/pdf/key-points-for-green-management-of-water-energy-food-in-the-2h6tyk3y.pdf

Key points for green management of water-energy-food in the Belt and Road Initiative: Resource utilization efficiency, final demand behaviors and trade inequalities

The impact of virtual water trade on urban water scarcity: A nested MRIO analysis of Yangtze River Delta cities in China

A novel classification of virtual water trade for the sustainability of global freshwater resources

Grain trade in Belt and Road (B&R) countries shows a mismatch between the volume and direction of grain flows and actual demand. With economic and industrial development, the water crisis has intensified, which poses a great challenge to the security of world grain supply and demand. There are few studies on the reconstruction of grain trade relations from the perspective of grain economic value. In this paper, a linear optimization model considering opportunity cost is proposed to fill the gap, and it is compared and analyzed with the optimization model considering only transportation cost. The grain supply and demand structures in both optimization results show characteristics of geographical proximity and long-tail distribution. Furthermore, the economic and water resource benefits resulting from the two optimal configurations are compared and analyzed. It is found that the economic benefits generated by grain trade in B&R countries with the consideration of opportunity cost not only cover transportation costs but also generate an economic value of about 130 trillion US dollars. Therefore, considering opportunity cost in grain trade is of great significance for strengthening cooperation and promoting the economic development of countries under the B&R framework. In terms of resource benefits, the grain trade with consideration of opportunity cost saves nearly 28 billion cubic meters of water, or about 5% of the total virtual water flow. However, about 72 billion cubic meters of water is lost for the grain trade with consideration of transportation cost. This study will help to formulate and adjust policies related to the “Belt and Road Initiative” (B&R Initiative), so as to maximize the economic benefits while optimizing the structure of grain trade and alleviating water scarcity pressures.

/pdf/optimization-and-benefit-analysis-of-grain-trade-in-belt-and-1ys4yeyf.pdf

Optimization and Benefit Analysis of Grain Trade in Belt and Road Countries

The world’s sustainable growth is being severely hampered by the inefficient use of water resources. Despite the widely acknowledged importance of trade in global and regional water and food security, societal reliance on local production, as well as international trade, remains inadequately assessed. Therefore, using South Korea as a case study, this study fills in this research gap by applying the virtual water concept, the logarithmic mean divisia index (LMDI) method, and the Tapio decoupling model. The virtual water concept was used to estimate South Korea’s net virtual water trade for major grain crops from 1992 to 2017. Then, the LMDI method was utilized to assess the driving factors causing changes in net virtual water trade. Lastly, the Tapio decoupling model was used to investigate the decoupling relationships between economic growth and the driving factors of net virtual water trade. The results showed that South Korea remains a net importer of virtual water flows with respect to grain crops, with an average import of 16,559.24 million m3 over the study period. In addition, the change in net virtual water trade could be attributed to the water intensity effect, product structure effect, economic effect, and population effect. However, water intensity and economic effects were the major decisive factors for decreases and increases in net virtual water trade, respectively, while the population and product structure effects had minor positive influences on the net virtual water trade. Furthermore, water intensity and economic growth showed a strong decoupling in most periods, while the decoupling state between product structure and economic growth was observed as expansive negative decoupling. Likewise, population size and economic growth showed a weak decoupling in most periods. The results reveal South Korea’s status as it concerns the virtual water trade of grain crops, thus providing valuable insights into the sustainability of trade activities for the management of local water resources.

/pdf/environmental-and-socioeconomic-determinants-of-virtual-2ph0vpb7.pdf

Environmental and Socioeconomic Determinants of Virtual Water Trade of Grain Products: An Empirical Analysis of South Korea Using Decomposition and Decoupling Model

Driving factors of virtual water in international grain trade: A study for belt and road countries

At present, water resource information management in China is mainly a centralized model, and there exist some problems such as high cost, low efficiency, and data storage insecurity. Blockchain technology provides a good solution which can create an efficient trust mechanism among the links in the process of water resource utilization. It guarantees the security of the data, avoiding the sudden collapse of the central institutions caused by some normal operations of the entire system. Based on a decentralization blockchain, we propose a decentralized water resource information management system for the whole process of “supply-use-consumption-discharge,” which improves the traditional water data storage. Specifically, the monitoring and business data are encrypted by the blockchain and are transmitted using a peer-to-peer network. Moreover, the centralized management mode is changed and part of the management work is dispersed to each node. Thus, decisions and measures can be made and implemented quickly after discovering problems to improve the efficiency of information transmission and management. In addition, two typical blockchain-based application scenarios for water resource management are designed. A blockchain-based approach makes issuing and monitoring water abstraction permits more convenient and obtaining license information more secure and verifiable. A reliable mechanism for tracing water quality ensures the accuracy and reliability of water quality information, enables the detection of locations with inadequate water quality, and clarifies people’s responsibility, thus guaranteeing the water safety of the residents.

/pdf/a-framework-of-blockchain-technology-in-intelligent-water-184j0mxw.pdf

A Framework of Blockchain Technology in Intelligent Water Management

Application of a novel signal decomposition prediction model in minute sea level prediction

Corrigendum to “Combining time varying filtering based empirical mode decomposition and machine learning to predict precipitation from nonlinear series” [J. Hydrol. 603 (2021) (1–23) 126914]

Understanding dissolved oxygen (DO) dynamics and corresponding driving factors are essential to improve aquatic environments and protect aquatic organisms. Although several studies have been conducted to investigate DO dynamics on low-frequency scales, high-frequency spectral characteristics of DO and the corresponding connections with hydro-biogeochemical drivers were little known. Accordingly, this study proposed a comprehensive framework to explore the periodic and aperiodic characteristics of DO, and the corresponding hydrological (water temperature) and biogeochemical (pH, ammonia nitrogen (NH3-N), and total phosphorus (TP)) controls in the Pearl River Basin of China based on high-frequency measurements and spectral analysis. The results showed that DO, water temperature, pH, NH3-N and TP all exhibited temporal fractal phenomena, i.e., 1/f fluctuations, in low-frequency domains. The scaling component β of water temperature was larger, implying that the self-similarity of water temperature was stronger. In high-frequency domains, DO exhibited obvious daily and half-day periods. Of the other four elements, water temperature and pH exhibited high-frequency periods, while NH3-N and TP did not. Based on the energy distribution derived from the continuous wavelet transform, three DO transience types, swing, abrupt, and mixed swing and abrupt, were characterized. The first type was characterized by continuous fluctuations, while the second type was characterized by a sudden change with a peak value. The last type had traits of both swing transience and abrupt transience. Through an analysis of maximal information coefficient and correlation coefficient, we found that linear relationships existed between water temperature and DO with correlation coefficient ranging from −0.46 to −0.83. In contrast, pH, NH3-N, and TP generally exhibited nonlinear relationships with DO, and the nonlinear coefficients were above 0.2. On the whole, the driving elements were different for each DO transience type. Hydrological elements mainly corresponded to DO swing transience. In contrast, biogeochemical elements were mainly related to DO abrupt transience. In general, this study provided a new perspective for revealing the high-frequency fluctuations of DO and corresponding drivers. The framework and results summarized in this study broadened our understanding on DO dynamics, and were conducive to river management, such as water quality anomaly detection, water quality prediction and regulation in advance. 

Chao Song

Papers

Driving factors of virtual water in international grain trade: A study for belt and road countries

A Framework of Blockchain Technology in Intelligent Water Management

Application of a novel signal decomposition prediction model in minute sea level prediction

Corrigendum to “Combining time varying filtering based empirical mode decomposition and machine learning to predict precipitation from nonlinear series” [J. Hydrol. 603 (2021) (1–23) 126914]

Detection of periodicity, aperiodicity, and corresponding driving factors of river dissolved oxygen based on high-frequency measurements