China has made considerable efforts to mitigate the pollution of lakes over the past decade, but the success rate of these restoration actions at a national scale remains unclear. The present study ...compiled a 13-year (2005–2017) comprehensive dataset consisting of 24,319 records from China's 142 lakes and reservoirs. We developed a novel Water Quality Index (WQI-DET), customized to China's water quality classification scheme, to investigate the spatio-temporal pollution patterns. The likelihood of regime shifts during our study period is examined with a sequential algorithm. Our analysis suggests that China's lake water quality has improved and is also characterized by two WQI-DET abrupt shifts in 2007 and 2010. However, we also found that the eutrophication problems have not been eradicated and heavy metal (HM) pollution displayed an increasing trend. Our study suggests that the control of Cr, Cd and As should receive particular attention in an effort to alleviate the severity of HM pollution. Priority strategies to control HM pollution include the reduction of the contribution from mining activities and implementation of soil remediation in highly polluted areas. The mitigation efforts of lake eutrophication are more complicated due to the increasing importance of internal nutrient loading that can profoundly modulate the magnitude and timing of system response to external nutrient loading reduction strategies. We also contend that the development of a rigorous framework to quantify the socioeconomic benefits from well-functioning lake and reservoir ecosystems is critically important to gain leeway and keep the investments to the environment going, especially if the water quality improvements in many Chinese lakes and reservoirs are not realized in a timely manner.
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•China's lake and reservoir water quality was investigated using a 13-year dataset.•China has been successful in improving water quality during the 2005–2017 period.•Eutrophication has been alleviated, but not fully eliminated until 2017.•Heavy metal (Cr, Cd, and As) pollution showed an increasing trend since 2012.
Data are essential in all areas of geophysics. They are used to better understand and manage systems, either directly or via models. Given the complexity and spatiotemporal variability of geophysical ...systems (e.g., precipitation), a lack of sufficient data is a perennial problem, which is exacerbated by various drivers, such as climate change and urbanization. In recent years, crowdsourcing has become increasingly prominent as a means of supplementing data obtained from more traditional sources, particularly due to its relatively low implementation cost and ability to increase the spatial and/or temporal resolution of data significantly. Given the proliferation of different crowdsourcing methods in geophysics and the promise they have shown, it is timely to assess the state of the art in this field, to identify potential issues and map out a way forward. In this paper, crowdsourcing‐based data acquisition methods that have been used in seven domains of geophysics, including weather, precipitation, air pollution, geography, ecology, surface water, and natural hazard management, are discussed based on a review of 162 papers. In addition, a novel framework for categorizing these methods is introduced and applied to the methods used in the seven domains of geophysics considered in this review. This paper also features a review of 93 papers dealing with issues that are common to data acquisition methods in different domains of geophysics, including the management of crowdsourcing projects, data quality, data processing, and data privacy. In each of these areas, the current status is discussed and challenges and future directions are outlined.
Key Points
Different crowdsourcing‐based methods for acquiring geophysical data are reviewed and categorized across seven domains of geophysics
Project management, data quality, data processing, and privacy issues have hampered wider uptake of crowdsourcing methods for practical applications
Future applications of crowdsourcing methods require public education, engagement strategies and incentives, technology developments, and government support
•Cyanobacteria serve as vital reservoir and source for antibiotic resistance genes.•Relatively high abundance of antibiotic resistance genes occurs in bloom season.•Cyanobacterial extracellular DNA ...carrying antibiotic resistance genes is persistent.•Antibiotic resistance genes are more stable in cyanobacteria at lower temperature.•Cyanobacterial blooms promote conjugative transfer of antibiotic resistance genes.
The widespread occurrence of antibiotic resistance genes (ARGs) throughout aquatic environments has raised global concerns for public health, but understanding of the emergence and propagation of ARGs in diverse environmental media remains limited. This study investigated the occurrence and spatio-temporal patterns of six classes of ARGs in cyanobacteria isolated from Taihu Lake. Tetracycline and sulfonamide resistance genes were identified as dominant ARGs. The abundance of ARGs in cyanobacteria was significantly higher in the bloom period than in the non-bloom period. The contribution and persistence of ARGs were higher in extracellular DNA (eDNA) than in intracellular DNA (iDNA) from cyanobacteria. Cyanobacteria-associated eDNA carrying ARGs was more stable at lower temperature. The relative abundances of ARGs in Microcystis and Synechococcus, the dominant genera of cyanobacterial blooms in Taihu Lake, were significantly higher than those in other cyanobacterial strains. The conjugative transfer efficiency for bacterial assimilation of ARGs in cyanobacteria was facilitated by increasing temperature and cyanobacterial cell concentration. Our results demonstrated that cyanobacteria could act as a significant reservoir and source for the acquisition and dissemination of ARGs in aquatic environments, hence the definition of negative ecological effects of cyanobacterial blooms was expanded.
Algal blooms in eutrophic waters often induce anoxia/hypoxia and enhance methane (CH4) emissions to the atmosphere, which may contribute to global warming. At present, there are very few strategies ...available to combat this problem. In this study, surface oxygen nanobubbles were tested as a novel approach for anoxia/hypoxia remediation and CH4 emission control. Incubation column experiments were conducted using sediment and water samples taken from Lake Taihu, China. The results indicated that algae-induced anoxia/hypoxia could be reduced or reversed after oxygen nanobubbles were loaded onto zeolite micropores and delivered to anoxic sediment. Cumulated CH4 emissions were also reduced by a factor of 3.2 compared to the control. This was mainly attributed to the manipulation of microbial processes using the surface oxygen nanobubbles, which potentially served as oxygen suppliers. The created oxygen-enriched environment simultaneously decreased methanogen but increased methanotroph abundances, making a greater fraction of organic carbon recycled as carbon dioxide (CO2) instead of CH4. The CH4/CO2 emission ratio decreased to 3.4 × 10–3 in the presence of oxygen nanobubbles, compared to 11 × 10–3 in the control, and therefore the global warming potential was reduced. This study proposes a possible strategy for anoxia/hypoxia remediation and CH4 emission control in algal bloom waters, which may benefit global warming mitigation.
The performance of the latest released Integrated Multi-satellitE Retrievals for GPM mission (IMERG) version 5 (IMERG v5) and the TRMM Multisatellite Precipitation Analysis 3B42 version 7 (3B42 v7) ...are evaluated and compared at multiple temporal scales over a semi-humid to humid climate transition area (Huaihe River basin) from 2015 to 2017. The impacts of rainfall rate, latitude and elevation on precipitation detection skills are also investigated. Results indicate that both satellite estimates showed a high Pearson correlation coefficient (r, above 0.89) with gauge observations, and an overestimation of precipitation at monthly and annual scales. Mean daily precipitation of IMERG v5 and 3B42 v7 display a consistent spatial pattern, and both characterize the observed precipitation distribution well, but 3B42 v7 tends to markedly overestimate precipitation over water bodies. Both satellite precipitation products overestimate rainfalls with intensity ranging from 0.5 to 25 mm/day, but tend to underestimate light (0–0.5 mm/day) and heavy (>25 mm/day) rainfalls, especially for torrential rains (above 100 mm/day). Regarding each gauge station, the IMERG v5 has larger mean r (0.36 for GPM, 0.33 for TRMM) and lower mean relative root mean square error (RRMSE, 1.73 for GPM, 1.88 for TRMM) than those of 3B42 v7. The higher probability of detection (POD), critical success index (CSI) and lower false alarm ratio (FAR) of IMERG v5 than those of 3B42 v7 at different rainfall rates indicates that IMERG v5 in general performs better in detecting the observed precipitations. This study provides a better understanding of the spatiotemporal distribution of accuracy of IMERG v5 and 3B42 v7 precipitation and the influencing factors, which is of great significance to hydrological applications.
Sediment dredging is an effective restoration method to control the internal phosphorus (P) loading of eutrophic lakes. However, the core question is that the real mechanism of dredging responsible ...for sediment internal P release still remains unclear. In this study, we investigated the P exchange across the sediment-water interface (SWI) and the internal P resupply ability from the sediments after dredging. The study is based on a one-year field simulation study in Lake Taihu, China, using a Rhizon soil moisture sampler, high-resolution dialysis (HR-Peeper), ZrO-Chelex diffusive gradients in thin film (ZrO-Chelex DGT), and P fractionation and adsorption isotherm techniques. The results showed low concentration of labile P in the pore water with a low diffusion potential and a low resupply ability from the sediments after dredging. The calculated flux of P from the post-dredged sediments decreased by 58% compared with that of non-dredged sediments. Furthermore, the resupply in the upper 20mm of the post-dredged sediments was reduced significantly after dredging (P<0.001). Phosphorus fractionation analysis showed a reduction of 25% in the mobile P fractions in the post-dredged sediments. Further analysis demonstrated that the zero equilibrium P concentration (EPC0), partitioning coefficient (Kp), and adsorption capacity (Qmax) on the surface sediments increased after dredging. Therefore, dredging could effectively reduce the internal P resupply ability of the sediments. The reasons for this reduction are probably the lower contributions of mobile P fractions, higher retention ability, and the adsorption capacity of P for post-dredged sediments. Overall, this investigation indicated that dredging was capable of effectively controlling sediment internal P release, which could be ascribed to the removal of the surface sediments enriched with total phosphorus (TP) and/or organic matter (OM), coupled with the inactivation of P to iron (Fe) (hydr)oxides in the upper 20mm active layer.
The probable mechanism of dredging on effectively controlling sediment internal P release to overlying waters is primarily to the removal of surface sediments rich in TP and/or OM combined with inactivation of P to iron (Fe) (hydr)oxides in the upper 20mm active layer sediments. Variations of SRP and soluble Fe (II) (a, c) measured by HP-Peepers and labile P and Fe (b, d) measured by DGT with depths in non-dredged and post-dredged sediments at the end of experiment. The location of the sediment-water interface is represented by zero. Values are means±SD of three replicates. Variations of adsorption isotherm parameters with sediment depths using the nonlinear form of the Langmuir equation in non-dredged and post-dredged sediment profiles at the end of experiment. Display omitted
•Evaluation of dredging was performed based on a one-year field simulation study.•Dredging decreased the concentrations of P in pore waters and its release to water.•Dredging reduced the resupply ability of internal P in the upper 20mm sediment.•The upper 20mm sediments had higher ability to adsorb and retain P after dredging.•Iron redox cycling of the upper 20mm sediment controlled internal P regeneration.
•Land use is an effective indicator for water quality in rapidly urbanized areas.•Multiple linear regression and CA–Markov models were combined to predict water quality.•The land use-based prediction ...model performed fairly well for total nitrogen.
Land use and land cover (LULC) have significant impacts on river water quality, particularly in regions subjected to rapid urbanization. However, it is unclear whether LULC (LULC type and pattern index) can be used as an effective indicator to predict water quality over the rapid urbanization regions. Here, we investigated the spatiotemporal changes of LULC and their impacts on the water quality of a river flowing through a rapidly developed area in China. Then, a cellular automata-Markov model was established to predict the LULC, which was used as a key indicator to predict future water quality by a multiple linear regression model. The results showed that construction land experienced rapid growth between 2000 and 2010 taking over arable land to a great extent, and the number of patch (NP) showed a significant downward trend during 2000–2010. The biochemical oxygen demand in five days (BOD5), total nitrogen (TN), and total phosphorus (TP) exhibited significantly positive correlations with construction land, while dissolved oxygen (DO) showed a significantly negative correlation with construction land. The DO exhibited a significantly positive correlation with the number of patch (NP), but TN and TP showed significantly negative correlations with NP. The water quality prediction model based on LULC performed well, especially TN prediction has a coefficient of determination of 0.691 and a mean relative error of 12.14%. The prediction of water quality in 2030 indicated that TN will not increase further, but TP will exhibit a remarkable increase in Zhenjiang city if the current development trend continues and no extra pollution control measures are taken.
It is typical to use a single portion of the available data to calibrate hydrological models, and the remainder for model evaluation. To minimize model‐bias, this partitioning must be performed so as ...to ensure distributional representativeness and mutual consistency. However, failure to account for data sampling variability (DSV) in the underlying Data Generating Process can weaken the model's generalization performance. While “K‐fold cross‐validation” can mitigate this problem, it is computationally inefficient since the calibration/evaluation operations must be repeated numerous times. This paper develops a general strategy for stochastic evolutionary parameter optimization (SEPO) that explicitly accounts for DSV when calibrating a model using any population‐based evolutionary optimization algorithm (EOA), such as Shuffled Complex Evolution (SCE). Inspired in part by the machine‐learning strategy of stochastic gradient descent (SGD), we use various representative random sub‐samples to drive the EOA toward the distribution of the model parameters. Unlike in SGD, derivative information is not required and hence SEPO can be applied to any hydrological model where such information is not readily available. To demonstrate the effectiveness of the proposed strategy, we implement it within the well‐known SCE, to calibrate the GR4J conceptual rainfall‐runoff model to 163 hydro‐climatically diverse catchments. Using only a single optimization run, our Stochastic SCE method converges to population‐based estimates of model parameter distributions (and corresponding simulation uncertainties), without compromising model performance during either calibration or evaluation. Further, it effectively reduces the need to perform independent evaluation tests of model performance under conditions that are represented by the available data.
Key Points
Development of a general strategy for accounting for uncertainty due to data sampling variability in the development of hydrological models
Demonstrating an efficient implementation using a modified version of the population‐based Shuffled Complex Evolution optimization algorithm
Large sample modeling study to demonstrate robustness of the method and to verify the reasonableness of using all data for calibration
Endocrine-disrupting compounds (EDCs) enter lakes mainly through river inflow. However, the occurrence, transport and fate of EDCs in the overlying water, suspended particulate matter (SPM) and ...sediment of inflowing rivers remain unclear. This study investigated the load of seven EDCs in a complex river-lake system of the Taihu Lake Basin during different seasons, with the aims of revealing the transport routes of EDCs and identifying the contributions from different sources. The results indicated that the levels of the seven EDCs in the wet season with high temperature and dilution effects were generally lower than those in the other seasons. EDC enrichment in the sediment was largely affected by the transport and fate of SPM. Moreover, the estrogenic activity and risks of EDCs were the highest in SPM. The mass loadings of particulate EDCs carried by SPM were 2.6 times that of overlying water. SPM plays a vital role in the transport and fate of EDCs in complex river-lake systems and thereby deserves more attention. Nonpoint sources, particularly animal husbandry activities and untreated domestic sewage, were the main sources of EDCs, amounting to 61.5% of the total load.
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•EDCs enrichment in sediment was affected by the spatial transport and fate of SPM.•The estrogenic activity levels and risks of EDCs were dominant by SPM.•The mass loadings of particulate EDCs were 2.6 times those of dissolved EDCs.•Nonpoint sources contributed to 61.5% of EDCs in the complex river-lake system.
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