Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin, China

Chen, Weizhong; Chen, Yan; Feng, Yazhong

doi:10.3390/e23070882

Cited by 9 publications

(7 citation statements)

References 53 publications

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“…As an indispensable natural resource for human survival and social development, water plays an extremely important role in sustainable socio-economic development [ 47 ]. However, increasing water scarcity under the influence of human activities and urbanization is seen as a global systemic risk [ 48 , 49 ].…”

Section: Discussionmentioning

confidence: 99%

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China

Shu,

Xia,

Han

et al. 2024

PLoS ONE

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Accurate forecasts of water demand are a crucial factor in the strategic planning and judicious use of finite water resources within a region, underpinning sustainable socio-economic development. This study aims to compare the applicability of various artificial intelligence models for long-term water demand forecasting across different water use sectors. We utilized the Tuojiang River basin in Sichuan Province as our case study, comparing the performance of five artificial intelligence models: Genetic Algorithm optimized Back Propagation Neural Network (GA-BP), Extreme Learning Machine (ELM), Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Random Forest (RF). These models were employed to predict water demand in the agricultural, industrial, domestic, and ecological sectors using actual water demand data and relevant influential factors from 2005 to 2020. Model performance was evaluated based on the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE), with the most effective model used for 2025 water demand projections for each sector within the study area. Our findings reveal that the GPR model demonstrated superior results in predicting water demand for the agricultural, domestic, and ecological sectors, attaining R2 values of 0.9811, 0.9338, and 0.9142 for the respective test sets. Also, the GA-BP model performed optimally in predicting industrial water demand, with an R2 of 0.8580. The identified optimal prediction model provides a useful tool for future long-term water demand forecasting, promoting sustainable water resource management.

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Section: Discussionmentioning

confidence: 99%

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China

Shu,

Xia,

Han

et al. 2024

PLoS ONE

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“…Equations () and () are used for standardization. The positive index:

X_{ij}^{'} goodbreak= \frac{X_{ij} - \min X_{ij}}{\max X_{ij} - \min X_{ij}}

The negative index:

X_{ij}^{'} goodbreak= \frac{\max X_{ij} - X_{ij}}{\max X_{ij} - \min X_{ij}}

Calculate the proportion of the standard values of the j th indexes in the i th year.

Y_{ij} goodbreak= \frac{{normalX}_{italicij}^{'}}{\sum_{i = 1}^{n} X_{ij}^{'}}

Calculate the entropy of the j th index (Chen et al, 2021).

E_{j} goodbreak= goodbreak- \frac{1}{\ln n} \sum_{i = 1}^{n} Y_{ij} \ln Y_{ij}

Calculate the weight of the j th index.

ω_{j} goodbreak= \frac{1 - E_{j}}{\sum_{j = 1}^{m} 1 - E_{j}}

The weights of the upper indexes are equal to the sum of the weights of the lower ones.…”

Section: Research Methods and Data Sourcesmentioning

confidence: 99%

The differential impacts of coercive pressure from environmental law and proactive environmental strategy on corporate environmental performance: The case study of a pulp and paper company

Xie

2022

Corp Soc Responsibility Env

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Pulp and paper companies are characterized by high-energy consumption and high-emission in production, placing a heavy burden on the environment. Exploring ways to improve their environmental performance is urgently needed. External coercive pressure from environmental law and internal proactive environmental strategy both enable companies to perform better, but little is known about the difference between them. To close this knowledge gap, our analysis is conducted on a case company in pulp and paper industry to compare the differential impacts of the New Environmental Protection Law of China and the proactive environmental strategy on its environmental performance. In addition, accurately evaluating the environmental performance of pulp and paper companies is essential while research on this topic is scant. Therefore, a novel environmental performance evaluation system for pulp and paper companies (EPESPP) is constructed, including not only internal but also external evaluation indexes based on news reports of various media measured by SNOWNLP sentiment analysis. According to the system, the environmental performance of the case company from 2010 to 2018 is evaluated by the entropy-weight-based catastrophe progression method (EWCPM). The results of our case study show that the implementation of a proactive environmental strategy is more conducive to comprehensively improving corporate environmental performance. In other words, the driving effect of the New Environmental Protection Law is not as strong as that of the proactive environmental strategy.

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“…However, due to the limitation of sample data volume, the situation that the more important indicators may be mistakenly deleted during the simplification process may occur. Based on the existing approximate set, indicator W 7 is added to the water resources subsystem, indicators F 2 and F 3 to the food subsystem, and indicators C 6 and C 9 to the ecological subsystem, respectively, to obtain the final index system, as shown in Table 2 below (Chen et al, 2021).…”

Section: Attribute Reduction Of the Indexesmentioning

confidence: 99%

Identification of key brittleness factors and multi-scenario analysis of the water-energy-food-ecology nexus vulnerability based on NRS-BN

Chen,

Pan,

Geng

2023

Front. Environ. Sci.

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Water, energy and food are the basic resources on which human beings depend for survival. With the intensification of human activities, the demand for resources represented by water, energy and food continues to increase, resulting in increasing pressure on the ecological environment, and the vulnerability of water, energy, food and ecosystem becomes increasingly prominent. Identifying the critical vulnerability factors of the water-energy-food-ecology nexus and formulating targeted management measures have become the key to achieving sustainable development. This paper innovatively proposes to study the water-energy-food-ecology nexus from the perspective of vulnerability for the first time, in which the vulnerability evaluation index system of the water-energy-food-ecology nexus is firstly constructed based on the VSD framework, and the attribute reduction is carried out using neighborhood rough sets. Then, a Bayesian network model is built and parameter learning is performed by combining machine learning and expert experience. Finally, different scenarios are set up to identify the key factors that hinder the vulnerability reduction of the water-energy-food-ecology nexus and obtain the vulnerability probability of the nexus under different scenarios using forward and backward inference and sensitivity analysis of Bayesian networks, overcoming the drawback that many prediction models cannot achieve diagnostic inference. The results show that: 1) from 2008 to 2019, the overall vulnerability of the water-energy-food-ecology nexus in the Yangtze River Economic Belt is low. 2) The key factors at the indicator level that hinder the vulnerability reduction of the water-energy-food-ecology nexus mainly include the storage capacity of water conservancy projects, wastewater discharge per 10,000-yuan GDP, and water consumption per 10,000-yuan GDP, and the subsystem level is water, food, energy and ecology system, in that order. 3) The reduction in vulnerability within an individual subsystem can have a beneficial impact on reducing vulnerability within the water-energy-food-ecology nexus. However, this reduction may also lead to an increase in vulnerability within other subsystems. Therefore, in the process of developing water, energy, food, and ecology system, high priority should be given to the coordinated development of all four.

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Assessment and Prediction of Water Resources Vulnerability Based on a NRS-RF Model: A Case Study of the Song-Liao River Basin, China

Cited by 9 publications

References 53 publications

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China

Long-term water demand forecasting using artificial intelligence models in the Tuojiang River basin, China

The differential impacts of coercive pressure from environmental law and proactive environmental strategy on corporate environmental performance: The case study of a pulp and paper company

Identification of key brittleness factors and multi-scenario analysis of the water-energy-food-ecology nexus vulnerability based on NRS-BN

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