{"type": "FeatureCollection", "features": [{"id": "10.1016/j.resconrec.2022.106325", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:16:37Z", "type": "Journal Article", "created": "2022-04-14", "title": "Life cycle assessment of struvite recovery and wastewater sludge end-use: A Flemish illustration", "description": "Phosphate rock (PR) has been designated as a Critical Raw Material in the European Union (EU). This has led to increased emphasis on alternative P recovery (APR) from secondary streams like wastewater sludge (WWS). However, WWS end-use is a contentious topic, and EU member states prefer different end-use pathways (land application/incineration/valorisation in cement kilns). Previous Life Cycle Assessments (LCA) on APRs from WWS reached contrasting conclusions; while most considered WWS as waste and highlighted a net benefit relative to PR mining and beneficiation, others viewed WWS as a resource and highlighted a net burden of the treatment. We used a combined functional unit (that views WWS from a waste as well as a resource perspective) and applied it on a Flemish wastewater treatment plant (WWTP) with struvite recovery as APR technology. Firstly, a retrospective comparison was performed to measure the WWTP performance before and after struvite recovery and the analysis was complemented by uncertainty and global sensitivity analyses. The results showed struvite recovery provides marginal environmental benefits due to improved WWS dewatering and reduced polymer use. Secondly, a prospective LCA approach was performed to reflect policy changes regarding WWS end-use options in Flanders. Results indicated complete mono-incineration of WWS, ash processing to recover P and the subsequent land application appears to be less sustainable in terms of climate change, human toxicity, and terrestrial acidification relative to the status quo, i.e., co-incineration with municipal solid waste and valorisation at cement kilns. Impacts on fossil depletion, however, favour mono-incineration over the status quo.", "keywords": ["BURDENS", "PHOSPHORUS RECOVERY", "Wastewater sludge treatment", "LCA", "SEWAGE-SLUDGE", "GLOBAL SENSITIVITY-ANALYSIS", "PRODUCT", "7. Clean energy", "01 natural sciences", "ENVIRONMENTAL IMPACTS", "6. Clean water", "12. Responsible consumption", "Global sensitivity analysis", "Phosphorus recovery", "Prospective LCA", " Global sensitivity analysis", "13. Climate action", "Earth and Environmental Sciences", "Full Length Article", "BENEFITS", "11. Sustainability", "SHIFT", "Prospective LCA", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.resconrec.2022.106325"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Resources%2C%20Conservation%20and%20Recycling", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.resconrec.2022.106325", "name": "item", "description": "10.1016/j.resconrec.2022.106325", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.resconrec.2022.106325"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-07-01T00:00:00Z"}}, {"id": "10.1016/j.biombioe.2012.02.011", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:15:34Z", "type": "Journal Article", "created": "2012-03-09", "title": "Origins Of The Debate On The Life-Cycle Greenhouse Gas Emissions And Energy Consumption Of First-Generation Biofuels \u2013 A Sensitivity Analysis Approach", "description": "Available results about energy and GreenHouse Gases (GHG) balances of biofuels from Life-Cycle Assessment (LCA) or life-cycle based studies present large discrepancies and thus, may lead to contradictory policy-making measures. This work reviewed seven important European LCA studies in a sensitivity analysis approach in order to get a better understanding of the roots of such a debate for three major biofuels in European production: rape methyl ester and ethanol from wheat and sugar beet. Global trends and variability of energy and GHG balances were depicted and completed with a sensitivity analysis carried out for each methodological and data parameter, which allowed making recommendations on the carrying out of LCA in a policy-making or a biofuels comparison context. Methodological choices, and especially allocation rule, appeared as key elements for results variation with influences on balances up to 149%; system expansion approach was identified as the most relevant rule since it integrates the market potential and the environmental interest of by-products promotion, which was pointed out as a crucial point for biofuels sustainability. The influence of local specificity for cultivation data was evaluated up to 167%, which puts too large geographical coverage in question. Modelling uncertainties due to N2O emissions from soils showed influences from 17 to 46%, which represents a crucial challenge for research and for LCA results accuracy. Approximations evaluation pointed out the need to integrate agricultural machinery into the assessment. Finally, land-use issue revealed its dramatic importance for LCA results and the need to define explicit scenarios for land-use alternatives.", "keywords": ["[SDV.BIO]Life Sciences [q-bio]/Biotechnology", "330", "http://aims.fao.org/aos/agrovoc/c_24420", "P06 - Sources d'\u00e9nergie renouvelable", "http://aims.fao.org/aos/agrovoc/c_37938", "http://aims.fao.org/aos/agrovoc/c_890", "\u00e9thanol", "02 engineering and technology", "7. Clean energy", "01 natural sciences", "630", "12. Responsible consumption", "11. Sustainability", "0202 electrical engineering", " electronic engineering", " information engineering", "http://aims.fao.org/aos/agrovoc/c_10677", "gaz \u00e0 effet de serre", "http://aims.fao.org/aos/agrovoc/c_34841", "[INFO.INFO-BT]Computer Science [cs]/Biotechnology", "Triticum", "http://aims.fao.org/aos/agrovoc/c_2671", "http://aims.fao.org/aos/agrovoc/c_1066", "0105 earth and related environmental sciences", "2. Zero hunger", "http://aims.fao.org/aos/agrovoc/c_27465", "Ethanol", "Sugar beet", "Brassica napus", "http://aims.fao.org/aos/agrovoc/c_2724", "Life cycle analysis LCA", "15. Life on land", "http://aims.fao.org/aos/agrovoc/c_9000056", "biocarburant", "13. Climate action", "Rapeseed methyl ester", "Wheat", "mod\u00e9lisation environnementale", "ester", "P01 - Conservation de la nature et ressources fonci\u00e8res", "impact sur l'environnement", "Beta vulgaris", "Sensitivity analysis", "P02 - Pollution", "http://aims.fao.org/aos/agrovoc/c_7950", "\u00e9valuation de l'impact"]}, "links": [{"href": "https://doi.org/10.1016/j.biombioe.2012.02.011"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Biomass%20and%20Bioenergy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.biombioe.2012.02.011", "name": "item", "description": "10.1016/j.biombioe.2012.02.011", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.biombioe.2012.02.011"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-05-01T00:00:00Z"}}, {"id": "10.1016/j.fcr.2021.108182", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:16:02Z", "type": "Journal Article", "created": "2021-05-25", "title": "Global sensitivity analysis of crop yield and transpiration from the FAO-AquaCrop model for dryland environments", "description": "Open AccessPeer reviewed", "keywords": ["2. Zero hunger", "570", "Yield", "0208 environmental biotechnology", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "630", "AquaCrop", "6. Clean water", "Transpiration", "Dryland", "13. Climate action", "Sensitivity analysis"]}, "links": [{"href": "https://eprints.soton.ac.uk/449637/1/AquaCrop_GSA_rev2.pdf"}, {"href": "https://eprints.soton.ac.uk/449637/2/Lu2021_AquaCrop_GSA.pdf"}, {"href": "https://doi.org/10.1016/j.fcr.2021.108182"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Field%20Crops%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.fcr.2021.108182", "name": "item", "description": "10.1016/j.fcr.2021.108182", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.fcr.2021.108182"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-01T00:00:00Z"}}, {"id": "10.1016/j.renene.2021.02.003", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:16:37Z", "type": "Journal Article", "created": "2020-11-05", "title": "Virtual fatigue diagnostics of wake-affected wind turbine via Gaussian Process Regression", "description": "<p>We propose a data-driven model to predict the short-term fatigue Damage Equivalent Loads (DEL) on a wake-affected wind turbine based on wind field inflow sensors and/or loads sensors deployed on an adjacent up-wind wind turbine. Gaussian Process Regression (GPR) with Bayesian hyperparameters calibration is proposed to obtain a surrogate from input random variables to output DELs in the blades and towers of the up-wind and wake-affected wind turbines. A sensitivity analysis based on the hyperparameters of the GPR and Kullback-Leibler divergence is conducted to assess the effect of different input on the obtained DELs. We provide qualitative recommendations for a minimal set of necessary and sufficient input random variables to minimize the error in the DEL predictions on the wake-affected wind turbine. Extensive simulations are performed comprising different random variables, including wind speed, turbulence intensity, shear exponent and inflow horizontal skewness. Furthermore, we include random variables related to the blades lift and drag coefficients with direct impact on the rotor aerodynamic induction, which governs the evolution and transport of the meandering wake. In addition, different spacing between the wind turbines and W\u00f6hler exponents for calculation of DELs are considered. The maximum prediction normalized mean squared error, obtained in the tower base DELs in the fore-aft direction of the wake affected wind turbine, is less than 4%. In the case of the blade root DELs, the overall prediction error is less than 1%. The proposed scheme promotes utilization of sparse structural monitoring (loads) measurements for improving diagnostics on wake-affected turbines.</p>", "keywords": ["bepress|Physical Sciences and Mathematics|Physics|Engineering Physics", "engrXiv|Engineering|Risk Analysis", "engrXiv|Engineering|Other Engineering", "bepress|Engineering", "engrXiv|Engineering|Mechanical Engineering|Fluid Mechanics", "bepress|Engineering|Mechanical Engineering", "engrXiv|Engineering|Mechanical Engineering", "bepress|Engineering|Mechanical Engineering|Applied Mechanics", "Gaussian Process Regression", "02 engineering and technology", "7. Clean energy", "Virtual sensing", "wind turbine", "bepress|Engineering|Computational Engineering", "engrXiv|Engineering|Civil and Environmental Engineering", "0202 electrical engineering", " electronic engineering", " information engineering", "uncertainty", "Fatigue", "wake", "engrXiv|Engineering|Civil and Environmental Engineering|Structural Engineering", "Uncertainty", "engrXiv|Engineering|Mechanical Engineering|Applied Mechanics", "Bayesian Calibration", "engrXiv|Engineering|Engineering Physics", "bepress|Engineering|Risk Analysis", "engrXiv|Engineering", "bepress|Engineering|Civil and Environmental Engineering", "engrXiv|Engineering|Computational Engineering", "Wake", "bepress|Engineering|Aerospace Engineering|Aerodynamics and Fluid Mechanics", "bepress|Engineering|Civil and Environmental Engineering|Structural Engineering", "fatigue", "bepress|Engineering|Other Engineering", "Sensitivity analysis", "Wind turbine", "Bayesian Gaussian process regression"]}, "links": [{"href": "https://doi.org/10.1016/j.renene.2021.02.003"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Renewable%20Energy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.renene.2021.02.003", "name": "item", "description": "10.1016/j.renene.2021.02.003", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.renene.2021.02.003"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-11-05T00:00:00Z"}}, {"id": "10.1016/j.watres.2019.114932", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:17:13Z", "type": "Journal Article", "created": "2019-07-30", "title": "Assessing practical identifiability during calibration and cross-validation of a structured model for high-solids anaerobic digestion", "description": "High-solids anaerobic digestion (HS-AD) of the organic fraction of municipal solid waste (OFMSW) is operated at a total solid (TS) content\u202f\u2265\u202f10% to enhance the waste treatment economy, though it might be associated to free ammonia (NH3) inhibition. This study aimed to calibrate and cross-validate a HS-AD model for homogenized reactors in order to assess the effects of high NH3 levels in HS-AD of OFMSW, but also to evaluate the suitability of the reversible non-competitive inhibition function to reproduce the effect of NH3 on the main acetogenic and methanogenic populations. The practical identifiability of structural/biochemical parameters (i.e. 35) and initial conditions (i.e. 32) was evaluated using batch experiments at different TS and/or inoculum-to-substrate ratios. Variance-based global sensitivity analysis and approximate Bayesian computation were used for parameter optimization. The experimental data in this study permitted to estimate up to 8 biochemical parameters, whereas the rest of parameters and biomass contents were poorly identifiable. The study also showed the relatively high levels of NH3 (i.e. up to 2.3\u202fg\u202fN/L) and ionic strength (i.e. up to 0.9\u202fM) when increasing TS in HS-AD of OFMSW. However, the NH3 non-competitive function was unable to capture the acetogenic/methanogenic inhibition. Therefore, the calibration emphasized the need for target-oriented experimental data to enhance the practical identifiability and the predictive capabilities of structured HS-AD models, but also the need for further testing the NH3 inhibition function used in these simulations.", "keywords": ["[SDE] Environmental Sciences", "[SDV]Life Sciences [q-bio]", "0207 environmental engineering", "high-solids anaerobic digestion model", "Bayes Theorem", "02 engineering and technology", "Solid Waste", "01 natural sciences", "7. Clean energy", "6. Clean water", "Refuse Disposal", "12. Responsible consumption", "[SDV] Life Sciences [q-bio]", "High-solids anaerobic digestion model", " ammonia inhibition", " ionic strength", " global sensitivity analysis", " approximate bayesian computation", "Bioreactors", "global sensitivity analysis", "[SDE]Environmental Sciences", "Calibration", "High-solids anaerobic digestion model", "Anaerobiosis", "ionic strength", "Methane", "ammonia inhibition", "approximate bayesian computation", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://www.iris.unina.it/bitstream/11588/757589/1/Post-print%20for%20IRIS.pdf"}, {"href": "https://hal.inrae.fr/hal-02623443/file/S0043135419307067.pdf"}, {"href": "https://doi.org/10.1016/j.watres.2019.114932"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.watres.2019.114932", "name": "item", "description": "10.1016/j.watres.2019.114932", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.watres.2019.114932"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-11-01T00:00:00Z"}}, {"id": "10.2166/wst.2018.398", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:20:24Z", "type": "Journal Article", "created": "2018-10-04", "title": "Sensitivity analysis for an elemental sulfur-based two-step denitrification model", "description": "Abstract                <p>A local sensitivity analysis was performed for a chemically synthesized elemental sulfur (S0)-based two-step denitrification model, accounting for nitrite (NO2\uffe2\uff88\uff92) accumulation, biomass growth and S0 hydrolysis. The sensitivity analysis was aimed at verifying the model stability, understanding the model structure and individuating the model parameters to be further optimized. The mass specific area of the sulfur particles (a*) and hydrolysis kinetic constant (k1) were identified as the dominant parameters on the model outputs, i.e. nitrate (NO3\uffe2\uff88\uff92), NO2\uffe2\uff88\uff92 and sulfate (SO42\uffe2\uff88\uff92) concentrations, confirming that the microbially catalyzed S0 hydrolysis is the rate-limiting step during S0-driven denitrification. Additionally, the maximum growth rates of the denitrifying biomass on NO3\uffe2\uff88\uff92 and NO2\uffe2\uff88\uff92 were detected as the most sensitive kinetic parameters.</p>", "keywords": ["Elemental sulfur", "Environmental Engineering", "0207 environmental engineering", "Biological surface-based hydrolysis; Elemental sulfur; Mathematical modeling; Sensitivity analysis; Two-step autotrophic denitrification; Environmental Engineering; Water Science and Technology", "02 engineering and technology", "01 natural sciences", "Two-step autotrophic denitrification", "Bioreactors", "European Joint Doctorates", "European Commission", "Knowmad Institut", "Biological surface-based hydrolysis", "Nitrites", "Netherlands", "Water Science and Technology", "0105 earth and related environmental sciences", "Aurora Universities Network", "EC", "Nitrates", "H2020", "Energy Research", "13. Climate action", "Denitrification", "Mathematical modeling", "Sensitivity analysis", "Sulfur"]}, "links": [{"href": "https://www.iris.unina.it/bitstream/11588/724909/2/2018%20-%20Kostrytsia%20et%20al.%20-%20Water%20Science%20%26%20Technology%20-%20Sensitivity%20analysis%20for%20S0-based%20denitrification%20model.pdf"}, {"href": "http://iwaponline.com/wst/article-pdf/78/6/1296/504647/wst078061296.pdf"}, {"href": "https://doi.org/10.2166/wst.2018.398"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Science%20and%20Technology", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.2166/wst.2018.398", "name": "item", "description": "10.2166/wst.2018.398", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.2166/wst.2018.398"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-09-20T00:00:00Z"}}, {"id": "10.3390/agronomy11122446", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-25T16:20:48Z", "type": "Journal Article", "created": "2021-12-01", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. Zero hunger", "sensitivity analysis", "S", "rice", "CERES-Rice", "CERES-Rice; rice; cultivars; Sobol\u2019 method; sensitivity analysis", "cultivars", "Sobol\u2019 method", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "Sobol' method", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2446/pdf"}, {"href": "https://doi.org/10.3390/agronomy11122446"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agronomy11122446", "name": "item", "description": "10.3390/agronomy11122446", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agronomy11122446"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "10.3390/w13223274", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:07Z", "type": "Journal Article", "created": "2021-11-19", "title": "Modeling the Soil Erosion Regulation Ecosystem Services of the Landscape in Polish Catchments", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, the soil erosion regulation ecosystem services of the CORINE land use/ land cover types along with soil intrinsic features and geomorphological factors were examined by using the soil erosion data of 327 catchments in Poland, with a mean area of 510 \u00b1 330 km2, applying a multivariate regression modeling approach. The results showed that soil erosion is accelerated by the discontinuous urban fabric (r = 0.224, p \u2264 0.01), by construction sites (r = 0.141, p \u2264 0.05), non-irrigated arable land (r = 0.237, p \u2264 0.01), and is mitigated by coniferous forest (r = \u22120.322, p \u2264 0.01), the clay ratio (r = \u22120.652, p \u2264 0.01), and the organic content of the soil (r = \u22120.622, p \u2264 0.01). The models also indicated that there is a strong relationship between soil erosion and the percentage of land use/land cover types (r2 = [0.62, 0.82, 0.83, 0.74]), i.e., mixed forest, non-irrigated arable land, fruit trees and berry plantations, broad-leaf forest, sport and leisure facilities, construction sites, and mineral extraction sites. The findings show that the soil erosion regulation ecosystem service is sensitive to broadleaf forests, rainfed agriculture, soil water content, terrain slope, drainage network density, annual precipitation, the clay ratio, the soil carbon content, and the degree of sensitivity increases from the broadleaf forest to the soil carbon content.</p></article>", "keywords": ["Akaike information criterion", "2. Zero hunger", "landscape composition", "goodness of fit tests", "regression models", "Goodness of fit tests", "Landscape composition", "04 agricultural and veterinary sciences", "Regression models", "15. Life on land", "01 natural sciences", "6. Clean water", "sensitivity analysis", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "Sensitivity analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://doi.org/10.3390/w13223274"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/w13223274", "name": "item", "description": "10.3390/w13223274", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w13223274"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-18T00:00:00Z"}}, {"id": "10.5061/dryad.rn8pk0pm8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:21:32Z", "type": "Dataset", "created": "2024-06-28", "title": "Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass-based biofuel production", "description": "unspecifiedThis study investigates uncertainties in greenhouse gas (GHG) emission  factors related to switchgrass-based biofuel production in Michigan. Using  three life cycle assessment (LCA) databases\u2014 US lifecycle inventory  database (USLCI), GREET, and Ecoinvent\u2014each with multiple versions, we  recalculated the global warming intensity (GWI) and GHG mitigation  potential in a static calculation. Employing Monte Carlo simulations along  with local and global sensitivity analyses, we assess uncertainties and  pinpoint key parameters influencing GWI. The convergence of results across  our previous study, static calculations, and Monte Carlo simulations  enhances the credibility of estimated GWI values. Static calculations,  validated by Monte Carlo simulations, offer reasonable central tendencies,  providing a robust foundation for policy considerations. However, the  wider range observed in Monte Carlo simulations underscores the importance  of potential variations and uncertainties in real-world applications.  Sensitivity analyses identify biofuel yield, GHG emissions of electricity,  and soil organic carbon (SOC) change as pivotal parameters influencing  GWI. Decreasing uncertainties in GWI may be achieved by making greater  efforts to acquire more precise data on these parameters. Our study  emphasizes the significance of considering diverse GHG factors and  databases in GWI assessments and stresses the need for accurate  electricity fuel mixes, crucial information for refining GWI assessments  and informing strategies for sustainable biofuel production.", "keywords": ["Sensitivity Analysis", "Switchgrass", "FOS: Environmental engineering", "Cellulosic biofuel", "Global warming intensity", "Greenhouse gas emission factor", "LCA database", "uncertainty analysis"], "contacts": [{"organization": "Kim, Seungdo, Dale, Bruce, Basso, Bruno,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.rn8pk0pm8"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.rn8pk0pm8", "name": "item", "description": "10.5061/dryad.rn8pk0pm8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.rn8pk0pm8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-07-16T00:00:00Z"}}, {"id": "10.5281/zenodo.8091705", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-25T16:23:36Z", "type": "Journal Article", "created": "2021-11-30", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. Zero hunger", "sensitivity analysis", "S", "rice", "CERES-Rice", "CERES-Rice; rice; cultivars; Sobol\u2019 method; sensitivity analysis", "cultivars", "Sobol\u2019 method", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "Sobol' method", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2446/pdf"}, {"href": "https://doi.org/10.5281/zenodo.8091705"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.8091705", "name": "item", "description": "10.5281/zenodo.8091705", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.8091705"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}, {"id": "10.7818/ECOS.2017.26-2.05", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:19Z", "type": "Journal Article", "created": "2017-08-29", "title": "Simulating the interaction among initial stand density and water and nutrient flows to understand the development of Pinus sylvestris and Fagus sylvatica mixedwoods under climate change", "description": "Open AccessEste trabajo ha sido financiado por medio de los proyectos AGL2012-33465 del Ministerio de Econom\u00eda y Competitividad, y el proyecto CIG-2012-326718-ECOPYREN3 de las Acciones Marie Curie del 7\u00ba Programa Marco de la Comisi\u00f3n Europea.", "keywords": ["Modelizaci\u00f3n ecol\u00f3gica", "0106 biological sciences", "FORECAST Climate", "Ecosystem-level models", "Water stress", "An\u00e1lisis de sensibilidad", "15. Life on land", "01 natural sciences", "6. Clean water", "Estr\u00e9s h\u00eddrico", "13. Climate action", "Mortalidad", "Mortality", "Sensitivity analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.7818/ECOS.2017.26-2.05"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecosistemas", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.7818/ECOS.2017.26-2.05", "name": "item", "description": "10.7818/ECOS.2017.26-2.05", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.7818/ECOS.2017.26-2.05"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2017-08-29T00:00:00Z"}}, {"id": "10754/669278", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:43Z", "type": "Journal Article", "created": "2021-05-24", "title": "Global sensitivity analysis of crop yield and transpiration from the FAO-AquaCrop model for dryland environments", "description": "Project Co-ordinators: Dr. Jose Alfonso G\u00f3mez Calero (Instituto de Agricultura Sostenible (IAS-CISC), Dr. Weifeng Xu (Fujian Agriculture and Forest University, FAFU). -- Trabajo desarrollado bajo la financiaci\u00f3n del proyecto \u201cSoil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems\u201d (773903), coordinado por Jos\u00e9 Alfonso G\u00f3mez Calero, investigador del Instituto de Agricultura Sostenible (IAS). The application of crop models towards improved local scale prediction and precision management requires the identification and description of the major factors influencing model performance. Such efforts are particularly important for dryland areas which face rapid population growth and increasing constraints on water supplies. In this study, a global sensitivity analysis on crop yield and transpiration was performed for 49 parameters in the FAO-AquaCrop model (version 6.0) across three dryland farming areas with different climatic conditions. The Morris screening method and the variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) method were used to evaluate the parameter sensitivities of several staple crops (maize, soybean or winter wheat) under dry, normal and wet scenarios. Results suggest that parameter sensitivities vary with the target model output (e.g., yield, transpiration) and the wetness condition. By synthesizing parameter sensitivities under different scenarios, the key parameters affecting model performance under both high and low water stress were identified for the three crops. Overall, factors relevant to root development tended to have large impacts under high water stress, while those controlling maximum canopy cover and senescence were more influential under low water stress. Parameter sensitivities were also shown to be stage-dependent from a day-by-day analysis of canopy cover and biomass simulations. Subsequent comparison with AquaCrop version 5.0 suggests that AquaCrop version 6.0 is less sensitive to uncertainties in soil properties. This work was partly funded through the \u2018A new paradigm in precision agriculture: assimilation of ultra-fine resolution data into a crop-yield forecasting model\u2019 project, supported by the King Abdullah University of Science and Technology, grant number OSR-2017-CRG6, and through the \u2018Building REsearch Capacity for sustainable water and food security In drylands of sub-saharan Africa (BRECcIA)\u2019 project, which is supported by UK Research and Innovation as part of the Global Challenges Research Fund, grant number NE/P021093/1. Matthew McCabe was funded by KAUST. G. De Lannoy was funded by EU project SHui GA 773903. Peer reviewed", "keywords": ["2. Zero hunger", "570", "Yield", "0208 environmental biotechnology", "0207 environmental engineering", "02 engineering and technology", "15. Life on land", "630", "AquaCrop", "6. Clean water", "Transpiration", "Dryland", "13. Climate action", "Sensitivity analysis"]}, "links": [{"href": "https://eprints.soton.ac.uk/449637/1/AquaCrop_GSA_rev2.pdf"}, {"href": "https://eprints.soton.ac.uk/449637/2/Lu2021_AquaCrop_GSA.pdf"}, {"href": "https://doi.org/10754/669278"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Field%20Crops%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10754/669278", "name": "item", "description": "10754/669278", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10754/669278"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-07-01T00:00:00Z"}}, {"id": "10261/279273", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:24:31Z", "type": "Journal Article", "created": "2021-11-19", "title": "Modeling the Soil Erosion Regulation Ecosystem Services of the Landscape in Polish Catchments", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, the soil erosion regulation ecosystem services of the CORINE land use/ land cover types along with soil intrinsic features and geomorphological factors were examined by using the soil erosion data of 327 catchments in Poland, with a mean area of 510 \u00b1 330 km2, applying a multivariate regression modeling approach. The results showed that soil erosion is accelerated by the discontinuous urban fabric (r = 0.224, p \u2264 0.01), by construction sites (r = 0.141, p \u2264 0.05), non-irrigated arable land (r = 0.237, p \u2264 0.01), and is mitigated by coniferous forest (r = \u22120.322, p \u2264 0.01), the clay ratio (r = \u22120.652, p \u2264 0.01), and the organic content of the soil (r = \u22120.622, p \u2264 0.01). The models also indicated that there is a strong relationship between soil erosion and the percentage of land use/land cover types (r2 = [0.62, 0.82, 0.83, 0.74]), i.e., mixed forest, non-irrigated arable land, fruit trees and berry plantations, broad-leaf forest, sport and leisure facilities, construction sites, and mineral extraction sites. The findings show that the soil erosion regulation ecosystem service is sensitive to broadleaf forests, rainfed agriculture, soil water content, terrain slope, drainage network density, annual precipitation, the clay ratio, the soil carbon content, and the degree of sensitivity increases from the broadleaf forest to the soil carbon content.</p></article>", "keywords": ["Akaike information criterion", "2. Zero hunger", "landscape composition", "goodness of fit tests", "regression models", "Goodness of fit tests", "Landscape composition", "04 agricultural and veterinary sciences", "Regression models", "15. Life on land", "01 natural sciences", "6. Clean water", "sensitivity analysis", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "Sensitivity analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://doi.org/10261/279273"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/279273", "name": "item", "description": "10261/279273", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/279273"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-18T00:00:00Z"}}, {"id": "2164/15915", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:25:26Z", "type": "Journal Article", "created": "2020-07-01", "title": "Global Research Alliance N2O chamber methodology guidelines: Summary of modeling approaches", "description": "Abstract<p>Measurements of nitrous oxide (N2O) emissions from agriculture are essential for understanding the complex soil\uffe2\uff80\uff93crop\uffe2\uff80\uff93climate processes, but there are practical and economic limits to the spatial and temporal extent over which measurements can be made. Therefore, N2O models have an important role to play. As models are comparatively cheap to run, they can be used to extrapolate field measurements to regional or national scales, to simulate emissions over long time periods, or to run scenarios to compare mitigation practices. Process\uffe2\uff80\uff90based models can also be used as an aid to understanding the underlying processes, as they can simulate feedbacks and interactions that can be difficult to distinguish in the field. However, when applying models, it is important to understand the conceptual process differences in models, how conceptual understanding changed over time in various models, and the model requirements and limitations to ensure that the model is well suited to the purpose of the investigation and the type of system being simulated. The aim of this paper is to give the reader a high\uffe2\uff80\uff90level overview of some of the important issues that should be considered when modeling. This includes conceptual understanding of widely used models, common modeling techniques such as calibration and validation, assessing model fit, sensitivity analysis, and uncertainty assessment. We also review examples of N2O modeling for different purposes and describe three commonly used process\uffe2\uff80\uff90based N2O models (APSIM, DayCent, and DNDC).</p", "keywords": ["Process-based", "Environmental Engineering", "Monitoring", "330", "Supplementary Data", "QH301 Biology", "Nitrous Oxide", "Goodness-of-fit", "01 natural sciences", "Empirical", "QH301", "Soil", "NE/M021327/1", "SDG 13 - Climate Action", "774378", "Nitrous Oxide/analysis", "European Commission", "Waste Management and Disposal", "Water Science and Technology", "0105 earth and related environmental sciences", "Policy and Law", "Natural Environment Research Council (NERC)", "NE/P019455/1", "Uncertainty", "Agriculture", "04 agricultural and veterinary sciences", "15. Life on land", "Pollution", "Management", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "Sensitivity analysis"]}, "links": [{"href": "https://onlinelibrary.wiley.com/doi/pdf/10.1002/jeq2.20119"}, {"href": "https://doi.org/2164/15915"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Environmental%20Quality", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2164/15915", "name": "item", "description": "2164/15915", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2164/15915"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2020-08-27T00:00:00Z"}}, {"id": "3212772330", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-25T16:26:06Z", "type": "Journal Article", "created": "2021-11-19", "title": "Modeling the Soil Erosion Regulation Ecosystem Services of the Landscape in Polish Catchments", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>In this study, the soil erosion regulation ecosystem services of the CORINE land use/ land cover types along with soil intrinsic features and geomorphological factors were examined by using the soil erosion data of 327 catchments in Poland, with a mean area of 510 \u00b1 330 km2, applying a multivariate regression modeling approach. The results showed that soil erosion is accelerated by the discontinuous urban fabric (r = 0.224, p \u2264 0.01), by construction sites (r = 0.141, p \u2264 0.05), non-irrigated arable land (r = 0.237, p \u2264 0.01), and is mitigated by coniferous forest (r = \u22120.322, p \u2264 0.01), the clay ratio (r = \u22120.652, p \u2264 0.01), and the organic content of the soil (r = \u22120.622, p \u2264 0.01). The models also indicated that there is a strong relationship between soil erosion and the percentage of land use/land cover types (r2 = [0.62, 0.82, 0.83, 0.74]), i.e., mixed forest, non-irrigated arable land, fruit trees and berry plantations, broad-leaf forest, sport and leisure facilities, construction sites, and mineral extraction sites. The findings show that the soil erosion regulation ecosystem service is sensitive to broadleaf forests, rainfed agriculture, soil water content, terrain slope, drainage network density, annual precipitation, the clay ratio, the soil carbon content, and the degree of sensitivity increases from the broadleaf forest to the soil carbon content.</p></article>", "keywords": ["Akaike information criterion", "2. Zero hunger", "landscape composition", "goodness of fit tests", "regression models", "Goodness of fit tests", "Landscape composition", "04 agricultural and veterinary sciences", "Regression models", "15. Life on land", "01 natural sciences", "6. Clean water", "sensitivity analysis", "11. Sustainability", "0401 agriculture", " forestry", " and fisheries", "Sensitivity analysis", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/22/3274/pdf"}, {"href": "https://doi.org/3212772330"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3212772330", "name": "item", "description": "3212772330", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3212772330"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-18T00:00:00Z"}}, {"id": "3215193907", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-05-25T16:26:06Z", "type": "Journal Article", "created": "2021-12-01", "title": "Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results. However, the effects of cultivar variation and specific-stage variations of climate conditions on model outputs still remain unclear. In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol\u2019 method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis day, maturity day, and yield). In addition, we also compared the differences in the sensitivity results under four specific-stage variations (vegetative phase, panicle-formation phase, ripening phase, and the whole growth season) of climate conditions. The results indicated that (1) parameter Tavg, G4, and P2O are the most influential parameters for all model outputs across cultivars during the whole growth season; (2) under the vegetative-phase variation of climate parameters; the variability of model outputs is mainly controlled by parameter P2O and Tavg; (3) under the panicle-formation-phase or ripening-phase variation of climate parameters, parameter P2O was the dominant variable for all model outputs; (4) parameter PORM had a considerable effect (the total sensitivity index, STi; STi&gt;0.05) on yield regardless of the various specific-stage variations of the climate parameters. Findings obtained from this study will contribute to understanding the comprehensive effects of crop parameters on model outputs under different cultivars and specific-stage variations of climate conditions.</p></article>", "keywords": ["2. Zero hunger", "sensitivity analysis", "S", "rice", "CERES-Rice", "CERES-Rice; rice; cultivars; Sobol\u2019 method; sensitivity analysis", "cultivars", "Sobol\u2019 method", "0401 agriculture", " forestry", " and fisheries", "Agriculture", "Sobol' method", "04 agricultural and veterinary sciences", "15. Life on land"], "contacts": [{"organization": "Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du,", "roles": ["creator"]}]}, "links": [{"href": "http://www.mdpi.com/2073-4395/11/12/2446/pdf"}, {"href": "https://doi.org/3215193907"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agronomy", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "3215193907", "name": "item", "description": "3215193907", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3215193907"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-30T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sensitivity+analysis&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sensitivity+analysis&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sensitivity+analysis&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sensitivity+analysis&offset=16", "hreflang": "en-US"}], "numberMatched": 16, "numberReturned": 16, "distributedFeatures": [], "timeStamp": "2026-05-26T09:10:42.864623Z"}