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Floods in urban environments often result in loss of life and destruction of property, with many negative socio-economic effects. However, the application of most flood prediction models still remains challenging due to data scarcity. This creates a need to develop novel hybridized models based on historical urban flood events, using, e.g., metaheuristic optimization algorithms and wavelet analysis. The hybridized models examined in this study (Wavelet-SVR-Bat and Wavelet-SVR-GWO), designed as intelligent systems, consist of a support vector regression (SVR), integrated with a combination of wavelet transform and metaheuristic optimization algorithms, including the grey wolf optimizer (GWO), and the bat optimizer (Bat). The efficiency of the novel hybridized and standalone SVR models for spatial modeling of urban flood inundation was evaluated using different cutoff-dependent and cutoff-independent evaluation criteria, including area under the receiver operating characteristic curve (AUC), Accuracy (A), Matthews Correlation Coefficient (MCC), Misclassification Rate (MR), and F-score. The results demonstrated that both hybridized models had very high performance (Wavelet-SVR-GWO: AUC = 0.981, A = 0.92, MCC = 0.86, MR = 0.07; Wavelet-SVR-Bat: AUC = 0.972, A = 0.88, MCC = 0.76, MR = 0.11) compared with the standalone SVR (AUC = 0.917, A = 0.85, MCC = 0.7, MR = 0.15). Therefore, these hybridized models are a promising, cost-effective method for spatial modeling of urban flood susceptibility and for providing in-depth insights to guide flood preparedness and emergency response services.

Water erosion is a major threat to biodiversity, according to the European Commission’s Soil Thematic Strategy, as it negatively affects soil structure, soil fertility and water availability for plants. The island of Crete (Southern Greece) has been characterized as a biodiversity hotspot including several Natura 2000 (N2K)-protected areas. The aim of this study was to model the soil loss rate in Crete regarding species richness, habitat types and their conservation status, as well as the MAES (Mapping and Assessment of Ecosystem and their Services) ecosystem types. To this end, the RUSLE soil erosion prediction model was implemented, using freely available geospatial data and cloud-computing processes. The estimated average soil loss in the study area was 6.15 t ha−1 y−1, while there was no significant difference between the terrestrial N2K (6.06 t ha−1 y−1) and non-N2K (6.19 t ha−1 y−1) areas. Notably, the natural habitats of principal importance for the conservation of biodiversity (referred to as “priority” areas), according to Annex I to Directive 92/43/EEC, are threatened by soil erosion with an estimated mean annual soil loss equal to 8.58 t ha−1 y−1. It is also notable that grasslands, heathland and shrubs and sparsely vegetated areas experienced the highest erosion rates among the identified MAES ecosystem types. The results showed that soil erosion is a serious threat to biodiversity in N2K-protected areas. Therefore, there is a need for systematic spatiotemporal monitoring and the implementation of erosion mitigation measures.

Η παρούσα διατριβή αποσκοπεί στην αξιολόγηση των επιπτώσεων της κλιματικής αλλαγής στην επιφανειακή απορροή των χειμαρρικών ρευμάτων της Κεντρικής Πίνδου και συμβάλει στην ορθολογική διαχείριση των υδατικών πόρων. Συγκεκριμένα μελετήθηκαν οι λεκάνες απορροής του Κλεινοβίτικου, του Ασπροπόταμου, του Κόρπου και του Πορταϊκού. Η περιοχή έρευνας παρουσιάζει αυξημένο υδρολογικό ενδιαφέρον, επειδή ανήκει στον ορεινό χώρο δύο υδρολογικών λεκανών (Πηνειός, Αχελώος), που τροφοδοτούν την Κεντρική Ελλάδα με νερό. Επιπλέον διαθέτει μακροχρόνιες χρονοσειρές μετεωρολογικών παραμέτρων από ένα πυκνό δίκτυο σταθμών σε μεγάλα υψόμετρα. Για τη χαρτογράφηση των χειμαρρικών ρευμάτων και την οριοθέτηση των λεκανών απορροής αναπτύχτηκε εργαλειοθήκη σε περιβάλλον Γεωγραφικών Συστημάτων Πληροφοριών (Γ.Σ.Π.) με τη χρήση της οπτικής γλώσσας προγραμματισμού ModelBuilder. Στη συνέχεια, προσδιορίστηκαν τα μορφομετρικά και υδρογραφικά χαρακτηριστικά των χειμαρρικών ρευμάτων και αναλύθηκαν οι παράγοντες που διαμορφώνουν το χειμαρρικό περιβάλλον (κλίμα, ανάγλυφο, βλάστηση και γεωλογικό υπόβαθρο). Οι ευδιάβρωτοι πετρολογικοί σχηματισμοί (φλύσχης, ασβεστόλιθος) που απαντώνται στην περιοχή σε συνδυασμό με το έντονο ανάγλυφο και το σημαντικό ύψος βροχοπτώσεων, ευνοούν την ανάπτυξη έντονων χειμαρρικών φαινομένων παρά το πολύ υψηλό ποσοστό δασοκάλυψης (65%) των λεκανών απορροής. Επιπρόσθετα, μελετήθηκε η χωρική μεταβλητότητα των βροχοπτώσεων, θερμοκρασιών αέρα και χιονοπτώσεων. Η συσχέτιση των παραπάνω μετεωρολογικών παραμέτρων με το υπερθαλάσσιο υψόμετρο έδωσε ικανοποιητικά αποτελέσματα, με εξαίρεση τις βροχοπτώσεις, όπου και αναπτύχθηκε μοντέλο πολλαπλής γραμμικής παλινδρόμησης λαμβάνοντας υπόψη τις γεωγραφικές συντεταγμένες και την απόσταση των σταθμών από τη θάλασσα. Χρησιμοποιήθηκε η μέθοδος των ελαχίστων τετραγώνων και o μη παραμετρικός έλεγχος Mann-Kendall για τον προσδιορισμό των τάσεων στις χρονοσειρές (βροχόπτωση, θερμοκρασία, χιονοπτώσεις) και του επιπέδου σημαντικότητας αυτών. Από την ανάλυση αυτή προέκυψε ότι στην πλειοψηφία των υπό εξέταση μετεωρολογικών σταθμών εμφανίζονται τάσεις μείωσης των ετήσιων βροχοπτώσεων (-1,5% έως -14,6%) και αύξησης των μέσων ετήσιων θερμοκρασιών (+2,2% έως +9,4%), που δεν είναι όμως στατιστικά σημαντικές. Σε ότι αφορά τις χιονοπτώσεις, καταγράφηκε τάση μείωσης, τόσο του ύψος χιονιού (-29,3% έως -58,7%) όσο και του αριθμού ημερών χιονιού (-24,8% έως -58,8%) στο σύνολο σχεδόν των υπό εξέταση σταθμών οι τάσεις δεν βρέθηκαν στατιστικά σημαντικές. Ακολούθησε η αξιολόγηση της ικανότητας των περιοχικών κλιματικών μοντέλων (Regional Climate Models - RCMs) του ευρωπαϊκού πρoγράμματος ENSEMBLES να προσομοιώνουν το βροχομετρικό και θερμοκρασιακό καθεστώς της περιοχής έρευνας. Κατά την αξιολόγηση, συγκρίθηκαν τα δεδομένα των σταθμών με τα δεδομένα του κοντινότερου σημείου πλέγματος των RMCs, για την περίοδο αναφοράς 1974-2000. Ως κριτήρια αξιολόγησης χρησιμοποιήθηκαν η τετραγωνική ρίζα του μέσου τετραγωνικού σφάλματος (RMSE), το μέσο σφάλμα μεροληψίας (MBE), το μέσο απόλυτο σφάλμα (MAE) και ο συντελεστής συσχέτισης (r). Σύμφωνα με τα κριτήρια αξιολόγησης φάνηκε ότι καλύτερη προσομοίωση, τόσο των βροχοπτώσεων όσο και των θερμοκρασιών, επιτυγχάνει το μοντέλο του ICTP (RegCM3) και έπεται το μοντέλο του HC (METO- HC_HadR M3Q0). Τέλος, εκτιμήθηκε η επιφανειακή απορροή των χειμαρρικών ρευμάτων, εφαρμόζοντας το μοντέλο υδατικού ισοζυγίου των Thornthwaite and Mather για τις συνθήκες της περιόδου βάσης (1974-2000) και τις εκτιμούμενες μελλοντικές συνθήκες (2074-2100). Προέκυψε πως θα υπάρξει σημαντική μείωση της επιφανειακής απορροής στο μέλλον. Σε ότι αφορά το μοντέλο ICTP (RegCM3) η μεγαλύτερη μείωση εμφανίζεται τους θερινούς μήνες (-14% έως -57,6%) και η μικρότερη τους φθινοπωρινούς (-0,8% έως -34,8%), ενώ σύμφωνα με το μοντέλο του HC (METO- HC_HadR M3Q0), η μεγαλύτερη μείωση εμφανίζεται τους φθινοπωρινούς μήνες (-7,8% έως -80,3%) και η μικρότερη τους χειμερινούς (-6,4% έως -33,4%). Τέλος, προτείνονται τα κατάλληλά υδρονομικά έργα, που περιλαμβάνουν τον χειρισμό των ορεινών λεκανών απορροής, των κοιτών και των κώνων πρόσχωσης των χειμαρρικών ρευμάτων, για προσαρμογή της διαχείρισης των λεκανών απορροής στην κλιματική αλλαγή.

Wildfires have been an integral part of the Mediterranean ecosystem. Moreover, the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report emphasizes that the Mediterranean basin is expected to be drier by the end of the 21st century, while future warming will possibly be higher than the global mean. Therefore, outbreaks of wildfires are expected to increase. One of the most important factors for wildfire behavior apart from the meteorological conditions, is fuel types. In this study, a detailed fuel type mapping in a case study area was addressed. To accomplish this goal, an object-based image analysis (OBIA) approach was implemented using the open-source Orfeo toolbox. The freely available Sentinel-2A satellite images were processed in combination with auxiliary European and National scale GIS data. The classification results demonstrate a high-quality Land Cover map with 84% of overall accuracy. The classified land cover polygons were associated with high-resolution tree cover density data derived from Copernicus Land Monitoring Service. This coupling led to the synthesis of the fuel type map. To this end, this approach can fulfill the efficient mapping of fuel types for operational purposes. This research has been co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH –CREATE –INNOVATE (project code:T2EDK-01967)

During the last few years, there is a growing concern about climate change and its negative effects on water availability. This study aims to evaluate the performance of regional climate models (RCMs) in simulating seasonal precipitation over the mountainous range of Central Pindus (Greece). To this end, observed precipitation data from ground-based rain gauge stations were compared with RCMs grid point&rsquo, s simulations for the baseline period 1974&ndash, 2000. Statistical indexes such as root mean square error (RMSE), mean absolute error (MAE), Pearson correlation coefficient, and standard deviation (SD) were used in order to evaluate the model&rsquo, s performance. The results demonstrated that RCMs fail to represent the temporal variability of precipitation time series with exception of REMO. Although, concerning the model&rsquo, s prediction accuracy, it was found that better performance was achieved by the RegCM3 model in the study area. In addition, regarding a future projection (2074&ndash, 2100), it was highlighted that precipitation will significantly decrease by the end of the 21st century, especially in spring (&minus, 30%). Therefore, adaption of mountainous catchment management to climate change is crucial to avoid water scarcity.

We present the systems we submitted for the shared tasks of the Workshop on Scholarly Document Processing at EMNLP 2020. Our approaches to the tasks are focused on exploiting large Transformer models pre-trained on huge corpora and adapting them to the different shared tasks. For tasks 1A and 1B of CL-SciSumm we are using different variants of the BERT model to tackle the tasks of “cited text span” and “facet” identification. For the summarization tasks 2 of CL-SciSumm, LaySumm and LongSumm we make use of different variants of the PEGASUS model, with and without fine-tuning, adapted to the nuances of each one of those particular tasks.

Floods are the most common natural disaster globally and lead to severe damage, especially in urban environments. This study evaluated the efficiency of a self-organizing map neural network (SOMN) algorithm for urban flood hazard mapping in the case of Amol city, Iran. First, a flood inventory database was prepared using field survey data covering 118 flooded points. A 70:30 data ratio was applied for training and validation purposes. Six factors (elevation, slope percent, distance from river, distance from channel, curve number, and precipitation) were selected as predictor variables. After building the model, the odds ratio skill score (ORSS), efficiency (E), true skill statistic (TSS), and the area under the receiver operating characteristic curve (AUC-ROC) were used as evaluation metrics to scrutinize the goodness-of-fit and predictive performance of the model. The results indicated that the SOMN model performed excellently in modeling flood hazard in both the training (AUC = 0.946, E = 0.849, TSS = 0.716, ORSS = 0.954) and validation (AUC = 0.924, E = 0.857, TSS = 0.714, ORSS = 0.945) steps. The model identified around 23% of the Amol city area as being in high or very high flood risk classes that need to be carefully managed. Overall, the results demonstrate that the SOMN model can be used for flood hazard mapping in urban environments and can provide valuable insights about flood risk management.

Soil is a non-renewable resource essential for life existence. During the last decades it has been threatened by accelerating erosion with negative consequences for the environment and the economy. The aim of the current study was to assess soil loss changes in a typical Mediterranean ecosystem of Northern Greece, under climate change. To this end, freely available geospatial data was collected and processed using open-source software package. The widespread RUSLE empirical erosion model was applied to estimate soil loss. Current and future rainfall erosivity were derived from a national scale study considering average weather conditions and RCMs outputs for the medium Representative Concentration Pathway scenario (RCP4.5). Results showed that average rainfall erosivity (R-Factor) was 508.85 MJ mm ha h−1 y−1 while the K-factor ranged from 0.0008 to 0.05 t ha h ha−1 MJ−1 mm−1 and LS-factor reached 60.51. Respectively, C-factor ranged from 0.01 to 0.91 and P-factor ranged from 0.42 to 1. The estimated potential soil loss rates will remain stable for the near future period (2021–2050), while an increase of approximately 9% is expected by the end of the 21th century (2071–2100). The results suggest that appropriate erosion mitigation strategies should be applied to reduce erosion risk. Subsequently, appropriate mitigation measures per Land Use/Land Cover (LULC) categories are proposed. It is worth noting that the proposed methodology has a high degree of transferability as it is based on open-source data.

Watershed prioritization based on the natural and anthropogenic factors involves by locating the critical areas of flood hazard, which cause socio-economic and environmental consequences to take up mitigation activities on priority basis. The pair-wise comparisons of natural and anthropogenic factors is a bit problematic, because these two mentioned factors are different from typology view point. In order to assess flood hazard potential by using (1) only natural factors (FHPNF), (2) only anthropogenic factors (FHPAF), and (3) ensemble the obtained sub-watersheds priorities from natural and anthropogenic factors , the coupling of the Analytical Hierarchy Process (AHP) and Geographical Information Systems (GIS) were applied the Gorganrood river basin of Iran. Each effective factor was assigned to appropriate weight based on Saaty’s 9 point scale and the obtained weights were normalized through the Eigenvector method. By using the Weighted Linear Combination (WLC), two flood hazard potential indexes were defined separately for anthropogenic and natural factors. Finally, both indices values were combined to determine sub-watersheds priority. For the validation of the predictions, the Receiver Operating Characteristic (ROC) curve and historical data of flash flood events were used. According to the results of ROC curves, the FHPNF and FHPAF maps showed a reasonable good performance in watershed prioritization with area under ROC curve (AUC) values of 76.1 and 79.5 %, respectively. In addition, these results imply that one and two sub-watersheds fall under very high and high priority, respectively. The results of this study act as guidelines for managers and planners to determine sub-watersheds priority and rational management of watersheds based on both natural and anthropogenic components.

Flooding is the most common natural hazard in Greece, and most of low-lying urban centers are flood-prone areas. Assessment of flood hazard zones is a necessity for rational management of watersheds. In this study, the coupling of the analytical hierarchy process and geographical information systems were used, in order to assess flood hazard, based either on natural or on anthropogenic factors. The proposed method was applied on Kassandra Peninsula, in Northern Greece. The morphometric and hydrographic characteristics of the watersheds were calculated. Moreover, the natural flood genesis factors were examined, and subsequently, the anthropogenic interventions within stream beds were recorded. On the basis of the above elements, two flood hazard indexes were defined, separately for natural and anthropogenic factors. According to the results of these indexes, the watersheds of the study area were grouped into hazard classes. At the majority of watersheds, the derived hazard class was medium (according to the classification) due to natural factors and very high due to anthropogenic. The results were found to converge to historical data of flood events revealing the realistic representation of hazard on the relating flood hazard maps.

The biggest threat to reservoirs after their construction, which can reduce their capacity, life cycle and water quality, is sediments carried inflowing streams. The sediment volumes in four reservoirs in Central Macedonia, Greece, were measured in this study. These measurements indicated the study reservoirs are under serious threat from sedimentation. Appropriate measures to protect these newly formed reservoirs from sedimentation also are proposed.

Lakes or natural reservoirs are usually formed by the water supplied by torrents runoff. Furthermore, runoff, according to the torrential environment that forms the watershed (climate, geology, vegetation and relief) is usually associated with debris fl ow. As a result, many lakes and reservoirs are undergoing an alluviation process which leads to an important reduction of their total capacity. In fact, long-term process of torrents may threaten their existence. Lakes and reservoirs have an important role since the impounding water is used for multi purposes such as municipal supply, irrigation and recreation. Often, lakes form wetlands that are really important and are protected by national or international treaties. In this paper, the methodology we use involve the analysis of torrential environment (potential) of the lake Volvi watershed. Moreover, the mean annual sediment yield calculated according to Gavrilovic method so as to assess the risk of alluviation. Also, Kronfellner‐Kraus method used in order to take under consideration the sediment that can fl ow into the lake after an extraordinary fl ood event. Finally, fl ood control works proposed so as minimize the threat of alluviation. The present study shows that the torrential environment (potential) is rather moderate, although during intense rainfalls great volume of water and

The aim of this study was to assess soil erosion changes in the mountainous catchment of the Portaikos torrent (Central Greece) under climate change. To this end, precipitation and temperature data were derived from a high-resolution (25 &times, 25 km) RegCM3 regional climate model for the baseline period 1974&ndash, 2000 and future period 2074&ndash, 2100. Additionally, three GIS layers were generated regarding land cover, geology, and slopes in the study area, whereas erosion state was recognized after field observations. Subsequently, the erosion potential model (EPM) was applied to quantify the effects of precipitation and temperature changes on soil erosion. The results showed a decrease (&minus, 21.2%) in annual precipitation (mm) and increase (+3.6 &deg, C) in mean annual temperature until the end of the 21st century, and the above changes are likely to lead to a small decrease (&minus, 4.9%) in soil erosion potential.

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961&ndash, 2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann&ndash, Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen&rsquo, s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately &minus, 1.9%, &minus, 3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.