A new artificial intelligence (AI) model, called Bagging-LMT - a combination of bagging ensemble and Logistic Model Tree (LMT) - is introduced for mapping flood susceptibility. A spatial database was generated for the Haraz watershed, northern Iran, that included a flood inventory map and eleven flood conditioning factors based on the Information Gain Ratio (IGR). The model was evaluated using precision, sensitivity, specificity, accuracy, Root Mean Square Error, Mean Absolute Error, Kappa and area under the receiver operating characteristic curve criteria. The model was also compared with four state-of-the-art benchmark soft computing models, including LMT, logistic regression, Bayesian logistic regression, and random forest. Results revealed that the proposed model outperformed all these models and indicate that the proposed model can be used for sustainable management of flood-prone areas.

A novel hybrid artificial intelligence approach for flood susceptibility assessment

Flood susceptibility mapping using novel ensembles of adaptive neuro fuzzy inference system and metaheuristic algorithms.

Flood is one of the most prevalent natural disasters that frequently occur in the northern part of Iran reported in hot spots of flood occurrences The main aim of the current study was to prepare flood susceptibility maps using four models, namely frequency ratio (FR), weights-of-evidence (WofE), analytical hierarchy process (AHP), and ensemble of frequency ratio with AHP (FR-AHP), and to compare them at Haraz Watershed in Mazandaran Province, Iran A total of 211 flood locations were prepared in GIS environment, of which 151 locations were randomly selected for modeling and the remaining 60 locations were used for validation aims In the next step, 10 flood-conditioning factors were prepared including slope angle, plan curvature, elevation, topographic wetness index, stream power index, rainfall, distance from river, geology, landuse, and normalized difference vegetation index The receiver operating characteristic curve and the area under the curve (AUC) were created for different flood susceptibility maps Validation of results showed that AUC values for success rate in training data set, for FR, WofE, AHP, and FR-AHP, were 9707, 9896, 9591, and 8619 % with prediction rates of 09657 (9657 %), 09596 (9596 %), 09492 (9492 %), and 08469 (8469 %), respectively Moreover, the results showed that the frequency ratio model had the highest AUC in comparison with other models Generally, the four models show a reasonable accuracy in flood-susceptible areas The results of this study can be useful for managers, researchers, and planners to manage the susceptible areas to flood and reduce damages

A GIS-based flood susceptibility assessment and its mapping in Iran: a comparison between frequency ratio and weights-of-evidence bivariate statistical models with multi-criteria decision-making technique

Flood susceptibility assessment in Hengfeng area coupling adaptive neuro-fuzzy inference system with genetic algorithm and differential evolution.

Application of fuzzy weight of evidence and data mining techniques in construction of flood susceptibility map of Poyang County, China.

Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope–Evros region, Greece

Defining flood-prone areas is particularly important for policy makers, in order to design mitigation strategies and implement flood risk management planning. The present research applies a multicriteria index method to assess flood hazard areas at a river basin scale, in a geographic information system (GIS) environment. The developed methodology has been applied for an area in northeastern Greece, by processing information of seven parameters: flow accumulation, distance from the drainage network, elevation, land use, rainfall intensity and geology. The method assigns a relative importance to each of the parameters for the occurrence and magnitude of flooding, and the relevant weight values are defined through an “analytical hierarchy process”. Subsequently, and according to the relative importance of each index, the spatial information is superimposed, resulting in a flood hazard map of the studied region, an area in northern Greece. The obtained results indicate flood-prone zones, with a very high flood hazard mainly occurring at the lowlands in the vicinity of the drainage network. The provided flood hazard map supports planning activities and mitigation plans that are crucial to protect both the agricultural activities and existing infrastructure from future flood events.

Assessing Flood Hazard at River Basin Scale with an Index-Based Approach: The Case of Mouriki, Greece

Supplying power to remote areas may be a challenge, even for those communities already connected to the main grid. Power is often transmitted from long distances, under adverse weather conditions, and with aged equipment. As a rule, modernizing grid infrastructure in such areas to make it more resilient faces certain financial limitations. Local distribution may face stability issues and disruptions through the year and—equally important—it cannot absorb significant amounts of locally-produced power. The European policy has underlined the importance of energy production in local level towards meeting energy security and climate targets. However, the current status of these areas makes the utilization of the local potential prohibitive. This study builds on the observation that in the vicinity of such mountainous areas, irrigation dams often cover different non energy-related needs (e.g., irrigation, drinking water). Transforming these dams to small-scale hydropower (SHP) facilities can have a twofold effect: it can enhance the local energy portfolio with a renewable energy source that can be regulated and managed. Moreover, hydropower can provide additional flexibility to the local system and through reservoir operation to allow the connection of additional solar photovoltaic capacities. The developed methodological approach was tested in remote communities of mountainous Greece, where an earth-fill dam provides irrigation water. The results show a significant increase of renewables’ penetration and enhanced communities’ electricity autarky.

https://www.mdpi.com/1996-1073/9/12/1054/pdf

Supporting Renewables’ Penetration in Remote Areas through the Transformation of Non-Powered Dams

The interest of those involved in hydroelectricity has been attracted by mini-hydro projects due to their minimal environmental impact and low installation cost. Besides, mini hydros can cooperate with an impressively wide extent of water-related infrastructure, offering a broad potential for investment. In the present chapter, the integrated solution of hydro implementation in water supply systems is presented. Thus, the benefits of a water-supply installation (with constant Q) are extended to energy production. However, defining the optimum operation of such a project is a complicated task, which may involve environmental, hydraulic, technical, and economical parameters. In the present chapter a novel approach is presented, the optimum management of mini hydros in a water supply system with the use of an optimization algorithm (i.e. Harmony Search Algorithm [HAS]). This approach is applied at a site in Northern Greece and is used as a case study of the present chapter. Ioannis Kougias Aristotle University of Thessaloniki, Greece Thomas Patsialis Aristotle University of Thessaloniki, Greece Nicolaos Theodossiou Aristotle University of Thessaloniki, Greece Jacques Ganoulis Aristotle University of Thessaloniki, Greece

Hydropower Projects within a Municipal Water Supply System: Optimum Allocation and Management using Harmony Search

The remote and mountainous regions face permanent problems with their electric network, such as stability problems, sudden drops in voltage and power quality that affect people’s daily life at home and their devices’ performance. The reasons for the poor quality of electricity are due to the aged, remote local distribution network and the often harsh weather conditions especially during winter months. Feeding the grid in reverse order is our proposed solution which will decrease electricity needs to be transmitted over great distances. Energy production in remote regions could be advantageous if it included the utilization of local renewable energy sources. The system of production, storage and management of energy could provide greater network stability which would then lead to better electricity quality, reduction of potential losses and failures under specific conditions. The present study focuses on the use of renewable sources to create a smart energy storage system with the goal to achieve the grid benefits analyzed. By examining currently available technologies and taking into account their potential commercial applications in the near future along with their costs, it appears that a promising approach is to use renewable in a hybrid mode combined with batteries for energy storage. The article develops an energy system (including photovoltaic, wind and hydroelectric power stations), which offers energy according to the demand in real time with appropriate modeling. The aim of the article is to create a system for producing, storing and managing energyby using renewable sources and batteries at minimal environmental impact.

Thomas Patsialis

Papers

Assessment of flood hazard areas at a regional scale using an index-based approach and Analytical Hierarchy Process: Application in Rhodope–Evros region, Greece

Assessing Flood Hazard at River Basin Scale with an Index-Based Approach: The Case of Mouriki, Greece

Supporting Renewables’ Penetration in Remote Areas through the Transformation of Non-Powered Dams

Hydropower Projects within a Municipal Water Supply System: Optimum Allocation and Management using Harmony Search

A technical study on energy storage and management for grid optimization in isolated areas