A comprehensive assessment of RCP4.5 projections and bias-correction techniques in a complex coastal karstic aquifer in the Mediterranean

This study aims to assess the projected precipitation and temperature changes at the coastal karstic aquifer of Salento (Apulia, Southern Italy) under the Representative Concentration Pathway RCP4.5. For this purpose, an ensemble of twelve Regional Climate Models (RCMs) driven by several General Circulation Models (GCMs) were collected. Eight bias-correction (BC) methods were applied at daily time steps, and their results were assessed on monthly and annual time steps, using daily records from 19 and 11 precipitation and temperature (minimum and maximum) stations, respectively, for the period 1960–2005. Missing data in the observed dataset were filled-in applying the best performing techniques out of the 5 that were employed and tested. The Linear Scaling and the Power Transformation were found to be the most effective methods for precipitation BC at the case study, while all methods performed equally well in correcting air temperature datasets. Results of future climate projections show a decrease in precipitation of about 6% and an increase in temperature of 2°C until the end of this century, compared to the historical period (1971–2005). This study forms the first comprehensive attempt to test the scientific literature’s most widely used bias-correction methods over the study area. The case study may be considered a benchmark for circum-Mediterranean regions because of its high geomorphological and structural complexity, regional size, surface water scarcity, and significant water withdrawals for human activities

Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data

[EN] The agricultural sector faces the challenge of ensuring food security without an excessive burden on the environment. Simulationmodels provide excellent instruments for researchers to gainmore insight into relevant processes and best agricultural practices and provide tools for planners for decision making support. The extent to which models are capable of reliable extrapolation and prediction is important for exploring new farming systems or assessing the impacts of future land and climate changes. A performance assessmentwas conducted by testing six detailed state-of-the-artmodels for simulation of nitrate leaching (ARMOSA, COUPMODEL, DAISY, EPIC, SIMWASER/STOTRASIM, SWAP/ANIMO) for lysimeter data of the Wagna experimental field station in Eastern Austria, where the soil is highly vulnerable to nitrate leaching. Three consecutive phases were distinguished to gain insight in the predictive power of themodels: 1) a blind test for 2005 2008 in which only soil hydraulic characteristics, meteorological data and information about the agricultural management were accessible; 2) a calibration for the same period in which essential information on field observations was additionally available to the modellers; and 3) a validation for 2009 2011 with the corresponding type of data available as for the blind test. A set of statistical metrics (mean absolute error, root mean squared error, index of agreement,model efficiency, root relative squared error, Pearson's linear correlation coefficient) was applied for testing the results and comparing the models. None of the models performed good for all of the statistical metrics. Models designed for nitrate leaching in high-input farming systems had difficulties in accurately predicting leaching in low-input farming systems that are strongly influenced by the retention of nitrogen in catch crops and nitrogen fixation by legumes. An accurate calibration does not guarantee a good predictive power of the model. Nevertheless all models were able to identify years and crops with high- and low-leaching rates.This research was made possible by the GENESIS project of the EU 7th Framework Programme (Project No. 226536; FP7-ENV-2008-1). We are grateful for the experimental data provided by Joanneum Raum (Graz, Austria). The modelling team of Democritus University of Thrace would like to thank Per-Erik Jansson (Royal Institute of Technology, Stockholm, Sweden) for his valuable help during the application of Coup Model.Groenendijk, P.; Heinen, M.; Klammler, G.; Fank, J.; Kupfersberger, H.; Pisinaras, V.; Gemitzi, A.... (2014). Performance assessment of nitrate leaching models for highly vulnerable soils used in low-input farming based on lysimeter data. Science of the Total Environment. 499:463-480. https://doi.org/10.1016/j.scitotenv.2014.07.002S46348049

COSMOS-Europe : a European network of cosmic-ray neutron soil moisture sensors

We thank TERENO (Terrestrial Environmental Observatories), funded by the Helmholtz-Gemeinschaft for the financing and maintenance of CRNS stations. We acknowledge financial support by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) of the research unit FOR 2694 Cosmic Sense (grant no. 357874777) and by the German Federal Ministry of Education of the Research BioökonomieREVIER, Digitales Geosystem – Rheinisches Revier project (grant no. 031B0918A). COSMOS-UK has been supported financially by the UK’s Natural Environment Research Council (grant no. NE/R016429/1). The Olocau experimental watershed is partially supported by the Spanish Ministry of Science and Innovation through the research project TETISCHANGE (grant no. RTI2018-093717-BI00). The Calderona experimental site is partially supported by the Spanish Ministry of Science and Innovation through the research projects CEHYRFO-MED (grant no. CGL2017-86839- C3-2-R) and SILVADAPT.NET (grant no. RED2018-102719-T) and the LIFE project RESILIENT FORESTS (grant no. LIFE17 CCA/ES/000063). The University of Bristol’s Sheepdrove sites have been supported by the UK’s Natural Environment Research Council through a number of projects (grant nos. NE/M003086/1, NE/R004897/1, and NE/T005645/1) and by the International Atomic Energy Agency of the United Nations (grant no. CRP D12014). Acknowledgements. We thank Peter Strauss and Gerhab Rab from the Institute for Land and Water Management Research, Federal Agency for Water Management Austria, Petzenkirchen, Austria. We thank Trenton Franz from the School of Natural Resources, University of Nebraska–Lincoln, Lincoln, NE, United States. We also thank Carmen Zengerle, Mandy Kasner, Felix Pohl, and Solveig Landmark, UFZ Leipzig, for supporting field calibration, lab analysis, and data processing. We furthermore thank Daniel Dolfus, Marius Schmidt, Ansgar Weuthen, and Bernd Schilling, Forschungszentrum Jülich, Germany. The COSMOS-UK project team is thanked for making its data available to COSMOS-Europe. Luca Stevanato is thanked for the technical details about the Finapp sensor. The stations at Cunnersdorf, Lindenberg, and Harzgerode have been supported by Falk Böttcher, Frank Beyrich, and Petra Fude, German Weather Service (DWD). The Zerbst site has been supported by Getec Green Energy GmbH and Jörg Kachelmann (Meteologix AG). The CESBIO sites have been supported by the CNES TOSCA program. The ERA5-Land data are provided by ECMWF (Muñoz Sabater, 2021). The Jena dataset was retrieved at the site of The Jena Experiment, operated by DFG research unit FOR 1451.Peer reviewedPublisher PD

Investigating the Effects of Agricultural Water Management in a Mediterranean Coastal Aquifer under Current and Projected Climate Conditions

Coastal delta plains are areas with high agricultural potential for the Mediterranean region because of their high soil fertility, but they also constitute fragile systems in terms of water resources management because of the interaction of underlying aquifers with the sea. Such a case is the Pinios River delta plain located in central Greece, which also constitutes a significant ecosystem. Soil and Water Assessment Tool (SWAT) and SEAWAT models were combined in order to simulate the impact of current water resources management practices in main groundwater budget components and groundwater salinization of the shallow aquifer developed in the area. Moreover, potential climate change impact was investigated using climate data from Regional Climate Model for two projected periods (2021–2050 and 2071–2100) and two sea level rise scenarios (increase by 0.5 and 1 m). Modeling results are providing significant insight: although the contribution of the river to groundwater inflows is significant, direct groundwater recharge from precipitation was found to be higher, while capillary rise constitutes a major part of groundwater outflows from the aquifer. Moreover, during the simulation period, groundwater flow from the aquifer to the sea were found to be higher than the inflows of seawater to the aquifer. Regarding climate change impact assessment, the results indicate that the variability in groundwater recharge posed by the high variability of precipitation during the projected periods is increasing the aquifer’s deterioration potential of both its quantity and quality status, the latter expressed by the increased groundwater Cl− concentration. This evidence becomes more significant because of the limited groundwater storage capacity of the aquifer. Concerning sea level rise, it was found to be less significant in terms of groundwater salinization impact compared to the decrease in groundwater recharge and increase in crop water needs

Impact of Climate Change on Irrigation Need and Groundwater Resources in Pinios Basin

Initially an area-differentiated modelling of groundwater recharge in River Pinios Basin (Greece) was carried out for the reference period 1971–2000 based on the mGROWA model. Subsequently, the model was applied to assess the impacts of climate change on groundwater recharge and irrigation need. For this purpose one bias-corrected RCM–GCM combination from the EURO-CORDEX ensemble of climate models for two emission scenarios (RCP 4.5 and RCP 8.5) have been used as input data for the projected periods 2011–2040 and 2040–2070 and 2700–2100. Results of the mGROWA model runs for the projected periods and the two emission scenarios indicate a different evolution of groundwater recharge and a general increase in irrigation need, however with different degrees of intensity

Fully Distributed Water Balance Modelling in Large Agricultural Areas—The Pinios River Basin (Greece) Case Study

Robust assessments of variations in freshwater availability are essential for current and future water resource management in the Pinios River Basin (PRB), which is one of the most productive basins of Greece in terms of agriculture. To support sustainable water resources management in the PRB, we set up and calibrated the mGROWA hydrological model at a high spatial (100 m) and temporal (daily) resolution for the period 1971–2000, with particular attention given to deriving crop-specific irrigation requirements. We developed and implemented a comprehensive methodological framework to overcome data scarcity constraints in the PRB, thus enabling the derivation of high-resolution spatially continuous estimates of many input variables required for the mGROWA model. We generated estimates of spatiotemporal variations in the water balance components actual evapotranspiration, irrigation requirements, total runoff, and groundwater recharge for the PRB. In addition, through the calculation of indices, such as the potential irrigation to groundwater recharge ratio (PIQR), we demonstrate a way to identify potential unsustainable water use in irrigated agriculture. The established mGROWA model can be used both as a hydrological reference model providing continuous decision support for water resources management, focusing on irrigation water use, and a basis for climate impact studies for the PRB

Assessing Annual Actual Evapotranspiration Based on Climate, Topography and Soil in Natural and Agricultural Ecosystems

Simple formulas for estimating annual actual evapotranspiration (AET) based on annual climate data are widely used in large scale applications. Such formulas do not have distinct compartments related to topography, soil and irrigation, and for this reason may be limited in basins with high slopes, where runoff is the dominant water balance component, and in basins where irrigated agriculture is dominant. Thus, a simplistic method for assessing AET in both natural ecosystems and agricultural systems considering the aforementioned elements is proposed in this study. The method solves AET through water balance based on a set of formulas that estimate runoff and percolation. These formulas are calibrated by the results of the deterministic hydrological model GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) for a reference surface. The proposed methodology is applied to the country of Greece and compared with the widely used climate-based methods of Oldekop, Coutagne and Turk. The results show that the proposed methodology agrees very well with the method of Turk for the lowland regions but presents significant differences in places where runoff is expected to be very high (sloppy areas and areas of high rainfall, especially during December–February), suggesting that the proposed method performs better due to its runoff compartment. The method can also be applied in a single application considering irrigation only for the irrigated lands to more accurately estimate AET in basins with a high percentage of irrigated agriculture

Effects of Weed Removal Practices on Soil Organic Carbon in Apple Orchards Fields

The accelerated climate crisis has exacerbated the existing water and soil management challenges in the Mediterranean region, which are usually attributed to the combination of both irrational irrigation and unsustainable farming practices. The current conditions and future projections indicate that water-related risks are expected to intensify during the coming decades. Moreover, farmers often do not possess high environmental awareness; they adopt non-sustainable farming practices such as the extensive use of herbicides instead of mowing/mulching for the weeds, thus affecting soil hydraulic characteristics and fertility. To investigate the effects of different weed-management practices on soil organic carbon and thus on soil water holding capacity and infiltrability, an extensive soil-sampling campaign was performed in the semi-arid Mediterranean agricultural pilot basin of Agia—Greece. The pilot is located in the Pinios river basin, which constitutes the most highly productive agricultural plain in the country. The Agia basin was selected since it presents the uneven spatiotemporal distribution of groundwater resources and the wide application of herbicides, while an urgent need exists to sustain and improve agricultural production, with the main crops being apples and cherries. Moreover, the Agia basin constitutes a highly instrumented area where the Pinios Hydrologic Observatory belonging to the International Long Term Ecological Research network has been developed, and thus additional field measurements could contribute to the overall data-collection framework. Soil sampling was conducted in apple orchards in April 2022, just before the beginning of the growing season. Ninety six soil samples in total were collected from eight different fields; half of them applied systematic herbicides treatment, and others mulching. For the upper soil profile (0–10 cm depth), the results indicate that soil organic carbon in the fields applying mowing was found to be higher by more than 30% compared to the fields applying herbicides. The corresponding difference for soil depth of 10–30 cm was 7%, thus demonstrating the effectiveness of mulching in increasing soil organic carbon. The results of the current study could be upscaled at a larger scale in the context of adapting agricultural water-stressed regions to climate change, whilst contributing significantly to the production cost and the preservation of the ecosystemic values of the regional nexus