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The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

The development of advanced computational models for improving the accuracy of streamflow forecasting could save time and cost for sustainable water resource management. In this study, a locally weighted learning (LWL) algorithm is combined with the Additive Regression (AR), Bagging (BG), Dagging (DG), Random Subspace (RS), and Rotation Forest (RF) ensemble techniques for the streamflow forecasting in the Jhelum Catchment, Pakistan. To build the models, we grouped the initial parameters into four different scenarios (M1–M4) of input data with a five-fold cross-validation (I–V) approach. To evaluate the accuracy of the developed ensemble models, previous lagged values of streamflow were used as inputs whereas the cross-validation technique and periodicity input were used to examine prediction accuracy on the basis of root correlation coefficient (R), root mean squared error (RMSE), mean absolute error (MAE), relative absolute error (RAE), and root relative squared error (RRSE). The results showed that the incorporation of periodicity (i.e., MN) as an additional input variable considerably improved both the training performance and predictive performance of the models. A comparison between the results obtained from the input combinations III and IV revealed a significant performance improvement. The cross-validation revealed that the dataset M3 provided more accurate results compared to the other datasets. While all the ensemble models successfully outperformed the standalone LWL model, the ensemble LWL-AR model was identified as the best model. Our study demonstrated that the ensemble modeling approach is a robust and promising alternative to the single forecasting of streamflow that should be further investigated with different datasets from other regions around the world.

In recent years, food security, especially supply, has been an important issue in China’s agricultural production. The stability of grain prices is related to the stability and development of the grain market. Based on agricultural production data from 1970 to 2015, this paper explores the influence of agricultural product price fluctuation on grain production by using the cobweb theory and vector error correction (VEC) model. The results show that changes in grain production in China are affected by fluctuations in agricultural product prices, that the production change lags behind the price change, and that there is a long-term equilibrium relationship between grain yield and agricultural product price. A Granger causality test shows that the change in agricultural product price is the Granger cause of grain yield change.

In recent years, food security, especially supply, has been an important issue in China’s agricultural production. The stability of grain prices is related to the stability and development of the grain market. Based on agricultural production data from 1970 to 2015, this paper explores the influence of agricultural product price fluctuation on grain production by using the cobweb theory and vector error correction (VEC) model. The results show that changes in grain production in China are affected by fluctuations in agricultural product prices, that the production change lags behind the price change, and that there is a long-term equilibrium relationship between grain yield and agricultural product price. A Granger causality test shows that the change in agricultural product price is the Granger cause of grain yield change.

The COVID-19 pandemic represents a type of force majeure that significantly and unexpectedly affected all human lifestyles. This study includes an integrative review of articles published across Scopus and Web of Science journals and compiled using the systematic review methodology based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement and VOSreview (visualization of similarities) software by defining keywords that include “construction industry” and “force majeure” and “environmental risks” as a starting point. Moreover, the research years and the countries covered by this research were determined in a second stage. Finally, the abstracts of selected studies were reviewed in order to extract factors similar to the pandemic conditions of COVID-19 along with the brief results of the research. Out of 6384 publications identified and 56 publications reporting, 20 studies fulfilled the inclusion criteria with full text. Based on our findings, there has been a continuous growth of publications on construction risk and environmental research since 2010. Malaysia had the greatest contribution to the research topic of the countries covered by the study, followed by Egypt. The Engineering, Construction and Architectural Management journal published the greatest number of publications related to the research topic. In this review, the most important previous studies are classified according to their handling of force majeure and environmental risks and the most important factors mentioned in these studies are identified. In addition, recommendations are made for dealing with the COVID-19 pandemic and for mitigating its effects on the construction industry in the Arab world and Malaysia. The results of this review will benefit researchers and construction companies alike in furthering research on reducing the risks of COVID-19 to construction projects and avoiding the significant economic loss that results from stopping these projects.

The COVID-19 pandemic represents a type of force majeure that significantly and unexpectedly affected all human lifestyles. This study includes an integrative review of articles published across Scopus and Web of Science journals and compiled using the systematic review methodology based on the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement and VOSreview (visualization of similarities) software by defining keywords that include “construction industry” and “force majeure” and “environmental risks” as a starting point. Moreover, the research years and the countries covered by this research were determined in a second stage. Finally, the abstracts of selected studies were reviewed in order to extract factors similar to the pandemic conditions of COVID-19 along with the brief results of the research. Out of 6384 publications identified and 56 publications reporting, 20 studies fulfilled the inclusion criteria with full text. Based on our findings, there has been a continuous growth of publications on construction risk and environmental research since 2010. Malaysia had the greatest contribution to the research topic of the countries covered by the study, followed by Egypt. The Engineering, Construction and Architectural Management journal published the greatest number of publications related to the research topic. In this review, the most important previous studies are classified according to their handling of force majeure and environmental risks and the most important factors mentioned in these studies are identified. In addition, recommendations are made for dealing with the COVID-19 pandemic and for mitigating its effects on the construction industry in the Arab world and Malaysia. The results of this review will benefit researchers and construction companies alike in furthering research on reducing the risks of COVID-19 to construction projects and avoiding the significant economic loss that results from stopping these projects.

In response to the pressing need for transportation decarbonization, this paper examines the often overlooked domain of inland waterway transport and seeks to answer which alternative fuel or power source is the most promising for that sector. As the shipping industry significantly contributes to global carbon emissions, it has been shifting towards alternative fuels and decarbonization measures in the effort to reduce them, whereas the inland waterways, operating predominantly on diesel engines, have not achieved equivalent substantial progress. Employing a systematic literature review and regional analysis, this study identifies notable trends. LNG initially emerged as a favored alternative fuel, but recent studies emphasize a shift towards “greener” solutions like batteries and hydrogen. Europe and Asia lead in these developments. This investigation uncovers critical gaps in research and development, particularly in the Northern European countries that have extensive inland waterway networks. It also calls for future studies to explore the performance of vessels that have adopted LNG compared to other emerging alternatives and emphasizes the importance of considering the time lag between technology development and research publication.