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1.
Freezing as a method of sample preservation for the analysis of dissolved inorganic nutrients in seawater 总被引：1，自引：0，他引：1
John E. Dore Terrence Houlihan Dale V. Hebel Georgia Tien Luis Tupas David M. Karl 《Marine Chemistry》1996,53(3-4)
It is often desirable or necessary to store collected seawater samples prior to analysis for dissolved inorganic nutrients. It is therefore important to establish preservation and storage techniques that will ensure sample integrity and will not alter the precision or accuracy of analysis. We have performed a series of experiments on the storage of nutrient samples collected at the oligotrophic North Pacific benchmark Station ALOHA, using both standard autoanalyses and low-level techniques. Our results reveal that for oligotrophic oceanic waters, the immediate freezing of an unfiltered water sample in a clean polyethylene bottle is a suitable preservation method. This procedure is simple, it avoids potentially contaminating sample manipulations and chemical additions, and it adequately preserves the concentrations of nitrate + nitrite, soluble reactive phosphate, and soluble reactive silicate within a single water sample. 相似文献
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Jesper Raakjær Dao Manh Son Karl-Johan Stæhr Holger Hovgård Nguyen Thi Dieu Thuy Kristine Ellegaard Frank Riget Dang Van Thi Phung Giang Hai 《Marine Policy》2007
Vietnam is in the process of introducing adaptive management based on indicators and time-series to manage its marine fisheries. The development of indicator-based frameworks for fisheries management has accelerated in recent years. This article describes the suite of indicators being suggested or used in Vietnam including the data-collection system. The Vietnamese approach is supported by an institutional structure consisting of a multi-disciplinary advisory system to facilitate the process of using indicators and to introduce knowledge-based management. The article concludes by identifying current problems and weaknesses and by providing suggestions for future improvement of the system. 相似文献
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Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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Binh Thai Pham Dieu Tien Bui Indra Prakash Long Hoang Nguyen M. B. Dholakia 《Environmental Earth Sciences》2017,76(10):371
Landslide susceptibility assessment using GIS has been done for part of Uttarakhand region of Himalaya (India) with the objective of comparing the predictive capability of three different machine learning methods, namely sequential minimal optimization-based support vector machines (SMOSVM), vote feature intervals (VFI), and logistic regression (LR) for spatial prediction of landslide occurrence. Out of these three methods, the SMOSVM and VFI are state-of-the-art methods for binary classification problems but have not been applied for landslide prediction, whereas the LR is known as a popular method for landslide susceptibility assessment. In the study, a total of 430 historical landslide polygons and 11 landslide affecting factors such as slope angle, slope aspect, elevation, curvature, lithology, soil, land cover, distance to roads, distance to rivers, distance to lineaments, and rainfall were selected for landslide analysis. For validation and comparison, statistical index-based methods and the receiver operating characteristic curve have been used. Analysis results show that all these models have good performance for landslide spatial prediction but the SMOSVM model has the highest predictive capability, followed by the VFI model, and the LR model, respectively. Thus, SMOSVM is a better model for landslide prediction and can be used for landslide susceptibility mapping of landslide-prone areas. 相似文献
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Paleoenvironments of the evolving Pliocene to early Pleistocene foreland basin in northwestern Taiwan: An example from the Dahan River section 
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下载免费PDF全文 The overriding of the Luzon volcanic arc atop the underlying Chinese rifted‐continental margin has caused the formation of the Taiwan mountain belts and a peripheral foreland basin west of the orogen since the late Miocene. In this study, lithofacies analysis and calcareous nannofossil biostratigraphic investigations of the Dahan River section in northwestern (NW) Taiwan were performed. Our results offer insights into the temporal evolution of the sedimentary environments and the competing effects of the sedimentation and basin tectonics of the NW Taiwan foreland basin from the Pliocene to early Pleistocene. Nannofossil biostratigraphic studies showed that the upper Kueichulin Formation and the overlying Chinshui Shale can be assigned to the NN15 biozone of the Pliocene age, and the Cholan Formation pertains to NN16–NN18 of the early Pleistocene. The NN15–NN16 boundary coincides roughly with the boundary of the Chinshui Shale and Cholan Formation. We recognized three major sedimentary environments in the studied foreland succession comprising the upper Kueichulin Formation, Chinshui Shale, Cholan Formation and Yangmei Formation, in ascending order. During the deposition of the upper Kueichulin Formation in the early Pliocene, the dominant environment was a wave‐ and tide‐influenced open marine setting. During the late Pliocene, the environment deepened to an outer‐offshore setting when the sediments of Chinshui Shale were accumulated. In the Pleistocene, the environment then shallowed to wave‐dominated estuaries during the deposition of the lower Cholan Formation, and the basin was rapidly filled, generating a meandering and sandy braided river environment during the deposition of the upper Cholan to the Yangmei Formation. In summary, the evolution of sedimentary environments in the studied succession shows a deepening then a shallowing and coarsening upward trend during the period from the Pliocene to the Pleistocene, spanning the age from approximately 4 to 1 Ma. 相似文献
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Modelling infiltration enhancement in a tropical urban catchment for improved stormwater management 总被引：1，自引：0，他引：1 下载免费PDF全文
下载免费PDF全文 To mitigate the impacts of impervious surfaces in urban areas, structures such as bioretention systems and permeable pavements have been installed to enhance infiltration in many countries. However, relatively little knowledge is available regarding the performance of such infiltration‐based structures in humid tropical and highly urbanized areas. This study investigates the feasibility of enhancing the infiltration of stormwater in tropical urbanized areas using Singapore as a case study. It first shows that the rainfall depth and intensity are both high, but the time interval between consecutive rainfall event is long in Singapore. It then numerically simulates single‐event local infiltration and finds that the fraction of infiltrated rainfall is actually high. It finally performs catchment‐scale simulations and finds that bioretention systems can enhance infiltration and groundwater recharge particularly during wet periods. However, local mounding of groundwater can be significant and can hinder the performance of those structures. Furthermore, with 5% of catchment area being converted to such structures, the infiltration of the entire catchment is enhanced but still not yet up to the natural level. To increase the overall effectiveness, future studies can look into bioretention systems with underdrain systems. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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Samples were continuously collected from aerosol, fresh snow, and snow pits on Glacier No. 1 at Urumqi River source in eastern Tianshan (天山) Mountains. The deposition processes and the characteristics of mineral dust microparticles from aerosol to fresh snow, and then evolution to the snow pit were determined. Total dust microparticle concentration in the surface snow and aerosol showed a similar temporal variation trend, which was strongly associated with regional and local at-mospheric circulation in the ... 相似文献
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Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam 总被引：6，自引：2，他引：4
Dieu Tien Bui Biswajeet Pradhan Owe Lofman Inge Revhaug Øystein B. Dick 《Natural Hazards》2013,66(2):707-730
The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years. 相似文献
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Fractal characterization of sediment particle-size distribution in the water-level fluctuation zone of the Three Gorges Reservoir,China 总被引：1，自引：0，他引：1
The combined effect of periodic water impoundment and seasonal natural flood events has created a 30 m high water-level fluctuation zone(WLFZ) around the Three Gorges Reservoir(TGR), China, forming a unique eco-landscape. Siltation, eutrophication, enrichment of heavy metals, and methane emissions in the WLFZ have been widely associated with sediment and soil particles generated from the upstream catchment or upland slopes. However, little attention has been paid to the complexity of sediment particle-size distributions in the WLFZ. In the present study, core samples(from a 345 cm thick sediment core from the base of the WLFZ), slope transect surface samples(across/up a WLFZ slope), and along-river/longitudinal surface samples(from the reservoir reaches) were collected. Laser granulometry and a volume-based fractal model were used to reveal the characteristics of sediment particle-size distributions. Results indicate that the alternation of coarse and fine particles in the sedimentary core profile is represented as a fluctuation of low and high values of fractal dimension(D), ranging from 2.59 to 2.77. On the WLFZ slope transect, surface sediment particles coarsen with increasing elevation, sand content increases from 3.3% to 78.5%, and D decreases from 2.76 to 2.53. Longitudinally, surface sediments demonstrate a downstream-fining trend, and D increases gradually downstream. D is significantly positively correlated with the fine particle content. We conclude that D is a useful measure for evaluating sediment particle-size distribution. 相似文献