Assessing and Predicting the Water Resources Vulnerability under Various Climate-Change Scenarios: A Case Study of Huang-Huai-Hai River Basin, China

Chen, Yan; Feng, Yazhong; Zhang, Fan; Yang, Fan

doi:10.3390/e22030333

Cited by 9 publications

(6 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Within near‐term water quality forecasts, hindcasts, and projections with uncertainty ( n = 16), multiple methods of uncertainty specification were used (Figure 7b). For example, some papers included the concept of uncertainty but did not quantify it (e.g., used different land use change scenarios as model drivers; Chen et al, 2020; these papers were categorized in the “present” category for uncertainty inclusion methods following Table 2), whereas others quantified and propagated uncertainty while also iteratively assimilating new observations to constrain initial conditions (e.g., Baracchini et al, 2020; Liu et al, 2020; these papers were categorized in the “assimilates” category for uncertainty inclusion methods following Table 2; Figure 7b). Of the 16 near‐term freshwater quality papers that reported uncertainty, four were projections (i.e., used scenarios to generate future predictions) and 12 were forecasts or hindcasts.…”

Section: Resultsmentioning

confidence: 99%

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Lofton

Howard

Thomas

et al. 2023

Global Change Biology

View full text Add to dashboard Cite

Near‐term freshwater forecasts, defined as sub‐daily to decadal future predictions of a freshwater variable with quantified uncertainty, are urgently needed to improve water quality management as freshwater ecosystems exhibit greater variability due to global change. Shifting baselines in freshwater ecosystems due to land use and climate change prevent managers from relying on historical averages for predicting future conditions, necessitating near‐term forecasts to mitigate freshwater risks to human health and safety (e.g., flash floods, harmful algal blooms) and ecosystem services (e.g., water‐related recreation and tourism). To assess the current state of freshwater forecasting and identify opportunities for future progress, we synthesized freshwater forecasting papers published in the past 5 years. We found that freshwater forecasting is currently dominated by near‐term forecasts of water quantity and that near‐term water quality forecasts are fewer in number and in the early stages of development (i.e., non‐operational) despite their potential as important preemptive decision support tools. We contend that more freshwater quality forecasts are critically needed and that near‐term water quality forecasting is poised to make substantial advances based on examples of recent progress in forecasting methodology, workflows, and end‐user engagement. For example, current water quality forecasting systems can predict water temperature, dissolved oxygen, and algal bloom/toxin events 5 days ahead with reasonable accuracy. Continued progress in freshwater quality forecasting will be greatly accelerated by adapting tools and approaches from freshwater quantity forecasting (e.g., machine learning modeling methods). In addition, future development of effective operational freshwater quality forecasts will require substantive engagement of end users throughout the forecast process, funding, and training opportunities. Looking ahead, near‐term forecasting provides a hopeful future for freshwater management in the face of increased variability and risk due to global change, and we encourage the freshwater scientific community to incorporate forecasting approaches in water quality research and management.

show abstract

Section: Resultsmentioning

confidence: 99%

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Lofton

Howard

Thomas

et al. 2023

Global Change Biology

View full text Add to dashboard Cite

show abstract

“…For the negative indicators, (0, µ-σ] is level 5, (µ-σ, µ] is level 4, (µ, µ+σ] is level 3, (µ+σ, µ+2σ] is level 2, (µ +2σ,∞] is level 1, and the opposite is true for the positive indicators. Other indicators refer to existing studies [34][35][36] and are combined with the situation of the Yangtze River Economic Belt itself. The classification criteria applicable to the Yangtze River Economic Belt region are shown in Table 2, below.…”

Section: Establishment and Grading Of Evaluation Index Systemmentioning

confidence: 99%

Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model

Chen

2021

Water

Self Cite

View full text Add to dashboard Cite

As an important agricultural production area in China, the Yangtze River Economic Belt has a large amount of water resources and rich types of energy. Water and energy resources are the supporting basis of food production, and the production and use of energy also need to consume a large amount of water resources. The three affect each other and are interdependent. Paying attention to the synergistic security of water-energy-food system in the Yangtze River Economic Belt is important for regional economic development. This paper uses the pressure-state-response (PSR) model and selects 27 indicators to build an evaluation index system of the regional water-energy-food system. We use the random forest model to evaluate the security level of the Yangtze River Economic Belt from 2008 to 2017, and the Haken model is employed to identify the driving factors that dominate the synergistic evolution of the system. Then we take the identified factors as the key control variables under each scenario and launch a scenario simulation of some provinces in the Yangtze River Economic Belt in 2025. The results show that due to the improvement of water and energy utilization efficiency and the advancement of agricultural production technology, the level of water-energy-food security in the Yangtze River Economic Belt improved significantly from 2008 to 2017. Each province performs differently in different subsystems, with water resources security being better in the upper reaches and Zhejiang and Shanghai in the lower reaches, and food security being better in the middle and lower reaches. The level of energy security is high in Sichuan, Yunnan, and Guizhou in the upper reaches and Shanghai and Anhui in the lower reaches. According to the results of scenario prediction for Jiangsu Province and Hubei Province in 2025, implementing moderate management in accordance with current management objectives can increase the overall security of the system to level 4. The two provinces should focus on controlling water resources and energy consumption and improving the utilization efficiency of water and energy in agricultural production.

show abstract

“…Hence, an accurate assessment of water resource vulnerability is essential to ensure the development of a human-nature coupled system and to achieve efficient uses of water resources. In particular, this concept and its guidance is most important in inland river basins of arid and semi-arid regions where water security problems are more conspicuous in China [3,4].…”

Section: Introductionmentioning

confidence: 99%

Assessment and Factor Diagnosis of Water Resource Vulnerability in Arid Inland River Basin: A Case Study of Shule River Basin, China

Chen

Shen

et al. 2023

Sustainability

View full text Add to dashboard Cite

Water resources in arid and semi-arid inland regions are highly vulnerable, facing threats from global climate change and human activities. Ensuring water resource sustainability requires scientifically evaluating the vulnerability of water resources and its driving factors. Taking the Shule River Basin, an inland river in northwest China, as an example, this study established an assessment system considering 16 influencing factors based on three aspects, including natural vulnerability, anthropogenic vulnerability, and carrying capacity vulnerability. The mature-element fuzzy model based on comprehensive weight and the Delphi method were used to evaluate the water resource vulnerability of the basin from 2005 to 2021. The results were as follows: (1) The water resource vulnerability in the Shule River Basin was between severe and moderate from 2005 to 2021, with a trend towards severe vulnerability. (2) The barrier analysis at the index level shows that factors of natural vulnerability had a low impact on water resource vulnerability in the basin from 2005 to 2019 but exerted a greater impact in 2020–2021, an impact that was far higher than that caused by factors of man-made vulnerability and water resource vulnerability. The impact of factors of anthropogenic vulnerability on water resource vulnerability was relatively low in the entire study period, except in 2016, 2017, 2020, and 2021. In 2005–2010, the factors of bearing capacity vulnerability had a great impact on water resource vulnerability, but in 2011–2021, the impact was alleviated and was gradually reduced. (3) Among the 16 factors affecting water resource vulnerability, the obstacle degree was higher than 6.5% for the following factors: the ratio of irrigation water use on farmland, the annual precipitation, total water resources, the annual quantity of wastewater effluent, the urbanization rate, the surface water control rate, and the degree of groundwater resource amount, exploration, and utilization obstacle values.

show abstract

Assessing and Predicting the Water Resources Vulnerability under Various Climate-Change Scenarios: A Case Study of Huang-Huai-Hai River Basin, China

Cited by 9 publications

References 49 publications

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Progress and opportunities in advancing near‐term forecasting of freshwater quality

Evaluation and Scenario Prediction of the Water-Energy-Food System Security in the Yangtze River Economic Belt Based on the RF-Haken Model

Assessment and Factor Diagnosis of Water Resource Vulnerability in Arid Inland River Basin: A Case Study of Shule River Basin, China

Contact Info

Product

Resources

About