Cost/benefit analysis of a benthic monitoring programme of organic benthic enrichment using different sampling and analysis methods

To investigate the combined effects of decreasing taxonomic resolution (i.e. species, family, phylum), the use of different mesh-size (1.0 mm and 0.5 mm) and the type of samplers used (van Veen vs. corers taken by divers) on the quality of data obtained, a comparative study was undertaken with the overall aim of identifying cost efficient methods for routinely monitoring the ecological change caused by Mediterranean fish farming. The results clearly showed that information loss was relatively low as data were aggregated at higher taxonomic levels, particularly up to the level of family or even order. It was also found that the extra information gained by sieving samples through a 0.5 mm sieve did not improve the ability to distinguish the potentially impacted sites from the control stations. Finally, it was found that a relatively large proportion of the available information concerning the community structure such as abundance, biomass or diversity is lost when sampling is carried out with corers. A cost/benefit ratio analysis for the two sampling and the two sieving methods showed minimal values for the van Veen samples (for both sieve fractions) at the family level, indicating that analysis at this level gives the best balance between precision of the results and decrease in taxonomic effort. However, if the time needed to sort the samples is included in the analysis, then samples taken with corers using a 0.5 mm sieve and identified to families seems like a good compromise between precision and cost.     

Assessing water erosion in Mediterranean tree crops using GIS techniques and field measurements: the effect of climate change

In this work, a dynamic GIS modeling approach is presented that incorporates: a) geoinformatic techniques, b) 55-year historical meteorological data, and c) field measurements, in order to estimate soil erosion risk in intensively cultivated regions. The proposed GIS-based modeling approach includes the estimation of soil erosion rates due to surface water flow under current and future climate change scenarios A2 and B1 for the years 2030 and 2050. The soil erosion was estimated using the Universal Soil Loss Equation (USLE). The proposed soil erosion model was validated using field measurements at different sites of the study area. The results show that an extended part of the study area is under intense erosion with the mean annual loss to be 4.85 t/ha year⁻¹. Moreover, an increase in rainfall intensity, especially for scenario B1, can generate a significant increase (32.44 %) in soil loss for the year 2030 and a much more (50.77 %) for the year 2050 in comparison with the current conditions. Regarding the scenario A2, a slight decrease (1.85 %) in soil loss was observed for the year 2030, while for 2050 the results show an adequate increase (7.31 %) in comparison with the present. All these approaches were implemented at one of the most productive agricultural areas of Crete in Greece dominated by olive and citrus crops.

     

Calculation of radar signal delays in the vicinity of the Sun due to the contribution of a Yukawa correction term in the gravitational potential

There has been a renewed interest in the recent years in the possibility of deviations from the predictions of Newton’s “inverse-square law” of universal gravitation. One of the reasons for renewing this interest lies in various theoretical attempts to construct a unified elementary particle theory, in which there is a natural prediction of new forces over macroscopic distances. Therefore the existence of such a force would only coexist with gravity, and in principle could only be detected as a deviation from the inverse square law, or in the “universality of free fall” experiments. New experimental techniques such that of Sagnac interferometry can help explore the range of the Yukawa correction λ≥10¹⁴ m where such forces might be present. It may be, that future space missions might be operating in this range which has been unexplored for very long time. To study the effect of the Yukawa correction to the gravitational potential and its corresponding signal delay in the vicinity of the Sun, we use a spherically symmetric modified space time metric where the Yukawa correction its added to the gravitational potential. Next, the Yukawa correction contribution to the signal delay is evaluated. In the case where the distance of closest approach is much less than the range λ, it results to a signal time delay that satisfies the relation t(b<λ)≅37.7t(b=λ).     

Multi-scale risk assessment of stream pollution by wastewater of olive oil mills in Kolymvari,Crete

In the streams of the Mediterranean island of Crete (Greece), olive mill wastewater (OMW) has been reported to reduce biodiversity up to 85 %. Mere conduction of impact assessment based on pollutant concentrations, however, cannot reveal how impacted areas may be connected to the pollution sources. In this study, we developed a new methodology which allows for a dynamic cause-effect linking of pollution sources and impacted areas through the pathways of OMW. Risk is hierarchically assessed and mapped at three different scales and more specifically, at the source scale (targeting olive mill units and their waste tanks), at the receptor scale (targeting potential impacted sites in the streams) and at the watershed scale (which is the scale of overall water management). The approach is based mainly on remote sensing data without taking account of groundwater regimes or field measurements. Involvement of local experts for recognizing spatial features of interest and selecting appropriate risk parameters was proved necessary and efficient in order to model the stream pollution risk realistically. Potential impacted sites in the stream network were occasionally verified by a field survey. The results comprise a set of risk maps at the three different scales. The constructed digital geo-database can be updated or modified and thus is considered to be a dynamic tool for future environmental management in the service of the local community.     

Probabilistic analysis of retaining walls

A methodology for the probabilistic analysis of reinforced concrete cantilever walls is developed and described in this paper. The wall’s external stability under static conditions is addressed and modeled as a series system with correlated failure modes. Computations of reliability are performed using Monte Carlo simulations for assumed probability distributions of the backfill and foundation material engineering properties. A case example is analyzed based on the described methodology. The results indicated that risk, measured by the system probability of failure, is not a linear function of safety ratios. All three safety ratios in question were positively correlated, with bearing capacity being subjected to higher degree of uncertainty. The degree of correlation was found to have an important effect on the system probability of failure. Considering the width of the base as varying design parameter, the study also showed that first-order reliability bounds, which are often applied in practice, may lead to a noteworthy over- or under-estimation of the design.     

Non-Integrability and Structure of the Resonance Zones in a Class of Galactic Potentials

The structure of the resonance zone in nearly integrable Hamiltonian systems is studied by a more general method than the pendulum approximation. This method applies to the case of a non-degenerate integrable part in the Hamiltonian. This problem may be overcome in a class of galactic-type polynomial potentials, in the case where the higher-order term is by itself integrable. An illustrative example is worked out.     

Performance of intertidal topography video monitoring of a meso-tidal reflective beach in South Portugal

This study discusses site-specific system optimization efforts related to the capability of a coastal video station to monitor intertidal topography. The system consists of two video cameras connected to a PC, and is operating at the meso-tidal, reflective Faro Beach (Algarve coast, S. Portugal). Measurements from the period February 4, 2009 to May 30, 2010 are discussed in this study. Shoreline detection was based on the processing of variance images, considering pixel intensity thresholds for feature extraction, provided by a specially trained artificial neural network (ANN). The obtained shoreline data return rate was 83%, with an average horizontal cross-shore root mean square error (RMSE) of 1.06 m. Several empirical parameterizations and ANN models were tested to estimate the elevations of shoreline contours, using wave and tidal data. Using a manually validated shoreline set, the lowest RMSE (0.18 m) for the vertical elevation was obtained using an ANN while empirical parameterizations based on the tidal elevation and wave run-up height resulted in an RMSE of 0.26 m. These errors were reduced to 0.22 m after applying 3-D data filtering and interpolation of the topographic information generated for each tidal cycle. Average beach-face slope tan(β) RMSE were around 0.02. Tests for a 5-month period of fully automated operation applying the ANN model resulted in an optimal, average, vertical elevation RMSE of 0.22 m, obtained using a one tidal cycle time window and a time-varying beach-face slope. The findings indicate that the use of an ANN in such systems has considerable potential, especially for sites where long-term field data allow efficient training.     

Monitoring and Modeling of Metal Concentration Distributions in Anoxic Basins: Aitoliko Lagoon, Greece

The balance between physicochemical processes, influencing vertical and temporal distributions of metal compounds in one relatively isolated anoxic environment, constitutes the objective of the present work. Ion activity product (IAP) was calculated for manganese and iron sulfides, in order to define the metal sulfide forms that control Fe and Mn solubility in the bottom waters of anoxic lagoons. Iron solubility depended on amorphous FeS formation, while manganese sulfides were a minor component in a solid solution lowering its solid-phase activity. A theoretical physicochemical model was developed for the iron speciation, based on experimental pH and redox potential data. A very good match was achieved for the measured and the theoretical total dissolved iron, at all depths. The dominance of oxidant iron species Fe(OH) ₃ ^? in the surface waters and their sequence by FeSH⁺ and FeS_aq in the deeper layers brings out the influence of physicochemical parameters (dissolved oxygen, sulfide, pH and E_h) in vertical distribution of dissolved metal species, in anoxic/hypoxic basins. Based on these findings, we can conclude that the distribution of manganese and iron is of special interest, not only because these are the indicators of redox conditions but also for the role of their oxidized/reduced forms in the formation of the biogeochemical structure of redox zone.     

Comparison of an artificial neural network and a conceptual rainfall–runoff model in the simulation of ephemeral streamflow

ABSTRACT

The rainfall–runoff process is governed by parameters that can seldom be measured directly for use with distributed models, but are rather inferred by expert judgment and calibrated against historical records. Here, a comparison is made between a conceptual model (CM) and an artificial neural network (ANN) for their ability to efficiently model complex hydrological processes. The Sacramento soil moisture accounting model (SAC-SMA) is calibrated using a scheme based on genetic algorithms and an input delay neural network (IDNN) is trained for variable delays and hidden layer neurons which are thoroughly discussed. The models are tested for 15 ephemeral catchments in Crete, Greece, using monthly rainfall, streamflow and potential evapotranspiration input. SAC-SMA performs well for most basins and acceptably for the entire sample with R² of 0.59–0.92, while scoring better for high than low flows. For the entire dataset, the IDNN improves simulation fit to R² of 0.70–0.96 and performs better for high flows while being outmatched in low flows. Results show that the ANN models can be superior to the conventional CMs, as parameter sensitivity is unclear, but CMs may be more robust in extrapolating beyond historical record limits and scenario building.

EDITOR M.C. Acreman; ASSOCIATE EDITOR not assigned