Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-5951-2021
© Author(s) 2021. 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-25-5951-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
18 Nov 2021
Research article |
| 18 Nov 2021
| 18 Nov 2021
AI-based techniques for multi-step streamflow forecasts: application for multi-objective reservoir operation optimization and performance assessment
Yuxue Guo
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Xinting Yu
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Haiting Gu
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
Jingkai Xie
Institute of Hydrology and Water Resources, Civil Engineering and
Architecture, Zhejiang University, Hangzhou, 310058, China
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Siwei Chen, Yuxue Guo, Yue-Ping Xu, and Lu Wang
Hydrol. Earth Syst. Sci., 28, 4989–5009, https://doi.org/10.5194/hess-28-4989-2024, https://doi.org/10.5194/hess-28-4989-2024, 2024
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Our research explores how increased CO2 levels affect water use efficiency in the Yellow River basin. Using updated climate models, we found that future climate change significantly impacts water use efficiency, leading to improved plant resilience against moderate droughts. These findings help predict how ecosystems might adapt to environmental changes, providing essential insights into ways of managing water resources under varying climate conditions.
Xinting Yu, Yuxue Guo, Siwei Chen, Haiting Gu, and Yue-Ping Xu
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This study introduces RDV-Copula, a new method to simplify complex vine copula structures by reducing dimensionality while retaining essential data. Applied to Shifeng Creek in China, RDV-Copula captured critical spatial-temporal relationships, demonstrating high synchronization probabilities and significant flood risks. Notably, it was found that increasing structure complexity does not always improve accuracy. This method offers an efficient tool for analyzing and simulating multisite flows.
Jingkai Xie, Yue-Ping Xu, Hongjie Yu, Yan Huang, and Yuxue Guo
Hydrol. Earth Syst. Sci., 26, 5933–5954, https://doi.org/10.5194/hess-26-5933-2022, https://doi.org/10.5194/hess-26-5933-2022, 2022
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Monitoring extreme flood events has long been a hot topic for hydrologists and decision makers around the world. In this study, we propose a new index incorporating satellite observations combined with meteorological data to monitor extreme flood events at sub-monthly timescales for the Yangtze River basin (YRB), China. The conclusions drawn from this study provide important implications for flood hazard prevention and water resource management over this region.
Siwei Chen, Yuxue Guo, Yue-Ping Xu, and Lu Wang
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Our research explores how increased CO2 levels affect water use efficiency in the Yellow River basin. Using updated climate models, we found that future climate change significantly impacts water use efficiency, leading to improved plant resilience against moderate droughts. These findings help predict how ecosystems might adapt to environmental changes, providing essential insights into ways of managing water resources under varying climate conditions.
Xinting Yu, Yuxue Guo, Siwei Chen, Haiting Gu, and Yue-Ping Xu
EGUsphere, https://doi.org/10.5194/egusphere-2024-2266, https://doi.org/10.5194/egusphere-2024-2266, 2024
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This study introduces RDV-Copula, a new method to simplify complex vine copula structures by reducing dimensionality while retaining essential data. Applied to Shifeng Creek in China, RDV-Copula captured critical spatial-temporal relationships, demonstrating high synchronization probabilities and significant flood risks. Notably, it was found that increasing structure complexity does not always improve accuracy. This method offers an efficient tool for analyzing and simulating multisite flows.
Lu Wang, Yue-Ping Xu, Haiting Gu, Li Liu, Xiao Liang, and Siwei Chen
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-226, https://doi.org/10.5194/hess-2024-226, 2024
Revised manuscript accepted for HESS
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To understand how eco-hydrological variables evolve jointly and why, this study develops a framework using correlation and causality to construct complex relationships between variables at the system level. Causality provides more detailed information that the compound causes of evolutions regarding any variable can be traced. Joint evolution is controlled by the combination of external drivers and direct causality. Overall, the study facilitates the comprehension of eco-hydrological processes.
Jing Liu, Yue-Ping Xu, Wei Zhang, Shiwu Wang, and Siwei Chen
Hydrol. Earth Syst. Sci., 28, 1325–1350, https://doi.org/10.5194/hess-28-1325-2024, https://doi.org/10.5194/hess-28-1325-2024, 2024
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Applying optimal water allocation models to simultaneously enable economic benefits, water preferences, and environmental demands at different decision levels, timescales, and regions is a challenge. In this study, a process-based three-layer synergistic optimal-allocation model (PTSOA) is established to achieve these goals. Reused, reclaimed water is also coupled to capture environmentally friendly solutions. Network analysis was introduced to reduce competition among different stakeholders.
Jingkai Xie, Yue-Ping Xu, Hongjie Yu, Yan Huang, and Yuxue Guo
Hydrol. Earth Syst. Sci., 26, 5933–5954, https://doi.org/10.5194/hess-26-5933-2022, https://doi.org/10.5194/hess-26-5933-2022, 2022
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Zhixu Bai, Yao Wu, Di Ma, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 25, 3675–3690, https://doi.org/10.5194/hess-25-3675-2021, https://doi.org/10.5194/hess-25-3675-2021, 2021
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To test our hypothesis that the fractal dimensions of streamflow series can be used to improve the calibration of hydrological models, we designed the E–RD efficiency ratio of fractal dimensions strategy and examined its usability in the calibration of lumped models. The results reveal that, in most aspects, introducing RD into model calibration makes the simulation of streamflow components more reasonable. Also, pursuing a better RD during calibration leads to only a minor decrease in E.
Chao Gao, Martijn J. Booij, and Yue-Ping Xu
Hydrol. Earth Syst. Sci., 24, 3251–3269, https://doi.org/10.5194/hess-24-3251-2020, https://doi.org/10.5194/hess-24-3251-2020, 2020
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This paper studies the impact of climate change on high and low flows and quantifies the contribution of uncertainty sources from representative concentration pathways (RCPs), global climate models (GCMs) and internal climate variability in extreme flows. Internal climate variability was reflected in a stochastic rainfall model. The results show the importance of internal climate variability and GCM uncertainty in high flows and GCM and RCP uncertainty in low flows especially for the far future.
Li Liu, Yue Ping Xu, Su Li Pan, and Zhi Xu Bai
Hydrol. Earth Syst. Sci., 23, 3335–3352, https://doi.org/10.5194/hess-23-3335-2019, https://doi.org/10.5194/hess-23-3335-2019, 2019
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The ensemble flood forecasting system can skillfully predict annual maximum floods with a lead time of more than 10 d and has skill in forecasting the snowmelt-related components about 7 d ahead. The accuracy of forecasts for the annual first floods is inferior, with a lead time of only 5 d. The snowmelt-induced surface runoff is the most poorly captured component by the system, and the well-predicted rainfall-related components are the major contributor to good performance.
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Subject: Water Resources Management | Techniques and Approaches: Mathematical applications
Synthesis of historical reservoir operations from 1980 to 2020 for the evaluation of reservoir representation in large-scale hydrologic models
A Bayesian model for quantifying errors in citizen science data: application to rainfall observations from Nepal
A novel objective function DYNO for automatic multivariable calibration of 3D lake models
The importance of non-stationary multiannual periodicities in the North Atlantic Oscillation index for forecasting water resource drought
Decreased virtual water outflows from the Yellow River basin are increasingly critical to China
Optimal water use strategies for mitigating high urban temperatures
Physical versus economic water footprints in crop production: a spatial and temporal analysis for China
Development of a revised method for indicators of hydrologic alteration for analyzing the cumulative impacts of cascading reservoirs on flow regime
Changing global cropping patterns to minimize national blue water scarcity
Climate change impacts on the Water Highway project in Morocco
HESS Opinions: How should a future water census address consumptive use? (And where can we substitute withdrawal data while we wait?)
Complex relationship between seasonal streamflow forecast skill and value in reservoir operations
Water footprint of crop production for different crop structures in the Hebei southern plain, North China
Benchmark levels for the consumptive water footprint of crop production for different environmental conditions: a case study for winter wheat in China
Technical note: Multiple wavelet coherence for untangling scale-specific and localized multivariate relationships in geosciences
Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds
The question of Sudan: a hydro-economic optimization model for the Sudanese Blue Nile
Evolution of the human–water relationships in the Heihe River basin in the past 2000 years
A dynamic water accounting framework based on marginal resource opportunity cost
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Jennie C. Steyaert and Laura E. Condon
Hydrol. Earth Syst. Sci., 28, 1071–1088, https://doi.org/10.5194/hess-28-1071-2024, https://doi.org/10.5194/hess-28-1071-2024, 2024
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Wei Xia, Taimoor Akhtar, and Christine A. Shoemaker
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Hydrol. Earth Syst. Sci., 25, 387–400, https://doi.org/10.5194/hess-25-387-2021, https://doi.org/10.5194/hess-25-387-2021, 2021
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Xingyu Zhou, Xiaorong Huang, Hongbin Zhao, and Kai Ma
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Hatem Chouchane, Maarten S. Krol, and Arjen Y. Hoekstra
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Nabil El Moçayd, Suchul Kang, and Elfatih A. B. Eltahir
Hydrol. Earth Syst. Sci., 24, 1467–1483, https://doi.org/10.5194/hess-24-1467-2020, https://doi.org/10.5194/hess-24-1467-2020, 2020
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Benjamin L. Ruddell
Hydrol. Earth Syst. Sci., 22, 5551–5558, https://doi.org/10.5194/hess-22-5551-2018, https://doi.org/10.5194/hess-22-5551-2018, 2018
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We now lack sufficient empirical observations of consumptive use of water by humans and their economy, so it is worth considering what we can do with the withdrawal-based water use data we already possess. Fortunately, a wide range of applied water management and policy questions can be addressed using currently available withdrawal data. This discussion identifies important data collection problems and argues that the withdrawal data we already possess are adequate for some important purposes.
Sean W. D. Turner, James C. Bennett, David E. Robertson, and Stefano Galelli
Hydrol. Earth Syst. Sci., 21, 4841–4859, https://doi.org/10.5194/hess-21-4841-2017, https://doi.org/10.5194/hess-21-4841-2017, 2017
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This study investigates the relationship between skill and value of ensemble seasonal streamflow forecasts. Using data from a modern forecasting system, we show that skilled forecasts are more likely to provide benefits for reservoirs operated to maintain a target water level rather than reservoirs operated to satisfy a target demand. We identify the primary causes for this behaviour and provide specific recommendations for assessing the value of forecasts for reservoirs with supply objectives.
Yingmin Chu, Yanjun Shen, and Zaijian Yuan
Hydrol. Earth Syst. Sci., 21, 3061–3069, https://doi.org/10.5194/hess-21-3061-2017, https://doi.org/10.5194/hess-21-3061-2017, 2017
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In this study, we analyzed the water footprint (WF) of crop production and found winter wheat, summer maize and vegetables were the top water-consuming crops in the Hebei southern plain (HSP). The total WF, WFblue, WFgreen and WFgrey for 13 years (2000–2012) of crop production were 604.8, 288.5, 141.3 and 175.0 km3, respectively, with an annual downtrend from 2000 to 2012. Finally, we evaluated a reasonable farming structure by analyzing scenarios of the main crops' WF.
La Zhuo, Mesfin M. Mekonnen, and Arjen Y. Hoekstra
Hydrol. Earth Syst. Sci., 20, 4547–4559, https://doi.org/10.5194/hess-20-4547-2016, https://doi.org/10.5194/hess-20-4547-2016, 2016
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Benchmarks for the water footprint (WF) of crop production can serve as a reference and be helpful in setting WF reduction targets. The study explores which environmental factors should be distinguished when determining benchmarks for the consumptive (green and blue) WF of crops. Through a case study for winter wheat in China over 1961–2008, we find that when determining benchmark levels for the consumptive WF of a crop, it is most useful to distinguish between different climate zones.
Wei Hu and Bing Cheng Si
Hydrol. Earth Syst. Sci., 20, 3183–3191, https://doi.org/10.5194/hess-20-3183-2016, https://doi.org/10.5194/hess-20-3183-2016, 2016
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Bivariate wavelet coherence has been used to explore scale- and location-specific relationships between two variables. In reality, a process occurring on land surface is usually affected by more than two factors. Therefore, this manuscript is to develop a multiple wavelet coherence method. Results showed that new method outperforms other multivariate methods. Matlab codes for a new method are provided. This method can be widely applied in geosciences where a variable is controlled by many factors.
Julie E. Shortridge, Seth D. Guikema, and Benjamin F. Zaitchik
Hydrol. Earth Syst. Sci., 20, 2611–2628, https://doi.org/10.5194/hess-20-2611-2016, https://doi.org/10.5194/hess-20-2611-2016, 2016
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This paper compares six methods for data-driven rainfall–runoff simulation in terms of predictive accuracy, error structure, interpretability, and uncertainty. We demonstrate that autocorrelation in model errors can result in biased estimates of important values and show how certain model structures can be more easily interpreted to yield insights on physical watershed function. Finally, we explore how model structure can impact uncertainty in climate change sensitivity estimates.
S. Satti, B. Zaitchik, and S. Siddiqui
Hydrol. Earth Syst. Sci., 19, 2275–2293, https://doi.org/10.5194/hess-19-2275-2015, https://doi.org/10.5194/hess-19-2275-2015, 2015
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.
A. Tilmant, G. Marques, and Y. Mohamed
Hydrol. Earth Syst. Sci., 19, 1457–1467, https://doi.org/10.5194/hess-19-1457-2015, https://doi.org/10.5194/hess-19-1457-2015, 2015
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As water resources are increasingly used for various purposes, there is a need for a unified framework to describe, quantify and classify water use in a region, be it a catchment, a river basin or a country. This paper presents a novel water accounting framework whereby the contribution of traditional water uses but also storage services are properly considered.
L. E. Condon, S. Gangopadhyay, and T. Pruitt
Hydrol. Earth Syst. Sci., 19, 159–175, https://doi.org/10.5194/hess-19-159-2015, https://doi.org/10.5194/hess-19-159-2015, 2015
T. K. Lissner, C. A. Sullivan, D. E. Reusser, and J. P. Kropp
Hydrol. Earth Syst. Sci., 18, 4039–4052, https://doi.org/10.5194/hess-18-4039-2014, https://doi.org/10.5194/hess-18-4039-2014, 2014
X. Chen, D. Naresh, L. Upmanu, Z. Hao, L. Dong, Q. Ju, J. Wang, and S. Wang
Hydrol. Earth Syst. Sci., 18, 1653–1662, https://doi.org/10.5194/hess-18-1653-2014, https://doi.org/10.5194/hess-18-1653-2014, 2014
J. Shi, J. Liu, and L. Pinter
Hydrol. Earth Syst. Sci., 18, 1349–1357, https://doi.org/10.5194/hess-18-1349-2014, https://doi.org/10.5194/hess-18-1349-2014, 2014
A. Castelletti, F. Pianosi, X. Quach, and R. Soncini-Sessa
Hydrol. Earth Syst. Sci., 16, 189–199, https://doi.org/10.5194/hess-16-189-2012, https://doi.org/10.5194/hess-16-189-2012, 2012
D. Anghileri, F. Pianosi, and R. Soncini-Sessa
Hydrol. Earth Syst. Sci., 15, 2025–2038, https://doi.org/10.5194/hess-15-2025-2011, https://doi.org/10.5194/hess-15-2025-2011, 2011
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Short summary
We developed an AI-based management methodology to assess forecast quality and forecast-informed reservoir operation performance together due to uncertain inflow forecasts. Results showed that higher forecast performance could lead to improved reservoir operation, while uncertain forecasts were more valuable than deterministic forecasts. Moreover, the relationship between the forecast horizon and reservoir operation was complex and depended on operating configurations and performance measures.
We developed an AI-based management methodology to assess forecast quality and forecast-informed...
