Turbulence in the presence of internal waves in the bottom boundary layer of the California inner shelf     

Rachel M. Allen  Julian A. Simeonov  Joseph Calantoni  Mark T. Stacey  Evan A. Variano 《Ocean Dynamics》2018,68(4-5):627-644

Turbulence measurements were collected in the bottom boundary layer of the California inner shelf near Point Sal, CA, for 2 months during summer 2015. The water column at Point Sal is stratified by temperature, and internal bores propagate through the region regularly. We collected velocity, temperature, and turbulence data on the inner shelf at a 30-m deep site. We estimated the turbulent shear production (P), turbulent dissipation rate (ε), and vertical diffusive transport (T), to investigate the near-bed local turbulent kinetic energy (TKE) budget. We observed that the local TKE budget showed an approximate balance (P?≈?ε) during the observational period, and that buoyancy generally did not affect the TKE balance. On a finer resolution timescale, we explored the balance between dissipation and models for production and observed that internal waves did not affect the balance in TKE at this depth.  相似文献   

Wide river or narrow river: Future river training strategy for Lower Yellow River under global change     

Xiaonan Li  Deyu Zhong  Y. Joseph Zhang  Yanjun Wang  Yongqiang Wang  Hongwu Zhang 《国际泥沙研究》2018,33(3):271-284

The choice of a river training strategy is extremely important for the Lower Yellow River (LYR). Currently, the wide-river training strategy applies in the training of the LYR. However, remarkable changes in the hydrological processes in the Yellow River basin, as well as immediate pressure from socio-economic development in the Yellow River basin, make it necessary to consider if there is a possibility to change the river training strategy from wide-river training to narrow-river training. This research investigates the impacts of different river training strategies on the LYR through numerical simulations. A one-dimensional (1-D) model was used to simulate the fluvial processes for the future 50 years and a three-dimensional (3-D) model was applied to study typical floods. The study focused on river morphology, the results show that if the present decreasing trend in both water discharge and sediment load persists, the deposition rate in the LYR will further decrease no matter what strategy is applied. Especially, narrow-river training can achieve the aim to increase the sediment transport capacity in the LYR compared with wide-river training. However, if the incoming water and sediment load recovers to the mean level of the last century, main channel shrinkage due to sedimentation inevitably occurs for both wide-river and narrow-river training. Most importantly, this study shows that narrow-river training reduces the deposition amount over the whole LYR, but it provides little help in alleviating the development of the “suspended river”. Instead, narrow-river training can cause aggradation in the transitional reach where the river pattern changes from highly wandering to meandering, further worsening the “hump deposition” there. Because of uncertainty regarding future changes in hydrological processes in the Yellow River basin, and the lack of feasible engineering measures to mitigate “suspended river” and “hump deposition” problems in the LYR, caution should be exercised with respect to changes in the river training strategy for the LYR.  相似文献   

Advancing Contaminant Mass Flux Analysis to Focus Remediation: The Three‐Compartment Model          下载免费PDF全文

John Horst  Scott Potter  Matthew Schnobrich  Nicklaus Welty  Ankit Gupta  Joseph Quinnan 《Ground Water Monitoring & Remediation》2017,37(4):15-22

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Developing observational methods to drive future hydrological science: Can we make a start as a community?     

Keith Beven  Anita Asadullah  Paul Bates  Eleanor Blyth  Nick Chappell  Stewart Child  Hannah Cloke  Simon Dadson  Nick Everard  Hayley J. Fowler  Jim Freer  David M. Hannah  Kate Heppell  Joseph Holden  Rob Lamb  Huw Lewis  Gerald Morgan  Louise Parry  Thorsten Wagener 《水文研究》2020,34(3):868-873

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Prediction of daily sediment discharge using a back propagation neural network training algorithm: A case study of the Narmada River,India     

Nibedita Bisoyi  Harish Gupta  Narayan Prasad Padhy  Govind Joseph Chakrapani 《国际泥沙研究》2019,34(2):125-135

Most of the studies on Artificial Neural Network (ANN) models remain restricted to smaller rivers and catchments. In this paper, an attempt has been made to correlate variability of sediment loads with rainfall and runoff through the application of the Back Propagation Neural Network (BPNN) algorithm for a large tropical river. The algorithm and simulation are done through MATLAB environment. The methodology comprised of a collection of data on rainfall, water discharge, and sediment discharge for the Narmada River at various locations (along with time variables) and application to develop a threelayer BPNN model for the prediction of sediment discharges. For training and validation purposes a set of 549 data points for the monsoon (16 June-15 November) period of three consecutive years (1996–1998) was used. For testing purposes, the BPNN model was further trained using a set of 732 data points of monsoon season of four years (2006–07 to 2009–10) at nine stations. The model was tested by predicting daily sediment load for the monsoon season of the year 2010–11. To evaluate the performance of the BPNN model, errors were calculated by comparing the actual and predicted loads. The validation and testing results obtained at all these locations are tabulated and discussed. Results obtained from the model application are robust and encouraging not only for the sub-basins but also for the entire basin. These results suggest that the proposed model is capable of predicting the daily sediment load even at downstream locations, which show nonlinearity in the transportation process. Overall, the proposed model with further training might be useful in the prediction of sediment discharges for large river basins.  相似文献   

Influence of topographic,geomorphic, and hydrologic variables on beaver dam height and persistence in the intermountain western United States     

Konrad C. Hafen  Joseph M. Wheaton  Brett B. Roper  Philip Bailey  Nicolaas Bouwes 《地球表面变化过程与地形》2020,45(11):2664-2674

Stream ecosystems can be dramatically altered by dam-building activities of North American beaver (Castor canadensis). The extent to which beavers’ ecosystem engineering alters riverscapes is driven by the density, longevity, and size (i.e. height and length) of the dams constructed. In comparison to the relative ubiquity of beaver dams on the landscape, there is a scarcity of data describing dam heights. We collected data describing dam height and dam condition (i.e. damaged or intact) of 500 beaver dams via rapid field survey, differentiating between primary and secondary dams and associating each dam with a beaver dam complex. With these data, we examined the influence of beaver dam type (primary/secondary), drainage area, streamflow, stream power, valley bottom width, and HUC12 watershed on beaver dam height with linear regression and the probability that a beaver dam was damaged with logistic regression. On average, primary dams were 0.46 m taller than secondary dams; 15% of observed dams were primary and 85% secondary. Dam type accounted for 21% of dam height variation (p <0.0001). Slope (p = 0.0107), discharge (p = 0.0029), and drainage area (p = 0.0399) also affected dam height, but each accounted for less than 3% of dam height variation. The average number of dams in a dam complex was 6.1 (SD ± 4.5) and ranged from 1 to 21. The watershed a beaver dam was located in accounted for the most variability (17.8%) in the probability that a beaver dam was damaged, which was greater than the variability explained by any multiple logistic regression model. These results indicate that temporally dynamic variables are important influencers of dam longevity and that beaver dam ecology is a primary factor influencing beaver dam height. © 2020 John Wiley & Sons, Ltd.  相似文献   

Sedimentation limits the erosion rate of a bioeroding sponge          下载免费PDF全文

Joseph Marlow  David Smith  Shinta Werorilang  James Bell 《Marine Ecology》2018,39(1)

Coral reefs are increasingly threatened by anthropogenic disturbances and consequently coral cover and complexity are declining globally. However, bioeroding sponges, which are the principal agents of internal bioerosion on many coral reefs, are increasing in abundance on some degraded reefs, tipping them towards net carbonate erosion. The aim of this study was to identify the environmental factors that drive the erosion rates of the common Indonesian bioeroding sponge Spheciospongia cf. vagabunda . Sponge explants were attached to limestone blocks and deployed across seven sites characterized by different environmental conditions in the UNESCO Wakatobi Biosphere Reserve in Indonesia. Average bioerosion rates were 12.0 kg m^?2 sponge tissue year^?1 (±0.87 SE ), and were negatively correlated with depth of settled sediment (r  = ?.717, p  < .01) and showed weak positive correlation with water movement (r  = .485, p  = .012). Our results suggest that although bioeroding sponges may generally benefit from coral reef degradation, bioerosion rates may be reduced on reefs that are impacted by high sedimentation, which is a common regional stressor in the South‐East Asian Indo‐Pacific.  相似文献   

NeuroTPR: A neuro‐net toponym recognition model for extracting locations from social media messages     

Jimin Wang  Yingjie Hu  Kenneth Joseph 《Transactions in GIS》2020,24(3):719-735

Social media messages, such as tweets, are frequently used by people during natural disasters to share real‐time information and to report incidents. Within these messages, geographic locations are often described. Accurate recognition and geolocation of these locations are critical for reaching those in need. This article focuses on the first part of this process, namely recognizing locations from social media messages. While general named entity recognition tools are often used to recognize locations, their performance is limited due to the various language irregularities associated with social media text, such as informal sentence structures, inconsistent letter cases, name abbreviations, and misspellings. We present NeuroTPR, which is a Neuro‐net ToPonym Recognition model designed specifically with these linguistic irregularities in mind. Our approach extends a general bidirectional recurrent neural network model with a number of features designed to address the task of location recognition in social media messages. We also propose an automatic workflow for generating annotated data sets from Wikipedia articles for training toponym recognition models. We demonstrate NeuroTPR by applying it to three test data sets, including a Twitter data set from Hurricane Harvey, and comparing its performance with those of six baseline models.  相似文献   

Evapotranspiration response to multiyear dry periods in the semiarid western United States     

Joseph Rungee  Roger Bales  Michael Goulden 《水文研究》2019,33(2):182-194

Analysis of measured evapotranspiration shows that subsurface plant‐accessible water storage (PAWS) can sustain evapotranspiration through multiyear dry periods. Measurements at 25 flux tower sites in the semiarid western United States, distributed across five land cover types, show both resistance and vulnerability to multiyear dry periods. Average (±standard deviation) evapotranspiration ranged from 660 ± 230 mm yr^?1 (October–September) in evergreen needleleaf forests to 310 ± 200 mm yr^?1 in grasslands and shrublands. More than 52% of the annual evapotranspiration in Mediterranean climates is supported on average by seasonal drawdown of subsurface PAWS, versus 29% in monsoon‐influenced climates. Snowmelt replenishes dry‐season PAWS by as much as 20% at sites with significant seasonal snow accumulation but was insignificant at most sites. Evapotranspiration exceeded precipitation in more than half of the observation years at sites below 35°N. Annual evapotranspiration at non‐energy‐limited sites increased with precipitation, reaching a mean wet‐year evapotranspiration of 833 mm for evergreen needleleaf forests, 861 mm for mixed forests, 558 mm for woody savannas, 367 mm for grasslands, and 254 mm for shrublands. Thirteen sites experienced at least one multiyear dry period, when mean precipitation was more than one standard deviation below the historical mean. All vegetation types except evergreen needleleaf forests responded to multiyear dry periods by lowering evapotranspiration and/or significant year‐over‐year depletion of subsurface PAWS. Sites maintained wet‐year evapotranspiration rates for 8–33 months before attenuation, with a corresponding net PAWS drawdown of as much as 334 mm. Net drawdown at many sites continued until the dry period ended, resulting in an overall cumulative withdrawal of as much as 558 mm. Evergreen needleleaf forests maintained high evapotranspiration during multiyear dry periods with no apparent PAWS drawdown; these forests currently avoid drought but may prove vulnerable to longer and warmer dry periods that reduce snowpack storage and accelerate evapotranspiration.  相似文献   

Improving a distributed hydrological model using evapotranspiration‐related boundary conditions as additional constraints in a data‐scarce river basin          下载免费PDF全文

Frank Joseph Wambura  Ottfried Dietrich  Gunnar Lischeid 《水文研究》2018,32(6):759-775

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