Salinity stress is one of the most vital abiotic stresses, impairing the productivity of crops in both irrigated and dry areas. A pot experiment was carried out in a greenhouse environment, aiming to examine the relevant tolerances and evaluate the effect of salinity stress on plant growth, fruit physiological, and quality traits of two strawberry cultivars, Camarosa and Rociera. The plants were irrigated with water with electrical conductivity (EC) of 0.4 dS m⁻¹ (control), or with a salt solution with either ECs 2 dS m⁻¹ (moderate salt stress) or 4 dS m⁻¹ (elevated salt stress). Furthermore, several meteorological parameters, as well as soil moisture, were monitored inside the greenhouse. The results showed that salinity induced osmotic stress, water deprivation, and toxic effects, affecting the growth parameters and yield of both cultivars. The elevated salt stress imposed a negative impact on Rociera’s fruits carbohydrates, organic acids, and anthocyanins, while the antioxidant capacity increased. However, Rociera exhibited high total yield/plant and total yield even under elevated salt stress compared to Camarosa. Camarosa plants grown under high salt levels presented low salinity tolerance index, plant water content, and growth parameters. The fruits exhibited low fresh weight but high sweetness index and antioxidant power. An accumulation of soluble sugars under saline conditions, especially sucrose, was also detected in cv. Camarosa fruits when compared to Rociera. Therefore, the two cvs. exhibited a different pattern of response to salinity stress concerning their physiological, biochemical and nutritional characteristics; however, either could be an interesting alternative for cultivation in areas where a slight salinization of the water or soil imposes a limitation on the rather salt-sensitive crops. Agronomic and biochemical evaluation of salinity stress coupled with monitoring of greenhouse microclimatic conditions will lead to a better understanding of the effects on plant growth and quality characteristics, enhancing the productivity of strawberry cultivars, especially under salt-affected environments.

Olive cultivation is expanding rapidly in the northwestern part of Greece, under both rainfed and irrigated practices. Irrigation can result in larger yields and economic returns, but trade-offs in the water–energy–pollution nexus remain a controversial and challenging issue. This study presents an environmental Life Cycle Assessment (LCA) of Greek olive orchard systems in the plain of Arta (Epirus), comparing rainfed (baseline), Decision Support System (DSS)-based (smart) irrigation practices and farmer experience-based (conventional) irrigation practices. The contributions in this paper are, first, to provide a first quantitative indication of the environmental performance of Greek olive growing systems under different management strategies, and second, to detail the advantages that can be achieved using smart irrigation in olive cultivation in the Greek and Mediterranean contexts. Eighteen midpoints (e.g., climate change, water scarcity, acidification, freshwater eutrophication, etc.), two endpoints (damages on human health and ecosystem quality), and a single score (overall environmental impact) were quantified using the IMPACT World+ life cycle impact assessment method. The LCA model was set up using the OpenLCA software v1.10.3. The functional units were 1 ton of product (mass-based) and 1 ha of cultivated area (area-based) on a cradle-to-farm gate perspective. Irrigated systems had the lowest impacts per mass unit due to higher yields, but showed the highest impacts per cultivated area. The DSS-based irrigation management could reduce water and energy use by 42.1% compared to conventional practices. This is translated into a reduction of 5.3% per 1 ton and 10.4% per 1 ha of the total environmental impact. A sensitivity analysis of impact assessment models demonstrated that the benefits could be up to 18% for 1 ton of product or 22.6% for 1 ha of cultivated land. These results outline that DSS-based irrigation is a promising option to support less resource-intensive and sustainable intensification of irrigated agriculture systems in the plain of Arta.

We present and validate a global parametric model of potential evapotranspiration (PET) with two parameters that are estimated through calibration, using as explanatory variables temperature and extraterrestrial radiation. The model is tested over the globe, taking advantage of the Food and Agriculture Organization (FAO CLIMWAT) database that provides monthly averaged values of meteorological inputs at 4300 locations worldwide. A preliminary analysis of these data allows for explaining the major drivers of PET over the globe and across seasons. The model calibration against the given Penman-Monteith values was carried out through an automatic optimization procedure. For the evaluation of the model, we present global maps of optimized model parameters and associated performance metrics, and also contrast its performance against the well-known Hargreaves-Samani method. Also, we use interpolated values of the optimized parameters to validate the predictive capacity of our model against monthly meteorological time series, at several stations worldwide. The results are very encouraging, since even with the use of abstract climatic information for model calibration and the use of interpolated parameters as local predictors, the model generally ensures reliable PET estimations. Exceptions are mainly attributed to irregular interactions between temperature and extraterrestrial radiation, as well as because the associated processes are influenced by additional drivers, e.g., relative humidity and wind speed. However, the analysis of the residuals shows that the model is consistent in terms of parameters estimation and model validation. The parameter maps allow for the direct use of the model wherever in the world, providing PET estimates in case of missing data, that can be further improved even with a short term acquisition of meteorological data.

Ombrian curves, i.e., curves linking rainfall intensity to return period and time scale, are well-established engineering tools crucial to the design against stormwaters and floods. Though the at-site construction of such curves is considered a standard hydrological task, it is a rather challenging one when large regions are of interest. Regional modeling of ombrian curves is particularly complex due to the need to account for spatial dependence together with the increased variability of rainfall extremes in space. We develop a framework for the parsimonious modeling of the extreme rainfall properties at any point in a given area. This is achieved by assuming a common ombrian model structure, except for a spatially varying scale parameter which is itself modeled by a spatial smoothing model for the 24 h average annual rainfall maxima that employs elevation as an additional explanatory variable. The fitting is performed on the pooled all-stations data using an advanced estimation procedure (K-moments) that allows both for reliable high-order moment estimation and simultaneous handling of space-dependence bias. The methodology is applied in the Thessaly region, a 13,700 km² water district of Greece characterized by varying topography and hydrometeorological properties.

The large-scale surface-water monitoring infrastructure for Greece Open Hydrosystem Information Network (Openhi.net) is presented in this paper. Openhi.net provides free access to water data, incorporating existing networks that manage their own databases. In its pilot phase, Openhi.net operates three telemetric networks for monitoring the quantity and the quality of surface waters, as well as meteorological and soil variables. Aspiring members must also offer their data for public access. A web-platform was developed for on-line visualization, processing and managing telemetric data. A notification system was also designed and implemented for inspecting the current values of variables. The platform is built upon the web 2.0 technology that exploits the ever-increasing capabilities of browsers to handle dynamic data as a time series. A GIS component offers web-services relevant to geo-information for water bodies. Accessing, querying and downloading geographical data for watercourses (segment length, slope, name, stream order) and for water basins (area, mean elevation, mean slope, basin order, slope, mean CN-curve number) are provided by Web Map Services and Web Feature Services. A new method for estimating the streamflow from measurements of the surface velocity has been advanced as well to reduce hardware expenditures, a low-cost ‘prototype’ hydro-telemetry system (at about half the cost of a comparable commercial system) was designed, constructed and installed at six monitoring stations of Openhi.net.