Change-point analysis of time-series data plays a vital role in various fields of earth sciences under changing environments. Most of the analysis approaches were usually designed to detect the change-point in the level of time-series mean. In this study, we aimed to propose a non-parametric approach to detect the change-point of different parameters of time-series data. In this approach, the Boot- strap method, coupling with Kernel density estimation, was first used to estimate the probability distribution function (pdf) of a parameter before and after any potential change-points. Second, the Ar-index based on the uncross area of the two pdfs was designed to quantify the difference of the parameter before and after each potential change-point. Finally, the potential change-point owning the largest Ar-index value was determined as the locations of the change-point of the parameter. The hydrological extreme series from four stations in the Hanjiang basin were used to demonstrate this approach. The Pettitt test method commonly used in hydrology was employed as a comparison to indirectly analyze the reliability of the proposed approach. The results show that change-point detected by the proposed approach in the four stations are identified with those detected by the Pettitt approach in the level of time-series mean. But in comparison with the Pettitt test, the proposed approach can provide more detection information for other parameters, such as coefficient of variation (Cv) and coefficient of skewness (Cs) of the series. The results also show that the degree of change in the series mean is greater than its Cv and Cs, while the degree of change in series Cv is greater than its Cs.

The construction of a model based on an analytic system and dynamic structure is an important technique in lake manage-ment. The Yan-Model conducts system simulations based on the dynamics of the main aquatic species but does not include filter-feeding fish and N elements, which have important effects on eutrophication. Based on the Yan-Model, modules for the filter-feeding fish A. nobilis and the N cycle were constructed and combined to form a new model, the Yan-Model II. After model calibration and validation, a scenario analysis was performed to simulate eutrophication regulation and external pollution impacts. The results show the following: (1) the simulated and measured values of the lake ecosystem were highly consistent (R > 0.9, RSR < 0.7); (2) an eutrophic lake could be effectively restored by planting Vallisneria natans (Lour.) Hara with low biomass density; (3) assuming that urban sewage drained into the lake, equal or more than 600 m3 of urban sewage would lead to an increase in the Chl-a concentration to a level that exceeded the eutrophication threshold; and (4) an Aristichthys nobilis density of 50 g/m3 had a strong ability to control phytoplankton growth. Using the improved model, this study successfully guided the ecological restoration of Dongshan Lake. This model can be used for lake management and sustainable development in urban ecosystems.

Open Access: the version of record is freely available at the ISEIS, International Society for Environmental Information Sciences, website via the DOI URL: https://doi.org/10.3808/jei.202100463.

In this paper the proposed constrained gravitational search algorithm (CGSA) is extended and used to solve multi-reservoir operation optimization problem. Tow constrained versions of GSA named partially constrained GSA (PCGSA) and fully constrained GSA (FCGSA) are outlined to solve this optimization problem. In the PCGSA, the problem constraints are partially satisfied, however, in the FCGSA, all the problem constraints are implicitly satisfied by providing the search space for each agent which contains only feasible solution and hence leading to smaller search space for each agent. These proposed constrained versions of GSA are very useful when they are applied to solve large scale multi-reservoir operation optimization problem. The constrained versions of GSA are formulated here for both possible variables of the problem means considering water release or storage volumes as the decision variables of the problem and therefore first and second formulations of these algorithms are proposed. The proposed algorithms are used to solve the well-known four and ten reservoir operation optimization problems and the results are presented and compared with those of original form of the GSA and any available results in the literature. The results indicate the superiority of the proposed algorithms and especially FCGSA over existing methods to optimally solve large scale multi-reservoir operation optimization problem.

The spatial distribution, magnitude and timing of precipitation events are being altered globally, often leading to extreme hydrologic conditions with serious implications to ecosystem services, water, food and energy security, as well as the welfare of billions of people. Motivated by the pressing need to understand, from a hydro-ecological perspective, how the dynamic nature of the hydrologic cycle will impact the environment in water-stressed regions, we implemented a novel approach that predicts precipitation spatio-temporal trends over the drought-burdened region of East Africa, based on other major hydrological components, such as vegetation water content (VWC), soil moisture (SM) and surface temperature (ST). The spatial patterns and characteristics of the inter-relations among the four aforementioned hydrologic variables were investigated over regions of East Africa characterized by different vegetation types and for various precipitation intensity rates during 2003-2011. To this end, we analyzed multi-year satellite microwave remote sensing observations of SM, ST, and VWC (derived from Naval Research Laboratory's WindSat radiometer) as well as their response to precipitation patterns (derived from NASA's TRMM 3B42 V7). We categorized precipitation into four bins (ranges) of intensity and trained five different state-of-the-art machine learning models for each of these categories. The models were then applied to predict the spatiotemporal precipitation dynamics over this complex region. Specifically, the Random Forest and Linear Regression models outperformed the others with the normalized mean absolute error being less than 27% for all of the categories. The characteristics of the predicted precipitation were in turn used to classify vegetation regimes in East Africa. Our results indicate significant discrepancies in the performance of the models with varying values in the predicting skill as well as their ability to accurately classify vegetation into different types. Our predictive models were able to forecast the three vegetation regimes, i.e., Forest/Woody Savanna, Savanna/Grasslands and Shrubland, with precision rate of at least 81% for all of the aforementioned precipitation bins.

River sediments, functioning as sink and source for nutrients, are one of the most diverse bacteria habitats in freshwater ecosystems. Recently, more attention has been paid to the sediment bacteria because of their important roles in biogeochemical cycling. Our study addresses the question of how sediment bacterial community varies taxonomically and functionally along one of the largest plateau river in the world (the Yarlung Tsangpo River) subject to anthropogenic pressures, including wastewater discharge and river damming, as they may lead to adverse impacts on river ecosystems. The results indicated that river damming retained biogeochemical nutrients of carbon, silica and nitrogen in the reservoir, while phosphorus was more sensitive to wastewater discharge. Besides, wastewater discharge resulted in asynchronous change of biomass and diversity in sediment bacteria while they were both inhibited by the construction of dam. Moreover, significant alterations in the community composition were observed in dam-associated sites, while according to exploratory bioinformatics prediction tool of PICRUSt, functional variation was not detected between upstream and downstream of the dam due to functional redundancy. In addition, revealed by General Additive Model (GAM) and Mantel test results, elevation was the endemic driver shaping the sediment bacterial community diversity and composition along with pH, while nutrient concentrations were responsible for functional variation. Furthermore, little synchronized dynamics of co-occurrence was exhibited in the sediment bacteria in the Yarlung Tsangpo River. Therefore, our study proposed that sediment bacterial community should be defined taxonomically and functionally when studying its variation in river ecosystems.

In oil sands open-pit mining, further processing of the extracted oil sands generates massive volumes of tailings. To save space, the tailings are deposited in in-pit tailings containments constructed by internal dykes using mine waste material. In this paper, an integrated mine planning framework is proposed and implemented using mixed-integer linear programming to optimize the production schedule with respect to dyke construction and in-pit tailings deposition. A case study is carried out to verify the performance of the proposed optimization model. The results demonstrate how the produced tailings are deposited in the excavated mining pits as the mining operation proceeds and the in-pit dykes are constructed using mine waste material. The framework facilitates sustainable oil sands mining through a reduced environmental footprint.

Information provision is a relatively recent but steadily growing environmental policy tool. Its emergency and topicality are due to the current escalation of ecological threats. Meanwhile, its high complexity and flexibility require a comprehensive approach to its design, which has to be tailored for specific characteristics of production process, market structure, and regulatory goals. This work proposes such an approach and builds a framework based on a three-level mathematical program extending well-known two-level Stackelberg game by introducing one more economic agent and one extra level of this sequential game. This study provides simple and very intuitive algorithms to compute optimal multi-tier information provision policies, both mandatory and voluntary. The paper urges for the wide implementation of such efficient environmental policy design tools.

In this study, a theoretical model of ecosocial climax is developed to evaluate human community in order to ensure efficient protection of ecosystem. Unlike previous works that emphasize analysis of nature, the present model are based on such ecological concepts as ecological chain and climax to analyze the problems of ecosocial system. The proposed model is used to compare the two ecosystems in George Eliot’s Silas Marner: the ecologically problematic community of Lantern Yard, and the ecologically sustainable community of Raveloe community. The result shows that governed by check and balance, negotiation and concession, morality and mutual contract, and rule of law, Raveloe is a climax community that encourages equality, interaction and exchange, adaptability and tolerance, diversity and wholeness, dynamic stability and sustainable development. It is shown that George Eliot’s ideal society is one of ecological social order with harmonious human relationships formed in humble reconciliation with nature in fear of God so that humans do not pose as threat to the equilibrium of nature. Hopefully, this interdisciplinary research might prove helpful to analysis of social problems in human society to contribute to reconciliation between humans and nature.

The OH-induced reactions are the most important reactions for the degradation of pharmaceutical and personal care proucts (PPCPs) in advanced oxidation process (AOP) systems. In this work, the transformation mechanisms of a typical PPCP, ketprofen (KP), are investigated in detail by combined density functional theory (DFT) simulations and laboratory experiments. We find that Habstraction pathways are preferred in the OH-initiated reactions, and the influence of the hydrogen bond between the OH radical and the carboxyl group cannot be neglected. The subsequent decarboxylation and decomposition reactions are likely to occur. In addition, under highly acidic condition, the protonation of the carbonyl group in KP or in other benzophenone-like compounds might inhibit the decomposition reactions. Meanwhile, the simulation results are well supported by the Fenton experiments.