resources allocation
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Author(s):  
Jie Hou ◽  
Ni Wang ◽  
Jungang Luo ◽  
Xu Zhang ◽  
Zhonghao Wang ◽  
...  

Abstract Water resources allocation is an important technical tool to alleviate the conflict between water supply and demand, improve the water resources utilization efficiency, and achieve the control target of total water resources utilization. However, the current water resources allocation theory is immature, and there are few objective and quantitative allocation methods, which leads to the relatively backward allocation practice. Moreover, the amounts of allocable water resources change dynamically, which makes the static and single traditional allocation scheme difficult to adapt to changes. To address the above issues, this research comprehensively integrated multiple types of allocation models to build a multi-method integrated simulation system for water resources allocation. The results show that the system supports visually generated schemes and dynamically simulates water resources allocation. The application of the simulation system enhances the reliability of results. And the dynamic adaptability of allocation results supports allocation decisions.


2021 ◽  
Author(s):  
Mulu Sewinet Kerebih ◽  
Ashok Kumar Keshari

Abstract In this study, the land and water resources allocation model was developed to determine optimal cropping patterns and water resources allocations at different rainfall probability exceedance levels (PEs) to ensure maximum agricultural return in the Hormat-Golina valley irrigation command area, Ethiopia. To account the uncertainty of rainfall variability, the monthly dependable rainfall was estimated at three levels of reliability (20, 50 and 80% PEs) which are representing wet, normal and dry seasons based on regional experience. The irrigation water demand which was used as an input to the optimization model was estimated at each level of reliability by using CROPWAT model. The net annual returns of optimal cropping patterns were estimated as 181, 179 and 175 million Ethiopia Birr at 20 %, 50 % and 80 % PEs, respectively. The result of the optimal cropping pattern indicates that, the net annual return of the command area was increased to 45.75%, 45.84% and 47.01% than the Government targeted at 20%, 50% and 80% PEs, respectively. The findings reveal that the optimal land and water resources allocation model is very useful to the planners and decision makers to maximize the agricultural return particularly in areas where land and water resources are limited.


Author(s):  
Ning Hao ◽  
Peixuan Sun ◽  
Luze Yang ◽  
Yu Qiu ◽  
Yingzi Chen ◽  
...  

In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of “Three Lines, Single Project”, a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 108 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 104 CNY, which is a reduction of [8461.404, 110,836] × 104 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.


2021 ◽  
Author(s):  
Jingwei Li ◽  
Wei Huang ◽  
Choon Ling Sia ◽  
Zhuo Chen ◽  
Tailai Wu ◽  
...  

BACKGROUND The SARS-COV-2 virus and its variants are posing extraordinary challenges for public health worldwide. More timely and accurate forecasting of COVID-19 epidemics is the key to maintaining timely interventions and policies and efficient resources allocation. Internet-based data sources have shown great potential to supplement traditional infectious disease surveillance, and the combination of different Internet-based data sources has shown greater power to enhance epidemic forecasting accuracy than using a single Internet-based data source. However, existing methods incorporating multiple Internet-based data sources only used real-time data from these sources as exogenous inputs, but didn’t take all the historical data into account. Moreover, the predictive power of different Internet-based data sources in providing early warning for COVID-19 outbreaks has not been fully explored. OBJECTIVE The main aim of our study is to explore whether combining real-time and historical data from multiple Internet-based sources could improve the COVID-19 forecasting accuracy over the existing baseline models. A secondary aim is to explore the COVID-19 forecasting timeliness based on different Internet-based data sources. METHODS We first used core terms and symptoms related keywords-based methods to extract COVID-19 related Internet-based data from December 21, 2019, to February 29, 2020. The Internet-based data we explored included 90,493,912 online news articles, 37,401,900 microblogs, and all the Baidu search query data during that period. We then proposed an autoregressive model with exogenous inputs, incorporating the real-time and historical data from multiple Internet-based sources. Our proposed model was compared with baseline models, and all the models were tested during the first wave of COVID-19 epidemics in Hubei province and the rest of mainland China separately. We also used the lagged Pearson correlations for the COVID-19 forecasting timeliness analysis. RESULTS Our proposed model achieved the highest accuracy in all the five accuracy measures, compared with all the baseline models in both Hubei province and the rest of mainland China. In mainland China except Hubei, the COVID-19 epidemics forecasting accuracy differences between our proposed model (model i) and all the other baseline models were statistically significant (model 1, t=–8.722, P<.001; model 2, t=–5.000, P<.001, model 3, t=–1.882, P =0.063, model 4, t=–4.644, P<.001; model 5, t=–4.488, P<.001). In Hubei province, our proposed model's forecasting accuracy improved significantly compared with the baseline model using historical COVID-19 new confirmed case counts only (model 1, t=–1.732, P=0.086). Our results also showed that Internet-based sources could provide a 2-6 days earlier warning for COVID-19 outbreaks. CONCLUSIONS Our approach incorporating real-time and historical data from multiple Internet-based sources could improve forecasting accuracy for COVID-19 epidemics and its variants, which may help improve public health agencies' interventions and resources allocation in mitigating and controlling new waves of COVID-19 or other epidemics.


2021 ◽  
Author(s):  
Gang Yao ◽  
Yong Liu ◽  
Gang Li ◽  
Xiaoxiang Zhang ◽  
Liang Wang

BACKGROUND During epidemics, how to allocate resources to suppress the spread of infectious disease is of great significance. Many researches focused on how to suppress the spread of infectious disease in the contact network. However, obtaining the contact network in a short period of time is difficult. OBJECTIVE When resources cannot meet the needs of multiple regions, it is necessary to consider how to allocate resources among multiple regions to limit the spread of the disease without details of the contact network. METHODS It proposed a resources allocation model to measure the cost of different allocation methods by the number of new infected individuals over a period of time. By calculating the probability of a susceptible individual being infected, it estimated the number of new infected individuals. In order to calculate the probability of a susceptible individual being infected by an infected individual in another region, conditional mutual information was introduced to estimate the strength of association relationship between regions. RESULTS Based on the proposed model, it compared the model costs of four different resources allocation methods and found three factors that affect the performance of each method, including the percentage of infected individuals, the resource coverage percentage, and the distribution of infected individuals in each region. CONCLUSIONS No method is better than other methods under any situations. When resources are allocated, the method with the least cost in a short period of time should be adopted according to the current infections, so as to control the epidemic as soon as possible.


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