Flooding edge or node weighted graphs

Reconstruction closings have all properties of a physical flooding of a topographic surface. They are precious for simplifying gradient images or, filling unwanted catchment basins, on which a subsequent watershed transform extracts the targeted objects. Flooding a topographic surface may be modeled as flooding a node weighted graph (TG), with unweighted edges, the node weights representing the ground level. The progression of a flooding may also be modeled on the region adjacency graph (RAG) of a topographic surface. On a RAG each node represents a catchment basin and edges connect neighboring nodes. The edges are weighted by the altitude of the pass point between both adjacent regions. The graph is flooded from sources placed at the marker positions and each node is assigned to the source by which it has been flooded. The level of the flood is represented on the nodes on each type of graphs. The same flooding may thus be modeled on a TG or on a RAG. We characterize all valid floodings on both types of graphs, as they should verify the laws of hydrostatics. We then show that each flooding of a node weighted graph also is a flooding of an edge weighted graph with appropriate edge weights. The highest flooding under a ceiling function may be interpreted as the shortest distance to the root for the ultrametric flooding distance in an augmented graph. The ultrametric distance between two nodes is the minimal altitude of a flooding for which both nodes are flooded. This remark permits to flood edge or node weighted graphs by using shortest path algorithms. It appears that the collection of all lakes of a RAG has the structure of a dendrogram, on which the highest flooding under a ceiling function may be rapidly found.Comment: 165 pages, 21 figure

A Mediterranean element of the vegetation: Junco maritimi-Cladietum marisci – a new association for Ukraine

Cladium mariscus (L.) Pohl (Cyperaceae) is a rare species in Europe considered by several authors to be a relict of the early Holocene period. It is listed in the Red Data Book of Ukraine, Annexes of the Habitat Directive and the Bern Convention. Communities with domination of this species are included in the Green Data Book of Ukraine. Substantial differences in major ecological factors for Cladium mariscus communities in the western (carbonate bogs) and the southern (marshes and floating swamps of the northern Black Sea) regions of Ukraine were shown. The author carried out comparisons of relevés characterizing different communities with Cladium mariscus within Europe. Based on the results of TWINSPAN analysis, four associations were identified, confirmed by floristic indices and ecological data: Cladietum marisci Allorge 1921, Soncho maritimi-Cladietum marisci (Br.-Bl. & O. de Bolòs 1957) Cirujano 1980, Dorycnio recti-Cladietum marisci Gradstein & Smittenberg 1977 and Junco maritimi-Cladietum marisci (Br.-Bl. & O. de Bolòs 1957) Géhu & Biondi 1988. Thus, in addition to the association Cladietum marisci, a new one was indicated for Ukraine, Junco maritimi-Cladietum marisci

Spatial and Temporal Dynamics of Salt Marsh Vegetation across Scales

Biogeographic patterns across a landscape are developed by the interplay of environmental processes operating at different spatial and temporal scales. This research investigated dynamics of salt marsh vegetation on the Skallingen salt marsh in Denmark responding to environmental variations at large, medium, and fine scales along both spatial and temporal spectrums. At the broad scale, this research addressed the importance of wind-induced rise of the sea surface in such biogeographic changes. A new hypothetical chain was suggested: recent trends in the North Atlantic Oscillation index toward its positive phase have led to increased storminess and wind tides on the ocean surface, resulting in increased frequency, duration, and magnitude of submergence and, hence, waterlogging of marsh soils and plants, which has retarded ecological succession. At the mid-scale, spatial patterns of vegetation and environmental factors were examined across tidal creeks. Sites closer to tidal creeks, compared to marsh interiors, were characterized by the dominance of later-successional species, higher bulk density, and lower nutrient contents and electrical conductivity. This finding implies that locations near creeks have experienced a better drainage condition than the inner marshes, which eventually facilitated the establishment of later-successional plants that are intolerant to physical stress. At the micro-scale, this research examined how the extent and mode of facilitation and competition vary for different combinations of plant species along physical gradients. Both positive and negative relationships were spatially manifested to a greater degree on the low marsh than on the mid marsh. This insight extends our current knowledge of scale-dependent interactions beyond pioneer zones to higher zones. On the low marsh, different types of bivariate point pattern (i.e., clustered, random, and regular) were observed for different combinations of species even at similar spatial scales. This finding implies that it is difficult to generalize at which scales competition and facilitation occur. To conclude, this research stresses the need for a holistic approach in future investigations of salt marsh biogeography. For example, based on results of this current research, it would be meaningful to develop a comprehensive simulation model that incorporates salt marsh ecology, geomorphology, and hydrology observed across scales

Smart Urban Water Networks

This book presents the paper form of the Special Issue (SI) on Smart Urban Water Networks. The number and topics of the papers in the SI confirm the growing interest of operators and researchers for the new paradigm of smart networks, as part of the more general smart city. The SI showed that digital information and communication technology (ICT), with the implementation of smart meters and other digital devices, can significantly improve the modelling and the management of urban water networks, contributing to a radical transformation of the traditional paradigm of water utilities. The paper collection in this SI includes different crucial topics such as the reliability, resilience, and performance of water networks, innovative demand management, and the novel challenge of real-time control and operation, along with their implications for cyber-security. The SI collected fourteen papers that provide a wide perspective of solutions, trends, and challenges in the contest of smart urban water networks. Some solutions have already been implemented in pilot sites (i.e., for water network partitioning, cyber-security, and water demand disaggregation and forecasting), while further investigations are required for other methods, e.g., the data-driven approaches for real time control. In all cases, a new deal between academia, industry, and governments must be embraced to start the new era of smart urban water systems

Regional analysis of groundwater droughts using hydrograph classification

Groundwater drought is a spatially and temporally variable phenomenon. Here we describe the development of a method to regionally analyse and quantify groundwater drought. The method uses a cluster analysis technique (non-hierarchical k-means) to classify standardised groundwater level hydrographs (the standardised groundwater level index, SGI) prior to analysis of their groundwater drought characteristics, and has been tested using 74 groundwater level time series from Lincolnshire, UK. Using the test data set, six clusters of hydrographs have been identified. For each cluster a correlation can be established between the mean SGI and a mean standardised precipitation index (SPI), where each cluster is associated with a different SPI accumulation period. Based on a comparison of SPI time series for each cluster and for the study area as a whole, it is inferred that the clusters are independent of the driving meteorology and are primarily a function of catchment and hydrogeological factors. This inference is supported by the observation that the majority of sites in each cluster are associated with one of the principal aquifers in the study region. The groundwater drought characteristics of the three largest clusters, which constitute ~ 80 % of the sites, have been analysed. There are differences in the distributions of drought duration, magnitude and intensity of groundwater drought events between the three clusters as a function of autocorrelation of the mean SGI time series for each cluster. In addition, there are differences between the clusters in their response to three major multi-annual droughts that occurred during the analysis period. For example, sites in the cluster with the longest SGI autocorrelation experience the greatest-magnitude droughts and are the slowest to recover from major droughts, with groundwater drought conditions typically persisting at least 6 months longer than at sites in the other clusters. Membership of the clusters is shown to be related to unsaturated zone thickness at individual boreholes. This last observation emphasises the importance of catchment and aquifer characteristics as (non-trivial) controls on groundwater drought hydrographs. The method of analysis is flexible and can be adapted to a wide range of hydrogeological settings while enabling a consistent approach to the quantification of regional differences in response of groundwater to meteorological drought

Climate dynamics : the performance of seasonal ensemble forecast for improving food security in Ethiopia

Part one of this thesis aims to define homogenous climatic regions using objective clustering methods and characterize seasonal cycles, trends, and anomalies in precipitation and temperature. Climate-based on amplifies inherent spatiotemporal climate variability in the Horn of Africa due to global, regional, coastal, and local processes. The homogeneous climatic regions and synoptic circulation types were defined using Principal Component Analysis (PCA) PCAK-means and PCAWards. Using the decision criteria of respective algorithms, four homogenous climatic regions were determined for Ethiopia. These climatic regions were distinctive in their seasonal cycles, trends, and anomalies in annual and seasonal precipitation and temperature. These results highlight that the trends in precipitation and temperature vary not only between climatic regions but also by rainy seasons. The short rains (received between November and December) increased by 50 mm/decade in the southwestern region where the evergreen forest meets with the long rainy season. The mean annual and seasonal temperature increased between 0.3 and 0.6 °C/decade virtually in all climatic regions. Regionalization methods were sensitive to spatial domain size but not to the length of the time series. Climatology of sea-level air pressure showed decreasing northward trend over the study domain, as did the temperature, wind velocity, and relative humidity at 500 hPa. However, geopotential height at 500 hPa and temperature at 850 hPa decreased toward the south over the domain. Circulation types were defined by applying PCA on a composite matrix of the six variables. From the first five Principal Components (PCs), ten circulation types (CTs) were defined over East Africa and then associated with environmental events. CTs clearly distinguished rainy seasons comprising different atmospheric states responsible for varying weathers. The summer season was described by a combination of strong positive anomalies in temperature at 850 hPa, northeasterly winds, and Somali jet at 500 hPa, and weak negative anomalies in temperature at 500 hPa. Trends in the number of days categorized in different CTs showed a significant variation among the groups. The drought events, defined using the consecutive dry days (CDD), correspond with positive anomalies in temperature at 850 hPa, northwesterly and Somali Jet, and negative anomalies in relative humidity at 500 hPa. Flooding, defined using a proxy of 80 mm/day per grid cell, was associated with strong westerly winds at 500 hPa, strong positive anomalies in temperature at the lower troposphere, strong easterlies and southwesterly, and positive anomalies in relative humidity at 500 hPa. Part two of the thesis aims to assess the performance of the seasonal ensemble forecast over the Horn of Africa for improving food security. A seasonal forecast with a horizon of up to seven months offers a great opportunity for agricultural optimization, which results in an improved economy and food security. For this purpose, the Weather Research and Forecasting (WRF) model was applied for dynamical downscaling of the latest seasonal forecasting system version 5 (SEAS5) for summer 2018 with different microphysics parameterizations, and initial and boundary conditions. Downscaling was performed by a horizontal resolution of 3 km over the topographically complex domain of East Africa. The seasonal ensemble forecast was evaluated using probabilistic metrics like the Brier skill score, probability ranking score, continuous probability ranking score, discrimination score, and ignorance score. The results of the WRF showed that the model has a strong warm bias in the 2m temperature and a wet bias in precipitation. The relative operating characteristics (ROC) curve showed a higher predicting probability of 2m temperature in below-normal and above-normal terciles over northern Ethiopia and the Indian Ocean, where the model performed better, highlighting the advantage of high-resolution simulations compared to ERA5. The median and distribution of WRF, SEAS5, and ERA5 showed remarkable variation between the homogenous climatic regions. Especially the summer of 2018 was wetter relative to climatology, and WRF overestimated this condition in the region.Der erste Teil dieser Arbeit zielt darauf ab, homogene Klimaregionen mit Hilfe objektiver Clustermethoden zu definieren und sie durch den saisonalen Verlauf, Trends und Anomalien von Niederschlag und Temperatur zu charakterisieren. Der Klimawandel verstärkt die schon an sich vorhandene rämlich-zeitliche Klimavariabilität am Horn von Afrika durch globale, regionale, küstennahe und lokale Prozesse. Die homogenen Klimaregionen und synoptischen Zirkulationstypen wurden mit Hilfe der Hauptkomponentenanalysen (PCA) PCA-K-Means und PCA-Wards bestimmt. Anhand der Entscheidungskriterien der jeweiligen Algorithmen wurden vier homogene Klimaregionen für Äthiopien bestimmt. Diese Klimaregionen unterschieden sich durch ihre saisonalen Verlauf, Trends und Anomalien bei den jährlichen und saisonalen Niederschlägen und Temperaturen. Diese Trends variieren bei Niederschlag und Temperatur nicht nur zwischen den Klimaregionen, sondern auch zwischen den Regenzeiten. In der südwestlichen Region, wo der immergrüne Wald mit der langen Regenzeit zusammentrifft, haben die Regenfälle zwischen November und Dezember um 50 mm/Dekade zugenommen. Die mittlere jährliche und saisonale Temperatur stieg nahezu in allen Klimaregionen um 0,3 °C bis 0,6 °C/Dekade. Die Regionalisierungsmethoden reagierten sensitiv auf die Größe der Region, nicht aber auf die Länge der Zeitreihen. Die Klimatologie des Luftdrucks auf Meereshöhe zeigte über dem Untersuchungsgebiet eine abnehmende Tendenz in Richtung Norden, ebenso wie die Temperatur, die Windgeschwindigkeiten und die relative Luftfeuchtigkeit in 500 hPa. Die geopotentielle Höhe in 500 hPa und die Temperatur in 850 hPa nahmen über dem untersuchten Gebiet nach Süden hin ab. Die Zirkulationstypen wurden durch Anwendung der PCA auf eine zusammengesetzte Matrix der sechs Variablen definiert. Aus den ersten fünf Hauptkomponenten (PC) wurden zwölf Zirkulationstypen (CTs) über Ostafrika definiert und dann mit verschiedenenen Ereignissen in Verbindung gebracht. Die CTs unterschieden eindeutig zwischen Regenzeiten und verschiedenen atmosphärischen Zuständen, die für unterschiedliche Wetterlagen verantwortlich sind. Die Sommersaison wird durch eine Kombination aus starken positiven Anomalien der Temperatur in 850 hPa, nordöstlichen Winden und dem Somali-Jet in 500 hPa und schwachen negativen Anomalien der Temperatur in 500 hPa beschrieben. Die Trends der Anzahl der Tage, die in verschiedene CTs eingestuft wurden, zeigten eine signifikante Variation zwischen den Gruppen. Dürreereignisse, die anhand der Zahl aufeinanderfolgender trockener Tage (CDD) definiert werden, entsprechen positiven Anomalien der Temperatur in 850 hPa, des Nordwest- und Somali Jets und negativen Anomalien der relativen Luftfeuchtigkeit in 500 hPa. Überschwemmungen, die anhand eines Proxys von 80 mm/Tag pro Gitterzelle definiert wurden, waren mit starken Westwinden in 500 hPa, starken positiven Temperaturanomalien in der unteren Troposphäre, starken Ost- und Südwestwinden und positiven Anomalien der relativen Luftfeuchtigkeit in 500 hPa verbunden. Im zweiten Teil der Arbeit wurde die Leistungsfähigkeit saisonaler Ensemble-Simulationen über dem Horn von Afrika untersucht. Eine saisonale Vorhersage mit einer Simulationsdauer von bis zu sieben Monaten bietet eine große Chance, die Landwirtschaft zu optimieren, was zu einer Verbesserung der wirtschaftlichen Lage und Ernährungssicherheit führt. Zu diesem Zweck wurde das Wettervorhersagemodell WRF verwendet, um das neueste saisonale Vorhersagesystem Version 5 (SEAS5) für den Sommer 2018 mit verschiedenen Multiphysik-Parametrisierungen im Hinblick auf die horizontale Auflösung weiter zu verfeinern. Dies wurde mit einer horizontalen Auflösung von 3 km über dem topografisch komplexen Gebiet von Ostafrika durchgeführt. Die saisonale Ensemble-Vorhersage wurde anhand probabilistischer Metriken wie dem Brier Skill Score, dem Probability Ranking Score, dem Continuous Probability Ranking Score, dem Discrimination Score und dem Ignorance Score bewertet. Die Ergebnisse zeigten, dass das Modell bei der Simulation der Temperatur in 2 m Höhe und beim Niederschlag zu hohe Werte aufweist. Die Relative Operating Characteristics (ROC) Kurve zeigte eine höhere Vorhersagewahrscheinlichkeit der 2-m Temperaturen im unter- und übernormalen Bereich über Nordäthiopien und dem Indischen Ozean, wo das Vorhersagemodell besser abschnitt, was den Vorteil von hochauflösenden Simulationen im Vergleich zu ERA5 verdeutlicht. Der Median und die Verteilung von WRF, SEAS5 und ERA5 zeigten größere Unterschiede zwischen den homogenen Klimaregionen. Besonders der Sommer 2018 war im Vergleich zur Klimatologie deutlich feuchter, wobei das WRF nochmals deutlich zu viel Niederschlag simulierte. Insgesamt war die Vorhersagequalität des WRF Modells im Hinblick auf die Simulationen von Niederschlägen im nordöstlichen Teil Äthiopiens deutlich besser als in den anderen Regionen