.5194/hess-28-3161-2024, https://doi.org/10.5194/hess-28-3161-2024, 2024
Short summary
Short summary
Flooding worsens due to climate change, with river dynamics being a key in local flood control. Predicting post-storm geomorphic changes is challenging. Using self-organizing maps and machine learning, this study forecasts post-storm alterations in stage–discharge relationships across 3101 US stream gages. The provided framework can aid in updating hazard assessments by identifying rivers prone to change, integrating channel adjustments into flood hazard assessment.
Yalan Song, Wouter J. M. Knoben, Martyn P. Clark, Dapeng Feng, Kathryn Lawson, Kamlesh Sawadekar, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 3051–3077, https://doi.org/10.5194/hess-28-3051-2024, https://doi.org/10.5194/hess-28-3051-2024, 2024
Short summary
Short summary
Differentiable models (DMs) integrate neural networks and physical equations for accuracy, interpretability, and knowledge discovery. We developed an adjoint-based DM for ordinary differential equations (ODEs) for hydrological modeling, reducing distorted fluxes and physical parameters from errors in models that use explicit and operation-splitting schemes. With a better numerical scheme and improved structure, the adjoint-based DM matches or surpasses long short-term memory (LSTM) performance.
Florian Willkofer, Raul R. Wood, and Ralf Ludwig
Hydrol. Earth Syst. Sci., 28, 2969–2989, https://doi.org/10.5194/hess-28-2969-2024, https://doi.org/10.5194/hess-28-2969-2024, 2024
Short summary
Short summary
Severe flood events pose a threat to riverine areas, yet robust estimates of the dynamics of these events in the future due to climate change are rarely available. Hence, this study uses data from a regional climate model, SMILE, to drive a high-resolution hydrological model for 98 catchments of hydrological Bavaria and exploits the large database to derive robust values for the 100-year flood events. Results indicate an increase in frequency and intensity for most catchments in the future.
Maik Renner and Corina Hauffe
Hydrol. Earth Syst. Sci., 28, 2849–2869, https://doi.org/10.5194/hess-28-2849-2024, https://doi.org/10.5194/hess-28-2849-2024, 2024
Short summary
Short summary
Climate and land surface changes influence the partitioning of water balance components decisively. Their impact is quantified for 71 catchments in Saxony. Germany. Distinct signatures in the joint water and energy budgets are found: (i) past forest dieback caused a decrease in and subsequent recovery of evapotranspiration in the affected regions, and (ii) the recent shift towards higher aridity imposed a large decline in runoff that has not been seen in the observation records before.
Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 28, 2809–2829, https://doi.org/10.5194/hess-28-2809-2024, https://doi.org/10.5194/hess-28-2809-2024, 2024
Short summary
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Mazda Kompanizare, Diogo Costa, Merrin L. Macrae, John W. Pomeroy, and Richard M. Petrone
Hydrol. Earth Syst. Sci., 28, 2785–2807, https://doi.org/10.5194/hess-28-2785-2024, https://doi.org/10.5194/hess-28-2785-2024, 2024
Short summary
Short summary
A new agricultural tile drainage module was developed in the Cold Region Hydrological Model platform. Tile flow and water levels are simulated by considering the effect of capillary fringe thickness, drainable water and seasonal regional groundwater dynamics. The model was applied to a small well-instrumented farm in southern Ontario, Canada, where there are concerns about the impacts of agricultural drainage into Lake Erie.
Eduardo Acuña Espinoza, Ralf Loritz, Manuel Álvarez Chaves, Nicole Bäuerle, and Uwe Ehret
Hydrol. Earth Syst. Sci., 28, 2705–2719, https://doi.org/10.5194/hess-28-2705-2024, https://doi.org/10.5194/hess-28-2705-2024, 2024
Short summary
Short summary
Hydrological hybrid models promise to merge the performance of deep learning methods with the interpretability of process-based models. One hybrid approach is the dynamic parameterization of conceptual models using long short-term memory (LSTM) networks. We explored this method to evaluate the effect of the flexibility given by LSTMs on the process-based part.
Adam Griffin, Alison L. Kay, Paul Sayers, Victoria Bell, Elizabeth Stewart, and Sam Carr
Hydrol. Earth Syst. Sci., 28, 2635–2650, https://doi.org/10.5194/hess-28-2635-2024, https://doi.org/10.5194/hess-28-2635-2024, 2024
Short summary
Short summary
Widespread flooding is a major problem in the UK and is greatly affected by climate change and land-use change. To look at how widespread flooding changes in the future, climate model data (UKCP18) were used with a hydrological model (Grid-to-Grid) across the UK, and 14 400 events were identified between two time slices: 1980–2010 and 2050–2080. There was a strong increase in the number of winter events in the future time slice and in the peak return periods.
Alberto Montanari, Bruno Merz, and Günter Blöschl
Hydrol. Earth Syst. Sci., 28, 2603–2615, https://doi.org/10.5194/hess-28-2603-2024, https://doi.org/10.5194/hess-28-2603-2024, 2024
Short summary
Short summary
Floods often take communities by surprise, as they are often considered virtually
impossibleyet are an ever-present threat similar to the sword suspended over the head of Damocles in the classical Greek anecdote. We discuss four reasons why extremely large floods carry a risk that is often larger than expected. We provide suggestions for managing the risk of megafloods by calling for a creative exploration of hazard scenarios and communicating the unknown corners of the reality of floods.
Peter Reichert, Kai Ma, Marvin Höge, Fabrizio Fenicia, Marco Baity-Jesi, Dapeng Feng, and Chaopeng Shen
Hydrol. Earth Syst. Sci., 28, 2505–2529, https://doi.org/10.5194/hess-28-2505-2024, https://doi.org/10.5194/hess-28-2505-2024, 2024
Short summary
Short summary
We compared the predicted change in catchment outlet discharge to precipitation and temperature change for conceptual and machine learning hydrological models. We found that machine learning models, despite providing excellent fit and prediction capabilities, can be unreliable regarding the prediction of the effect of temperature change for low-elevation catchments. This indicates the need for caution when applying them for the prediction of the effect of climate change.
Nicolás Álamos, Camila Alvarez-Garreton, Ariel Muñoz, and Álvaro González-Reyes
Hydrol. Earth Syst. Sci., 28, 2483–2503, https://doi.org/10.5194/hess-28-2483-2024, https://doi.org/10.5194/hess-28-2483-2024, 2024
Short summary
Short summary
In this study, we assess the effects of climate and water use on streamflow reductions and drought intensification during the last 3 decades in central Chile. We address this by contrasting streamflow observations with near-natural streamflow simulations. We conclude that while the lack of precipitation dominates streamflow reductions in the megadrought, water uses have not diminished during this time, causing a worsening of the hydrological drought conditions and maladaptation conditions.
Fengjing Liu, Martha H. Conklin, and Glenn D. Shaw
Hydrol. Earth Syst. Sci., 28, 2239–2258, https://doi.org/10.5194/hess-28-2239-2024, https://doi.org/10.5194/hess-28-2239-2024, 2024
Short summary
Short summary
Mountain snowpack has been declining and more precipitation falls as rain than snow. Using stable isotopes, we found flows and flow duration in Yosemite Creek are most sensitive to climate warming due to strong evaporation of waterfalls, potentially lengthening the dry-up period of waterfalls in summer and negatively affecting tourism. Groundwater recharge in Yosemite Valley is primarily from the upper snow–rain transition (2000–2500 m) and very vulnerable to a reduction in the snow–rain ratio.
Qiutong Yu, Bryan A. Tolson, Hongren Shen, Ming Han, Juliane Mai, and Jimmy Lin
Hydrol. Earth Syst. Sci., 28, 2107–2122, https://doi.org/10.5194/hess-28-2107-2024, https://doi.org/10.5194/hess-28-2107-2024, 2024
Short summary
Short summary
It is challenging to incorporate input variables' spatial distribution information when implementing long short-term memory (LSTM) models for streamflow prediction. This work presents a novel hybrid modelling approach to predict streamflow while accounting for spatial variability. We evaluated the performance against lumped LSTM predictions in 224 basins across the Great Lakes region in North America. This approach shows promise for predicting streamflow in large, ungauged basin.
Marcus Buechel, Louise Slater, and Simon Dadson
Hydrol. Earth Syst. Sci., 28, 2081–2105, https://doi.org/10.5194/hess-28-2081-2024, https://doi.org/10.5194/hess-28-2081-2024, 2024
Short summary
Short summary
Afforestation has been proposed internationally, but the hydrological implications of such large increases in the spatial extent of woodland are not fully understood. In this study, we use a land surface model to simulate hydrology across Great Britain with realistic afforestation scenarios and potential climate changes. Countrywide afforestation minimally influences hydrology, when compared to climate change, and reduces low streamflow whilst not lowering the highest flows.
Qian Zhu, Xiaodong Qin, Dongyang Zhou, Tiantian Yang, and Xinyi Song
Hydrol. Earth Syst. Sci., 28, 1665–1686, https://doi.org/10.5194/hess-28-1665-2024, https://doi.org/10.5194/hess-28-1665-2024, 2024
Short summary
Short summary
Input data, model and calibration strategy can affect the accuracy of flood event simulation and prediction. Satellite-based precipitation with different spatiotemporal resolutions is an important input source. Data-driven models are sometimes proven to be more accurate than hydrological models. Event-based calibration and conventional strategy are two options adopted for flood simulation. This study targets the three concerns for accurate flood event simulation and prediction.
Fabio Ciulla and Charuleka Varadharajan
Hydrol. Earth Syst. Sci., 28, 1617–1651, https://doi.org/10.5194/hess-28-1617-2024, https://doi.org/10.5194/hess-28-1617-2024, 2024
Short summary
Short summary
We present a new method based on network science for unsupervised classification of large datasets and apply it to classify 9067 US catchments and 274 biophysical traits at multiple scales. We find that our trait-based approach produces catchment classes with distinct streamflow behavior and that spatial patterns emerge amongst pristine and human-impacted catchments. This method can be widely used beyond hydrology to identify patterns, reduce trait redundancy, and select representative sites.
Cyril Thébault, Charles Perrin, Vazken Andréassian, Guillaume Thirel, Sébastien Legrand, and Olivier Delaigue
Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, https://doi.org/10.5194/hess-28-1539-2024, 2024
Short summary
Short summary
Streamflow forecasting is useful for many applications, ranging from population safety (e.g. floods) to water resource management (e.g. agriculture or hydropower). To this end, hydrological models must be optimized. However, a model is inherently wrong. This study aims to analyse the contribution of a multi-model approach within a variable spatial framework to improve streamflow simulations. The underlying idea is to take advantage of the strength of each modelling framework tested.
Lele Shu, Xiaodong Li, Yan Chang, Xianhong Meng, Hao Chen, Yuan Qi, Hongwei Wang, Zhaoguo Li, and Shihua Lyu
Hydrol. Earth Syst. Sci., 28, 1477–1491, https://doi.org/10.5194/hess-28-1477-2024, https://doi.org/10.5194/hess-28-1477-2024, 2024
Short summary
Short summary
We developed a new model to better understand how water moves in a lake basin. Our model improves upon previous methods by accurately capturing the complexity of water movement, both on the surface and subsurface. Our model, tested using data from China's Qinghai Lake, accurately replicates complex water movements and identifies contributing factors of the lake's water balance. The findings provide a robust tool for predicting hydrological processes, aiding water resource planning.
Ricardo Mantilla, Morgan Fonley, and Nicolás Velásquez
Hydrol. Earth Syst. Sci., 28, 1373–1382, https://doi.org/10.5194/hess-28-1373-2024, https://doi.org/10.5194/hess-28-1373-2024, 2024
Short summary
Short summary
Hydrologists strive to “Be right for the right reasons” when modeling the hydrologic cycle; however, the datasets available to validate hydrological models are sparse, and in many cases, they comprise streamflow observations at the outlets of large catchments. In this work, we show that matching streamflow observations at the outlet of a large basin is not a reliable indicator of a correct description of the small-scale runoff processes.
Lillian M. McGill, E. Ashley Steel, and Aimee H. Fullerton
Hydrol. Earth Syst. Sci., 28, 1351–1371, https://doi.org/10.5194/hess-28-1351-2024, https://doi.org/10.5194/hess-28-1351-2024, 2024
Short summary
Short summary
This study examines the relationship between air and river temperatures in Washington's Snoqualmie and Wenatchee basins. We used classification and regression approaches to show that the sensitivity of river temperature to air temperature is variable across basins and controlled largely by geology and snowmelt. Findings can be used to inform strategies for river basin restoration and conservation, such as identifying climate-insensitive areas of the basin that should be preserved and protected.
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. Discuss., https://doi.org/10.5194/hess-2024-81, https://doi.org/10.5194/hess-2024-81, 2024
Revised manuscript accepted for HESS
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.
Stephanie R. Clark, Julien Lerat, Jean-Michel Perraud, and Peter Fitch
Hydrol. Earth Syst. Sci., 28, 1191–1213, https://doi.org/10.5194/hess-28-1191-2024, https://doi.org/10.5194/hess-28-1191-2024, 2024
Short summary
Short summary
To determine if deep learning models are in general a viable alternative to traditional hydrologic modelling techniques in Australian catchments, a comparison of river–runoff predictions is made between traditional conceptual models and deep learning models in almost 500 catchments spread over the continent. It is found that the deep learning models match or outperform the traditional models in over two-thirds of the river catchments, indicating feasibility in a wide variety of conditions.
Dipti Tiwari, Mélanie Trudel, and Robert Leconte
Hydrol. Earth Syst. Sci., 28, 1127–1146, https://doi.org/10.5194/hess-28-1127-2024, https://doi.org/10.5194/hess-28-1127-2024, 2024
Short summary
Short summary
Calibrating hydrological models with multi-objective functions enhances model robustness. By using spatially distributed snow information in the calibration, the model performance can be enhanced without compromising the outputs. In this study the HYDROTEL model was calibrated in seven different experiments, incorporating the SPAEF (spatial efficiency) metric alongside Nash–Sutcliffe efficiency (NSE) and root-mean-square error (RMSE), with the aim of identifying the optimal calibration strategy.
Luis Andres De la Fuente, Mohammad Reza Ehsani, Hoshin Vijai Gupta, and Laura Elizabeth Condon
Hydrol. Earth Syst. Sci., 28, 945–971, https://doi.org/10.5194/hess-28-945-2024, https://doi.org/10.5194/hess-28-945-2024, 2024
Short summary
Short summary
Long short-term memory (LSTM) is a widely used machine-learning model in hydrology, but it is difficult to extract knowledge from it. We propose HydroLSTM, which represents processes like a hydrological reservoir. Models based on HydroLSTM perform similarly to LSTM while requiring fewer cell states. The learned parameters are informative about the dominant hydrology of a catchment. Our results show how parsimony and hydrological knowledge extraction can be achieved by using the new structure.
Nienke Tessa Tempel, Laurene Bouaziz, Riccardo Taormina, Ellis van Noppen, Jasper Stam, Eric Sprokkereef, and Markus Hrachowitz
EGUsphere, https://doi.org/10.5194/egusphere-2024-115, https://doi.org/10.5194/egusphere-2024-115, 2024
Short summary
Short summary
This study explores the impact of climatic variability on root zone water storage capacities 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.
Louise Mimeau, Annika Künne, Flora Branger, Sven Kralisch, Alexandre Devers, and Jean-Philippe Vidal
Hydrol. Earth Syst. Sci., 28, 851–871, https://doi.org/10.5194/hess-28-851-2024, https://doi.org/10.5194/hess-28-851-2024, 2024
Short summary
Short summary
Modelling flow intermittence is essential for predicting the future evolution of drying in river networks and better understanding the ecological and socio-economic impacts. However, modelling flow intermittence is challenging, and observed data on temporary rivers are scarce. This study presents a new modelling approach for predicting flow intermittence in river networks and shows that combining different sources of observed data reduces the model uncertainty.
Elena Macdonald, Bruno Merz, Björn Guse, Viet Dung Nguyen, Xiaoxiang Guan, and Sergiy Vorogushyn
Hydrol. Earth Syst. Sci., 28, 833–850, https://doi.org/10.5194/hess-28-833-2024, https://doi.org/10.5194/hess-28-833-2024, 2024
Short summary
Short summary
In some rivers, the occurrence of extreme flood events is more likely than in other rivers – they have heavy-tailed distributions. We find that threshold processes in the runoff generation lead to such a relatively high occurrence probability of extremes. Further, we find that beyond a certain return period, i.e. for rare events, rainfall is often the dominant control compared to runoff generation. Our results can help to improve the estimation of the occurrence probability of extreme floods.
Alberto Bassi, Marvin Höge, Antonietta Mira, Fabrizio Fenicia, and Carlo Albert
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-47, https://doi.org/10.5194/hess-2024-47, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
The goal is to remove the impact of meteorological drivers in order to uncover the unique landscape fingerprints of a catchment from streamflow data. Our results reveal an optimal two-feature summary for most catchments, with a third feature needed for challenging cases, associated with aridity and intermittent flow. Baseflow index, aridity, and soil/vegetation attributes strongly correlate with learned features, indicating their importance for streamflow prediction.
Claire Kouba and Thomas Harter
Hydrol. Earth Syst. Sci., 28, 691–718, https://doi.org/10.5194/hess-28-691-2024, https://doi.org/10.5194/hess-28-691-2024, 2024
Short summary
Short summary
In some watersheds, the severity of the dry season has a large impact on aquatic ecosystems. In this study, we design a way to predict, 5–6 months in advance, how severe the dry season will be in a rural watershed in northern California. This early warning can support seasonal adaptive management. To predict these two values, we assess data about snow, rain, groundwater, and river flows. We find that maximum snowpack and total wet season rainfall best predict dry season severity.
Yi Nan and Fuqiang Tian
Hydrol. Earth Syst. Sci., 28, 669–689, https://doi.org/10.5194/hess-28-669-2024, https://doi.org/10.5194/hess-28-669-2024, 2024
Short summary
Short summary
This paper utilized a tracer-aided model validated by multiple datasets in a large mountainous basin on the Tibetan Plateau to analyze hydrological sensitivity to climate change. The spatial pattern of the local hydrological sensitivities and the influence factors were analyzed in particular. The main finding of this paper is that the local hydrological sensitivity in mountainous basins is determined by the relationship between the glacier area ratio and the mean annual precipitation.
Michael J. Vlah, Matthew R. V. Ross, Spencer Rhea, and Emily S. Bernhardt
Hydrol. Earth Syst. Sci., 28, 545–573, https://doi.org/10.5194/hess-28-545-2024, https://doi.org/10.5194/hess-28-545-2024, 2024
Short summary
Short summary
Virtual stream gauging enables continuous streamflow estimation where a gauge might be difficult or impractical to install. We reconstructed flow at 27 gauges of the National Ecological Observatory Network (NEON), informing ~199 site-months of missing data in the official record and improving that accuracy of official estimates at 11 sites. This study shows that machine learning, but also routine regression methods, can be used to supplement existing gauge networks and reduce monitoring costs.
Sungwook Wi and Scott Steinschneider
Hydrol. Earth Syst. Sci., 28, 479–503, https://doi.org/10.5194/hess-28-479-2024, https://doi.org/10.5194/hess-28-479-2024, 2024
Short summary
Short summary
We investigate whether deep learning (DL) models can produce physically plausible streamflow projections under climate change. We address this question by focusing on modeled responses to increases in temperature and potential evapotranspiration and by employing three DL and three process-based hydrological models. The results suggest that physical constraints regarding model architecture and input are necessary to promote the physical realism of DL hydrological projections under climate change.
Guillaume Evin, Matthieu Le Lay, Catherine Fouchier, David Penot, Francois Colleoni, Alexandre Mas, Pierre-André Garambois, and Olivier Laurantin
Hydrol. Earth Syst. Sci., 28, 261–281, https://doi.org/10.5194/hess-28-261-2024, https://doi.org/10.5194/hess-28-261-2024, 2024
Short summary
Short summary
Hydrological modelling of mountainous catchments is challenging for many reasons, the main one being the temporal and spatial representation of precipitation forcings. This study presents an evaluation of the hydrological modelling of 55 small mountainous catchments of the northern French Alps, focusing on the influence of the type of precipitation reanalyses used as inputs. These evaluations emphasize the added value of radar measurements, in particular for the reproduction of flood events.
Lena Katharina Schmidt, Till Francke, Peter Martin Grosse, and Axel Bronstert
Hydrol. Earth Syst. Sci., 28, 139–161, https://doi.org/10.5194/hess-28-139-2024, https://doi.org/10.5194/hess-28-139-2024, 2024
Short summary
Short summary
How suspended sediment export from glacierized high-alpine areas responds to future climate change is hardly assessable as many interacting processes are involved, and appropriate physical models are lacking. We present the first study, to our knowledge, exploring machine learning to project sediment export until 2100 in two high-alpine catchments. We find that uncertainties due to methodological limitations are small until 2070. Negative trends imply that peak sediment may have already passed.
Robert Hull, Elena Leonarduzzi, Luis De La Fuente, Hoang Viet Tran, Andrew Bennett, Peter Melchior, Reed M. Maxwell, and Laura E. Condon
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-264, https://doi.org/10.5194/hess-2023-264, 2024
Revised manuscript accepted for HESS
Short summary
Short summary
Large-scale hydrologic a needed tool to explore complex watershed processes and how they may evolve under a changing climate. However, calibrating them can be difficult because they are costly to run and have many unknown parameters. We implement a state-of-the-art approach to model calibration with a set of experiments in the Upper Colorado River Basin.
Salam A. Abbas, Ryan T. Bailey, Jeremy T. White, Jeffrey G. Arnold, Michael J. White, Natalja Čerkasova, and Jungang Gao
Hydrol. Earth Syst. Sci., 28, 21–48, https://doi.org/10.5194/hess-28-21-2024, https://doi.org/10.5194/hess-28-21-2024, 2024
Short summary
Short summary
Research highlights.
1. Implemented groundwater module (gwflow) into SWAT+ for four watersheds with different unique hydrologic features across the United States.
2. Presented methods for sensitivity analysis, uncertainty analysis and parameter estimation for coupled models.
3. Sensitivity analysis for streamflow and groundwater head conducted using Morris method.
4. Uncertainty analysis and parameter estimation performed using an iterative ensemble smoother within the PEST framework.
Shima Azimi, Christian Massari, Giuseppe Formetta, Silvia Barbetta, Alberto Tazioli, Davide Fronzi, Sara Modanesi, Angelica Tarpanelli, and Riccardo Rigon
Hydrol. Earth Syst. Sci., 27, 4485–4503, https://doi.org/10.5194/hess-27-4485-2023, https://doi.org/10.5194/hess-27-4485-2023, 2023
Short summary
Short summary
We analyzed the water budget of nested karst catchments using simple methods and modeling. By utilizing the available data on precipitation and discharge, we were able to determine the response lag-time by adopting new techniques. Additionally, we modeled snow cover dynamics and evapotranspiration with the use of Earth observations, providing a concise overview of the water budget for the basin and its subbasins. We have made the data, models, and workflows accessible for further study.
Yuhang Zhang, Aizhong Ye, Bita Analui, Phu Nguyen, Soroosh Sorooshian, Kuolin Hsu, and Yuxuan Wang
Hydrol. Earth Syst. Sci., 27, 4529–4550, https://doi.org/10.5194/hess-27-4529-2023, https://doi.org/10.5194/hess-27-4529-2023, 2023
Short summary
Short summary
Our study shows that while the quantile regression forest (QRF) and countable mixtures of asymmetric Laplacians long short-term memory (CMAL-LSTM) models demonstrate similar proficiency in multipoint probabilistic predictions, QRF excels in smaller watersheds and CMAL-LSTM in larger ones. CMAL-LSTM performs better in single-point deterministic predictions, whereas QRF model is more efficient overall.
Léo C. P. Martin, Sebastian Westermann, Michele Magni, Fanny Brun, Joel Fiddes, Yanbin Lei, Philip Kraaijenbrink, Tamara Mathys, Moritz Langer, Simon Allen, and Walter W. Immerzeel
Hydrol. Earth Syst. Sci., 27, 4409–4436, https://doi.org/10.5194/hess-27-4409-2023, https://doi.org/10.5194/hess-27-4409-2023, 2023
Short summary
Short summary
Across the Tibetan Plateau, many large lakes have been changing level during the last decades as a response to climate change. In high-mountain environments, water fluxes from the land to the lakes are linked to the ground temperature of the land and to the energy fluxes between the ground and the atmosphere, which are modified by climate change. With a numerical model, we test how these water and energy fluxes have changed over the last decades and how they influence the lake level variations.
Cited articles
Barnett, T. P., Adam, J. C., and Lettenmaier, D. P.: Potential impacts of a
warming climate on water availability in snow-dominated regions, Nature,
438, 303–309, https://doi.org/10.1038/nature04141, 2005.
Barnhart, T. B., Molotch, N. P., Livneh, B., Harpold, A. A., Knowles, J. F.,
and Schneider, D.: Snowmelt rate dictates streamflow, Geophys. Res. Lett.,
43, 8006–8016, https://doi.org/10.1002/2016GL069690, 2016.
Beaudoing, H., Rodell, M., and NASA/GSFC/HSL: GLDAS Noah Land Surface Model L4 3 hourly 0.25×0.25∘ V2.1, Greenbelt, Maryland, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), [data set], https://doi.org/10.5067/E7TYRXPJKWOQ (last access: 9 September 2022), 2020.
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. M., van Dijk, A. I. J. M., McVicar, T. R., and Adler, R. F.: MSWEP V2 global 3hourly 0.1∘ precipitation: methodology and quantitative assessment, GloH2O, [data set], http://www.gloh2o.org/mswx/ (last access: 9 September 2022), 2019.
Bian, Q., Xu, Z., Zheng, H., Li, K.,
Liang, J., Fei, W., Shi, C., Zhang, S.,
and Yang, Z.: Multiscale Changes in Snow Over the Tibetan Plateau
During 1980–2018 Represented by Reanalysis Data Sets and Satellite
Observations, J. Geophys. Res.-Atmos., 125, e2019JD031914,
https://doi.org/10.1029/2019JD031914, 2020.
Bibi, S., Wang, L., Li, X. P., Zhou, J., Chen, D. L., and Yao, T. D.: Climatic
and associated cryospheric, biospheric, and hydrological changes on the
Tibetan Plateau: a review, Int. J. Climatol., 38, 1–17,
https://doi.org/10.1002/joc.5411, 2018.
Biemans, H., Siderius, C., Lutz, A. F., Nepal, S., Ahmad, B., Hassan, T.,
von Bloh, W., Wijngaard, R. R., Wester, P., Shrestha, A. B., and Immerzeel
W. W.: Importance of snow and glacier meltwater for agriculture on the
Indo-Gangetic Plain, Nat. Sustain., 2, 594–601,
https://doi.org/10.1038/s41893-019-0305-3, 2019.
Beck, H. E., van Dijk, A. I. J. M., Levizzani, V., Schellekens, J., Miralles, D. G., Martens, B., and de Roo, A.: MSWEP: 3-hourly 0.25∘ global gridded precipitation (1979–2015) by merging gauge, satellite, and reanalysis data, Hydrol. Earth Syst. Sci., 21, 589–615, https://doi.org/10.5194/hess-21-589-2017, 2017.
Chen, D. L., Xu, B. Q. Yao, T. D., Guo, Z. T., Cui, P., Chen, F. H., Zhang,
R. H., Zhang, X. Z., Zhang, Y. L., Fan, J. Hou, Z. Q., and Zhang, T. H.:
Assessment of past, present and future environmental changes on the Tibetan
Plateau, Chin. Sci. Bull., 60, 3025–3035,
https://doi.org/10.1360/N972014-01370, 2015.
China Meteorological Administration: Hourly observations from ground weather stations in China, National Meteorological Science Data Center, [data set], http://data.cma.cn/data/cdcdetail/dataCode/A.0012.0001.html, last access: 9 September 2022.
Cuo, L., Zhang, Y. X., Zhu, F., and Liang, L. Q.: Characteristics and
changes of streamflow on the Tibetan Plateau: A review, J. Hydrol.-Reg.
Stud.,
2, 49–68, https://doi.org/10.1016/j.ejrh.2014.08.004, 2014.
Chen, Y. P., Gagen, M. H., Chen, F., Zhang, H. L., Shang, H. M., and Xu, H.
F.: Precipitation variations recorded in tree rings from the upper Salween
and Brahmaputra River valleys, China. Ecol. Indi., 113, 106189, https://doi.org/10.1016/j.ecolind.2020.106189, 2020.
Cucchi, M., Weedon, G. P., Amici, A., Bellouin, N., Lange, S., Müller Schmied, H., Hersbach, H., and Buontempo, C.: WFDE5: bias-adjusted ERA5 reanalysis data for impact studies, Earth Syst. Sci. Data, 12, 2097–2120, https://doi.org/10.5194/essd-12-2097-2020, 2020.
Cuo, L., Beyene, T. K., Voisin, N., Su, F. G., Lettenmaier, D. P., Alberti,
M., and Richey, J. E.: Effects of mid-twenty-first century climate and land
cover change on the hydrology of the Puget Sound basin, Washington, Hydrol. Proc., 25,
1729–1753, https://doi.org/10.1002/hyp.7932, 2 011.
Ding, Y. J., Zhang, S. Q., Wu, J. K., Zhao, Q. D., Li, X. Y., and Qin, J.:
Recent progress on studies on cryospheric hydrological processes changes in
China, Adv. Water Sci.,
31, 690–702, https://doi.org/10.14042/j.cnki.32.1309.2020.05.006,
2020.
Ding, J., Yan, H., Xue, S., Feng, J., and Chen, Z.: Study on cooperative
development of water resources for international rivers in Southeast Asia,
J. Water Resour,
26, 97–102, https://doi.org/10.11705/j.issn.1672-643X.2015.02.018, 2015.
Earth Resources Observation and Science Center: A global land cover database primarily derived from 1992 to 1993 1-km AVHRR data, The U.S. Geological Survey's (USGS), [data set], https://doi.org/10.5066/F7GB230D (last access: 9 September 2022), 1997.
Etchevers, P., Durand, Y., Habets, F., Martin, E., and Noilhan, J.: Impact
of spatial resolution on the hydrological simulation of the Durance
high-Alpine catchment, France, Ann. Glaciol., 32, 87–92, https://doi.org/10.3189/172756401781819337, 2001.
Fan, H. and He, D. M.: Regional climate and its change in the Nujiang River
basin, Acta Geogr. Sin., 67, 621–630,
https://doi.org/10.11821/xb201205005, 2012.
FAO: Digital soil map of the world and derived soil properties, Land and
Water Digital Media Series Rev. 1, United Nations Food and Agriculture
Organization CD-ROM, 2003.
Food and Agriculture Organization of United Nations, Land and Water Develepment Division: Digital soil map of the world and derived soil properties, FAO, [data set], https://data.apps.fao.org/map/catalog/srv/eng/catalog.search#/metadata/446ed430-8383-11db-b9b2-000d939bc5d8, (last access: 9 September 2022), 2003.
Global Modeling and Assimilation Office (GMAO): MERRA-2 tavg1_2d_flx_Nx: 2d,1-Hourly,Time-Averaged,Single-Level,Assimilation,Surface Flux Diagnostics V5.12.4, Greenbelt, MD, USA, Goddard Earth Sciences Data and Information Services Center (GES DISC), [data set], https://doi.org/10.5067/7MCPBJ41Y0K6, (last access: 9 September 2022), 2015.
Guo, J. H. (Eds.): Hydrogeography of western Sichuan and northern Yunnan, Scientific Publishing (China), BeiJing, China, 1985.
Guo, W. Q., Liu, S. Y., Xu, L., Wu, L. Z., Shangguan, D. H., Yao, X. J.,
Wei, J. F., Bao, W. J., Yu, P. C., Liu, Q., and Jiang, Z. L.: The second
Chinese glacier inventory: data, methods and results, J. Glaciol., 61,
357–372, https://doi.org/10.3189/2015JoG14J209, 2015.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition
of the mean squared error and NSE performance criteria: Implications for
impr oving hydrological modelling, J. Hydrol., 377, 80–91,
https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
He, J., Yang, K., Tang, W., Lu, H., Qin, J., Chen, Y., and Li, X.: The first
high-resolution meteorological forcing dataset for land process studies over
China, Sci. Data, 7, 25,
https://doi.org/10.1038/s41597-020-0369-y, 2020.
Hersbach, H., Bell, B., Berrisford, P., Biavati, G., Horányi, A., Muñoz Sabater, J., Nicolas, J., Peubey, C., Radu, R., Rozum, I., Schepers, D., Simmons, A., Soci, C., Dee, D., and Thépaut, J.-N.: ERA5 hourly data on single levels from 1959 to present. Copernicus Climate Change Service (C3S) Climate Data Store (CDS), [data set], https://doi.org/10.24381/cds.adbb2d47 (last access: 9 September 2022), 2019.
He, D., Zhao, W., and Feng, Y.: Research progress of international rivers
in China, J. Geogr. Sci. 14, 21–28,
https://doi.org/10.1007/BF02841103, 2004.
Henderson, G. R., Peings, Y., Furtado, J. C., and Kushner, P. J.:
Snow-atmosphere coupling in the Northern Hemisphere, Nat. Clim. Change, 8,
954–963, https://doi.org/10.1029/2011GL048049, 2018.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A.,
Muñoz-Sabater, J., et al.: The ERA5 global reanalysis, Q. J. Roy.
Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803,
2020.
Hock, R., Rasul, G., Adler, C., Cáceres, B., Gruber, S., Hirabayashi, Y.,
Jackson, M., Kääb, A., Kang, S., Kutuzov, S., Milner, A., Molau, U., Morin,
S., Orlove, B., and Steltzer, H.: High Mountain Areas, in: IPCC Special Report
on the Ocean and Cryosphere in a Changing Climate, edited by: Pörtner, H.-O., Roberts, D. C.,
Masson-Delmotte, V., Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K.,
Alegría, A., Nicolai, M., Okem, A., Petzold, J., Rama, B., Weyer, N. M.,
https://www.ipcc.ch/srocc/chapter/chapter-2/ (last access: 9 September 2022), 2019.
Hong, M. and He S.: Spatial and Temporal Change of Rainfall in Nujiang Basin
in Recent 50 Years, Res. Soil Water Conser., 26, 248–252,
https://doi.org/10.13869/j.cnki.rswc.2019.03.036, 2019.
Huning, L. S. and AghaKouchak, A.: Global snow drought hot spots and
characteristics, P. Natl. Acad. Sci. USA, 117, 19753–19759,
https://doi.org/10.1073/pnas.1915921117, 2020.
Immerzeel, W. W., Lutz, A. F., Andrade, M., Bahl, A., Biemans, H., Bolch, T.,
Hyde, S., Brumby, S., Davies, B.J., Elmore, A. C., Emmer, A., Feng, M.,
Fernandez, A., Haritashya, U., Kargel, J. S., Koppes, M.,
Kraaijenbrink, P. D. A., Kulkarni, A. V., Mayewski, P. A., Nepal, S.,
Pacheco, P., Painter, T. H., Pellicciotti, F., Rajaram, H., Rupper, S.,
Sinisalo, A., Shrestha, A. B., Viviroli, D., Wada, Y., Xiao, C., Yao, T.,
and Baillie, J. E. M.: Importance and vulnerability of the world's water towers,
Nature, 577, 364–369,
https://doi.org/10.1038/s41586-019-1822-y, 2020.
Immerzeel, W. W., Van Beek, L. P., and Bierkens, M. F. P.: Climate change
will affect the Asian water towers, Science, 328, 1382–1385,
https://doi.org/10.1126/science.1183188, 2010.
IPCC, 2019: IPCC Special Report on the Ocean and Cryosphere in a Changing
Climate, edited by: Pörtner, H.-O., Roberts, D. C., Masson-Delmotte, V.,
Zhai, P., Tignor, M., Poloczanska, E., Mintenbeck, K., Alegrie, A.,
Nicolai, M., Okem, A., Petzold, J., Rama, B., and Weyer, N. M., IPCC, https://www.ipcc.ch/report/srocc/ (last access: 9 September 2022), 2019.
Jarvis, A., Reuter, H. I., Nelson, A., and Guevara, E.: Hole-filled SRTM for the globe Version 4, available from the CGIAR-CSI SRTM 90m Database, [data set], http://srtm.csi.cgiar.org, (last access: 9 September 2022), 2008.
Jia, X., Zhang, C., Wu, R. G., and Qian, Q. F.: Influence of Tibetan Plateau
autumn snow cover on interannual variations in spring precipitation over
southern China, Clim. Dynam., 56, 767–782,
https://doi.org/10.1007/s00382-020-05497-8, 2021.
Kraaijenbrink, P. D. A., Stigter, E. E., Yao, T. D., and Immerzeel, W. W.:
Climate change decisive for Asia's snow meltwater supply, Nat. Clim. Chang.,
1, 591–597, https://doi.org/10.1038/s41558-021-01074-x, 2021.
Khanal, S., Lutz, A. F., Kraaijenbrink, P. D. A., van den Hurk, B., Yao, T.,
and Immerzeel, W. W.: Variable 21st century climate change response for
rivers in High Mountain Asia at seasonal to decadal time scales, Water
Resour. Res., 57, e2020WR029266,
https://doi.org/10.1029/2020WR029266, 2021.
Kapnick, S., Delworth, T., Ashfaq, M., Malyshev, S., and Milly, P. C. D.:
Snowfall less sensitive to warming in Karakoram than in Himalayas due to a
unique seasonal cycle, Nat. Geosci., 7, 834–840,
https://doi.org/10.1038/ngeo2269, 2014.
Lange, S. and Büchner, M.: ISIMIP3b bias-adjusted atmospheric climate input data (v1.1). ISIMIP Repository, [data set], https://doi.org/10.48364/ISIMIP.842396.1 (last access: 9 September 2022), 2021.
Li, H., Li, X., Yang, D., Wang, J., Gao, B., Pan, X., Zhang, Y., and Hao, X.:
Tracing snowmelt paths in an integrated hydrological model for understanding
seasonal snowmelt contribution at basin scale, J. Geophys. Res.-Atmos., 124,
8874–8895, https://doi.org/10.1029/2019JD030760, 2019.
Li, W., Guo, W., Qiu, B., Xue, Y., Hu, P., and Wei, J.: Influence of
Tibetan Plateau snow cover on East Asian atmospheric circulation at
medium-range time scales, Nat. Commun., 9, 4243,
https://doi.org/10.1038/s41467-018-06762-5, 2018.
Liang, S. L.: The Global Land Surface Satellite (GLASS) Product Suite, National Earth System Science Data Center, National Science & Technology Infrastructure of China, [data set], https://doi.org/10.12041/geodata.GLASS_LAI_MODIS(0.05D).ver1.db (last access: 9 September 2022), 2015.
Lutz, A., Immerzeel, W. W., Shrestha, A. B., and Bierkens, M. F. P.:
Consistent increase in High Asia's runoff due to increasing glacier melt and
precipitation, Nat. Clim. Change, 4, 587–592,
https://doi.org/10.1038/nclimate2237, 2014.
Liu, S., Ding W., Mo X. G., Wang S., Liu C., Luo X., He D., Bajracharya, S.
R., Shrestha, A., and Agrawal, N. K.: Climate Change and Its Impact on
Runoff in Lancang and Nujiang River Basins, Adv. Clim. Change Res., 13,
356–365, 2017.
Luo, X., He, D. M., Ji, X. Lu, Y., and Li, Y.: Low Flow Variations in the
Middle and Upper Nujiang River Basin and Possible Responds to Climate Change
in Recent 50 Years, Acta Geogr. Sin., 36, 107–113,
https//doi.org/10.13249/j.cnki.sgs.2016.01.013, 2016.
Liu, C., Bai, P., Wang, Z., Liu S., and Liu, X. M.: Study on prediction of
ungaged basins case study on the Tibetan Platea, J. Hydra. Eng., 47,
272–282, https://doi.org/10.13243/j.cnki.slxb.20150925, 2016.
Liu, S., Yan, D., Wang, H., Qin, T., Wen, B., and Lu, Y.: Separation of
snowfall from precipitation and its evolution trend and reasons analysis in
upper reaches of Nujiang River Basin, J. Hydra. Eng., 49, 254–262,
https//doi.org/10.13243/j.cnki.slxb.20160789, 2018.
Liu, W., Wang, L., Sun, F., Li, Z., Wang, H., Liu, J., Yang, T., Zhou, J.,
and Qi, J.: Snow hydrology in the upper Yellow River basin under climate
change: A land surface modeling perspective. J. Geophys. Res-Atmos., 123,
12676–12691, https://doi.org/10.1029/2018JD028984, 2018.
Li, C., Su, F., Yang, D., Tong, K., Meng, F., and Kan, B.: Spatiotemporal
variation of snow cover over the Tibetan Plateau based on MODIS snow
product, 2001–2014, Int. J. Climatol., 38, 708–728,
https://doi.org/10.1002/joc.5204, 2017.
Lange, S. and Büchner, M.: ISIMIP3b bias-adjusted atmospheric climate
input data (v1.1), ISIMIP Repository,
https://doi.org/10.48364/ISIMIP.842396.1, 2021a.
Lange, S.: Trend-preserving bias adjustment and statistical downscaling with ISIMIP3BASD (v1.0), Geosci. Model Dev., 12, 3055–3070, https://doi.org/10.5194/gmd-12-3055-2019, 2019.
Lange, S.: ISIMIP3BASD v2.5.0, Zenodo,
https://doi.org/10.5281/zenodo.4686991, 2021b.
Lange, S., Menz, C., Gleixner, S., Cucchi, M., Weedon, G. P., Amici, A.,
Bellouin, N., Schmied, H. M., Hersbach, H., Buontempo, C., and Cagnazzo, C.:
WFDE5 over land merged with ERA5 over the ocean (W5E5 v2.0),
https://doi.org/10.48364/ISIMIP.342217, 2021c.
Muhammad, S.: Improved daily MODIS TERRA/AQUA Snow and Randolph Glacier Inventory (RGI6.0) data for High Mountain Asia (2002–2019), PANGAEA [data set], https://doi.org/10.1594/PANGAEA, (last access: 9 September 2022), 2020.
Musselman, K. N., Addor, N., Vano, J. A., and Molotch, N. P.: Winter melt
trends portend widespread declines in snow water resources, Nat. Clim.
Change, 11, 418–424,
https://doi.org/10.1038/s41558-021-01014-9, 2021.
Mao, R. J., Wang, L., Zhou, J., Liu, X. P., Qi, J., and Zhong, X. Y.:
Evaluation of Various Precipitation Products Using Ground-Based Discharge
Observation at the Nujiang River Basin, China, Water, 11, 2308,
https://doi.org/10.3390/w11112308, 2019.
Muhammad, S. and Thapa, A.: An improved Terra–Aqua MODIS snow cover and Randolph Glacier Inventory 6.0 combined product (MOYDGL06∗) for high-mountain Asia between 2002 and 2018, Earth Syst. Sci. Data, 12, 345–356, https://doi.org/10.5194/essd-12-345-2020, 2020.
Marty, C., Tilg, A., and Jonas, T.: Recent Evidence of Large-Scale Receding
Snow Water Equivalents in the European Alps, J. Hydrometeorol., 18,
1021–1031, https://doi.org/10.1175/JHM-D-16-0188.1, 2017.
Nepal, S., Flügel, W. A., and Shrestha, A. B.: Upstream-downstream
linkages of hydrological processes in the Himalayan region, Ecol. Proc.,
3, 1–16, https://doi.org/10.1186/s13717-014-0019-4, 2014.
Nepal, S., Khatiwada, K. R., Pradhananga, S., Kralisch, S., Samyn, D.,
Bromand, M. T., Jamal, N., Dildar, M., Durrani, F., Rassouly F., Azizi, F.,
Salehi, W., Malikzooi, R., Krause, P., Koirala, S., and Chevallier, P.:
Future snow projecteds in a small basin of the Western Himalaya, Sci. Total
Environ., 795,
148587, https://doi.org/10.1016/j.scitotenv.2021.148587, 2021.
Pulliainen, J., Luojus, K., Derksen, C., Mudryk, L., Lemmetyinen, J.,
Salminen, M., Ikonen, J., Takala, M., Cohen, J., Smolander, T., and Norberg,
J.: Patterns and trends of Northern Hemisphere snow mass from 1980 to 2018,
Nature, 581, 294–298,
https://doi.org/10.1038/s41586-020-2258-0, 2020.
Panday, P. K., Thibeault, J., and Frey, K. E.: Changing temperature and
precipitation extremes in the Hindu Kush-Himalayan region: an analysis of
CMIP3 and CMIP5 simulations and projecteds, Int. J. Climatol., 35,
3058–3077, https://doi.org/10.1002/joc.4192, 2015.
Qin, Y., Abatzoglou, J. T., Siebert, S., Huning, L. S., AghaKouchak, A.,
Mankin, J. S., Hong, C., Tong, D., Davis, S. J., and Mueller, N. D.:
Agricultural risks from changing snowmelt, Nat. Clim. Change, 10, 459–465,
https://doi.org/10.1038/s41558-020-0746-8, 2020.
Qi, J., Wang, L., Zhou, J., Song, L., Li, X. P., and Zeng, T.: Coupled Snow
and Frozen Ground Physics Improves Cold Region Hydrological Simulations: An
Evaluation at the upper Yangtze River Basin (Tibetan Plateau), J. Geophys.
Res.-Atmos., 124, 12985–13004,
https://doi.org/10.1029/2019JD031622, 2019.
Qi, W., Feng, L., Yang, H., and Liu, J.: Warming winter, drying spring and
shifting hydrological regimes in Northeast China under climate change, J.
Hydrol., 606, 127390,
https://doi.org/10.1016/j.jhydrol.2021.127390, 2022.
Qi, W., Feng, L., Liu, J., and Yang, H.: Snow as an important natural
reservoir for runoff and soil moisture in Northeast China. J. Geophys.
Res.-Atmos., 125, e2020JD033086,
https://doi.org/10.1029/2020JD033086, 2020.
Shrestha, M., Wang, L., Koike, T., Xue, Y., and Hirabayashi, Y.: Improving the snow physics of WEB-DHM and its point evaluation at the SnowMIP sites, Hydrol. Earth Syst. Sci., 14, 2577–2594, https://doi.org/10.5194/hess-14-2577-2010, 2010.
Shrestha, M., Wang, L., Koike, T., Tsutsui, H., Xue, Y., and Hirabayashi, Y.: Correcting basin-scale snowfall in a mountainous basin using a distributed snowmelt model and remote-sensing data, Hydrol. Earth Syst. Sci., 18, 747–761, https://doi.org/10.5194/hess-18-747-2014, 2014.
Sanjay, J., Krishnan, R., Shrestha, A. B., Rajbhandari, R., and Ren, G. Y.:
Downscaled climate change projecteds for the Hindu Kush Himalayan region
using CORDEX South Asia regional climate models, Adv. Clim. Change Res., 8,
185–198, https://doi.org/10.1016/j.accre.2017.08.003, 2017.
Su, F., Zhang L., Ou, T., Chen, D., Yao, T., and Tong, K.: Hydrological
response to future climate changes for the major upstream river basins in
the Tibetan Plateau, Global Planet. Change, 136, 82–95,
https://doi.org/10.1016/j.gloplacha.2015.10.012, 2016.
Song, L., Wang, L., Li, X. P., Zhou, J., Luo, D. L., Jin, H. J., Qi, J.,
Zeng, T., and Yin, Y. Y.: Improving permafrost physics in a distributed
cryosphere-hydrology model and its evaluations at the upper Yellow River
Basin, J. Geophys. Res-Atmos., 125, e2020JD032916,
https://doi.org/10.1029/2020JD032916, 2020.
Scherrer, S. C., Ceppi, P., Croci-Maspoli, M., and Appenzeller, C.:
Snow-albedo feedback and Swiss spring temperature trends, Theor. Appl.
Climatol., 110, 509–516,
https://doi.org/10.1007/s00704-012-0712-0, 2012.
Sohrabi, M. M., Tonina, D., Benjankar, R.,Kumar, M., Kormos, P., Marks, D.
and Luce, C.: On the role of spatial resolution on snow estimates using a
process-based snow model across a range of climatology and elevation,
Hydrol. Proc., 33, 1260–1275, https://doi.org/10.1002/hyp.13397, 2019.
Tang, Q. H., Cuo, L., Su, F. G., Liu, X. C., Sun, H., Ding, J., Wang, L.,
Leng, G. Y., Zhang, Y. Q., Sang, Y. F., Fang, H. Y., Zhang, S. F., Han, D.
M., Liu, X. M., He, L., Xu, X. M., Tang, Y., and Chen, D. L.: Streamflow
change on the Qinghai-Tibet Plateau and its impacts, Chin. Sci. Bull., 64,
2807–2821, https://doi.org/10.1360/TB-2019-0141, 2019.
Tang, Q. H., Liu, X. C., Zhou, Y. Y., Wang, J., and Yun, X. B.: Cascading
Impacts of Asian Water Tower Change on Downstream Water Systems, Bull. Chin.
Acad. Sci., 34, 1306–1312,
https://doi.org/10.16418/j.issn.1000-3045.2019.11.013, 2019.
Viviroli, D., Kummu, M., Meybeck, M., Kallio, M., and Wada, Y.: Increasing
dependence of lowland populations on mountain water resources, Nat. Sustain.,
3, 917–928, https://doi.org/10.1038/s41893-020-0559-9, 2020.
Wan, Z.: New refinements and validation of the collection-6 MODIS
land-surface temperature/emissivity product, Remote Sens. Environ., 140,
36–45, https://doi.org/10.1016/j.rse.2013.08.027, 2014.
Wan, Z., Hook, S., and Hulley, G.: MYD11A2 MODIS/Aqua Land Surface Temperature/Emissivity 8-Day L3 Global 1 km SIN Grid V006, NASA EOSDIS Land Processes DAAC [data set], https://doi.org/10.5067/MODIS/MYD11A2.006 (last access: 9 September 2022), 2015.
Wang, L., Sun, L. T., Shrestha, M., Li, X. P., Liu, W. B., Zhou, J., Yang,
K., Lu, H., and Chen, D. L.: Improving snow process modeling with
satellitebased estimation of near-surface-air-temperature lapse rate, J.
Geophys. Res.-Atmos., 121, 12005–12030,
https://doi.org/10.1002/2016JD025506, 2016.
Wang, L., Yao, T. D., Chai, C. H., Cuo, L., Su, F. G., Zhang, F., Yao, Z.,
Zhang, Y. S., Li, X. P., Qi, J., Hu, Z. D., Liu, J. S., and Wang, Y. W.:
TP-River: Monitoring and Quantifying Total River Runoff from the Third Pole,
B. Am. Meteorol. Soc., 102, 948–965,
https://doi.org/10.1175/BAMS-D-20-0207.1, 2020.
Wang, L., Koike, T., Yang, K., and Yeh, J. F.: Assessment of a distributed
biosphere hydrological model against streamflow and MODIS land surface
temperature in the upper Tone River Basin, J. Hydrol., 377, 21–34,
https://doi.org/10.1016/j.jhydrol.2009.08.005, 2009b.
Wang, L., Koike, T., Yang, K., Jin, R., and Li, H.: Frozen soil parameterization in a distributed biosphere hydrological model, Hydrol. Earth Syst. Sci., 14, 557–571, https://doi.org/10.5194/hess-14-557-2010, 2010.
Wang, L., Zhou, J., Qi, J., Sun, L., Yang, K., Tian, L., Lin, Y., Liu, W.,
Shrestha, M., Xue, Y., Koike, T., Ma, Y., Li, X., Chen, Y., Chen, D., Piao,
S., and Lu, H.: Development of a land surface model with coupled snow and
frozen soil physics, Water Resour. Res., 53, 5085–5103,
https://doi.org/10.1002/2017WR020451, 2017.
Winstral, A., Marks, D., and Gurney, R: Assessing the Sensitivities of a
Distributed Snow Model to Forcing Data Resolution, J. Hydrometeorol., 15,
1366–1383, https://doi.org/10.1175/JHM-D-13-0169.1, 2014.
Xiao, L., Che, T., Chen, L., Xie, H., and Dai, L.: Quantifying Snow Albedo
Radiative Forcing and Its Feedback during 2003–2016, Remote Sens., 9, 883,
https://doi.org/10.3390/rs9090883, 2017.
Xu, W., Ma, L., Ma, M., Zhang, H., and Yuan, W.: Spatial-temporal
variability of snow cover and depth in the Qinghai-Tibetan Plateau, J.
Climate, 30, 1521–1533, https://doi.org/10.1175/JCLI-D-15-0732.1, 2017.
Xiao, Z., Liang, S., Wang, J., Chen, P., Yin, X., Zhang, L., and Song, J.: Use
of general regression neural networks for generating the GLASS Leaf Area
Index Product from Time Series MODIS Surface Reflectance, IEEE T. Geosci.
Remote, 52, 209–223,
https://doi.org/10.1109/TGRS.2013.2237780, 2014.
Xue, B., Wang, L., Yang, K., Tian, L., Qin, J., Chen, Y., Zhao, L., Ma, Y.,
Koike, T., Hu, Z., and Li, X.: Modeling the land surface water and energy
cycles of a mesoscale watershed in the central Tibetan Plateau during summer
with a distributed hydrological model, J. Geophys. Res.-Atmos, 118,
8857–8868, https://doi.org/10.1002/jgrd.50696, 2013.
Yan, D., Ma, N., and Zhang, Y.: Development of a fine-resolution snow depth
product based on the snow cover probability for the Tibetan Plateau:
Validation and spatial-temporal analyses, J. Hydrol., 604, 127027,
https://doi.org/10.1016/j.jhydrol.2021.127027, 2022.
You, Q., Wu, T., Shen, L., Pepin, N., Zhang, L., Jiang, Z., Wu, Z., Kang,
S., and AghaKouchak, A.: Review of snow cover variation over the Tibetan Plateau
and its influence on the broad climate system, Earth-Sci. Rev., 201, 103043,
https://doi.org/10.1016/j.earscirev.2019.103043, 2020.
Yao, T., Xue, Y., Chen, D., Chen, F., Thompson, L., Cui, P., Koike, T., Lau,
W. K., Lettenmaier, D., Mosbrugger, V., Zhang, R., Xu, B., Dozier, J.,
Gillespie, T., Gu, Y., Kang, S., Piao, S., Sugimoto, S., Ueno, K., Wang, L.,
Wang, W., Zhang, F., Sheng, Y., Guo, W., Yang, X., Ma, Y., Shen, S. S. P.,
Su, Z., Chen, F., Liang, S., Liu, Y., Singh, V. P., Yang, K., Yang, D.,
Zhao, X., Qian, Y., Zhang, Y., and Li, Q.: Recent Third Pole's rapid warming
accompanies cryospheric melt and water cycle intensification and
interactions between monsoon and environment: Multidisciplinary approach
with observations, modeling, and analysis, B. Am. Meteorol. Soc., 100,
423–444, https://doi.org/10.1175/BAMS-D-17-0057.1, 2019.
Yao, T., Wu, G., Xu, B., Wang, W., Gao, J., and An, B.: Asian Water Tower
Change and Its Impacts, Bull. Chin. Acad. Sci., 34, 1203–1209,
https://doi.org/10.16418/j.issn.1000-3045.2019.11.003, 2019.
Yao, Z., Duan, R., and Liu, Z.: Changes in Precipitation and Air Temperature
and Its Impacts on Runoff in the Nujiang River basin, Resour. Sci., 34,
202–210, 2012.
You, W., Wu, X., and Guo, Z.: Transboundary flow change features of the
Nujiang river in the longitudinal range gorge region, Mount. Res., 26,
22–28, https://doi.org/10.3969/j.issn.1008-2786.2008.01.005, 2008.
Yang, K. and He, J.: China meteorological forcing dataset (1979–2018), National Tibetan Plateau Data Center, [data set], https://doi.org/10.11888/AtmosphericPhysics.tpe.249369.file, (last access: 9 September 2022), 2019.
Yang, F., Lu, H., Yang, K., Huang, G., Li, Y., Wang, W., Lu, P., Tian, F.,
and Huang, Y.: Hydrological characteristics and changes in the Nu-Salween
River basin revealed with model-based reconstructed data, J. Mt. Sci., 18,
2982–3002, https://doi.org/10.1007/s11629-021-6727-1, 2021.
Yang, Y., Wen, B., Yan, Y., Niu, Y., Dai, Y., Li, M., and Gong, X.:
Partitioning the contributions of cryospheric change to the increase of
streamflow on the Nu river, J. Hydrol., 598, 126330,
https://doi.org/10.1016/j.jhydrol.2021.126330, 2021.
Zhao, Q., Wang, J., Gao, H., Zhang, S., Zhao, C., Xu, J., Han, H., and
Shangguan D.: Projecting climate change impacts on hydrological processes on
the Tibetan Plateau with model calibration against the glacier inventory
data and observed streamflow, J. Hydrol., 573, 60–81,
https://doi.org/10.1016/j.jhydrol.2019.03.043, 2019.
Zhang, W., Xiao, Z., Zheng, J., and Ren, J.: Long-term variation
characteristics of Nujiang River discharge and its response to climate
change, Chin. Sci. Bull., 52, 135–141,
https://doi.org/10.1007/s11434-007-7019-z, 2007.
Zhong, X., Wang, L., Zhou, J., Li, X., and Wang, Y.: Precipitation Dominates
Long-Term Water Storage Changes in Nam Co Lake (Tibetan Plateau) Accompanied
by Intensified Cryosphere Melts Revealed by a Basin-Wide Hydrological
Modelling, Remote Sens-Base, 12, 1926,
https://doi.org/10.3390/rs12121926, 2020.
Zhou, J., Wang, L., Zhong, X., Yao, T., Qi, J., Wang, Y., and Xue, Y.:
Quantifying the major drivers for the expanding lakes in the interior
Tibetan Plateau, Sci. Bull., 67, 474–478,
https://doi.org/10.1016/j.scib.2021.11.010, 2021.
Short summary
This work quantifies future snow changes and their impacts on hydrology in the upper Salween River (USR) under SSP126 and SSP585 using a cryosphere–hydrology model. Future warm–wet climate is not conducive to the development of snow. The rain–snow-dominated pattern of runoff will shift to a rain-dominated pattern after the 2040s under SSP585 but is unchanged under SSP126. The findings improve our understanding of cryosphere–hydrology processes and can assist water resource management in the USR.
This work quantifies future snow changes and their impacts on hydrology in the upper Salween...