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

Predicting land cover changes using a CA Markov model under different shared socioeconomic pathways in Greece

Land change modeling (LCM) is a complex GIS procedure aiming at predicting land cover changes in the future, contributing thus to the design of interventions that help maintain ecosystem services and mitigate climate change impacts. In the present work, the land change model for Greece, a typical Mediterranean country, has been developed, based on historical information from remotely sensed land cover data. Land cover types based on the International Geosphere-Biosphere Program (IGBP) classification were obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product, i.e. MCD12Q1, provided annually from 2001 to 2018 at a spatial resolution of 500 m. Initially, the dominant land cover changes and their driving variables for the decade of 2001 to 2011 were determined and the transition potential of land was mapped using a multi-layer perceptron (MLP) neural network. Four dominant land-cover transformations were found in Greece from 2001 to 2011, i.e. land transformation from Savannas to Woody Savannas, from Savannas to Grasslands, from Grasslands to Savannas, and from Croplands to Grasslands. Driving variables were found to be the Evidence Likelihood of Land Cover, i.e. the relative frequency with which different land cover categories occurred within the areas that transitioned, the Altitude as realized in the Digital Elevation Model of Greece from ASTER GDEM, the Distance from previously changed land and two climate variables i.e. Mean Annual Precipitation and Mean Annual Minimum Temperature. After the model was calibrated, its predictive ability was tested for land cover prediction for 2018 and was found to be 96.7%. Future land cover projections up to 2030 were developed incorporating CMIP6 climate data under two Shared Socioeconomic Pathways (SSPs), i.e SSP126 corresponding to a sustainable future and SSP585, which describes the future world based on fossil-fueled development. The results indicate that major historical land transformations in Greece, do not correspond to land degradation or desertification, as it has been reported in previous works. On the contrary, the land cover transitions indicate that the Woody Savannas gain areas constantly, whereas Grasslands and Croplands lose areas, and forested areas of all types demonstrate moderate gains. Concerning future land cover, the present work indicates that the direction of historical changes will also prevail in the next decade, with the most severe scenario, i.e. SSP585 slowing down the rate of changes and the most sustainable one, i.e. SSP126, accelerating the rate of expansion of woody vegetation land cover type

A Spatial Downscaling Methodology for GRACE Total Water Storage Anomalies Using GPM IMERG Precipitation Estimates

A downscaling framework for coarse resolution Gravity Recovery and Climate Experiment (GRACE) Total Water Storage Anomaly (TWSA) data is described, exploiting the observations of precipitation from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG). Considering that the major driving force for changes in TWS is precipitation, we tested our hypothesis that coarse resolution, i.e., 1°, GRACE TWSA can be effectively downscaled to 0.1° using GPM IMERG data. The algorithm for the downscaling process comprises the development of a regression equation at the coarse resolution between the GRACE and GPM IMERG data, which is then applied at the finer resolution with a subsequent residual correction procedure. An ensemble of GRACE data from three processing centers, i.e., GFZ, JPL and CSR, was used for the time period from June 2018 until March 2021. To verify our downscaling methodology, we applied it with GRACE data from 2005 to 2015, and we compared it against modeled TWSA from two independent datasets in the Thrace and Thessaly regions in Greece for the same period and found a high performance in all examined metrics. Our research indicates that the downscaled GRACE observations are comparable to the TWSA estimated with hydrological modeling, thus highlighting the potential of GRACE data to contribute to the improvement of hydrological model performance, especially in ungauged basins

Estimating Groundwater Abstractions at the Aquifer Scale Using GRACE Observations

Groundwater monitoring requires costly in situ networks, which are difficult to maintain over long time periods, especially in countries facing economic recession such as Greece. Our work aims at providing a methodology to estimate groundwater abstractions at the aquifer scale using publicly available remotely sensed data from the NASA’s Gravity Recovery and Climate Experiment (GRACE) together with publicly available meteorological observations that serve as input variables to an Artificial Neural Network (ANN) method. The methodology was demonstrated in an alluvial aquifer in NE Greece for a 10-year period (2005–2014), where irrigation agriculture poses a serious threat to both groundwater resources and their dependent ecosystems. To generalize the developed model, an ensemble of 100 ANNs was created by the initial weight randomization approach and output was computed by averaging the output of each individual model. Scaled Root Mean Square Error and Nash–Sutcliffe coefficient were used to test the model efficiency. Both of these performance metrics indicated that monthly groundwater abstractions can be estimated efficiently and that the developed methodology offers an inexpensive substitute for in situ groundwater monitoring when in situ networks are not available or cannot operate properly

Assimilating Soil Moisture Information to Improve the Performance of SWAT Hydrological Model

The present work aims to highlight the possibility of improving model performance by assimilating soil moisture information in the calibration and validation process. The Soil and Water Assessment Tool (SWAT) within QGIS, i.e., QSWAT, was used to simulate the hydrological processes within the test basin, i.e., Vosvozis River Basin (VRB) in NE Greece. The model calibration and validation were conducted via SWAT-CUP for a four-year period from 2019 to 2022, in three different ways, i.e., using the traditional calibration process with river flow measurements, using satellite-based soil moisture only in the calibration, and finally incorporating satellite-based soil moisture datasets and calibrating using simultaneously flow and soil moisture information. All modeling approaches used the same set of input data related to topography, land cover, and soil information. This study utilized the recently released global scale daily downscaled soil moisture at 1 km from the Soil Moisture Active Passive (SMAP) mission to generate soil moisture datasets. Two performance indicators were evaluated: Nash Sutcliffe (NS) and coefficient of determination (R2). Results showed that QSWAT successfully simulated river flow in VRB with NS = 0.61 and R2 = 0.69 for the calibration process using river flow measurements at the outlet of VRB. However, comparing satellite-based soil moisture, NS and R2 were considerably lower with an average derived from the 19 subbasins (NS = 0.55, R2 = 0.66), indicating lower performance related to the simulation of soil moisture regime. Subsequently, introducing satellite-derived soil moisture as an additional parameter in the calibration process along with flow improved the acquired average soil moisture results of the 19 subbasins (NS = 0.85, R2 = 0.91), while preserving the satisfactory performance related to flow simulation (NS = 0.57, R2 = 0.66). Our work thus demonstrates how assimilating available satellite-derived soil moisture information into the SWAT model may offer considerable improvement in the description of soil moisture conditions, keeping the satisfactory performance in flow simulation

Simulation of coastal aquifer with the coupled use of finite elements and G.I.S.

A quasi three-dimensional finite element model that simulates both steady and transient freshwater and saltwater flow, separated by a sharp interface has been developed to study coastal aquifer systems. The model takes into account the flow dynamics of both the salt and the fresh water. The governing equations are discretized by a Galerkin finite element discretization scheme. The system of non linear equations is solved applying the Gauss - Seidel iterative method. The non linearities are treated using Picard iterations. In order to avoid instabilities during the solution process and to achieve a smoother solution, the average of the three values of saturated thickness of each liquid phase (fresh and salt water) in each finite element is used. The same technique is applied in the case of hydraulic conductivities in an heterogeneous aquifer. The model has been verified in simple cases where analytical solutions exist for steady and transient flow, both for unconfined and confined aquifers whereas the simplifying assumption according to which the same value of hydraulic conductivity and specific storage for both fresh and salt water is used, seems to be in good agreement to the analytical solution. All necessary data is introduced and managed through a GIS computer program. The simulation program is used as a tool of the GIS program, thus forming an integrated management tool in order to simulate and study saline intrusion in coastal aquifers. Application of the model to Yermasogia aquifer in Cyprus, illustrates the coupled use of modeling and GIS techniques for the examination of regional coastal aquifer systems.Ένα ημιτρισδιάστατο μοντέλο πεπερασμένων στοιχείων, που προσομοιώνει τη μόνιμη και μη μόνιμη ροή του γλυκού και του θαλασσινού νερού, τα οποία διαχωρίζονται από μια οξεία διεπιφάνεια, αναπτύχθηκε για τη μελέτη των παράκτιων υδροφορέων. Το μοντέλο λαμβάνει υπόψη την υδροδυναμική τόσο του θαλασσινού όσο και του γλυκού νερού. Οι εξισώσεις ροής διακριτοποιούνται χρησιμοποιώντας τη μέθοδο Galerkin των πεπερασμένων στοιχείων. Το σύστημα των μη γραμμικών εξισώσεων που προκύπτει επιλύεται με την επαναληπτική μέθοδο Gauss - Seidel, ενώ η μη γραμμικότητα αντιμετωπίζεται χρησιμοποιώντας επαναλήψεις Picard. Για την αποτροπή φαιμομένων αστάθειας κατά τη διαδικασία επίλυσης και για να επιτευχθεί μια πιο ομαλή λύση, χρησιμοποιείται σε κάθε πεπερασμένο στοιχείο ο μέσος όρος των τριών τιμών των κορεσμένων παχών της κάθε φάσης (γλυκού και θαλασσινού νερού). Η ίδια τεχνική ακολουθείται και στην περίπτωση της υδραυλικής αγωγιμότητας όταν πρόκειται για ετερογενή υδροφορέα. Το μοντέλο επαληθεύεται σε απλές περιπτώσεις για τις οποίες υπάρχουν αναλυτικές λύσεις για μόνιμες και μη μόνιμες ροές, τόσο για ελεύθερο όσο και για υπό πίεση υδροφορέα, ενώ η απλοποιητική παραδοχή σύμφωνα με την οποία χρησιμοποιείται η ίδια τιμή υδραυλικής αγωγιμότητας και ειδικής αποθηκευτικότητας και για τις δύο φάσεις υγρού, προσεγγίζει ικανοποιητικά τις αναλυτικές λύσεις. Όλα τα απαραίτητα στοιχεία εισάγονται και διαχειρίζονται μέσω των Γεωγραφικών Συστημάτων Πληροφοριών. Το πρόγραμμα προσομοίωσης αποτελεί ουσιαστικά ένα “εργαλείο” των Γεωγραφικών Συστημάτων Πληροφοριών, με τη συνδυασμένη χρήση των οποίων δημιουργείται ένα ολοκληρωμένο σύστημα διαχείρισης των παράκτιων υδροφορέων. Η εφαρμογή του μοντέλου στον υδροφορέα Γερμασόγειας Κύπρου, δείχνει τη χρήση του μοντέλου πεπερασμένων στοιχείων που αναπτύχθηκε στη μελέτη των συστημάτων των παράκτιων υδροφορέων

A Spatial Downscaling Methodology for GRACE Total Water Storage Anomalies Using GPM IMERG Precipitation Estimates

A downscaling framework for coarse resolution Gravity Recovery and Climate Experiment (GRACE) Total Water Storage Anomaly (TWSA) data is described, exploiting the observations of precipitation from the Global Precipitation Measurement (GPM) mission, using the Integrated Multi-satellite Retrievals for GPM (IMERG). Considering that the major driving force for changes in TWS is precipitation, we tested our hypothesis that coarse resolution, i.e., 1°, GRACE TWSA can be effectively downscaled to 0.1° using GPM IMERG data. The algorithm for the downscaling process comprises the development of a regression equation at the coarse resolution between the GRACE and GPM IMERG data, which is then applied at the finer resolution with a subsequent residual correction procedure. An ensemble of GRACE data from three processing centers, i.e., GFZ, JPL and CSR, was used for the time period from June 2018 until March 2021. To verify our downscaling methodology, we applied it with GRACE data from 2005 to 2015, and we compared it against modeled TWSA from two independent datasets in the Thrace and Thessaly regions in Greece for the same period and found a high performance in all examined metrics. Our research indicates that the downscaled GRACE observations are comparable to the TWSA estimated with hydrological modeling, thus highlighting the potential of GRACE data to contribute to the improvement of hydrological model performance, especially in ungauged basins

Transboundary Nile basin dynamics: Land use change, drivers, and hydrological impacts under socioeconomic pathways

Landscape transitions in the Nile River basin will likely accelerate over the next decades due to socioeconomic developments and climate change. However, the assessments of land use/land cover (LULC) changes and their impact on the water resources over the Nile basin lacked a transboundary perspective. Here we used coupled basin-scale geospatial-hydrological models to project future LULC changes in the Nile basin and its three tributaries (i.e., White Nile, Blue Nile, and Atbara River), explored their drivers and projected hydrological impacts under different shared socioeconomic pathways (SSPs) during 2020–2060. Compared to 1992–2019, significant increases in the forested area (>50 × 103 km2) are expected to occur in the upstream areas of the White Nile and the Blue Nile in South Sudan and Ethiopia, with larger increases projected under higher emission scenarios. Consequently, it will likely reduce the downstream seasonal river discharge for the White and Blue Nile by up to 8.4% (SSP5) and 8.9% (SSP2), respectively. An increase of 7.4% in the Blue Nile discharge is expected during the flood season if the current urbanization/deforestation rates would prevail in the future. Large decreases (>15 × 103 km2) of unused land are expected in the Atbara River sub-catchment with increases in natural vegetation socioeconomic-related LULC types, leading to a river flow decrease of 15% during the rainy season under the SSPs. The basin-scale LULC changes are projected to decrease the Main Nile flow to Egypt by 3.6% under SSPs and increase by 2.1% if the historical trends prevail. The results highlight a close association between landscape dynamics, socioeconomic growth, and climate change over the Nile basin and suggest adaptive LULC planning and conservation measures

Evaluation of MODIS, Climate Change Initiative, and CORINE Land Cover Products Based on a Ground Truth Dataset in a Mediterranean Landscape

Land cover can reflect global environmental changes if their associated transitions are quantitatively and correctly analysed, thus helping to assess the drivers and impacts of climate change and other applied research studies. It is highly important to acquire accurate spatial land cover information to perform multidisciplinary analyses. This work aims at estimating the accuracy of three widely used land cover products, the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product (MCD12Q1), the European Space Agency Climate Change Initiative land cover (ESA-CCI-LC), and the EU CORINE land cover (CLC), all for the reference year of 2018, by comparing them against a fine resolution land cover dataset created for this study with combined ground surveys and high-resolution Large Scale Orthophotography (LSO 25/2015). Initially, the four datasets had their land cover classes harmonized and all were resampled to the same spatial resolution. The accuracy metrics used to conduct the comparisons were Overall Accuracy, Producer’s Accuracy, User’s Accuracy, and the Kappa Coefficient. Comparisons with the reference dataset revealed an underestimation of the forested areas class in all three compared products. Further analysis showed that the accuracy metrics were reasonably high for the broad classes (forest vs. non-forest), with an overall accuracy exceeding 70% in all examined products. On the contrary, in the detailed classification (total land cover mapping), the comparison of the reference dataset with the three land cover products highlighted specific weaknesses in the classification results of the three products, showing that CLC depicted more precisely the landscape characteristics than the two other products, since it demonstrated the highest overall accuracy (37.47%), while MODIS and ESA-CCI-LC revealed a percentage that did not exceed 22%