Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-387-2021
© 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-25-387-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
26 Jan 2021
Research article |
| 26 Jan 2021
| 26 Jan 2021
Optimal water use strategies for mitigating high urban temperatures
Bin Liu
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
School of Software Engineering, Chengdu University of Information
Technology, Chengdu, China
University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Shuang Liu
Key Laboratory of Mountain Hazards and Earth Surface Processes,
Institute of Mountain Hazards and Environment, Chinese Academy of Sciences,
Chengdu, China
Yujing Zeng
Program in Atmospheric and Oceanic Sciences, Princeton University,
Princeton, New Jersey, USA
Ruichao Li
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Longhuan Wang
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Binghao Jia
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Peihua Qin
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
Si Chen
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
University of Chinese Academy of Sciences, Beijing, China
Jinbo Xie
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics, Institute of Atmospheric Physics, Chinese
Academy of Sciences, Beijing, China
ChunXiang Shi
National Meteorological Information Center, China Meteorological
Administration, Beijing, China
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Jennie C. Steyaert and Laura E. Condon
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Hydrol. Earth Syst. Sci., 26, 2035–2044, https://doi.org/10.5194/hess-26-2035-2022, https://doi.org/10.5194/hess-26-2035-2022, 2022
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Hydrol. Earth Syst. Sci., 25, 5951–5979, https://doi.org/10.5194/hess-25-5951-2021, https://doi.org/10.5194/hess-25-5951-2021, 2021
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Xi Yang, La Zhuo, Pengxuan Xie, Hongrong Huang, Bianbian Feng, and Pute Wu
Hydrol. Earth Syst. Sci., 25, 169–191, https://doi.org/10.5194/hess-25-169-2021, https://doi.org/10.5194/hess-25-169-2021, 2021
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Xingyu Zhou, Xiaorong Huang, Hongbin Zhao, and Kai Ma
Hydrol. Earth Syst. Sci., 24, 4091–4107, https://doi.org/10.5194/hess-24-4091-2020, https://doi.org/10.5194/hess-24-4091-2020, 2020
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Hatem Chouchane, Maarten S. Krol, and Arjen Y. Hoekstra
Hydrol. Earth Syst. Sci., 24, 3015–3031, https://doi.org/10.5194/hess-24-3015-2020, https://doi.org/10.5194/hess-24-3015-2020, 2020
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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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The present work addresses the impact of climate change on the Water Highway project in Morocco. This project aims to transfer 860 × 106 m3 yr−1 of water from the north to the south. As the project is very sensitive to the availability of water in the northern regions, we evaluate its feasibility under different future climate change scenarios: under a pessimistic climate scenario, the project is infeasible; however, under an optimistic scenario a rescaled version might be feasible.
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 implemented both urban water use schemes in a model (Weather Research and Forecasting model) and assessed their cooling effects with different amounts of water in different parts of the city (center, suburbs, and rural areas) for both road sprinkling and urban irrigation by model simulation. Then, we developed an optimization scheme to find out the optimal water use strategies for mitigating high urban temperatures.
We implemented both urban water use schemes in a model (Weather Research and Forecasting model)...
