{"type": "FeatureCollection", "features": [{"id": "10.1016/j.agwat.2016.04.009", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:15:44Z", "type": "Journal Article", "created": "2016-04-27", "title": "Irrigation Regime Affected Soc Content Rather Than Plow Layer Thickness Of Rice Paddies: A County Level Survey From A River Basin In Lower Yangtze Valley, China", "description": "Abstract   While the impacts of farm management practices such as fertilization, tillage and straw return on soil organic carbon dynamics in croplands have been widely studied, the effects of irrigation management in irrigated rice paddies have not yet been widely assessed. Changes in plow layer thickness and soil organic carbon content of rice paddies were analyzed using data obtained in a county-level survey of soil fertility conducted in 2005 and 2006 in Guichi County, Anhui Province, China. Both soil thickness and organic carbon content of plow layer showed skewed normal distributions, with their averages of 14.58\u00a0\u00b1\u00a03.92\u00a0cm, and 16.45\u00a0\u00b1\u00a06.02\u00a0g/kg, respectively. The irrigation method was found to have significant influences on both plow layer thickness and soil organic carbon content, as the plow layer thickness and soil organic carbon content had an inverse response to the irrigation intensity derived from different irrigation methods. The land-level performance of irrigation/drainage infrastructure and the irrigation water sources were detected to have significant effect on plow layer thickness, but little influence on soil organic carbon content. While the capacity of irrigation/drainage infrastructure had a remarkable effect on soil organic carbon content but little impact on plow layer thickness. However, the irrigation condition for surveyed fields was detected to have little effect on both plow layer thickness and soil organic carbon content. These results indicated that irrigation management should keep the balance between surface erosion on plow layer thickness and soil organic carbon accumulation. Hence, developing new technique for good irrigation infrastructure and water management in future will help soil organic carbon accumulation as well as improve the soil for enhanced crop growth in rice agriculture.", "keywords": ["330", "QH301 Biology", "01 natural sciences", "QH301", "water management", "land-use", "sequential reduction processes", "P losses", "fields", "SDG 15 - Life on Land", "0105 earth and related environmental sciences", "2. Zero hunger", "Soil organic carbon", "04 agricultural and veterinary sciences", "Irrigation water source", "15. Life on land", "topsoil organic-carbon", "6. Clean water", "lowland rice", "Irrigation management", "13. Climate action", "soil colloidal suspensions", "0401 agriculture", " forestry", " and fisheries", "Rice paddy", "lake region", "stability behavior", "Soil thickness"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2016.04.009"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agricultural%20Water%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.agwat.2016.04.009", "name": "item", "description": "10.1016/j.agwat.2016.04.009", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2016.04.009"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-07-01T00:00:00Z"}}, {"id": "10.1016/j.envres.2019.108608", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:15Z", "type": "Journal Article", "created": "2019-07-26", "title": "Antibiotic resistance gene distribution in agricultural fields and crops. A soil-to-food analysis", "description": "Despite the social concern about the generalization of antibiotic resistance hotspots worldwide, very little is known about the contribution of different potential sources to the global risk. Here we present a quantitative analysis of the distribution of Antibiotic Resistance Genes (ARGs) in soil, rhizospheric soil, roots, leaves and beans in tomato, lettuce and broad beans crops (165 samples in total), grown in nine commercial plots distributed in four geographical zones in the vicinity of Barcelona (North East Spain). We also analyzed five soil samples from a nearby forest, with no record of agricultural activities. DNA samples were analyzed for their content in the ARGs sul1, tetM, qnrS1, blaCTX-M-32, blaOXA-58, mecA, and blaTEM, plus the integron intI1, using qPCR methods. In addition, soil microbiomes from the different plots were analyzed by amplicon-targeted 16S rRNA gene sequencing. Our data show a decreasing gradient of ARG loads from soil to fruits and beans, the latter showing only from 0.1 to 0.01% of the abundance values in soil. The type of crop was the main determinant for both ARG distribution and microbiome composition among the different plots, with minor contributions of geographic location and irrigation water source. We propose that soil amendment and/or fertilization, more than irrigation water, are the main drivers of ARG loads on the edible parts of the crop, and that they should therefore be specifically controlled.", "keywords": ["0301 basic medicine", "2. Zero hunger", "Microbiomes", "Agriculture", "Drug Resistance", " Microbial", "Irrigation water", "15. Life on land", "01 natural sciences", "6. Clean water", "Anti-Bacterial Agents", "3. Good health", "qPCR", "Soil", "03 medical and health sciences", "Antibiotic resistance genes", "Genes", " Bacterial", "Spain", "RNA", " Ribosomal", " 16S", "Rhizosphere", "Endophytes", "Food Analysis", "Soil Microbiology", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.envres.2019.108608"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.envres.2019.108608", "name": "item", "description": "10.1016/j.envres.2019.108608", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.envres.2019.108608"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-01T00:00:00Z"}}, {"id": "10.1016/j.jhazmat.2020.123424", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:43Z", "type": "Journal Article", "created": "2020-07-07", "title": "Occurrence and human health risk assessment of antibiotics and their metabolites in vegetables grown in field-scale agricultural systems", "description": "The occurrence of antibiotics (ABs) in four types of commercially grown vegetables (lettuce leaves, tomato fruits, cauliflower inflorescences, and broad bean seeds) was analyzed to assess the human exposure and health risks associated with different agronomical practices. Out of 16 targeted AB residues, seven ABs belonging to three groups (i.e., benzyl pyrimidines, fluoroquinolones, and sulfonamides) were above the method detection limit in vegetable samples ranging from 0.09 ng g-1 to 3.61 ng g-1 fresh weight. Data analysis (quantile regression models, principal component and hierarchical cluster analysis) showed manure application, irrigation with river water (indirect wastewater reuse), and vegetable type to be the most significant factors for AB occurrence in the targeted crops. Metabolites were detected in 70 of the 80 vegetable samples analyzed, and their occurrence was both plant- and compound-specific. In 73 % of the total samples, the concentration of AB metabolites was higher than the concentration of their parent compound. Finally, the potential human health risk estimated using the hazard quotient approach, based on the acceptable daily intake and the estimated daily intake, showed a negligible risk for human health from vegetable consumption. However, canonical-correspondence analysis showed that detected ABs explained 54 % of the total variation in AB resistance genes abundance in the vegetable samples. Thus, further studies are needed to assess the risks of antibiotic resistance promotion in vegetables and the significance of the occurrence of their metabolites.", "keywords": ["2. Zero hunger", "Agricultural Irrigation", "0211 other engineering and technologies", "02 engineering and technology", "Irrigation water", "Wastewater", "Commercial crops", "Risk Assessment", "01 natural sciences", "6. Clean water", "Anti-Bacterial Agents", "3. Good health", "Antibiotics", "Vegetables", "Metabolites", "Humans", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.1016/j.jhazmat.2020.123424"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Journal%20of%20Hazardous%20Materials", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.jhazmat.2020.123424", "name": "item", "description": "10.1016/j.jhazmat.2020.123424", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.jhazmat.2020.123424"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-01-01T00:00:00Z"}}, {"id": "10.1016/j.scitotenv.2018.10.268", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:16:55Z", "type": "Journal Article", "created": "2018-10-22", "title": "Antibiotic resistance genes distribution in microbiomes from the soil-plant-fruit continuum in commercial Lycopersicon esculentum fields under different agricultural practices", "description": "While the presence of antibiotic resistance genes (ARGs) in agricultural soils and products has been firmly established, their distribution among the different plant parts and the contribution of agricultural practices, including irrigation with reclaimed water, have not been adequately addressed yet. To this end, we analyzed the levels of seven ARGs (sul1, blaTEM, blaCTX-M-32, mecA, qnrS1, tetM, blaOXA-58), plus the integrase gene intl1, in soils, roots, leaves, and fruits from two commercial tomato fields irrigated with either unpolluted groundwater or from a channel impacted by treated wastewater, using culture-independent, quantitative real-time PCR methods. ARGs and intl1 sequences were found in leaves and fruits at levels representing from 1 to 10% of those found in roots or soil. The relative abundance of intl1 sequences correlated with tetM, blaTEM, and sul1 levels, suggesting a high horizontal mobility potential for these ARGs. High-throughput 16S rDNA sequencing revealed microbiome differences both between sample types (soil plus roots versus leaves plus fruits) and sampling zones, and a correlation between the prevalence of Pseudomonadaceae and the levels of different ARGs, particularly in fruits and leaves. We concluded that both microbiome composition and ARGs levels in plants parts, including fruits, were likely influenced by agricultural practices.", "keywords": ["0301 basic medicine", "2. Zero hunger", "0303 health sciences", "Antibiotic resistance", "Microbiota", "Microbiomes", "Agriculture", "Drug Resistance", " Microbial", "Horizontal gene transfer", "Irrigation water", "15. Life on land", "6. Clean water", "qPCR", "Soil", "03 medical and health sciences", "Solanum lycopersicum", "Genes", " Bacterial", "Fruit", "Soil Microbiology", "Environmental Monitoring"]}, "links": [{"href": "https://doi.org/10.1016/j.scitotenv.2018.10.268"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Science%20of%20The%20Total%20Environment", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.scitotenv.2018.10.268", "name": "item", "description": "10.1016/j.scitotenv.2018.10.268", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.scitotenv.2018.10.268"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-01T00:00:00Z"}}, {"id": "10.13031/trans.56.10215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:19:26Z", "type": "Journal Article", "created": "2013-11-20", "title": "Impact Of Water And Nitrogen Management Strategies On Maize Yield And Water Productivity Indices Under Linear-Move Sprinkler Irrigation", "description": "Abstract.    With uncertainty in future irrigation water availability and regulations on nutrient application amounts, experimentally determined effects of \u00e2\u20ac\u0153controllable\u00e2\u20ac\u009d management strategies such as nitrogen (N), water, and their combination on crop water productivity (CWP, also known as crop water use efficiency) and actual evapotranspiration (ET a ) are essential. The effects of various N application rates (0, 84, 140, 196, and 252 kg ha -1 ) under fully irrigated (FIT), limited irrigation (75% FIT), and rainfed conditions on maize (Zea mays L.) yield and various CWP indices were investigated in 2011 and 2012 growing seasons under linear-move sprinkler irrigation in south central Nebraska. CWP was presented as crop water use efficiency (CWUE), irrigation water use efficiency (IWUE), and evapotranspiration water use efficiency (ETWUE). The seasonal rainfall amounts in 2011 and 2012 were 371 mm and 296 mm, respectively, as compared with the long-term average of 469 mm. Two experimental seasons were contrasted with extreme warmer temperatures, greater solar radiation, and lower rainfall in 2012. Maximum grain yield of 12.68 metric tons ha -1  and 14.42 tons ha -1  was observed in 2011 and 2012, respectively, under the fully irrigated and 252 kg N ha -1  treatment. Grain yield was linearly related to ET a  and curvilinearly related to N and irrigation application amounts. Lower N treatments were more susceptible to interannual effects on the grain yield response to irrigation water amount. CWUE ranged from 1.52 kg m -3  (FIT and 84 kg N ha -1 ) to 2.58 kg m -3  (rainfed and 196 kg N ha -1 ) with an average of 2.15 kg m -3  in 2011, and from 1.49 kg m -3  (FIT and 0 kg N ha -1 ) to 2.72 kg m -3  (rainfed and 252 kg N ha -1 ) with an average of 2.33 kg m -3  in 2012. CWUE had a positive quadratic relationship with N application amount and decreased with both the presence and amount of irrigation at a given N application amount. The maximum IWUE for 75% FIT and FIT in 2011 was 1.80 kg m -3  (252 kg N ha -1 ) and 1.51 kg m -3  (252 kg N ha -1 ), respectively, whereas in 2012 the maximum IWUE values were 1.40 kg m -3  (196 kg N ha -1 ) and 1.78 kg m -3  (252 kg N ha -1 ), respectively. A curvilinear relationship was observed between IWUE and N application amount. An optimal N application amount of 196 kg ha -1  was identified for the pooled data to maximize the increase in grain yield above rainfed conditions per unit of applied irrigation water under limited irrigation management practices. In 2011, ETWUE ranged from 0.22 kg m -3  (140 kg N ha -1 ) to 1.46 kg m -3  (196 kg N ha -1 ) and from -0.21 kg m -3  (84 kg N ha -1 ) to 3.74 kg m -3  (252 kg N ha -1 ) for 75% FIT and FIT, respectively, whereas in 2012 ETWUE ranged from -0.07 kg m -3  (0 kg N ha -1 ) to 1.87 kg m -3  (252 kg N ha -1 ) and from -0.14 kg m -3  (0 kg N ha -1 ) to 3.65 kg m -3  (196 kg N ha -1 ) for 75% FIT and FIT, respectively. The results support that there is an optimal N level for each irrigation regime and, in general, lower N application amounts are required to reach maximum productivity (e.g., CWUE) under limited and rainfed conditions as compared with the FIT. In other words, there is an optimal N application amount to maximize the effectiveness of irrigation water on increasing grain yield above rainfed yields. The optimal N level for maximum productivity varied not only between the irrigation levels, but also exhibited interannual variability for the same irrigation level, indicating that these variables are impacted by the climatic conditions.", "keywords": ["Civil and Environmental Engineering", "2. Zero hunger", "0106 biological sciences", "Irrigation water use efficiency", "Environmental Engineering", "Evapotranspiration", "Bioresource and Agricultural Engineering", "Limited irrigation", "Nitrogen", "Crop water use efficiency", "Other Civil and Environmental Engineering", "04 agricultural and veterinary sciences", "15. Life on land", "551", "01 natural sciences", "630", "6. Clean water", "Maize", "Engineering", "0401 agriculture", " forestry", " and fisheries", "Evapotranspiration water use efficiency", "Crop water productivity"], "contacts": [{"organization": "Rudnick, Daran, Irmak, Suat,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.13031/trans.56.10215"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Transactions%20of%20the%20ASABE", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.13031/trans.56.10215", "name": "item", "description": "10.13031/trans.56.10215", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.13031/trans.56.10215"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-11-18T00:00:00Z"}}, {"id": "10.3390/agriculture9040079", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:20:53Z", "type": "Journal Article", "created": "2019-04-22", "title": "Deficit Drip Irrigation in Processing of Tomato Production in the Mediterranean Basin: A Data Analysis for Italy", "description": "<p>In this study, the effects of deficit irrigation (DI) on crop yields and irrigation water utilization efficiency (IWUE) of processing tomato are contrasting. This study aimed at analyzing a set of field experiments with drip irrigation available for Mediterranean Italy in terms of marketable yields and IWUE under DI. Both yields and IWUE were compared with the control treatment under full irrigation, receiving the maximum water restoration (MWR) in each experiment. The study also aimed at testing the effect of climate (aridity index) and soil parameters (texture). Main results indicated that yields would marginally decrease at 70\uffe2\uff80\uff9380% of MWR and variable irrigation regimes during the crop cycle resulted in higher crop yields. However, results were quite variable and site-dependent. In fact, DI proved more effective in fine textured soils and semiarid climates. We recommend that further research should address variable irrigation regimes and soil and climate conditions that proved more unfavorable in terms of crop response to DI.</p>", "keywords": ["2. Zero hunger", "0106 biological sciences", "deficit irrigation", "Agriculture (General)", "tomato fruit yield", "04 agricultural and veterinary sciences", "15. Life on land", "irrigation water use eciency", "01 natural sciences", "6. Clean water", "S1-972", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "irrigation water use efficiency", "Mediterranean region"]}, "links": [{"href": "http://www.mdpi.com/2077-0472/9/4/79/pdf"}, {"href": "https://www.mdpi.com/2077-0472/9/4/79/pdf"}, {"href": "https://doi.org/10.3390/agriculture9040079"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Agriculture", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/agriculture9040079", "name": "item", "description": "10.3390/agriculture9040079", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/agriculture9040079"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-04-19T00:00:00Z"}}, {"id": "10.3390/w11091918", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:21:13Z", "type": "Journal Article", "created": "2019-09-16", "title": "Modeling Sugar Beet Responses to Irrigation with AquaCrop for Optimizing Water Allocation", "description": "<p>Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past published calibrations, together with important modifications in the program, deemed it necessary to conduct a study aimed at the calibration of AquaCrop (version 6.1) using the results of a single deficit irrigation experiment. The model was validated with additional data from eight farms differing in location, years, varieties, sowing dates, and irrigation. The overall performance of AquaCrop for simulating canopy cover, biomass, and final yield was accurate (RMSE = 11.39%, 2.10 t ha\uffe2\uff88\uff921, and 0.85 t ha\uffe2\uff88\uff921, respectively). Once the model was properly calibrated and validated, a scenario analysis was carried out to assess the crop response in terms of yield and water productivity to different irrigation water allocations in the two main production areas of sugar beet in Spain (spring and autumn sowing). The results highlighted the potential of the model by showing the important impact of irrigation water allocation and sowing time on sugar beet production and its irrigation water productivity.</p>", "keywords": ["2. Zero hunger", "Water productivity", "Sugar beet", "sugar beet", "04 agricultural and veterinary sciences", "15. Life on land", "calibration", "irrigation water allocation", "Modelling", "AquaCrop", "6. Clean water", "Irrigation water allocation", "modelling", "Calibration", "water productivity", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://doi.org/10.3390/w11091918"}, {"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/w11091918", "name": "item", "description": "10.3390/w11091918", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w11091918"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-14T00:00:00Z"}}, {"id": "2972466247", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:26:06Z", "type": "Journal Article", "created": "2019-09-16", "title": "Modeling Sugar Beet Responses to Irrigation with AquaCrop for Optimizing Water Allocation", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past published calibrations, together with important modifications in the program, deemed it necessary to conduct a study aimed at the calibration of AquaCrop (version 6.1) using the results of a single deficit irrigation experiment. The model was validated with additional data from eight farms differing in location, years, varieties, sowing dates, and irrigation. The overall performance of AquaCrop for simulating canopy cover, biomass, and final yield was accurate (RMSE = 11.39%, 2.10 t ha\u22121, and 0.85 t ha\u22121, respectively). Once the model was properly calibrated and validated, a scenario analysis was carried out to assess the crop response in terms of yield and water productivity to different irrigation water allocations in the two main production areas of sugar beet in Spain (spring and autumn sowing). The results highlighted the potential of the model by showing the important impact of irrigation water allocation and sowing time on sugar beet production and its irrigation water productivity.</p></article>", "keywords": ["2. Zero hunger", "Water productivity", "Sugar beet", "sugar beet", "04 agricultural and veterinary sciences", "15. Life on land", "calibration", "irrigation water allocation", "Modelling", "AquaCrop", "6. Clean water", "Irrigation water allocation", "modelling", "Calibration", "water productivity", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://doi.org/2972466247"}, {"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": "2972466247", "name": "item", "description": "2972466247", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2972466247"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-14T00:00:00Z"}}, {"id": "10261/205841", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:39Z", "type": "Journal Article", "created": "2019-09-16", "title": "Modeling Sugar Beet Responses to Irrigation with AquaCrop for Optimizing Water Allocation", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past published calibrations, together with important modifications in the program, deemed it necessary to conduct a study aimed at the calibration of AquaCrop (version 6.1) using the results of a single deficit irrigation experiment. The model was validated with additional data from eight farms differing in location, years, varieties, sowing dates, and irrigation. The overall performance of AquaCrop for simulating canopy cover, biomass, and final yield was accurate (RMSE = 11.39%, 2.10 t ha\u22121, and 0.85 t ha\u22121, respectively). Once the model was properly calibrated and validated, a scenario analysis was carried out to assess the crop response in terms of yield and water productivity to different irrigation water allocations in the two main production areas of sugar beet in Spain (spring and autumn sowing). The results highlighted the potential of the model by showing the important impact of irrigation water allocation and sowing time on sugar beet production and its irrigation water productivity.</p></article>", "keywords": ["2. Zero hunger", "Water productivity", "Sugar beet", "sugar beet", "04 agricultural and veterinary sciences", "15. Life on land", "calibration", "irrigation water allocation", "Modelling", "AquaCrop", "6. Clean water", "Irrigation water allocation", "modelling", "Calibration", "water productivity", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://doi.org/10261/205841"}, {"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": "10261/205841", "name": "item", "description": "10261/205841", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/205841"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-14T00:00:00Z"}}, {"id": "10261/399158", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:46Z", "type": "Journal Article", "created": "2024-12-17", "title": "Plastic input and dynamics in industrial composting", "description": "Green and biowaste, processed within large facilities into compost, is a key fertilizer for agricultural and horticultural soils. However, due to improper waste disposal of plastic, its residues often remain or even lead to the formation ofmicroplastics (1\u00a0\u00b5m - 5\u00a0mm, MiPs) in the final compost product. To better understand the processes, we first quantified 'macroplastics' (> 20\u00a0mm, MaPs) input via biowaste collection into an industrial composting plant, and, then determined MiP concentrations at five stages during the composting process (before and after shredding and screening processes), and in the water used for irrigation. The total concentrations of MaPs in the biowaste collected from four different German districts ranged from 0.36 to 1.95\u00a0kg ton-1 biowaste, with polyethylene (PE) and polypropylene (PP) representing the most abundant types. The 'non-foil' and 'foil' plastics occurred in similar amounts (0.51\u00a0\u00b1\u00a00.1\u00a0kg ton-1 biowaste), with an average load of 0.08\u00a0\u00b1\u00a00.01 items kg-1 and 0.05\u00a0\u00b1\u00a00.01 items kg-1, respectively. Only 0.3\u00a0\u00b1\u00a00.1\u00a0kg MaP t-1 biowaste was biodegradable plastic. Compost treatment by shredding tripled the total number of MaPs and MiPs to 33 items kg-1, indicating an enrichment of particles during the process and potential fragmentation. Noticeably, a substantial amount of small MiPs (up to 22,714\u00a0\u00b1\u00a02,975 particles L-1) were found in the rainwater used for compost moistening, being thus an additional, generally overlooked plastic source for compost. Our results highlight that reducing plastic input via biowaste is key for minimizing MiP contamination of compost.", "keywords": ["ddc:550", "Composting", "Industrial Waste", "600", "Biowaste", "Irrigation water", "Microplastic pollution", "620", "Refuse Disposal", "Soil", "Waste Management", "Fragmentation", "Germany", "Life Science", "Fertilizers", "Plastics"]}, "links": [{"href": "https://doi.org/10261/399158"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Waste%20Management", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/399158", "name": "item", "description": "10261/399158", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/399158"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2025-02-01T00:00:00Z"}}, {"id": "10396/18990", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-25T16:24:48Z", "type": "Journal Article", "created": "2019-09-16", "title": "Modeling Sugar Beet Responses to Irrigation with AquaCrop for Optimizing Water Allocation", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Process-based crop models such as AquaCrop are useful for a variety of applications but must be accurately calibrated and validated. Sugar beet is an important crop that is grown in regions under water scarcity. The discrepancies and uncertainty in past published calibrations, together with important modifications in the program, deemed it necessary to conduct a study aimed at the calibration of AquaCrop (version 6.1) using the results of a single deficit irrigation experiment. The model was validated with additional data from eight farms differing in location, years, varieties, sowing dates, and irrigation. The overall performance of AquaCrop for simulating canopy cover, biomass, and final yield was accurate (RMSE = 11.39%, 2.10 t ha\u22121, and 0.85 t ha\u22121, respectively). Once the model was properly calibrated and validated, a scenario analysis was carried out to assess the crop response in terms of yield and water productivity to different irrigation water allocations in the two main production areas of sugar beet in Spain (spring and autumn sowing). The results highlighted the potential of the model by showing the important impact of irrigation water allocation and sowing time on sugar beet production and its irrigation water productivity.</p></article>", "keywords": ["2. Zero hunger", "Water productivity", "Sugar beet", "sugar beet", "04 agricultural and veterinary sciences", "15. Life on land", "calibration", "irrigation water allocation", "Modelling", "AquaCrop", "6. Clean water", "Irrigation water allocation", "modelling", "Calibration", "water productivity", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://www.mdpi.com/2073-4441/11/9/1918/pdf"}, {"href": "https://doi.org/10396/18990"}, {"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": "10396/18990", "name": "item", "description": "10396/18990", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10396/18990"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-09-14T00:00:00Z"}}, {"id": "c26de669-90f9-43a1-ae4d-6b1b9660f5e0", "type": "Feature", "geometry": {"type": "Polygon", "coordinates": [[[-180.0, -90.0], [-180.0, 90.0], [180.0, 90.0], [180.0, -90.0], [-180.0, -90.0]]]}, "properties": {"themes": [{"concepts": [{"id": "boundaries"}], "scheme": "https://standards.iso.org/iso/19139/resources/gmxCodelists.xml#MD_TopicCategoryCode"}], "updated": "2022-01-26T10:48:26", "language": "eng", "title": "GlobWat: a global water balance model to assess water use in irrigated agriculture", "description": "GlobWat uses spatially distributed input layers consisting of monthly precipitation, number of wet days per month, coefficient of variation of precipitation, monthly reference evapotranspiration, maximum soil moisture storage capacity, maximum percolation flux, irrigated areas, land use, and areas of open water and wetlands. All these input layers are based on freely available spatial dataset with a resolution of 10 arc minutes for the climate dataset and 5 arc minutes for all the terrain and land dataset (data sources are provided in the downloadable files).\nThe water balance is calculated in two steps. First a vertical water balance is calculated that includes rainfall dependent evapotranspiration and evapotranspiration from crops under irrigated circumstances (for which it is assumed that it can be provided by surface water or groundwater). In a second stage, a horizontal water balance is calculated to correct for incremental evapotranspiration from open water and wetlands and to calculate discharges from river (sub-) basins taking into consideration the water needed for irrigation.", "formats": [{"name": "TIFF"}, {"name": "WWW:DOWNLOAD-1.0-http--download"}, {"name": "OGC:WMS-1.1.1-http-get-map"}, {"name": "WWW:LINK-1.0-http--related"}], "keywords": ["irrigation water use", "hydrology", "climate", "AQUAMAPS_analyses", "Tag_AQUASTAT", "World"], "contacts": [{"name": "Jippe Hoogeveen", "organization": "FAO-UN Land and Water Division", "position": "Water Resources Officer", "roles": ["author"], "phones": [{"value": null}], "emails": [{"value": "Jippe.Hoogeveen@fao.org"}], "addresses": [{"deliveryPoint": ["Viale delle Terme di Caracalla"], "city": "Rome", "administrativeArea": null, "postalCode": "00153", "country": "Italy"}], "links": [{"href": null}]}, {"organization": "FAO-UN Land and Water Division", "roles": ["contributor"]}]}, "links": [{"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP1_prec.zip", "description": "GlobWat input files, part 1: monthly precipitation (10.6 MB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP2_eto.zip", "description": "GlobWat input files, part 2: monthly reference evapotranspiration (8.6 MB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP3_raind.zip", "description": "GlobWat input files, part 3: rain days per month (3.7 MB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP4_cov.zip", "description": "GlobWat input files, part 4: monthly coefficient of variation of precipitation (11.4 MB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP5-soilp.zip", "description": "GlobWat input files, part 5: soil related parameters (soil moisture, percolation flux, rooting depth and calibration factors, 2 MB).", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-InputP6-misc.zip", "description": "GlobWat input files, part 6: land use, irrigation areas, administrative areas and basins codes (5 MB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/Filenames-keys.xls", "description": "List of input and output files (36 KB)", "protocol": "WWW:DOWNLOAD-1.0-http--download", "rel": null}, {"href": "https://data.apps.fao.org/map/gsrv/gsrv1/aquamaps/wms", "name": "etoyr_7416", "description": "example of GlobWat input: reference ET", "protocol": "OGC:WMS-1.1.1-http-get-map", "rel": null}, {"href": "https://storage.googleapis.com/fao-maps-catalog-data/geonetwork/aquamaps/GlobWat-1.0codes-docGN.zip", "description": "GlobWat v 1.0 executable and Fortran codes (1.3 MB). 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