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With climate warming and accelerated urbanisation, severe urban flooding has become a common problem worldwide. Frequent extreme rainfall events and the siltation of drainage pipes further increase the burden on urban drainage networks. However, existing studies have not fully considered the effects of rainfall and pipeline siltation on the response characteristics of flooding when constructing numerical models of urban flooding simulations. To solve this problem, a surface-subsurface coupling model was constructed by combining the Saint-Venant equation, Manning equation, a one-dimensional pipeline model (SWMM), and a two-dimensional surface overflow model (LISFLOOD-FP). Then, the SWMM model considering pipeline siltation and the two-dimensional surface overflow model (LISFLOOD-FP) were coupled with the flow exchange governing equation, and the urban flooding response characteristics considering the coupling effect of "rainfall and drainage pipeline siltation" were analysed. To enhance the solvability of waterlogging prediction, an intelligent prediction model of urban flooding based on Bayes-CNN-BLSTM was established by combining a convolutional neural network (CNN), bidirectional long short-term memory neural network (BLSTM), Bayesian optimisation (Bayes), and an interpretable loss function error correction method. The actual rainfall events and flooding processes recorded by the monitoring equipment at Huizhou University were used to calibrate and verify the model. The results show that in the Rainfall 1 and Rainfall 2 scenarios, the overload rates of the pipelines in the current siltation scenario were 60.06 % and 68.37 %, respectively, and the proportions of overflow nodes were 24.87 % and 25.89 %, respectively. When the drainage network was initially put into operation, the overload rates of the pipeline were 36.67 % and 41.16 %, and the overflow nodes accounted for 3.05 % and 4.06 %, respectively. The inundated area and volume of urban flooding increased when the combined siltation coefficient (CSC) was 0.2; therefore, two desilting schemes were determined. Under Rainfall 1, Rainfall 2, and the four rainfall recurrence periods, the Bayes-CNN-BLSTM model had clear advantages in terms of accuracy, reliability, and robustness., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Pollution control and carbon emission reduction pose significant challenges for developing countries, and achieving synergistic reductions in pollution and carbon emissions (SRPCs) has emerged as the optimal choice. Digitization, a prevailing trend in the current era, presents new opportunities for realizing the SRPC. We utilize data from Chinese A-share listed companies from 2007 to 2022 to investigate the impact of corporate digital transformation on the SRPC. The research reveals the following. (1) Enterprise digital transformation significantly promotes the SRPC, a conclusion validated through a series of robustness tests. However, the SRPC resulting from digital transformation is characterized by weak synergy, which is primarily observed in the coordinated reduction in air pollution and carbon emissions. (2) This effect is notably stronger for companies near environmental regulatory authorities, those receiving government environmental subsidies, and state-owned enterprises (SOEs). (3) Enhancing managerial collaborative management capabilities, promoting corporate technological innovation capabilities, and alleviating financing pressure are the primary mechanisms at play. This research provides important policy and practical insights for promoting the SRPC in the context of digitization, fostering sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Ecological drought is a complex comprehensive process in which the water conditions for normal growth and development of vegetation are changed due to insufficient water supply. In this study, based on the remotely sensed vegetation health index (VHI) and the Famine Early Warning Systems Network Land Data Assimilation System (FLDAS) datasets from 1982 to 2020 in China, the Breaks For Additive Seasons and Trend algorithm (BFAST) was used to analyze the dynamic variations of ecological drought, the standardized regression coefficient method was applied to identify the primary drivers of ecological drought, and the regression analysis was adopted to reveal the coupling effect of atmospheric circulation factors on ecological drought. The results indicated that: (1) the ecological drought showed an overall decreasing trend during 1982-2020 in China, with a negative mutation point that occurred in April 1985; (2) spring drought and summer drought were more likely to occur in the South China, and autumn drought and winter drought were more likely to appear in the Sichuan Basin; (3) the propagation time from meteorological to ecological drought was shorter in summer (2.67 months) and longer in winter (7 months), with average r values of 0.76 and 0.53, respectively; (4) the Trans Polar Index (TPI), Arctic Oscillation (AO) and El Niño-Southern Oscillation (ENSO) had important impacts on ecological drought, which can be used as input factors of drought early warning system to improve the accuracy of drought prediction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

River eco-environmental value assessment is indispensable for the optimal allocation of watershed water resources. In this study, river eco-environmental values were divided into the values inside and outside the river based on the energy transfer and transformation of the water cycle. Their spatial distribution characteristics (spatial distribution map, spatial autocorrelation, and spatial aggregation) of 67 regions (states, leagues, and cities) in the Yellow River Basin (YRB) were analysed by combining emergy theory and GeoDa 1.14 software (emergy-GeoDa), and the significance of the results was tested. The results showed that: (1) the eco-environmental values inside the river were higher than those outside in the YRB, proving that eco-environmental water inside the river should be guaranteed and water consumption outside the river should not occupy water inside the river from the perspective of value; (2) the spatial distributions of eco-environmental values inside and outside the river were uneven, but obvious spatial aggregations were observed; (3) high- and low-value aggregations of eco-environmental values were observed inside the river in the lower and upper reaches of the YRB, respectively; (4) high- and low-value aggregations of eco-environmental values were observed outside the river in the middle and upper reaches of the YRB, respectively. It was suggested that ecological conservation and high-quality development should be considered as the goals for consolidating the river eco-environmental values in high-value areas and promoting in low-value areas, and low-value areas should be improved by high-value areas while allocating water resources in the YRB. These results provide suggestions for the sustainable development of river eco-environmental system in the YRB from a spatial perspective. In addition, the analysis method is also applicable for studying the spatial distribution characteristics of the values generated by the water and energy cycles of other regions., Competing Interests: Declaration of competing interest All authors declare that No conflict of interest exists., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Promoting environmental management system reform in an orderly manner and coordinating central and local environmental protection responsibilities are important for high-quality economic development. Based on panel data of 289 cities in China from 2008 to 2016, this paper uses the fixed effects model and threshold regression model to discuss the relationships among regional competition, environmental decentralization, and target selection of local governments and to analyze whether environmental decentralization produces the Porter effect. Findings show that environmental decentralization does significantly promote economic development, strengthen environmental pollution control, and generate a strong Porter effect, due to greater R&D investment, improvement in green technology innovation ability, and optimization of the industrial structure. The effect of environmental decentralization shows significant regional heterogeneity in terms of regional financial pressure, economic development level, and environmental pressure, while regional competition distorts the effect of environmental decentralization. With the intensification of regional competition, environmental decentralization greatly improves the emission intensity of pollutants, whereas it promotes economic development after inhibiting it. The above conclusions are of great significance for pushing forward environmental decentralization, formulating a differentiated environmental decentralization strategy, and perfecting the government performance appraisal system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Water rights transaction has proved to be an effective method for constructing an efficient water distribution system (WDS) in various regions of the Yellow River Basin (YRB). In this study, an optimal WDS in the YRB is proposed by considering the comprehensive value of water resources, administrative management system, and market-based system. To accurately quantify the comprehensive value of water resources, the work analysis method of suspended load and bedload based on the emergy theory and time-averaged motion equation is introduced, and the quantification process of sediment transport value in the river course is formulated in the YRB. Based on this, an administrative and market-based game for water rights transaction is formulated. In this double-layer game model, the administrative authorities of the basin (Yellow River Conservancy Commission) and the corresponding regions (Water Resources Department) seek to maximize their own target revenue function/comprehensive value of the water resources. Then, the optimal trading quantity of water in each region and the bargain price can be solved. A case study is presented in the YRB to verify the effectiveness of this method. The results reveal that (1) the error rate of the riverbed shear stress as well as the sediment transport rate between the theoretical value and the calculated value does not exceed 8.76%, which indicates the rationality of the calculation method of sediment transport value; (2) the proposed dynamic differential game and pricing game perform well in determining the optimal trading quantity of water in each region. They also reveal the bargain price with optimal results of ¥ 4151.1456 half yearly and ¥ 8197.3466 per year in 2018, outperforming other methodologies., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)