Accurately predicting river flows over daily timescales is considered as an important task for sustainable management of freshwater ecosystems, agricultural applications, and water resources ...management. In this research paper, artificial intelligence (AI) techniques, namely the cascade correlation neural networks (CCNN) and the random forest (RF) models, were employed in daily river stage and river flow prediction for two river systems (i.e., Dulhunty River and Herbert River) in Australia. To develop the CCNN and RF models, a significant 3-day antecedent river stage and river flow time series were used. 80% of the whole data were used for model training and the remaining 20% for model testing. A total of ten different model structures with different input combinations were used to evaluate the optimal model in the training phase, and the results were analyzed using statistical metrics including the root mean square error (RMSE), Nash–Sutcliffe coefficient (NS), Willmott’s index of agreement (WI), and Legate and McCabe’s index (
E
LM
) in the testing phase. The inter-comparison of CCNN and RF models for both river systems showed that the CCNN model was able to generate a more accurate prediction of the river stage and river flow compared to the RF model. Due to hydro-geographic differences leading to a different underlying historical data characteristics, the optimal CCNN’s performance for the Dulhunty River was found to be most accurate, in terms of
E
LM
= 0.779, WI = 0.964, and
E
NS
= 0.862 versus 0.775, 0.968, and 0.885 for the Herbert River. Following the performance accuracies, the authors ascertained that the CCNN model can be taken as a preferred data intelligent tool for river stage and river flow prediction.
Understanding the effects of complex issues such as water scarcity on human society from the people's perspective is necessary to show how to adapt to these challenges. This research investigates and ...prioritizes the effects of water scarcity on the sustainability of rural communities through a mixed research methodology, including a case study and a survey in a semi-arid region, located in southern Iran. The results of using the Analytical Hierarchy Processing (AHP) technique showed that local people identify the economic dimension of sustainability as a priority dimension. Moreover, the alternative of unsustainability under water scarcity in the area received the highest priority and had a larger value than the sustainability alternative. This can be the result of the restricting international policies against Iran and the global climatic condition. Local communities, particularly farmers, perceive climate change and water scarcity as a global issue and a local challenge, which causes semi-arid areas to move towards unsustainability rather than sustainability. The sustainability of semi-arid areas under water scarcity requires climate change adaptation, appropriate long-term planning, and the removal of restricting international economic policies against nations.
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•The climate becomes warmer or colder and the annual precipitation of an area increases under climate change conditions.•Climate change and water scarcity are recognized as serious risks threatening sustainable development in various aspects.•Components affecting this prioritization are mostly climate change, poor long-term planning, and restricting global economic policies toward Iran.
Carbon dioxide emissions from fossil fuel-fired power stations are attracting growing attention as a potential approach for reducing greenhouse gas emissions. Post-combustion capture of CO2 with ...monoethanolamine (MEA) is one of the most successful and mature technologies for mitigating carbon dioxide emissions. The most crucial problem of this technique is the high heat requirement of the reboiler for solvent regeneration. In this study, seven different configurations for carbon capture, namely, standard absorption, vapor recompression, vapor recompression process with split-flow, absorption column with intercooling, rich-split, combined, and rich-split with vapor recompression, are studied. The simulation results showed that the reboiler energy consumption intensity of alternative configurations lowered by 15.2 %, 18.4 %, 2.9 %, 7.4 %, 20.3 %, and 23.2 %, respectively, with regard to the standard absorption configuration. Seven configurations were ranked based on the total investment cost, steam consumption, power consumption, and water consumption. Combined and rich-split were the best, and vapor recompression and Rich-split with vapor recompression were the worst.
•Seven different configurations of carbon capture by MEA absorption were studied.•TOPSIS method was used to rank configurations based on techno-economic criteria.•Combined and rich-split process configurations were the best ones.•Vapor recompression process configuration was the worst configuration.
We propose a novel optimization method based on wideband orthogonal frequency division multiplexing (OFDM) signals to detect random extended targets with known covariance matrix in the presence of ...additive white Gaussian noise. Mutual information is used as our criterion for waveform design under transmitted power constraint. We utilize the advantage of OFDM signal to intelligently design the complex weights of the transmitted waveform. For making complete use of the transmission power, a novel iterative algorithm is introduced based on maximizing mutual information criterion between the target impulse response and the received echoes. We have derived the optimal Neyman–Pearson detector for the corresponding hypothesis testing problem and provided different numerical experiments to demonstrate the achieved performance improvement when the proposed method is applied.
The efficient and sustainable use of water has become a necessity in regions prone to drought and water scarcity. One such region is the Fars province of Iran, where farmers often face uncertainties ...in irrigation water supply due to frequent droughts and declining groundwater levels. This study employed a quantitative research methodology, utilizing surveys and questionnaires to collect data. Specifically, the study used the choice experiment (CE) methodology to evaluate policy attributes aimed at guaranteeing agricultural water supply. The research was conducted in Marvdasht County within the Fars province, with a sample size of 170 farmers and 4080 observations collected in 2015. The collected data were analyzed using the conditional logit (CL) model. The sample size was determined using the stratified random sampling method. The results of the study indicate that age has a negative effect on farmers' willingness to pay (WTP) for guaranteed water supply, while education has a positive effect. Additionally, the study found that farmers' WTP for different policies varied, with the highest WTP observed for the use of water-saving technologies (estimated at 254.89 IRR per m3) across all areas. Consequently, the study recommends that policies promoting the adoption of water-saving technologies should be prioritized globally. It is worth noting that water policies can significantly differ between countries and regions due to various factors, including local water challenges, legal frameworks, cultural norms, and socio-economic conditions. Therefore, when formulating water policies, it is crucial to consider the specific context and tailor them to the unique circumstances of each region or country.
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•Evaluate attributes of policies to guarantee agricultural water supply by using CE method.•Farmers didn't have an amount of guaranteed irrigation water supply due to frequent droughts.•CL model with interaction effects has been used to import the socio-economic characteristics of farmers.•The policies aimed at the adoption of water-saving technologies should be given a higher preference.•A common understanding of water management is needed by stakeholders.
This paper investigates the dynamics of the time-series of water temperature of the Skokomish River (2019–2020) at hourly time scale by employing well-known nonlinear methods of chaotic data analysis ...including average mutual information, false nearest neighbors, correlation exponent, and local divergence rates. The delay time and the embedding dimension were calculated as 1400 and 9, respectively. The results indicated that the thermal regime in this river is chaotic due to the correlation dimension (1.38) and the positive largest Lyapunov exponent (0.045). Furthermore, complex networks have been applied to study the periodicity of thermal time-series throughout a year. A special algorithm is then used to find the so-called communities of the nodes. The algorithm found three communities which have been called Cold, Intermediate, and Warm. The temperatures in these three communities are, respectively, in the intervals (0.8, 5.8), (5.8, 11.63), and (11.63, 15.8). This analysis indicates that highest variations in water temperature occur between warm and cold seasons, and complex networks are highly capable to analyze hydrothermal fluctuations and classify their time-series.
Infectious bronchitis virus (IBV) is one of the most critical pathogens in the poultry industry, causing serious economic losses in all countries including Iraq. IBV has many genotypes that do not ...confer any cross-protection. This virus has been genotyped by sequence analysis of the S1 glycoprotein gene. A total of 100 tracheal and kidney tissue specimens from different commercial broiler flocks in the middle and south of Iraq were collected from September 2013 to September 2014. Thirty-two IBV-positive samples were selected from among the total and were further characterized by nested PCR. Phylogenetic analysis revealed that isolates belong to four groups (group I, variant 2 IS/1494-like; group II, 793/B-like; group III, QX-like; group IV, DY12-2-like). Sequence analysis revealed nucleotide sequence identities within groups I, II, and III of 99.68 %-100 %, 99.36 %-100 %, and 96.42 %-100 %, respectively. Group I (variant 2) was the dominant IBV genotype. One Chinese-like recombinant virus (DY12-2-like) that had not been reported in the Middle East was detected. In addition, the presence of QX on broiler chicken farms in the area studied was confirmed. This is the first comprehensive study on the genotyping of IBV in Iraq with useful information regarding the molecular epidemiology of IBV. The phylogenetic relationship of the strains with respect to different time sequences and geographical regions displayed complexity and diversity. Further studies are needed and should include the isolation and full-length molecular characterization of IBV in this region.
This study has been done with the aim of developing and validating a perceptual scale for small‐scale farmers in arid regions and also redirecting interventions towards sustainability; it was ...conducted in the two qualitative and quantitative phases. In the scale validation process, principal component analysis was employed to identify the latent dimensions of farmers' perceptions of climate change. The results showed that the scale of farmers' perceptions of climate change has five latent dimensions including “awareness and knowledge,” “ascription of responsibility,” “forgetfulness and optimism about the future,” “perceived risk,” and “human agency.” The results of model validation revealed that all fitness indices are at a suitable level, and this scale might be used by climate change social interventions for sustaining agricultural activities, in water‐scarce areas. Given that forgetfulness and optimism are due to the weakness of farmers' episodic memory, it was recommended that climate change social interventions be focused on improving episodic memory using episodic future thinking.
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