Session 36 - Environmental data analysis and modelling

[CEST2019_00956] Spatial explicit evaluation of potential future developments of forests due to climatic change and nitrogen deposition
by Jenssen M., Nickel S., Schröder W.

Climate change and atmospheric nitrogen deposition can impact the integrity of ecosystems. Therefore, the EU Biodiversity Strategy foresees that Member States map and assess the state of ecosystems and their services in their national territory. By example of Germany, this article presents a quantitative, spatially explicit as well as nationally, regionally and site-specifically applicable methodology for classifying and mapping forest ecosystems and identifying changes of their integrity comparing their reference states (1961-1990) with measured (1991-2010) und potential future conditions (2011-2017). To this end, measured environmental data were complemented by dynamic modelling of future climate and soil conditions. A fuzzy rule-based model for estimating spatial patterns and temporal trends of soil moisture was developed and tested at the federal and regional level. Forest ecosystem conditions were evaluated and ordinated at three levels (indicators, functions and ecosystem type) with regard to functionality, chemical and biological characteristics, stress tolerance against climate change and nitrogen deposition scenarios for the years 1961-1990, 1991-2011 and 2011-2070.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:45 to 16:00
Oral presentation in Environmental data analysis and modelling
[CEST2019_00820] 50-year precipitation trends in Nestos Delta-Natura 2000 site
by Proutsos N., Korakaki E., Bourletsikas A., Karetsos G., Tsagari K., Georgiadis C.

Nestos Delta (north Greece) is a complex ecosystem of high ecological importance, protected by the European Union as a Natura 2000 site. The presence of the habitats 3170* and 91E0*, which are highly connected with water resources availability, impose the continuous monitoring of precipitation in the area, since even minor changes of the precipitation regime could have a significant effect on the habitats’ viability. Aim of this work is to detect significant precipitation changes by analyzing datasets from 5 nearby station for a time period of about 50 years. The results indicate statistically significant decreasing changes mainly at lower altitudes, and increasing at higher.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:09 to 16:12
Flash presentation in Environmental data analysis and modelling
[CEST2019_00828] Meteorological Data Science: exploiting causality discovery in time-series for knowledge discovery and improved forecasting
by Gkikas A., Maragoudakis M.

Climate change and its impact on everyday life still remains one of the greatest challenge of our era. The complex nature of climate data addresses the use of data science techniques to provide predictive analytics to the task at hand. While most existing approaches exploit correlation between observations and features to improve forecasting, the present work deals with causality, a principle that enhances robustness and provides better insight to domain experts. More specifically, a novel framework for causality discovery is proposed, based on statistical (i.e. Granger causality tests) as well as on non-linear state space reconstruction algorithms (i.e. Convergent Cross Mapping, a very effective algorithm in dynamic systems, such as the task at hand) in order to find the causal relations between meteorological time series. Furthermore, the framework also supports methods for graph analysis, thus providing informative visualizations on the influential levels of causality. Experiment results on a dataset of real observations from different cities of Greece, obtained through crawling of Internet sites of Davis weather stations demonstrate the ability to model and visualize the relations of the meteorological parameters amongst the cities. Moreover, by utilizing such causal inference knowledge, the forecasting performance for each city is significantly improved, since only relevant and informative features were taken into consideration.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:00 to 15:15
Oral presentation in Environmental data analysis and modelling
[CEST2019_00708] Performance Evaluation Of Mass Transfer-Based Method Using Global Performance Index In Semi-Arid Region Saudi Arabia
by Islam S., Abdullah R.A.B., Hirol H., Mallick J., Khan R.A.

The standard method for the estimation of reference evapotranspiration (ETo) is FAO-Penman-Monteith (FAO56-PM). However, it requires various climatic parameters which are often hard to achieve due to various reason. In order to bridge this gap an alternative equation has to be find out. The main aim of this research work was to assess the performance of the various mass transfer-based method with respect to standard FAO56-PM. Daily meteorological data from 1980 to 2018 has been used to compute reference evapotranspiration. Daily ETo values were computed. Among the computed values 70% of them were used to calibrate the mass transfer equations under study and remaining 30 % data were used to validate the calibrated equation against the standard method. The calibrated models were analysed and compared using statistical tools and ranked using Global Performance Indicator where a higher value represented a model’s better performance. The models were then arranged using GPI and it was found that Albrecht model resulted in best estimation capability. The results of this study could be used by the water management system, crop cultivators, crop advisors, researchers and students from universities and research centres. Moreover, it is beneficial for the decision maker in the vast field of agriculture, hydrology and environment.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:30 to 15:45
Oral presentation in Environmental data analysis and modelling
[CEST2019_00486] Thermal bridge modelling, based on conjugated heat transfer and CFD methods
by Mijorski S., Ivanov M.

In the building structure, the “thermal bridge” is defined as an isolated zone, where construction elements have higher thermal conductivity, compared with the rest of the building envelope. Thus, a significant temperature difference may exist between adjacent solid and air volumes within the developments, especially in winter conditions. The existence of thermal bridge mostly affects the energy performance of buildings, due to the increased heat losses from the occupied spaces. But also, the decreased surface temperature in these zones, could lead to moisture accumulation and substantial humidity related problems in the indoor environment.
Considering these important effects, the presented study describes the development of numerical model of a thermal bridge distribution, based on conjugated heat transfer in concrete external wall section. The thermal bridge distribution is analyzed relative to the indoor and outdoor air parameters, and the envelope thermal properties. The achieved surface temperature sensitivity results may be used for further moisture accumulation model development or enhancements.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:06 to 16:09
Flash presentation in Environmental data analysis and modelling
[CEST2019_00322] Environmental genotoxicity and risk assessment in herring (Clupea harengus), Atlantic cod (Gadus morhua) and flounder (Platichthys flesus) caught in the Gotland Basins from the Baltic Sea (2010-2017)
by Pažusienė J., Valskienė R., Stankevičiūtė M., Butrimavičienė L., Baršienė J.

Eight nuclear abnormalities of geno-cytotoxicity were studied in peripheral blood erythrocytes of herring (Clupea harengus membras), flounder (Platichthys flesus) and Atlantic cod (Gadus morhua) sampled (2010–2017) from the Polish and the Lithuanian Exclusive Economic Zones (EEZs) in the Baltic Sea. At all study stations, total genotoxicity (∑Gentox) were found to be higher than total cytotoxicity (∑Cytox). A significant time-related decrease in genotoxicity was detected in the Lithuanian EEZ (2015–2017), while in the Polish EEZ (2014–2016), the opposite tendency was revealed. The highest ∑Gentox and ∑Cytox values recorded in the fish sampled at the study stations located relatively close to each other clearly indicate an increased environmental geno-cytotoxicity pressure for fish in these areas. Exceptionally high and high level genotoxicity risks to herring followed by those to flounder and cod were determined at a higher percentage of the stations studied.

Session: 36, Room: F, at Fri, 09/06/2019 - 15:15 to 15:30
Oral presentation in Environmental data analysis and modelling
[CEST2019_00269] An integrated methodology to estimate the contribution of environmental factors controlling the spatial variation of total dissolved solids. Application on Jiu River Basin (Romania)
by Moroşanu G.A., Zaharia L., Ioana-Toroimac G.

Through this research, we aim to develop a methodology for estimating the contribution of the natural and anthropic factors to the spatial variation of Total Dissolved Solids (TDS). The study area is Jiu River Basin, a Danube tributary from SW Romania.
TDS content was measured on Jiu River and its main tributaries, in periods of low waters in the summer of 2017 and 2018. For the area upstream each point, the following factors considered as primarily responsible for the TDS concentration were mapped and integrated in GIS and statistical analysis: geology, vegetation, soil textures, relevant human activities (coal-mining industry and agriculture in the valleys and in the catchments upstream the measuring points).
Using the principal component analysis (PCA) and regression models, scores were assigned to quantify the contributions to the spatial variation of TDS in the rivers. The results showed that coal mining and lithology (marls’ dominance) play the main role in explaining the TDS variation.
The development of such an integrated methodology improved the understanding of the relationship between the rivers’ TDS and the environmental drivers.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:03 to 16:06
Flash presentation in Environmental data analysis and modelling
[CEST2019_00221] Species prioritization for recovery potential estimation. Case of study: Seasonally dry tropical forest at an inter Andean valley of Cauca River, South America
by Alvarado-Solano D.P., Otero J.T., Šarapatka B.

Seasonally dry tropical forest (SDTF) at the Colombian inter-Andean valley of Cauca River (IVCR) has been under constant transformation. Following the current SDTF’s global distribution, it has remained as small and sparse fragments embedded in an anthropogenic landscape. Information regarding the known species composition is a basic input in any modelling scheme. Environmental data is also needed to understand its influence as an explanatory variable for the species occurrences. Knowledge about the biomes and ecoregions where they have been registered may help to understand the way in which the multiple species have been distributed through environmental gradients. In such a way we could recognize the relevance that IVCR plays for the conservation of SDTF plant species in the long term. From multiple datasets, a database with 1725 plant species was built. After applying different criteria set (endangered, endemic, conservation status, at national and regional level), different species subsets were obtained. For a first subset with the species prioritized, Maxent Algorithm on R Studio has been applied to produce predictive habitat suitability models to support the detection of potential areas for restoration. Restoration scenarios will be built for each subset of prioritized species which can be used for landscape planning purposes.

Session: 36, Room: F, at Fri, 09/06/2019 - 16:00 to 16:03
Flash presentation in Environmental data analysis and modelling