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To accurately evaluate the development level of ecological civilization in coastal cities, this paper proposes an evaluation algorithm of coastal city ecological civilization development based on Improved BP neural network, constructs the evaluation index system, and establishes the BP neural network-based evaluation model. By collecting the relevant data of 30 cities in China Line standardization, as the input learning matrix, entropy and coefficient of variation are used to evaluate the development level of ecological civilization. Through 5000 training times, the error accuracy is close to 10–7, and the cities with low ecological civilization level and less cultivated land resources per capita are found out. Based on the improved BP neural network method, according to the development level of coastal cities, the ecological culture of coastal cities is put forward as a whole. The countermeasures and suggestions of construction are given. • In this study, the ecological civilization development level of the coastal cities in Jiangsu was evaluated. • The evaluation results showed the overall development level of ecological civilization. • In the assessment, the comprehensive level of the secondary indexes is better than that of Donghai and Guanyun. • Jiangsu coastal cities have higher ecological civilization development levels, and Donghai and Guanyun is relatively low. [ABSTRACT FROM AUTHOR]

Distributed Constraint Optimization (DCOP)-based approaches, as the distributed version of constraint optimization, provide a framework for coordinated decision making by a team of agents. In this paper, an agent-based DCOP model is developed to allocate water and reclaimed wastewater to demands considering the conflicting interests of involved stakeholders. One of the well-known DCOP algorithms, ADOPT1, is modified to incorporate an agent responsible for monitoring and conserving water resources. This new algorithm considers the social characteristics of agents and a new form of interaction between agents. For the first time in the literature, a real-world water and reclaimed wastewater allocation problem is formulated as a DCOP and solved using the Modified ADOPT (MADOPT) algorithm. To evaluate the MADOPT algorithm, it is applied to a water and reclaimed wastewater allocation problem in Tehran, Iran. The results illustrate the applicability and efficiency of the proposed methodology in dealing with large-scale multi-agent water resources systems. It is also shown that agents' selfishness and social relationships could affect their water use policies. • A multi-agent model is presented for urban water and treated wastewater management. • A modified version of Asynchronous Distributed Constraint Optimization is proposed. • The algorithm considers a monitoring agent which exists in environmental systems. • The algorithm is applied to a large-scale real-world environmental system. • The results illustrate the applicability and efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

Parameters monitoring is essential to maintain the stability and efficiency of the wastewater treatment process, which has spurred ubiquitous installation of sensors in wastewater treatment plants (WWTPs). As the rich process data of WWTPs is not effectively transformed into actionable knowledge for system optimization due to improper sensor installation, the sensor placement scheme needs to be optimized. In this paper, a weighted sensor placement optimization model based on sensor cost, information richness and reliability is established to transform the sensor optimization problem to a nonlinear mathematical programming problem. Then a discrete multi-objective state transition algorithm is proposed to find the Pareto optimal solutions. Finally, an evaluation strategy is designed to select the most suitable solution for industrial application. The results of simulation experiments on three different WWTPs demonstrate the validity and superiority of the proposed method, increasing the degree of variable observability and measurement redundancy while keeping the sensor cost at a low level. [Display omitted] • A weighted multi-objective sensor placement model considering importance of flows is established. • A novel discrete multi-objective state transition algorithm is proposed to find optimal solutions effectively. • An evaluation strategy consisting of corrosion degree and maintenance cost is designed for decision making. • The applicability of the proposed method is demonstrated by three typical WWTP configurations. [ABSTRACT FROM AUTHOR]

Water quality monitoring programs have been widely implemented worldwide to monitor and assess water quality and to understand its trends. However, water quality analysis based on point-source field observations is difficult to perform at large spatial and temporal scales. In this paper, a fully automated Google Earth Engine (GEE) application algorithm was developed to estimate the total suspended solids (TSS) concentration in the Chesapeake Bay based on the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra imagery. Combining long-term archived satellite data (2002–2020) with field observations, the concentrations and spatiotemporal patterns of TSS in the bay water were evaluated. Time series analysis showed a statistically significant decreasing trend in TSS concentration between 2002 and 2020, suggesting that the sediment concentration in the bay has gradually been decreasing over the last two decades. The decreasing trend was observed in 49 out of 60 segments of the bay, implying that substantial progress has been made toward attaining the Chesapeake Bay water quality standards. Based on the monthly TSS analysis, 12 major peak events of TSS were identified in the Chesapeake Bay, which coincided with extreme winter blizzards and summer hurricane events. The GEE application and the results presented herein complement the existing monitoring program in attaining the water quality standards of the bay. • Chesapeake Bay's temporal trends in water quality were assessed from 2002 to 2020 using Google Earth Engine Application. • New empirical model for satellite retrieval of total suspended solids was developed for the Chesapeake Bay waters. • The total suspended solids in the bay shows a significant decreasing trend (p < 0.05) in the last 20 years. • Short-term fluctuations caused by extreme weather events are evident. [ABSTRACT FROM AUTHOR]

In water distribution system (WDS), chlorine is often injected as disinfectant to control the growth of microorganism in WDS. However, the chlorine reacts with organism to form disinfectant byproduct, which can bring risk to human health. As such, the chlorine at nodes in WDS should be kept between acceptable range, which is simulated based on the response at nodes corresponding to unit injection mass at boosters. To deal with the uncertainty in chlorine decay process and lower and upper chlorine concentration limits, an inexact left-hand-side chance-constrained programming (ILCCP) model was proposed in this paper and applied to two WDSs. The response coefficients matrix was expressed as random variables with normal probability distribution in the constraints of lower and upper limits, which was obtained through Monte Carlo simulation by linking with EPANET software. The intervals of injection mass were obtained by solving the ILCCP model with a two-step algorithm. Moreover, the effects of random bulk decay coefficients and interval of chlorine limits on the injection mass were analyzed and compared. The results indicated that the lower bounds of optimal injection mass increased with the rise of probability lever for lower limits, while the upper bounds decreased with the rise of the probability level for upper limits. The results can help managers determine the chlorine injection mass under uncertain scenarios, and can be applied to more complicated WDS to obtain meaningful results. • An inexact left-hand-side chance-constrained programming model was proposed. • Response coefficients were expressed as random variables with normal distribution. • Effects of decay coefficients and limits on the injection mass were analyzed. [ABSTRACT FROM AUTHOR]