Silas Michaelides

Rainfall erosivity in Europe

Rainfall is one the main drivers of soil erosion. The erosive force of rainfall is expressed as rainfall erosivity. Rainfall erosivity considers the rainfall amount and intensity, and is most commonly expressed as the R-factor in the USLE model and its revised version, RUSLE. At national and continental levels, the scarce availability of data obliges soil erosion modellers to estimate this factor based on rainfall data with only low temporal resolution (daily, monthly, annual averages). The purpose of this study is to assess rainfall erosivity in Europe in the form of the RUSLE R-factor, based on the best available datasets. Data have been collected from 1541 precipitation stations in all European Union (EU) Member States and Switzerland, with temporal resolutions of 5 to 60 min. The R-factor values calculated from precipitation data of different temporal resolutions were normalised to R-factor values with temporal resolutions of 30 min using linear regression functions. Precipitation time series ranged from a minimum of 5 years to a maximum of 40 years. The average time series per precipitation station is around 17.1 years, the most datasets including the first decade of the 21st century. Gaussian Process Regression (GPR) has been used to interpolate the R-factor station values to a European rainfall erosivity map at 1 km resolution. The covariates used for the R-factor interpolation were climatic data (total precipitation, seasonal precipitation, precipitation of driest/wettest months, average temperature), elevation and latitude/longitude. The mean R-factor for the EU plus Switzerland is 722 MJ mm ha(-1) h(-1) yr(-1), with the highest values (>1000 MJ mm ha(-1) h(-1) yr(-1)) in the Mediterranean and alpine regions and the lowest (<500 MJ mm ha(-1) h(-1) yr(-1)) in the Nordic countries. The erosivity density (erosivity normalised to annual precipitation amounts) was also the highest in Mediterranean regions which implies high risk for erosive events and floods.

Long term changes in diurnal temperature range in Cyprus

Abstract Long term temperature data from two stations on the island of Cyprus have been analysed. Increasing trends of approximately 1°C/100 years in the annual mean temperatures are found at both stations. However, the minimum daily temperatures have generally increased at a larger rate than the maximum daily temperatures, resulting in a decrease in the long-term diurnal temperature range. This decrease ranges from −0.5°C/100 years to −3.5°C/100 years, depending on the location. The reduction in the diurnal temperature range is consistent with observations from other parts of the globe, and may indicate that the climate in this region of the globe is part of a larger global climate change that has been occurring over the last century. It is possible that long term changes in greenhouse gas concentrations in the atmosphere are responsible for the long-term annual mean temperature increase. Furthermore, the changes in the diurnal temperature range can possibly be explained by increases in cloud cover and/or tropospheric aerosols. It is possible that part of these changes is caused by local land-use changes, primarily by the increasing urbanization of Cyprus.

A Modified SEBAL Modeling Approach for Estimating Crop Evapotranspiration in Semi-arid Conditions

Remote sensing methods are becoming attractive to estimate crop evapotranspiration, as they cover large areas and can provide accurate and reliable estimations; intensive field monitoring is also not required, although some ground-truth measurements can be helpful in interpreting satellite images. For the purposes of this paper, modeling and remote sensing techniques were integrated for estimating actual evapotranspiration of groundnuts (Arachishypogaea, L.) that is cultivated near Mandria Village in Paphos District of Cyprus. The Surface Energy Balance Algorithm for Land (SEBAL) was adopted for the first time in Cyprus, employing the essential adaptations for local soil and meteorological conditions. Landsat-5 TM and 7 ETM+ images were used to retrieve the needed spectral data. The SEBAL model is enhanced with empirical equations determined as part of the present study, regarding crop canopy factors, in order to increase its accuracy. Maps of ETa were created using the SEBAL modified model (CYSEBAL) for the area of interest. The results have been compared to the measurements from an evaporation pan (which was used as a reference) and those of the original SEBAL model. The statistical comparison has shown that the modified SEBAL yields results that are comparable to those of the evaporation pan. T-test application has revealed that the statistical difference between SEBAL and CYSEBAL is significant and quite crucial, especially in a place with limited surface and underground water resources.

Mapping monthly rainfall erosivity in Europe

Rainfall erosivity as a dynamic factor of soil loss by water erosion is modelled intra-annually for the first time at European scale. The development of Rainfall Erosivity Database at European Scale (REDES) and its 2015 update with the extension to monthly component allowed to develop monthly and seasonal R-factor maps and assess rainfall erosivity both spatially and temporally. During winter months, significant rainfall erosivity is present only in part of the Mediterranean countries. A sudden increase of erosivity occurs in major part of European Union (except Mediterranean basin, western part of Britain and Ireland) in May and the highest values are registered during summer months. Starting from September, R-factor has a decreasing trend. The mean rainfall erosivity in summer is almost 4 times higher (315 MJ mm ha− 1 h− 1) compared to winter (87 MJ mm ha− 1 h− 1). The Cubist model has been selected among various statistical models to perform the spatial interpolation due to its excellent performance, ability to model non-linearity and interpretability. The monthly prediction is an order more difficult than the annual one as it is limited by the number of covariates and, for consistency, the sum of all months has to be close to annual erosivity. The performance of the Cubist models proved to be generally high, resulting in R2 values between 0.40 and 0.64 in cross-validation. The obtained months show an increasing trend of erosivity occurring from winter to summer starting from western to Eastern Europe. The maps also show a clear delineation of areas with different erosivity seasonal patterns, whose spatial outline was evidenced by cluster analysis. The monthly erosivity maps can be used to develop composite indicators that map both intra-annual variability and concentration of erosive events. Consequently, spatio-temporal mapping of rainfall erosivity permits to identify the months and the areas with highest risk of soil loss where conservation measures should be applied in different seasons of the year.

Mapping potato crop height and leaf area index through vegetation indices using remote sensing in Cyprus

This paper aims to model leaf area index (LAI) and crop height to spectral vegetation indices (VI), such as normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), and weighted difference vegetation index (WDVI). The intended purpose is to create empirical statistical models to support evapotranspiration algorithms applied under the current conditions in the island of Cyprus. Indeed, a traditionally agricultural area was selected in the Mandria Village in the Paphos District area in Cyprus, where one of the islands main exported crops, potatoes, are cultivated. A GER-1500 field spectroradiometer was used in this study in order to retrieve the necessary spectrum data of the different crops for estimating the VI’s. A field campaign was undertaken with spectral measurements of LAI and crop height using the Sun-Scan canopy analyzer, acquired simultaneously with the spectroradiometric measurements between March and April of 2008 and 2009. Regarding the measurements, the phenological cycle of potatoes was followed. Several regression models have been applied to relate LAI/crop height and the three indices. It was found that the best fitted vegetation index to both LAI and crop height was WDVI. When LAI was regressed against WDVI for potatoes, the determination coefficient (R2) was 0.72, while for crop height R2 reached 0.78. Two Landsat TM-5 images acquired simultaneously during the spectroradiometric and LAI and crop height measurements are used to validate the proposed regression model. From the whole analysis it was found that the modeled results are very close to real values. This fact enables the specific empirical models to be used in the future for hydrological purposes.

Synergetic use of TERRA/MODIS imagery and meteorological data for studying aerosol dust events in Cyprus

This paper presents the results from the analysis of TERRA/Moderate Resolution Imaging Spectrometer (MODIS) images for the detection and mapping of particulate air pollution in Cyprus. For this purpose, a set of selected air pollution events for the year 2002 was used, mainly associated with dust transported over the area from the surrounding deserts. The results depict the potential of the use of remotely sensed data (MODIS) for monitoring and air pollution quality mapping at a full extent over Cyprus, providing useful information that could be used in combination with other available data sources (meteorological data, ground-based air pollution monitoring stations, etc.).

Vulnerability of transportation to extreme weather and climate change

The Special Issue is forwarded by the coordinators of three European funded projects that have been completed recently and that form the source for most of the research papers presented here. The Foreward is followed by twelve original research papers focusing on weather and climate-related impacts on various modes of transportation, with emphasis on the European region. Language: en

Use of Field Spectroscopy for Exploring the Impact of Atmospheric Effects on Landsat 5 TM/7 ETM+ Satellite Images Intended for Hydrological Purposes in Cyprus

The spectroradiometric retrieved reflectance of a local crop, namely, beans (Phaseolus vulgaris), is directly compared to the reflectance of Landsat 5TM and 7ETM+ atmospherically corrected and uncorrected satellite images. Also, vegetation indices from the same satellite images—atmospherically corrected and uncorrected—are compared with the corresponding vegetation indices produced from field measurements using a spectroradiometer. Vegetation Indices are vital in the estimation of crop evapotransiration under standard conditions (ETc) because they are used in stochastic or empirical models for describing crop canopy parameters such as the Leaf Area Index (LAI) or crop height. ETc is finally determined using the FAO Penman-Monteith method adapted to satellite data, and is used to examine the impact of atmospheric effects. Regarding the reflectance comparison, the main problem was observed in Band 4 of Landsat 5TM and 7ETM+, where the difference, for uncorrected images, was more than 20% and statistically significant. Results regarding ETc show that omission or ineffective atmospheric corrections in Landsat 5TM,/7ETM+ satellite images always results in a water deficit when estimating crop water demand. Diminished estimated crop water requirements can result in a reduction in output or, if critical, crop failure. The paper seeks to illustrate the importance of removing atmospheric effects from satellite images designated for hydrological purposes.

Transport system management under extreme weather risks: views to project appraisal, asset value protection and risk-aware system management

Abstract Until recently, research on potential economic impacts of climate change and extreme weather events on transport infrastructure was scarce, but currently this area is rapidly expanding. Indeed, there is a growing international interest, including the European area, regarding the impacts of extreme weather and climate change on the management of various transportation modes. This paper reviews briefly the present status regarding the knowledge of financial aspects of extreme weather impacts on transportation, using recent research findings from Europe, and proposes some new views in cost-benefit analysis, project appraisal and asset value protection for the management of transport systems under extreme weather risks. Quite often, risk management is understood as a response to truly extreme impacts, but this constitutes a misunderstanding. Some values are more extreme than others, and in the context of extreme weather, some weather phenomena are more extreme in their intensity and resulting impacts. An analysis of the level of costs and risks to societies, as a result of extreme weather, reveals that the risks in different European Union member states deviate substantially from each other. Also, the preparedness of different societies to deal with extreme weather events is quite variable. Extreme weather and climate change costs and risks represent a new type of item, which has to be dealt with in project appraisal. Although a fully established procedure does not exist, some fundamental ideas of cost-benefit analysis under extreme weather scenarios are presented in this paper, considering accident costs, time costs and infrastructure-related costs (comprising physical damages to infrastructures and increased maintenance costs). Cost-benefit analysis is usually associated with capital investments, but the original idea of cost-benefit analysis is not restricted to investment appraisal. Therefore, activities such as enhanced maintenance, minor upgrades, adoption of new designs, improved information services and others may be subject to cost-benefit analysis. Extreme weather and climate change costs and risks represent a new type of item, which apparently has to be dealt with also in project appraisal. A fully established procedure does not exist, although some basic principles have been introduced in analytical format. There is a lack of models to estimate extreme weather impacts and consequences and how to adapt to those costs. Optimising the efforts in maintenance and new design standards is even further away, but constitutes an overwhelming task. In this respect, new approaches and ways of thinking in preserving asset’s residual value, return periods, sustainability and equity and formal methods supplementing cost-benefit analysis are put forward. The paper concludes with a call for the need for more integrated management of transport systems. In particular, it is recognised that the different stages of transport system planning pose their own challenges when assessing the costs and benefits of policy measures, strategies and operational decisions.

Identification of weather trends for use as a component of risk management for port operations

Efficiency in modern shipping must not come at the expense of undertaking avoidable risks. The complexity of most activities in shipping requires a cooperative effort made by specialists to comprehend the uncertainties of risk and to seek measures for its reduction. Such an effort, however, must not hinder operations but aim at promoting productivity by addressing those factors that have a negative effect on it. This imperative need to deal with the problems of risk led to the development of a series of risk-related disciplines. Identifying the factors that create hazards and finding an effective way of minimizing them, whenever possible, leads to smoother operations, better time frames and, eventually, lower costs. One of the factors that can generate risks and reduce productivity in maritime-related operations is weather. Like any other factor that bears uncertainties and risks, weather hampers actual port operations (such as the loading/unloading of goods and passengers), but it also leads to problems for a whole chain of upstream and downstream industries. In this study, an attempt is made to identify and register hazardous weather trends in the Port of Limassol (used as a case study for Mediterranean ports). An up-to-date picture of the prevailing weather conditions in the area is presented with the aim to provide vital information for risk assessment purposes, both in the short and in the long term.