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1.
Jeffrey Wade Laura Lautz Christa Kelleher Philippe Vidon Julianne Davis Julio Beltran Casey Pearce 《水文研究》2020,34(26):5340-5353
Beaver dam analogues (BDAs) are a cost-effective stream restoration approach that leverages the recognized environmental benefits of natural beaver dams on channel stability and local hydrology. Although natural beaver dams are known to exert considerable influence on the hydrologic conditions of a stream system by mediating geomorphic processes, nutrient cycling, and groundwater–surface water interactions, the impacts of beaver-derived restoration methods on groundwater–surface water exchange are poorly characterized. To address this deficit, we monitored hyporheic exchange fluxes and streambed porewater biogeochemistry across a sequence of BDAs installed along a central Wyoming stream during the summer of 2019. Streambed fluxes were quantified by heat tracing methods and vertical hydraulic gradients. Biogeochemical activity was evaluated using major ion porewater chemistry and principal component analysis. Vertical fluxes of approximately 1.0 m/day were observed around the BDAs, as was the development of spatially heterogeneous zones of nitrate production, groundwater upwelling, and anaerobic reduction. Strong contrasts in hyporheic zone processes were observed across BDAs of differing sizes. This suggests that structures may function with size-dependent behaviour, only altering groundwater–surface water interactions after a threshold hydraulic step height is exceeded. Patterns of hyporheic exchange and biogeochemical cycling around the studied BDAs resemble those around natural beaver dams, suggesting that BDAs may provide comparable benefits to channel complexity and near-stream function over a 1-year period. 相似文献
2.
WANGXie-kang HUANGEr CUIPeng 《中国地理科学(英文版)》2003,13(3):262-266
Debris flow is one of the most destructive phenomena of natural hazards. Recently, major natural haz-ard, claiming human lives and assets, is due to debris flow in the world. Several practical methods for forecasting de-bris flow have been proposed, however, the accuracy of these methods is not high enough for practical use because of the stochastic and non-linear characteristics of debris flow. Artificial neural network has proven to be feasible and use-fill in developing models for nonlinear systems. On the other hand, predicting the future behavior based on a time se-ries of collected historical data is also an important tool in many scientific applications. In this study we present a three-layer feed-forward neural network model to forecast surge of debris flow according to the time series data collect-ed in the Jiangjia Ravine, situated in north part of Yunnan Province of China. The simulation and prediction of debris flow using the proposed approach shows this model is feasible, however, further studies are needed. 相似文献
3.
The emergence of artificial neural network (ANN) technology has provided many promising results in the field of hydrology and water resources simulation. However, one of the major criticisms of ANN hydrologic models is that they do not consider/explain the underlying physical processes in a watershed, resulting in them being labelled as black‐box models. This paper discusses a research study conducted in order to examine whether or not the physical processes in a watershed are inherent in a trained ANN rainfall‐runoff model. The investigation is based on analysing definite statistical measures of strength of relationship between the disintegrated hidden neuron responses of an ANN model and its input variables, as well as various deterministic components of a conceptual rainfall‐runoff model. The approach is illustrated by presenting a case study for the Kentucky River watershed. The results suggest that the distributed structure of the ANN is able to capture certain physical behaviour of the rainfall‐runoff process. The results demonstrate that the hidden neurons in the ANN rainfall‐runoff model approximate various components of the hydrologic system, such as infiltration, base flow, and delayed and quick surface flow, etc., and represent the rising limb and different portions of the falling limb of a flow hydrograph. Copyright © 2004 John Wiley & Sons, Ltd. 相似文献
4.
形变大地测量学的进展、问题与地震预报 总被引:12,自引:7,他引:5
简要概括了形变大地测量学的革命性进展,研讨了它的科学特色、功能和定义以及对地球科学和防灾减灾的推动。形变大地测量学有助于从根本上击破多年来制约地震预报的“瓶颈”,但也存在不少急待解决的问题。着重研讨了在21世纪前10年,形变大地测量学如何依托多年的学科积累并充分受益于人造卫星和数字化等新技术,开展创新性研究和试验以推进地震预报。为此,对当前的研究工作提出了12条科学技术途径。最后对学科名称提出了建议。 相似文献
5.
Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass.
However, the model proposed by them has some drawbacks according to fuzzy logic principles. This discussion will focus on
the main fuzzy logic principles which authors and potential readers should take into consideration. 相似文献
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7.
赤点石斑鱼人工配合饵料中蛋白质最适含量的研究 总被引:11,自引:1,他引:11
本文探讨了不同蛋白质含量的配合饵料对赤点石斑鱼(Epinephelusakaara)生长的影响。通过60d度验得出:在各配合饵料组中,蛋白质含量为49.52%的试验的相对增重率(46.84%)体长相对增长率(15.96%)、蛋白质效率(60.35%)和饵料转化率(29.85%)等均为最佳。配合饵料组鱼体肌肉营养成分(蛋白质、脂肪、氨基酸和鲜味氨基酸)也均优于对照组,而更接近野生鱼。经回归方程分析,赤点石斑鱼人工配合饵料中蛋白质最适含量为48.37%~49.24%。 相似文献
8.
地形坡度对多金属结核分布的控制作用 总被引:3,自引:3,他引:3
选取我国东太平洋多金属结核开辟区内的一个区域作为研究区,利用人工神经网络中应用最为广泛的BP网络,建立控制多金属结核分布的地质因素与多金属结核分布之间的映射关系,探讨地形坡度对多金属结核分布的控制作用.结果表明,在经度、纬度、水深、坡度四个因素中,坡度对结核分布影响程度最大;多金属结核主要分布于坡度小于5°的地方;当坡度小于5°时,丰度与地形坡度呈正相关,品位与地形坡度呈负相关,丰度与品位呈负相关;品位与坡度似呈指数关系,坡度增大,品位降低. 相似文献
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