Spatio-temporal variation of irrigation water requirements for wheat and maize in the Yellow River Basin, China, 1974–2017

Liu, Yanqi; Lin, Yi-Fan; Huo, Zailin; Zhang, Chenglong; Wang, Chaozi; Xue, Jingyuan; Huang, Guanhua

doi:10.1016/j.agwat.2021.107451

Cited by 35 publications

(14 citation statements)

References 47 publications

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“…Nowadays, the Fabric system mainly completes the identification and management of identity information through the digital certificate mechanism, but the Public Key Infrastructure (PKI) technology principally provided by the CA node is the control of personal identity certificate information, such as generation, cancellation, etc. [25][26][27][28].…”

Section: Alliance Chain Hyperledger Fabricmentioning

confidence: 99%

Application of Blockchain Technology in Water Rights Trading in the Irrigation Area under the Internet-of-Things Environment

Xie

Yang

et al. 2022

Security and Communication Networks

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Water rights trading is an important way to solve the shortage of water resources. Combined with the characteristics of water resources and the requirements of the market economy, the organic combination of the government and the market should be strengthened. Through the establishment of a water rights system and a water rights trading market, the implementation of water rights trading will be promoted. Due to the decentralized and distributed structure, blockchain technology greatly reduces its intermediary cost in the application process. The tamper-resistant timestamp feature can realize data tracking and information anticounterfeiting, and flexible programming attributes can promote the specification of market order. Firstly, the reasons for water rights trading are studied, and the water rights trading system is analyzed. It is found that the system has the problems of the cumbersome transaction process and high transaction costs. According to the characteristics of water rights trading, the alliance chain Hyperledger Fabric is selected as the underlying network system of the trading system. Secondly, combined with water rights trading, Hyperledger Fabric multichannel technology is used to design a three-channel accounting method, and the chain code for water rights trading is designed and implemented based on the Go language. CouchDB is adopted to store key-value data, and Ubuntu, Docker, and Docker Compose are used to construct an operating environment of the chain code. Finally, the proposed system is tested. The test findings reveal that the distributed water volume of experimental area 1 is 41.8368 million m3, the current water volume is 23.831 million m3, and the quota management water volume is 20.432 million m3. The distributed water volume in area 2 is 40.4605 million m3, the current water volume is 4317.64 m3, and the quota management water volume is 77.4795 million m3. The distributed water volume in area 3 is 65.6928 million m3, the current water volume is 77.472 million m3, and the quota management water volume is 64.412 million m3. The water rights trading system based on Hyperledger Fabric can record each transaction data, which can be stored in each node, and the data stored in each node are the same. The proposed scheme provides a certain reference for the application of blockchain technology in water rights trading in irrigation areas.

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Section: Alliance Chain Hyperledger Fabricmentioning

confidence: 99%

Application of Blockchain Technology in Water Rights Trading in the Irrigation Area under the Internet-of-Things Environment

Xie

Yang

et al. 2022

Security and Communication Networks

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“…The EPHD of YRB in China is a national and regional development strategy that started in 2019 (Yuan X et al, 2021) [ 5 ], so there are a large number of studies involving the YRB (Jiang et al, 2015; Liu et al, 2022; Shi and Wang, 2021; Wang et al, 2021; Wei et al, 2021; Xu and Song, 2022; Xu et al, 2009; Yuan et al, 2020; Yuan et al, 2022; Zhai et al, 2021; Zhang and Xu, 2022) [ 2 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 ]. Studies of the YRB mainly focused on the ecological environment, water resource, agriculture, climate change, carbon footprint, etc., such as the irrigation water rebound effect in YRB (Xu and Song, 2022) [ 10 ]: the irrigation water rebound effect included four parts, the effect in product income, product substitution, factor income, and the factor substitution.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Studies of the YRB mainly focused on the ecological environment, water resource, agriculture, climate change, carbon footprint, etc., such as the irrigation water rebound effect in YRB (Xu and Song, 2022) [ 10 ]: the irrigation water rebound effect included four parts, the effect in product income, product substitution, factor income, and the factor substitution. Liu et al (2022) [ 7 ] analyzed the meteorological factors and water requirements of four crops in the YRB from 1971 to 2017, as well as the characteristics in spatio-temporal variation. Yuan et al (2022) [ 5 ] analyzed the carbon footprint and estimated the amount of embodied carbon transfer between provincial regions and industrial sectors in YRB by the model of the multi-regional input–output, they found that the carbon footprint of the YRB from 2012 to 2017 declined by 23.4%.…”

Section: Literature Reviewmentioning

confidence: 99%

Spatial Difference and Convergence of Ecological Common Prosperity: Evidence from the Yellow River Basin in China

Liu

Yang

2023

IJERPH

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Analyzing the spatial difference and convergence of ecological common prosperity (ECP) in the Yellow River Basin (YRB) will be beneficial for the environmental governance and multi-regional economic coordination. Based on the panel data of 97 cities in the YRB from 2003 to 2019, this paper measured and analyzed the index of ECP, the Gini coefficient of ECP, and the convergence of ECP. The results indicate that the ECP of YRB shows a steady growth trend (with an average growth rate of 4.71% yearly) and the overall differences are low (average Gini coefficient is 0.1509 from 2003 to 2019). In different areas, the Gini coefficient between the medium-stream and downstream of YRB is the largest (average value of Gini coefficient is 0.1561). From the decomposition of the overall differences of ECP, the contribution degree of the density of transvariation is the highest for annual average, with a contribution rate of 43.37%, the rate of intra-regional and the inter-regional differences are 31.86% and 24.77%, respectively. The results indicate that the overall differences of ECP in YRB are getting smaller because of cooperation and governance, but the differences between and within regions exist because of geographical feature. There is a significant spatial β convergence trend of ECP, the convergence rate in the upstream and downstream area is faster under the economic geographical matrix than others, and the rate in the medium-stream area is faster under the administrative adjacency matrix. Therefore, strengthening economic and environmental cooperation between and within regions is more beneficial to achieve a better quality of life, as well as the long-term goals of 2035.

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“…The Yellow River Basin is the second largest river basin in China [ 8 ]. In recent years, many previous studies have indicated that the surface runoff and groundwater baseflow have decreased significantly due to global climate change and human activities [ 9 , 10 ].…”

Section: Introductionmentioning

confidence: 99%

Investigating Historical Baseflow Characteristics and Variations in the Upper Yellow River Basin, China

Zhao

Kong

et al. 2022

IJERPH

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The baseflow of the Yellow River is vital and important for water resource management and for understanding the hydrological cycle and ecohydrology setting in this arid and semi-arid basin. This study uses a Lyne and Hollick digital filtering technique to investigate the behaviors of the baseflow and the baseflow index in the upper reaches of the Yellow River Basin (China). The observed streamflow discharges along the river were used to analyze the baseflow trend, persistence, and periodic characteristics during the period of 1950–2000. The results show that the average baseflow and BFI in the upper reaches of the Yellow River exhibit a decreasing trend and will continue to decline in the future. Generally, the annual average baseflow and BFI for the most upstream areas of the Yellow River show little difference, while the baseflow and BFI exhibit significant differences for the downstream areas. The filtered annual baseflow varied between 128 × 108 m3/year and 193 × 108 m3/year for the Yellow River. The BFI ranged from 0.54 to 0.65, with an average of 0.60. This indicates that on average, 60% of the long-term streamflow is likely controlled by groundwater discharge and shallow subsurface flow. Statistics show that two periodic variations were observed in the baseflow evolution process. The results indicate that on average, the first and second main cycles of baseflow behaviors occur at 28 years and 12–17 years, respectively. Correspondingly, the estimation indicates that the abrupt change points tend to appear in the 1960s, the 1980s, and the 1990s. An improved understanding of baseflow behaviors can help guide future strategies to manage the river regime, its water resources, and water quality.

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Spatio-temporal variation of irrigation water requirements for wheat and maize in the Yellow River Basin, China, 1974–2017

Cited by 35 publications

References 47 publications

Application of Blockchain Technology in Water Rights Trading in the Irrigation Area under the Internet-of-Things Environment

Application of Blockchain Technology in Water Rights Trading in the Irrigation Area under the Internet-of-Things Environment

Spatial Difference and Convergence of Ecological Common Prosperity: Evidence from the Yellow River Basin in China

Investigating Historical Baseflow Characteristics and Variations in the Upper Yellow River Basin, China

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