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Impact Study of Impoundment of the Three Gorges Reservoir on Salt-Water Dynamics and Soil Salinity in the Yangtze River Estuary J. Environ. Inform. (IF 4.604) Pub Date : 2020-07-18 W. P. Xie; J. S. Yang; R. J. Yao; X. P. Wang
As the largest hydropower project in China, the impact of the Three Gorges Project (TGP) on the ecological environment has aroused public attention and has been studied from various aspects. After the TGP was operated, seasonably adjusted runof f by the Three Gorge Reservoir (TGR) might cause great changes of hydrological regime in the lower reaches of the Yangtze River, especially the estuarine areas
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Space-Time Ground-Level PM2.5 Distribution at the Yangtze River Delta: A Comparison of Kriging, LUR, and Combined BME-LUR Techniques J. Environ. Inform. (IF 4.604) Pub Date : 2020-07-18 L. Xiao; G. Christakos; J. Y. He; Y. C. Lang
Ambient air PM2.5 is one of the major pollutants linked to respiratory and lung diseases in the Yangtze River Delta (YRD), which is China’s leading economic region and one of the top economic regions worldwide. The main objectives of this work is to compare the accuracy of some widely-used techniques to characterize and predict the space-time distribution of ground-level PM2.5 in the YRD, and to propose
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Comparing the Performance of an Autoregressive State-Space Approach to the Linear Regression and Artificial Neural Network for Streamflow Estimation J. Environ. Inform. (IF 4.604) Pub Date : 2020-08-04 Y. Yang; T. T. Huang; Y. Z. Shi; O. Wendroth; B. Y. Liu
Accurate streamflow estimation remains a great challenge although diverse modeling techniques have been developed during recent decades. In contrast to the process based models, the empirical data driven methods are easy to operate, require low computing capacity and yield fairly accurate outcomes, among which the state space (STATE) approach takes use of the temporal structures inherent in streamflow
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Predicting Ground Level Ozone in Marrakesh by Machine-Learning Techniques J. Environ. Inform. (IF 4.604) Pub Date : 2020-07-14 J. Ordieres-Meré; J. Ouarzazi; B. El Johra; B. Gong
This study was undertaken to produce local, short-term, artificial intelligence-based models that estimate the ozone level with special attention to the relationship between diurnal and nocturnal ozone variations of some primary pollutants and meteorological parameters in the city of Marrakesh, Morocco. Hourly data has been collected from the three air-quality monitoring stations in the city. This
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Using High Resolution Images from UAV and Satellite Remote Sensing for Best Management Practice Analyses J. Environ. Inform. (IF 4.604) Pub Date : 2020-07-01 B. Yang; S. T. Y. Tong; R. Fan
Best Management Practices (BMPs) are commonly adopted to ameliorate the quality of runoff and reduce the frequency and intensity of flash floods in urban areas. To date, many of the BMP studies are conducted using coarse resolution data. However, the accuracy of such studies may be compromised due to the shortcomings inherent in the input data; as such, the evaluation of the BMP cost-effectiveness
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Numerical Simulation of Water Quality and Self-Purification in a Mountainous River Using QUAL2KW J. Environ. Inform. (IF 4.604) Pub Date : 2020-06-23 O. Babamiri; A. Vanaei; X. Guo; P. Wu; A. Richter; K. T. W. Ng
Understanding the water quality in mountainous rivers is critical for sustainable water resources management. By using the rivers’ self-purification to improve water quality is also the most economical and sustainable way to clean water. In the present study, the QUAL2KW model is applied to investigate the water quality and self -purification capacity in a mountainous river. The Abbasabad River in
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Extension of the Constrained Gravitational Search Algorithm for Solving Multi-Reservoir Operation Optimization Problem J. Environ. Inform. (IF 4.604) Pub Date : 2020-06-22 R. Moeini; M. Soltani-nezhad
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
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Estimation of Forest Leaf Area Index Using Meteorological Data: Assessment of Heuristic Models J. Environ. Inform. (IF 4.604) Pub Date : 2020-06-22 S. Karimi; A. H. Nazemi; A. A. Sadraddini; T. R. Xu; S. M. Bateni; A. F. Fard
Leaf Area Index (LAI) is an important structural feature of our ecosystem as it affects energy, carbon, and water exchanges between the land surface and overlying atmosphere. Global scale LAI datasets have been obtained by regression, heuristic data driven, and radiative transfer models using remotely sensed land surface reflectance data. However, the estimation of LAI from remotely sensed data is
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A Stochastic Optimization Model for Carbon-Emission Reduction Investment and Sustainable Energy Planning under Cost-Risk Control J. Environ. Inform. (IF 4.604) Pub Date : 2020-03-04 L. Ji; G. H. Huang; D. X. Niu; Y. P. Cai; J. G. Yin
Restricted by conventional energy resources and environmental space, the sustainable development of urban power sector faces enormous challenges. Renewable energy generation and carbon capture and storage (CCS) are attractive technologies for reducing conventional energy resource consumption and improving CO2 emission mitigation. Considering the limitation of expensive investment cost on their wide
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Using Satellite Remote Sensing and Machine Learning Techniques Towards Precipitation Prediction and Vegetation Classification J. Environ. Inform. (IF 4.604) Pub Date : 2020-01-28 D. Stampoulis; H. G. Damavandi; D. Boscovic; J. Sabo
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
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Conservation-Targeted Hydrologic-Economic Models for Water Demand Management J. Environ. Inform. (IF 4.604) Pub Date : 2019-12-11 Y. Xiao; L. Fang; K. W. Hipel
Two basin-wide hydrologic-economic optimization models are presented to estimate how much water can be conserved while maintaining at least the same level of economic output. Water consumption is interpreted as either water diverted to consumptive users or water consumed by all users. Two different formulations for representing the two interpretations of water consumption are examined. The characteristics
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Computational Text Analysis of a Scientific Resilience Management Corpus: Environmental Insights and Implications J. Environ. Inform. (IF 4.604) Pub Date : 2019-11-18 J. Nassour; D. Leykin; M. Elhadad; O. Cohen
Resilience is a multifaceted concept describing the ability to cope with change or disruption. Its importance in the era of emergency preparedness and response, combined with its multidisciplinary attributes, have led researches to study similarities and differences in the meaning of resilience across various fields. A systematic literature review, conducted in the field of resilience management by
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Assessment of Parametric Sensitivity Analysis Methods Based on A Quasi Two-Dimensional Groundwater Model J. Environ. Inform. (IF 4.604) Pub Date : 2019-06-21 Z. H. Di; A. Z. Ye; Q. Y. Duan; X. X. Wang
Parametric sensitivity analysis (SA) aims to select the sensitive parameters that most significantly affect the model output variables, which helps to improve model optimization efficiency by adjusting a small number of sensitive parameters instead of all adjustable parameters. The qualitative and quantitative SA methods have been commonly used to quantify the sensitive parameters of the models. However
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Effects of Early Dry Season on Habitat Suitability for Migratory Birds in China’s Two Largest Freshwater Lake Wetlands after the Impoundment of Three Gorges Dam J. Environ. Inform. (IF 4.604) Pub Date : 2019-04-22 H. P. Wu; J. Chen; G. M. Zeng; J. J. Xu; L. H. Sang; Q. Liu; J. Dai; W. P. Xiong; Z. Yuan; Y. Q. Wang; S. J. Ye
Dongting Lake and Poyang Lake, the China’s two largest freshwater lakes, are the most important wintering area and pathways for migratory birds in East Asia. As a result of human activities (impounding of the Three Gorges Dam (TGD), and sand mining) and climate change, the dry season of Dongting Lake and Poyang Lake came early after the impoundment of TGD. And the early dry season (EDS) would change
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Information Provision in Environmental Policy Design J. Environ. Inform. (IF 4.604) Pub Date : 2019-04-22 V. Danilina; A. Grigoriev
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
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DCT-based Least-Squares Predictive Model for Hourly AQI Fluctuation Forecasting J. Environ. Inform. (IF 4.604) Pub Date : 2019-04-15 Z. C. Yang
Recently the issue of air quality has become a global public health concern. As air pollution has been reported as the largest single environmental health risk in the world, analysis and prediction of air quality is increasingly important. Normally, either statistical models or CTM (“deterministic chemistry-transport”) models are used for forecasting air PM (“particulate matter”) levels. Actually,
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A Hybrid Intelligence System Based on Relevance Vector Machines and Imperialist Competitive Optimization for Modelling Forest Fire Danger Using GIS J. Environ. Inform. (IF 4.604) Pub Date : 2018-12-20 H. V. Le; Q. T. Bui; D. Tien Bui; H. H. Tran; N. D. Hoang
This article proposes and verifies a novel intelligence approach for modelling forest fire danger, namely ICA-RVM, developed based on Relevance Vector Machine (RVM) and Imperialist Competitive Algorithm (ICA), state-of-the art machine learning techniques that have not been investigated for forest fire danger modeling. RVM is used to establish a prediction model that computes probability of fire danger
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Improvement of Instantaneous Point Source Model for Simulating Radionuclide Diffusion in Oceans under Nuclear Power Plant Accidents J. Environ. Inform. (IF 4.604) Pub Date : 2017-11-07 A. F. Zhai; X. W. Ding; Y. Zhao; W. H. Xiao; B. X. Lu
Simulation methods have become an important tool to reveal radionuclide migration during accidental radionuclide releases and predict influences of accidents on the marine environment. The instantaneous point source model is a useful method to simulate the large-scale radionuclide diffusion in marine areas. However, the simulation accuracy of this method requires improvement as it didn’t take radionuclide
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A Hierarchical Approach for Inland Lake Pollutant Load Allocation: A Case Study in Tangxun Lake Basin, Wuhan, China J. Environ. Inform. (IF 4.604) Pub Date : 2017-04-06 Y. Y. Zhou; J. H. Wang; W. H. Xiao; Y. H. Huang; H. Yang; B. D. Hou; Y. Chen; H. T. Zhang
Water pollution control is a challenging task in water resources management. It is widely believed that integrating efficiency and fairness of socio-economic factors is an effective solution for water problems of inland Lake Basin. In this paper, a hierarchical approach of Tri-level Pollutant Loading Allocation (TPLA) was developed for the optimal allocation of pollutant load reduction. In TPLA, pollutant