Athanasios Loukas

Potential climate change impacts on flood producing mechanisms in southern British Columbia, Canada using the CGCMA1 simulation results

Abstract The potential impacts of the future climate change on the causes of flood flows were investigated for two mountainous watersheds located in two different climatic regions of British Columbia. The Canadian Centre for Climate Modeling Analysis General Circulation Model (CGCMa1) has been used to estimate changes in the precipitation and temperature. The UBC Watershed Model (Version 4.0) was used to simulate the discharge of the two study watersheds and to identify the causes of peak flows. In the simulations, apart from changes in precipitation and temperature, changes in the spatial distribution of precipitation with elevation, cloud cover, glacier extension, vegetation distribution, vegetation biomass production, and plant physiology were considered. The results showed that the future climate for the two study watersheds would be wetter and warmer than the present climate. The majority of the flood events in the coastal rainfed watershed of Upper Campbell are and would be generated by fall rainfall events and winter rain-on-snow events, whereas in the interior snowcovered Illecillewaet basin the floods are and would be produced by spring rain and snowmelt events and summer events. The analysis indicated that the overall flood magnitude and frequency of occurrence in the Upper Campbell watershed would increase. On the other hand, the number and the magnitude of the flood flows would decrease under the future climatic conditions in the Illecillewaet basin. Based on these findings, different management practices should be applied in the two watersheds to overcome the effects of the future climate change.

Severity-duration-frequency analysis of droughts and wet periods in Greece

Abstract There is an escalation in the frequency and severity of extreme events due to a number of environmental and/or anthropogenic factors. Droughts and exceptionally wet periods are regional phenomena, which are considered as major environmental extremes, especially in semiarid regions of the world, such as Greece. The development of severity-duration-frequency (SDF) relationships of droughts and wet periods over Greece is important in contemporary hydroclimatic and agroclimatic design and planning in the country. The Palmer Drought Severity Index (PDSI) is used for a quantitative description of droughts and wet periods. Statistical tests and visual inspection indicate that the EV1 (Gumbel) frequency distribution fits satisfactorily all the identified durations of droughts and wet periods, respectively. Moreover, the SDF curves show that decreasing frequencies (i.e. increasing recurrence intervals) correspond to increasing severities of droughts and wet periods, respectively. The developed SDF relationships are used to produce tables and isoseverity maps of Greece for each identified duration and all the selected return periods or frequencies, which constitute an essential aid for design purposes. The results of the study indicate that there is a decreasing pattern of the severities of droughts and wet periods from west to east and that, for similar durations and return periods, the wet spells are, in general, more extreme than droughts in Greece.

Multi-Criteria Analysis Framework for Potential Flood Prone Areas Mapping

A fundamental component of the European natural disaster management policy is the detection of potential flood-prone areas, which is directly connected to the European Directive (2007/60). This study presents a framework for mapping potential flooding areas incorporating geographic information systems (GIS), fuzzy logic and clustering techniques, and multi-criteria evaluation methods. Factors are divided in different groups which do not have the same level of trade off. These groups are related to geophysical, morphological, climatological/meteorological and hydrological characteristics of the basin as well as to anthropogenic land use. GIS and numerical simulation are used for geographic data acquisition and processing. The selected factor maps are considered in order to estimate the spatial distribution of the potential flood prone areas. Using these maps, the study area is classified into five categories of flood vulnerable areas. The Multi-Criteria Analysis (MCA) techniques consist of the crisp and fuzzy analytical hierarchy processes (AHP) and are enhanced with different standardization methods. The classification is based on different clustering techniques and it is applied in two approaches. In the first approach, all criteria are normalized before the MCA process and then, the clustering techniques are applied to derive the final flood prone area maps. In the second approach, the criteria are clustered before and after the MCA process for the potential flood prone area mapping. The methodology is demonstrated in Xerias River watershed, Thessaly region, Greece. Xerias River floodplain was repeatedly flooded in the last few years. These floods had major impacts on agricultural areas, transportation networks and infrastructure. Historical flood inundation data has been used for the validation of the methodology. Results show that multiple MCA techniques should be taken into account in initial low-cost detection surveys of flood-prone areas and/or in preliminary analysis of flood hazard mapping.

Spatial variability of reference evapotranspiration in Greece

Abstract Optimal interpolation using geostatistical techniques, such as kriging, can be used for contouring and mapping of regionalized variables. In this study spatial variability of reference evapotranspiration over Greece is investigated using geostatistics. An exponential semivariogram model with only one pair of drift coefficients is used as the most appropriate fitted theoretical model. Kriging estimates of reference evapotranspiration rates and kriging variance have been conducted at 380 locations covering the Greece in a square grid mesh of 50 km. The results are used to plot contour maps of mean monthly and annual total reference evapotranspiration rates as well as contour maps of the kriging variance. Mapping of reference evapotranspiration and of kriging variance all over Greece is implemented as an agroclimatic parameter. The plotted results have been used to identify the spatial characteristics of evapotranspiration along several directions. Moreover, the impact of the main topography and climatic features in Greece to the analysis results is examined. Verification of the reference evapotranspiration kriging estimates is also performed. Numerous comparisons show that the results of the verification procedure are acceptable, thus suggesting that geostatistics can be used for the description of the spatial variability and for agroclimatic mapping of reference evapotranspiration over large regions with complex terrain such as Greece. Moreover, the analysis results and mapping of reference evapotranspiration can be used for agroclimatic purposes and design.

Flood producing mechanisms identification in southern British Columbia, Canada

Abstract The causes of peak flows in two climatically different mountainous-forested basins of British Columbia have been identified. The U.B.C. watershed model was used to identify the causes of peak flows, since this model separately calculates the runoff components, i.e. rainfall, snowmelt and glacier runoff. The results showed that the flood flows in the maritime basin of Upper Campbell are mainly generated by rainfall during the fall months and winter rain-on-snow events. Rainfall runoff constitutes the largest percentage of peak flow for all types of events. On the other hand, the flood flows in the inland basin of Illecillewaet are mainly produced by spring rain and snowmelt events, snowmelt events alone and summer events when runoff from the glacier melt contributes to peak discharge. However, snowmelt runoff is the dominant component of peak flows. Based on these findings, flood frequency analysis showed that considering the flow component frequency distributions marginally improves the probability distribution flows in the two examined watersheds.

Nonstationary Frequency Analysis of Annual Maximum Rainfall Using Climate Covariates

The perception that hydrometeorological processes are non stationary on timescales that are applicable to extreme value analysis is recently well documented due to natural climate variability or human intervention. In this study the generalized extreme value (GEV) distribution is used to assess nonstationarity in annual maximum daily rainfall time series for selected meteorological stations in Greece and Cyprus. The GEV distribution parameters are specified as functions of time-varying covariates and estimated using the conditional density network (CDN) as proposed by Cannon (2010). The CDN is a probabilistic extension of the multilayer perceptron neural network. If one of the covariates is dependent on time, then the GEV-CDN model could perform non stationary extreme value analysis. Model parameters are estimated via the generalized maximum likelihood (GML) approach using the quasi-Newton BFGS optimization algorithm, and the appropriate GEV-CDN model architecture for a selected meteorological station is selected by fitting increasingly complicated models and choosing the one that minimizes the Akaike information criterion with small sample size correction or the Bayesian information criterion. For each meteorological station in Greece and Cyprus different formulations are tested with combinational cases of stationary and non stationary parameters of the GEV distribution, linear and nonlinear architecture of the CDN and combinations of the input climatic covariates. Climatic covariates examined in this study are the Southern Oscillation Index (SOI), which describes atmospheric circulation in the eastern tropical Pacific related to El Niño Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO) index that varies on an interdecadal rather than inter annual time scale and atmospheric circulation patterns as expressed by the Mediterranean Oscillation Index (MOI) and North Atlantic Oscillation (NAO) indices.

Cotton yield estimation based on NOAA/AVHRR produced NDVI

Abstract The high temporal resolution of the NOAA/AVHRR satellite data can provide an efficient and consistent way for biomass and yield monitoring and assessment. The reflected radiation provides an indication of the type and density of canopy. A combination of spectral bands results in the vegetation indices, which are based on the spectral signatures of vegetation and account for the difference in response of the vegetation to the visible and near infrared channels. A widely used index for vegetation monitoring is the Normalized Difference Vegetation Index (NDVI), which is the normalized difference of visible (red) and near infrared channels. The condition, distribution, structure and the development of the vegetation through the phenological stages can affect the relation between yield and NDVI. The primary objective of this study consists of examining the feasibility of applying a regression model for cotton yield monitoring by using the NDVI. NOAA/AVHRR images of six areas covered with cotton have been examined for a period of three years. The results show that the temporal variability of cotton yield from year to year can be monitored by the use of NDVI.

Optimal Management of an Overexploited Aquifer under Climate Change: The Lake Karla Case

This paper presents a study for finding the optimal management plan of an overexploited aquifer under global climate change. The study area is the aquifer of the basin of Lake Karla, located in the eastern part of Thessaly in Greece. An optimization method has been used to evaluate the optimum volume of water that can be extracted from the aquifer and the optimum position of the wells with the objective of water table rise to a desirable sustainable level, taking into consideration the climate change forcing. The modelling system consists of a series of interlinked models: a hydrological, a lake-aquifer, a reservoir operation, a groundwater, and an optimization model. The climate change forcing on precipitation and temperature has been evaluated using the outputs of Canadian Centre for Climate Model Analysis General Circulation Model (CGCMa2) and a hybrid downscaling method which combines a multiple regression (MLR) model and a timeseries model for two socioeconomic emissions scenarios. The results of this study show that climate change plays an important role, as it affects the optimum volume of the extracted groundwater and the position of the irrigation wells.

Rainfall-frequency mapping for Greece

Abstract For the design of hydrotechnical projects in ungauged watersheds, the flood flow is estimated by various methods, which demand the estimation of rainfall of particular critical duration and return period. For medium-sized and large basins, the storms causing flood flows have usually duration larger than 24 hours. In this study daily rainfall data from 24 meteorological stations for the period 1950 to 1981 were used. These stations are evenly distributed over Greece. From these data, the rainfall depths for various durations were computed, i.e. 1 to 7 days. The Extreme Value I (Gumbel) theoretical distribution had the best fit to the data from other theoretical distributions and it was fitted to the maximum annual rainfall depths for various durations. As a result, the Depth-Duration_Frequency relationships for each station were estimated and mapped for Greece. Moreover, the analysis showed that the rainfall of various durations and return periods represents a certain percentage of the mean annual precipitation for hydrologicaly homogeneous areas of Greece. The homogeneous areas were identified through factor analysis of monthly precipitation data from 37 meteorological stations. The results of this study can be used for the estimation of rainfall at ungauged sites in medium and large watersheds but they should be applied with caution in mountainous areas. For the estimation of rainfall in these areas the climatic conditions of the region and the orographic enhancement of rainfall should be considered.

The role of agrometeorological and agrohydrological indices in the phenology of wheat in central Greece

Abstract In this study the relationship between several agrometeorological and agrohydrological indices related to temperature, humidity, precipitation and solar radiation as well as yield is examined. The agrometeorological and agrohydrological indices computed and used in this study are: heat unit, cumulative rainfall, effective phototemperature, nyctotemperature, photothermal unit, vapor pressure deficit and crop-drying days. Factor analysis was employed to indicate the significance of each parameter during various phenological stages. The agrometeorological and agrohydrological indices are correlated with the yield of wheat in two areas of central Greece, namely: Larissa (for the years 1957–1980) and Trikala (for the years 1963–1980). The results suggest a grouping, of the nine parameters that were used, in three main factors explaining 87% of the total variance of the data. It has been found that temperature and rainfall are the factors explaining most of the total variance of the data set. The contribution of humidity was also significant, especially during the last phenological stages of wheat. These results can be explained by the climatological conditions that prevail in the two study areas. Overall, the results show the importance of the agrometeorological and agrohydrological indices for monitoring the development of wheat through its phenological stages.