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Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion (2019)
Journal Article
Alexakis, D. D., Tapoglou, E., Vozinaki, A. K., & Tsanis, I. K. (2019). Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion. Remote Sensing, 11(9), https://doi.org/10.3390/rs11091106

Soil erosion is one of the main causes of soil degradation among others (salinization, compaction, reduction of organic matter, and non-point source pollution) and is a serious threat in the Mediterranean region. A number of soil properties, such as... Read More about Integrated Use of Satellite Remote Sensing, Artificial Neural Networks, Field Spectroscopy, and GIS in Estimating Crucial Soil Parameters in Terms of Soil Erosion.

Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete (2019)
Journal Article
Tapoglou, E., Vozinaki, A., & Tsanis, I. (2019). Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete. Water, 11(3), https://doi.org/10.3390/w11030587

Frequency analysis on extreme hydrological and meteorological events under the effect of climate change is performed in the island of Crete. Data from Regional Climate Model simulations (RCMs) that follow three Representative Concentration Pathways (... Read More about Climate Change Impact on the Frequency of Hydrometeorological Extremes in the Island of Crete.

Hydrometeorological impact of climate change in two Mediterranean basins (2018)
Journal Article
Vozinaki, A. K., Tapoglou, E., & Tsanis, I. K. (2018). Hydrometeorological impact of climate change in two Mediterranean basins. International Journal of River Basin Management, 16(2), 245-257. https://doi.org/10.1080/15715124.2018.1437742

The impact of climate change in specific hydrological issues is investigated in two Mediterranean watersheds of the island of Crete, Koutsoulidis, and Giofyros, by using the HBV hydrological model. Koutsoulidis basin is analysed in terms of future wa... Read More about Hydrometeorological impact of climate change in two Mediterranean basins.

Comparison of a black-box model to a traditional numerical model for hydraulic head prediction (2016)
Journal Article
Tapoglou, E., Chatzakis, A., & Karatzas, G. (2016). Comparison of a black-box model to a traditional numerical model for hydraulic head prediction. Global NEST journal, 18(4), 761-770. https://doi.org/10.30955/gnj.002002

Two different methodologies for hydraulic head simulation were compared in this study. The first methodology is a classic numerical groundwater flow simulation model, Princeton Transport Code (PTC), while the second one is a black-box approach that u... Read More about Comparison of a black-box model to a traditional numerical model for hydraulic head prediction.

A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation (2014)
Journal Article
Tapoglou, E., Karatzas, G. P., Trichakis, I. C., & Varouchakis, E. A. (2014). A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation. Journal of hydrology, 519(PD), 3193-3203. https://doi.org/10.1016/j.jhydrol.2014.10.040

Artificial Neural Networks (ANNs) and Kriging have both been used for hydraulic head simulation. In this study, the two methodologies were combined in order to simulate the spatial and temporal distribution of hydraulic head in a study area. In order... Read More about A spatio-temporal hybrid neural network-Kriging model for groundwater level simulation.

Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization (2014)
Journal Article
Tapoglou, E., Trichakis, I. C., Dokou, Z., Nikolos, I. K., & Karatzas, G. P. (2014). Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization. Hydrological Sciences Journal, 59(6), 1225-1239. https://doi.org/10.1080/02626667.2013.838005

Artificial neural networks (ANNs) have recently been used to predict the hydraulic head in well locations. In the present work, the particle swarm optimization (PSO) algorithm was used to train a feed-forward multi-layer ANN for the simulation of hyd... Read More about Groundwater-level forecasting under climate change scenarios using an artificial neural network trained with particle swarm optimization.