A time delay artificial neural network approach for flow routing in a river system

International audienceRiver flow routing provides basic information on a wide range of problems related to the design and operation of river systems. In this paper, three layer cascade correlation Time Delay Artificial Neural Network (TDANN) models have been developed to forecast the one day ahead daily flow at Ilarionas station on the Aliakmon river, in Northern Greece. The networks are time lagged feed-formatted with delayed memory processing elements at the input layer. The network topology is using multiple inputs, which include the time lagged daily flow values further up at Siatista station on the Aliakmon river and at Grevena station on the Venetikos river, which is a tributary to the Aliakmon river and a single output, which are the daily flow values at Ilarionas station. The choice of the input variables introduced to the input layer was based on the cross-correlation. The use of cross-correlation between the ith input series and the output provides a short cut to the problem of the delayed memory determination. Kalman's learning rule was used to modify the artificial neural network weights. The networks are designed by putting weights between neurons, by using the hyperbolic-tangent function for training. The number of nodes in the hidden layer was determined based on the maximum value of the correlation coefficient. The results show a good performance of the TDANN approach for forecasting the daily flow values, at Ilarionas station and demonstrate its adequacy and potential for river flow routing. The TDANN approach introduced in this study is sufficiently general and has great potential to be applicable to many hydrological and environmental applications

Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece

Strymon is a transboundary river of Greece, Bulgaria and Former Yugoslav Republic of Macedonia (FYROM) in southeastern Europe. Water quality parameters and the discharge have been monitored each month just 10 km downstream of the river’s entry into Greece. The data of nine water quality variables (T, ECw, DO, SO₄^2-, Na⁺+K⁺, Mg²⁺ , Ca²⁺, NO₃^&#8254;, TP) and the discharge for the period 1980-1997 were selected for this analysis. In this paper a) the time series of monthly values of water quality parameters and the discharge were analysed using statistical methods, b) the existence of trends and the evaluation of the best fitted models were performed and c) the relationships between concentration and loads of constituents both with the discharge were also examined. Boxplots for summarising the distribution of a data set were used. The &#967²-test and the Kolmogorov-Smirnov test were used to select the theoretical distribution which best fitted the data. Simple regression was used to examine the concentration-discharge and the load-discharge relationships. According to the correlation coefficient (r) values the relation between concentrations and discharge is weak (r< 0.592) while the relation between loads and discharge is very strong (r > 0.902). Trends were detected using the nonparametric Spearman’s criterion upon the data for the variables: Q, ECw, DO, SO₄^2-, Na⁺+K⁺ and NO₃^&#8254; on which temporal trend analysis was performed.</p> <p style='line-height: 20px;'><b>Keywords: </b>Strymon river, water quality, discharge, concentration, load, statistics, trend

Statistical and trend analysis of water quality and quantity data for the Strymon River in Greece

International audienceStrymon is a transboundary river of Greece, Bulgaria and Former Yugoslav Republic of Macedonia (FYROM) in southeastern Europe. Water quality parameters and the discharge have been monitored each month just 10 km downstream of the river's entry into Greece. The data of nine water quality variables (T, ECw, DO, SO42-, Na++K+, Mg2+ , Ca2+, NO3?, TP) and the discharge for the period 1980-1997 were selected for this analysis. In this paper a) the time series of monthly values of water quality parameters and the discharge were analysed using statistical methods, b) the existence of trends and the evaluation of the best fitted models were performed and c) the relationships between concentration and loads of constituents both with the discharge were also examined. Boxplots for summarising the distribution of a data set were used. The &#9672-test and the Kolmogorov-Smirnov test were used to select the theoretical distribution which best fitted the data. Simple regression was used to examine the concentration-discharge and the load-discharge relationships. According to the correlation coefficient (r) values the relation between concentrations and discharge is weak (r 0.902). Trends were detected using the nonparametric Spearman's criterion upon the data for the variables: Q, ECw, DO, SO42-, Na++K+ and NO3? on which temporal trend analysis was performed. Keywords: Strymon river, water quality, discharge, concentration, load, statistics, trend

DOWNSCALING OUTPUTS OF THE GENERAL CIRCULATION MODELS FOR THE PREDICTION OF THE MONTHLY PRECIPITATION IN A STATION BY USING NEURAL NETWORKS

Η πρόβλεψη της κλιματικής αλλαγής βασίζεται κυρίως στις εκτιμήσεις των μοντέλων γενικής κυκλοφορίας (General Circulation Models) (GCMs). Οι εκτιμήσεις αυτές αναφέρονται σε μεγάλη χωρική ανάλυση και είναι επιβεβλημένη η εφαρμογή διαδικασιών για τον υποβιβασμό κλίμακας (downscaling) σε κλίμακα είτε τοπική είτε σταθμού. Στην εργασία αυτή ο υποβιβασμός περιγράφει τη σχέση μεταξύ μετεωρολογικών μεταβλητών μεγάλης κλίμακας που προσομοιώνονται από GCMs μοντέλα όπως είναι η βροχόπτωση, η θερμοκρασία, η υγρασία κ.λπ. και της μηνιαίας βροχόπτωσης ενός σταθμού και γίνεται με την εφαρμογή τεχνητών νευρωνικών δικτύων (Artificial Neural Networks) (ANNs) σε συνδυασμό με ανάλυση κυρίων συνιστωσών (PCA). Από την ανάλυση των αποτελεσμάτων συμπεραίνεται η καταλληλότητα των ANNs μοντέλων για τον υποβιβασμό κλίμακας μετεωρολογικών μεταβλητών όπως η βροχόπτωση, η θερμοκρασία, η εξατμισοδιαπνοή κ.λπ.Climate change predictions are generally based on the estimations by general circulation models (GCMs). The GCMs outputs are usually at resolution that is too coarse for many climate change impact studies. Hence, there is a great need to develop tools for downscaling GCM predictions of climate change to regional and local or station scales. This paper examines the potential of the Artificial Neural Network models (ANNs) in combination with Principal Component Analysis (PCA) to describe the relationship between large-scale atmospheric variables such as precipitation, temperature, humidity, pressure, geopotential height etc., and monthly precipitation for a station. It was concluded that ANN-based downscaling models are reliable and can be applied to atmospheric variables downscaling, like precipitation, temperature, evapotranspiration etc

The impact of the COVID-19 pandemic on refugees and asylum seekers in Greece: A retrospective analysis of national surveillance data from 2020.

Background: Migrants globally, including refugees and asylum seekers, have experienced adverse clinical and socioeconomic impacts of the COVID-19 pandemic. For approximately 56,000 refugees and asylum seekers in Reception and Identification Centers (RICs) and Reception Sites (RS) in Greece, living in severely substandard living conditions, prevention measures have been impossible with limited provision in terms of routine testing, surveillance, and access to healthcare. These migrant populations have experienced prolonged lockdowns and restricted movement since the pandemic began. We aimed to assess the impact of COVID-19 on refugees and asylum seekers in reception facilities in Greece and explore implications for policy and practice. Methods: A retrospective analysis of policy documents and national surveillance data was conducted to identify COVID-19 outbreaks and estimate incidence among asylum seekers and refugees residing in these camps during the first 9 months of the epidemic in Greece (26th February - 15th November 2020). Incidence proportion (IP) of COVID-19 confirmed cases was calculated for three population groups (refugees and asylum seekers in RICs, refugees and asylum seekers in RSs, and the general population in Greece) during three time periods (first wave, second wave, and overall across the 9-month period). Findings: Twenty-five COVID-19 outbreaks were identified in refugee and asylum seeker reception facilities, with 6 (85.7%) of 7 RICs and 18 (56.3%) of 32 RSs reporting at least one outbreak during the study period. The overall 9-month COVID-19 IP among refugee and asylum seeker populations residing in RSs on the Greek mainland was 1758 cases per 100,000 population; in RICs the incidence was 2052 cases per 100,000 population. Compared to the general population the risk of COVID-19 infection among refugees and asylum seekers in reception facilities was 2.5 to 3 times higher (p-value<0.001). The risk of acquiring COVID-19 infection was higher among refugee and asylum seeker populations in RSs on the Greek mainland (IP ratio: 2.45; 95% CI: 2.25-2.68) but higher still among refugee and asylum seeker populations in RICs in the Greek islands and the land border with Turkey (IP ratio: 2.86; 95% CI: 2.64-3.10), where living conditions are particularly poor. Interpretation: We identified high levels of COVID-19 transmission among refugees and asylum seekers in reception facilities in Greece. The risk of COVID-19 infection among these enclosed population groups has been significantly higher than the general population of Greece, and risk increases as living conditions deteriorate. These data have immediate implications for policy and practice. Strategies are now needed to ensure refugee and asylum seeker populations are included in national response plans to reduce transmission in at-risk groups for COVID-19, alongside inclusion in plans for COVID-19 vaccine roll out

The effectiveness of sexual assault referral centres with regard to mental health and substance use: a national mixed-methods study – the MiMoS Study

Background Sexual assault referral centres have been established to provide an integrated service that includes forensic examination, health interventions and emotional support. However, it is unclear how the mental health and substance use needs are being addressed. Aim To identify what works for whom under what circumstances for people with mental health or substance use issues who attend sexual assault referral centres. Setting and sample Staff and adult survivors in English sexual assault referral centres and partner agency staff. Design A mixed-method multistage study using realist methodology comprising five work packages. This consisted of a systematic review and realist synthesis (work package 1); a national audit of sexual assault referral centres (work package 2); a cross-sectional prevalence study of mental health and drug and alcohol needs (work package 3); case studies in six sexual assault referral centre settings (work package 4), partner agencies and survivors; and secondary data analysis of outcomes of therapy for sexual assault survivors (work package 5). Findings There is a paucity of evidence identified in the review to support specific ways of addressing mental health and substance use. There is limited mental health expertise in sexual assault referral centres and limited use of screening tools based on the audit. In the prevalence study, participants (n = 78) reported high levels of psychological distress one to six weeks after sexual assault referral centre attendance (94% of people had symptoms of post-traumatic stress disorder). From work package 4 qualitative analysis, survivors identified how trauma-informed care potentially reduced risk of re-traumatisation. Sexual assault referral centre staff found having someone with mental health expertise in the team helpful not only in helping plan onward referrals but also in supporting staff. Both sexual assault referral centre staff and survivors highlighted challenges in onward referral, particularly to NHS mental health care, including gaps in provision and long waiting times. Work package 5 analysis demonstrated that people with recorded sexual assault had higher levels of baseline psychological distress and received more therapy but their average change scores at end point were similar to those without sexual trauma. Limitations The study was adversely affected by the pandemic. The data were collected during successive lockdowns when services were not operating as usual, as well as the overlay of anxiety and isolation due to the pandemic. Conclusions People who attend sexual assault centres have significant mental health and substance use needs. However, sexual assault referral centres vary in how they address these issues. Access to follow-up support from mental health services needs to be improved (especially for those deemed to have ‘complex’ needs) and there is some indication that co-located psychological therapies provision improves the survivor experience. Routine data analysis demonstrated that those with sexual assault can benefit from therapy but require more intensity than those without sexual assault. Future work Further research is needed to evaluate the effectiveness and cost-effectiveness of providing co-located psychological therapy in the sexual assault referral centres, as well as evaluating the long-term needs and outcomes of people who attend these centres. Funding This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (16/117/03) and is published in full in Health and Social Care Delivery Research; Vol. 11, No. 21. Trial registration This trial is registered as PROSPERO 2018 CRD42018119706 and ISRCTN 18208347