Early detection model for the urban stream syndrome using specific stream power and regime theory

2021 ◽  
pp. 127167
Author(s):  
K.M. MacKenzie ◽  
B. Gharabaghi ◽  
A. Binns ◽  
H. Whiteley
2015 ◽  
Vol 40 (3) ◽  
pp. 480-492 ◽  
Author(s):  
Geoff J. Vietz ◽  
Christopher J. Walsh ◽  
Tim D. Fletcher

The urban stream syndrome is an almost universal physical and ecological response of streams to catchment urbanization. Altered channel geomorphology is a primary symptom that includes channel deepening, widening and instability. While the common approach is to treat the symptoms (e.g. modifying and stabilizing the channel), many stream restoration objectives will not be achieved unless the more vexing problem, treating the cause, is addressed in some way. Research demonstrates that the dominant cause of geomorphic change in streams in urban catchments is an altered flow regime and increase in the volume of stormwater runoff. Thus, managers can choose to treat the symptoms by modifying and controlling the channel to accommodate the altered flow regime, or treat the cause by modifying the flow regime to reduce the impact on channel morphology. In both cases treatments must, at the least, explicitly consider hydrogeomorphology—the science of the linkages between various hydrologic and geomorphic processes—to have a chance of success. This paper provides a review of recent literature (2010 to early 2015) to discuss fluvial hydrogeomorphology in the management of streams subject to urbanization. We suggest that while the dominant approach is focused on combating the symptoms of catchment urbanization (that we refer to as channel reconfiguration), there is increasing interest in approaches that attempt to address the causes by using stormwater control measures at a range of scales in the catchment (e.g. flow-regime management). In many settings in the oft-constrained urban catchment, effective management of stream morphology may require multiple approaches. To conclude, we identify five research areas that could inform urban hydrogeomorphology, one of the most challenging of which is the extent to which the volume of excess urban stormwater runoff can be reduced to mitigate the impact on stream geomorphology.


2016 ◽  
Vol 35 (1) ◽  
pp. 412-420 ◽  
Author(s):  
Derek B. Booth ◽  
Allison H. Roy ◽  
Benjamin Smith ◽  
Krista A. Capps

2020 ◽  
Author(s):  
Seung-Hyun Jeong ◽  
Tae Rim Lee ◽  
Jung Bae Kang ◽  
Mun-Taek Choi

BACKGROUND Early detection of childhood developmental delays is very important for the treatment of disabilities. OBJECTIVE To investigate the possibility of detecting childhood developmental delays leading to disabilities before clinical registration by analyzing big data from a health insurance database. METHODS In this study, the data from children, individuals aged up to 13 years (n=2412), from the Sample Cohort 2.0 DB of the Korea National Health Insurance Service were organized by age range. Using 6 categories (having no disability, having a physical disability, having a brain lesion, having a visual impairment, having a hearing impairment, and having other conditions), features were selected in the order of importance with a tree-based model. We used multiple classification algorithms to find the best model for each age range. The earliest age range with clinically significant performance showed the age at which conditions can be detected early. RESULTS The disability detection model showed that it was possible to detect disabilities with significant accuracy even at the age of 4 years, about a year earlier than the mean diagnostic age of 4.99 years. CONCLUSIONS Using big data analysis, we discovered the possibility of detecting disabilities earlier than clinical diagnoses, which would allow us to take appropriate action to prevent disabilities.


Proceedings ◽  
2018 ◽  
Vol 2 (11) ◽  
pp. 576
Author(s):  
Eleni A. Athanasiadou ◽  
Maria Tratsela ◽  
Eleni Gkrimpa

Grey, blue and green infrastructure supports socio-ecological processes the city undergoes. Yet, procedures of constructing anthropogenic habitats often undermine the value of natural landscape elements such as urban streams. Thessaloniki’s backbone comprises of urban streams that run from the suburban forest of ‘Seih-Sou’ to the Thermaikos Gulf acting as corridors of the natural urban matrix. Policies of the past have dealt with urban streams through extensive engineering drainage methods, eliminating the risk of flooding, yet resulting in rapid stormwater runoff, water quality problems, disturbed riparian ecosystems, leading to the urban stream syndrome. Furthermore, they have failed to address urban streams as an inseparable part of the landscape and thus to incorporate them in people’s mental map and everyday activities. The paper discusses the case of ‘Polygnotou stream’ which forms the beginning of the large scale engineered peripheral moat of Thessaloniki, constructed in the 60’s, and playing the role of the water recipient for six urban streams in total. It falls unknown to the majority of people living in the area, yet its services as an ecosystem ought to be acknowledged, helping inform decision makers of its socio-ecologic, perceptual and economic value. In addition, Polygnotou stream, adjacent streams and the peripheral moat overall, could be considered as a touristic product of great importance.


2016 ◽  
Vol 19 (4) ◽  
pp. 1623-1643 ◽  
Author(s):  
Dave M. Epstein ◽  
Julia E. Kelso ◽  
Michelle A. Baker

Agromet ◽  
2018 ◽  
Vol 32 (2) ◽  
pp. 81
Author(s):  
Elza Surmaini ◽  
Erni Susanti ◽  
Yeli Sarvina ◽  
M. Ridho Syahputra

<p>Droughts and floods due to extreme climate events has caused yield loss in various regions of Indonesia, including the Provinces of Aceh and North Sumatra. An early detection model needs to be developed to anticipate the negative impacts of extreme climate event. The model may describe the association of surplus and rainfall deficits with paddy damage due to drought and flood. We used Standardized Precipitation Index (SPI) to explore drought and flood characteristics in period 1989-2016. The study aimed: (i) to analyze the relationship between SPI and paddy damage due to drought and flood events, (ii) to analyze the critical value of the duration and intensity of SPI which causes paddy damage, and (iii) to determine which districts were prone to drought and flood in the Provinces of Aceh and North Sumatra. The results concluded that SPI-3 and -6 months can better describe the frequency of drought and rice flooding. In addition, drought on paddy occured mostly if the SPI was smaller than -1 which took place within 4-5 months, whereas flood occured if the SPI was greater than 1. Short duration drought (2-3 months) were observed in five districts in Aceh (2) and North Sumatra (3). On other hand, more flood districts were identified (9 districts).</p>


2019 ◽  
Vol 11 (18) ◽  
pp. 4975 ◽  
Author(s):  
Karl Wantzen ◽  
Carlos Alves ◽  
Sidia Badiane ◽  
Raita Bala ◽  
Martín Blettler ◽  
...  

In many countries of the Global South, aquatic ecosystems such as streams, rivers, lakes, and wetlands are severely impacted by several simultaneous environmental stressors, associated with accelerated urban development, and extreme climate. However, this problem receives little attention. Applying a DPSIR approach (Drivers, Pressures, State, Impacts, Responses), we analyzed the environmental impacts and their effects on urban hydrosystems (including stagnant waters), and suggest possible solutions from a series of case studies worldwide. We find that rivers in the Global South, with their distinctive geographical and socio-political setting, display significant differences from the Urban Stream Syndrome described so far in temperate zones. We introduce the term of ‘Southern Urban Hydrosystem Syndrome’ for the biophysical problems as well as the social interactions, including the perception of water bodies by the urbanites, the interactions of actors (e.g., top-down, bottom-up), and the motivations that drive urban hydrosystem restoration projects of the Global South. Supported by a synthesis of case studies (with a focus on Brazilian restoration projects), this paper summarizes the state of the art, highlights the currently existing lacunae for research, and delivers examples of practical solutions that may inform UNESCO’s North–South–South dialogue to solve these urgent problems. Two elements appear to be specifically important for the success of restoration projects in the Global South, namely the broad acceptance and commitment of local populations beyond merely ‘ecological’ justifications, e.g., healthy living environments and ecosystems with cultural linkages (‘River Culture’). To make it possible implementable/practical solutions must be extended to (often poor) people having settled along river banks and wetlands.


Author(s):  
Panpan Zheng ◽  
Shuhan Yuan ◽  
Xintao Wu

Many online platforms have deployed anti-fraud systems to detect and prevent fraudulent activities. However, there is usually a gap between the time that a user commits a fraudulent action and the time that the user is suspended by the platform. How to detect fraudsters in time is a challenging problem. Most of the existing approaches adopt classifiers to predict fraudsters given their activity sequences along time. The main drawback of classification models is that the prediction results between consecutive timestamps are often inconsistent. In this paper, we propose a survival analysis based fraud early detection model, SAFE, which maps dynamic user activities to survival probabilities that are guaranteed to be monotonically decreasing along time. SAFE adopts recurrent neural network (RNN) to handle user activity sequences and directly outputs hazard values at each timestamp, and then, survival probability derived from hazard values is deployed to achieve consistent predictions. Because we only observe the user suspended time instead of the fraudulent activity time in the training data, we revise the loss function of the regular survival model to achieve fraud early detection. Experimental results on two real world datasets demonstrate that SAFE outperforms both the survival analysis model and recurrent neural network model alone as well as state-of-theart fraud early detection approaches.


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