Water shortage risk evaluation and its primary cause: Empirical evidence from rural China

Liu, Wenxin; Zhang, Yao; Xu, Ruifan; Zhang, Zhen

doi:10.1111/1477-8947.12249

Cited by 10 publications

(6 citation statements)

References 31 publications

(25 reference statements)

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“…Determining the weight is a key problem in calculating the index. Analytic hierarchy process, entropy value method, equal weight method, and other weighting methods are all commonly used to determine the weight [43]. This work used the principal component analysis (PCA) method.…”

Section: Weight Determination Methodsmentioning

confidence: 99%

Sustainable Development Levels and Influence Factors in Rural China Based on Rural Revitalization Strategy

Shi

Yang

2022

Sustainability

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Accurate and quantitative assessments of rural development can offer important information for the formulation of rural development strategies. The purpose of this study was to provide a new perspective on the evaluation of rural sustainable development, overcoming the limitations of past studies that were based on simple analyses using a single method. In doing so, we aimed to provide a theoretical reference for formulating differentiated policies for regional rural development. In the present study, the rural development levels of 31 provincial administrative regions in China from 2000 to 2020 were analyzed based on the rural revitalization index framework, using five dimensions proposed in a previous study, i.e., industrial prosperity, ecological livability, rural civilization, effective governance, and a rich life. China’s rural sustainable development level was calculated using kernel density estimation and least squares estimation of temporal and spatial analyses. The results revealed that the development levels of rural areas in China are improving, but the improvement is not spatially consistent across rural areas. On the basis of the driving factors and causal mechanism, seven types of rural development levels were identified. We further analyzed the main reasons for the spatial differences in rural development levels and offer suggestions for improvement.

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Section: Weight Determination Methodsmentioning

confidence: 99%

Sustainable Development Levels and Influence Factors in Rural China Based on Rural Revitalization Strategy

Shi

Yang

2022

Sustainability

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“…The application of irrigation water at the study area by smallholder farmers seeks to supplement the precipitation shortfalls in meeting crop water requirements of their respective farms. Although rainfall dependence reduces the risk of agricultural produce contamination, inconsistent weather patterns could interfere with agricultural production [78]. Thus, owing to the swiftly changing climate, water shortages have become a widespread problem, and droughts are occurring more frequently in South Africa [79].…”

Section: Farmer Socioeconomic Characteristicsmentioning

confidence: 99%

An Analysis of the Acceptance of Water Management Systems among Smallholder Farmers in Numbi, Mpumalanga Province, South Africa

Morepje,

Agholor,

Sithole

et al. 2024

Sustainability

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The study investigated the relationship between smallholder farmers’ socioeconomic characteristics and their choice to implement formal water management systems in the context of agricultural output in Numbi, Mpumalanga Province, South Africa. Numbi is a farming community situated in the Mbombela Local Municipality within the Ehlanzeni District Municipality of Mpumalanga Province. The study featured 141 smallholder farmers who were chosen using a straightforward random sampling method. A systematic and structured questionnaire was used to collect the data, and binary logistic regression was used to analyze the acceptability of formal water management systems among smallholder farmers. The results revealed statistically significant relationships with gender (p = 0.025), age (p = 0.186), educational level (p = 0.087), farm size (p = 0.151), household size (p = 0.041), and the use of alternative irrigation (p < 0.001). These findings underscore the importance of socioeconomic factors in influencing smallholder farmers’ openness to adopting formal water management systems. The study, therefore, recommends that policymakers, extension agents, and other stakeholders should prioritize farmer socioeconomic factors when advocating for the acceptance of formal water management systems. Hence, water-use efficiency, increased crop yields, and livelihood security will be eminent, thus improving the overall farmer quality of life in the study area.

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“…3 Liu et al evaluated the urban water utilization efficiency of 284 cities in China between 2003 and 2018 by the Slacks-based measure of super-efficiency, and explore its spatial differences through ESDA, there were significant spatial differences in urban water utilization efficiency across China, with considerable global and local spatial autocorrelation. 4 Liu et al quantitatively analyze the water shortage risk in rural China during 1997–2019, and within rural China, the trend of water shortage risk shows positive spatial correlation and temporal variation based on ESDA. 5 Sun et al developed water poverty indicators for rural areas of China by introducing the driving forces–pressures–states–impacts–responses (DPSIR) model, and ESDA of the results suggests that the distribution of water poverty displays low–low and high–high clustering.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial pattern and driving factors for interprovincial water use in China: Based on SNA and LMDI

Zhang

Huang

Shi

et al. 2023

Energy & Environment

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China, the world's largest developing country, faces a severe water shortage. As the government has set a goal of limiting water use to 7000 × 108 m3 by 2035, how to control the increase in water use will be a thorny issue for China. Unbalanced and uncoordinated regional socio-economic development is an important feature of China. Research on the interaction between provincial water use will help to optimize the rational allocation of water resources and control of water use. In this paper, SNA (social network analysis) method is first used to explore the characteristics of social network relationship between inter-provincial water use, construct a two-stage model of SNA–LMDI, and decompose the driving factors of inter-provincial water use evolution. We found the following points. (1) From 2000 to 2018, the spatial correlation network structure of water use is tending to be stable, and the stability and risk resistance of the whole network are enhanced. (2) From different angles to quantify the centricity analysis, can be found that eastern provinces located right in the heart of water network, obviously larger impact on water resources utilization in other provinces, Shanghai and Beijing is located in the former two, and central and western provinces in the edge position. (3) The national water use spatial correlation network can be divided into four blocks, net beneficial block, bidirectional spillover block, brokers block, and net spillover block. (4) Technological progress and industrial structure adjustment were the primary and secondary factors inhibiting the increase of total water use, while income increase was the main factor promoting the increase of total water use, population scale expansion had a weak role in promoting the increase of total water use. Some policy implications are put forward related to our research conclusions.

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Water shortage risk evaluation and its primary cause: Empirical evidence from rural China

Abstract: This study explores the level of rural water shortage risk from the perspective of disaster risk and poverty. Based on related causes and characteristics, we quantitatively analyze the water shortage risk in rural China during 1997-2019.

Cited by 10 publications

References 31 publications

Sustainable Development Levels and Influence Factors in Rural China Based on Rural Revitalization Strategy

Sustainable Development Levels and Influence Factors in Rural China Based on Rural Revitalization Strategy

An Analysis of the Acceptance of Water Management Systems among Smallholder Farmers in Numbi, Mpumalanga Province, South Africa

Spatial pattern and driving factors for interprovincial water use in China: Based on SNA and LMDI

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