{"type": "FeatureCollection", "features": [{"id": "10.1007/s11356-019-06540-w", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:14:58Z", "type": "Journal Article", "created": "2019-10-23", "title": "Evaluating the performance of SALTMED model under alternate irrigation using saline and fresh water strategies to winter wheat in the North China Plain", "description": "The effective water management in the North China Plain (NCP) needs a tool to predict winter wheat production due to water quality. A large quantity of brackish water is stored underground in this region, and whether this water can be used properly in agriculture is becoming a crucial issue that is about to be resolved. The SALTMED model is a generic modeling tool for efficient irrigation management strategies, especially for cyclic use of saline and fresh water as well as different water qualities, and it still needs further investigation for alternate irrigation using saline and fresh water at different growth stages of winter wheat. Therefore, the aim of this investigation was to evaluate the performance of SALTMED model and simulate the production of winter wheat grown under different irrigation strategies. Irrigation strategies comprised rain-fed cultivation (NI), fresh and saline water irrigation (FS), saline and fresh water irrigation (SF), saline water irrigation (SS), and fresh water irrigation (FF). Three-year observed data were used for the validations of SALTMED model. The values of evaluation indices of relative error, RMSE, NRMSE, index of agreement (D-index), and R2 between simulated and observed grain yield were 6.8%, 0.8, 10.7, 0.9, and 0.9, respectively. The model results supported and matched the observed data and indicated similar differences among the irrigated and rain-fed treatments. It is concluded that the SALTMED model is able to predict grain yield of winter wheat and its productivity under the alternate irrigation using saline and fresh water and their interaction in the climate condition of the NCP", "keywords": ["0106 biological sciences", "2. Zero hunger", "China", "Agricultural Irrigation", "Fresh water", "Water productivity", "Rain", "Water", "Agriculture", "Fresh Water", "15. Life on land", "01 natural sciences", "6. Clean water", "Winter wheat", "Model - Saline water", "Biomass", "Seasons", "Grain yield", "Edible Grain", "Triticum"]}, "links": [{"href": "https://doi.org/10.1007/s11356-019-06540-w"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s11356-019-06540-w", "name": "item", "description": "10.1007/s11356-019-06540-w", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s11356-019-06540-w"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-23T00:00:00Z"}}, {"id": "10.1016/j.agwat.2010.07.007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:15:14Z", "type": "Journal Article", "created": "2010-08-10", "title": "Effects Of Irrigation Strategies And Soils On Field Grown Potatoes: Yield And Water Productivity", "description": "Abstract   Yield and water productivity of potatoes grown in 4.32\u00a0m2 lysimeters were measured in coarse sand, loamy sand, and sandy loam and imposed to full (FI), deficit (DI), and partial root-zone drying (PRD) irrigation strategies. PRD and DI as water-saving irrigation treatments received 65% of FI after tuber bulking and lasted for 6 weeks until final harvest. Analysis across the soil textures showed that fresh yields were not significant between the irrigation treatments. However, the same analysis across the irrigation treatments revealed that the effect of soil texture was significant on the fresh yield and loamy sand produced significantly higher fresh yield than the other two soils, probably because of higher leaf area index, higher photosynthesis rates, and \u201cstay-green\u201d effect late in the growing season. More analysis showed that there was a significant interaction between the irrigation treatments and soil textures that the highest fresh yield was obtained under FI in loamy sand. Furthermore, analysis across the soil textures showed that water productivities, WP (kg\u00a0ha\u22121 fresh tuber yield\u00a0mm\u22121 ET) were not significantly different between the irrigation treatments. However, across the irrigation treatments, the soil textures were significantly different. This showed that the interaction between irrigation treatments and soil textures was significant that the highest significant WP was obtained under DI in sandy loam. While PRD and DI treatments increased WP by, respectively, 11 and 5% in coarse sand and 28 and 36% in sandy loam relative to FI, they decreased WP in loamy sand by 15 and 13%. The reduced WP in loamy sand was due to nearly 28% fresh tuber yield loss in PRD and DI relative to FI even though ET was reduced by 9 and 11% in these irrigation treatments. This study showed that different soils will affect water-saving irrigation strategies that are worth knowing for suitable agricultural water management. So, under non-limited water resources conditions, loamy sand produces the highest yield under full irrigation but water-saving irrigations (PRD and DI) are not recommended due to considerable loss (28%) in yield. However, under restricted water resources, it is recommended to apply water-saving irrigations in sandy loam and coarse sand to achieve the highest water productivity.", "keywords": ["0106 biological sciences", "2. Zero hunger", "BRIC", "Potato tuber yield", "Water productivity", "04 agricultural and veterinary sciences", "15. Life on land", "01 natural sciences", "/dk/atira/pure/core/keywords/Bric", "Full irrigation", "6. Clean water", "Soild tectures", "0401 agriculture", " forestry", " and fisheries", "Partial root-zone drying irrigation", "Deficit irrigation"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2010.07.007"}, {"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.2010.07.007", "name": "item", "description": "10.1016/j.agwat.2010.07.007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2010.07.007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2010-11-01T00:00:00Z"}}, {"id": "10.1016/j.agwat.2020.106585", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:15:15Z", "type": "Journal Article", "created": "2020-10-18", "title": "Parameterization of the AquaCrop model for simulating table grapes growth and water productivity in an arid region of Mexico.", "description": "Abstract   Currently, the AquaCrop model has been widely tested for many fruit/grain crops; root and tuber crops; leafy vegetables, or forage crops, but is restricted to annual herbaceous species, while deciduous crops have received less if no attention. In this context, this study aims to test for the first time the ability of the AquaCrop model to simulate canopy cover (CC), actual evapotranspiration (ETa), total soil water content (TWC), biomass (B) and fruit yield (FY) of table grapes vineyards (Vitis vinifera L., cvs. Perlette and Superior) at the Costa de Hermosillo, Sonora in Northwest Mexico. Observed weather and soil physical parameters, with measured crop parameters from an experiment conducted during 2005 were used to develop climate, soil and crop input files for AquaCrop and for calibrating the model. While collected data during the 2006 growing season were used to validate the model.\u00a0The model adequately simulated CC, ETa and TWC during 2005 and 2006. The Root Mean Square Error (RMSE) between observed and measured CC, ETa and TWC were 5.18%, 0.46\u00a0mm/day and 10.11\u00a0mm during 2005, and 8.82%, 0.84\u00a0mm/day and 9.1\u00a0mm during 2006, respectively. The good accuracy of simulations of CC, ETa and TWC by the model have been confirmed by additional statistical parameters like the coefficient of determination (R2), The Mean Bias Error (MBE), the Willmott\u2019s index of agreement (d) and the Nash\u2013Sutcliffe Efficiency (NSE).  For the B and FY simulations, the results showed that the model correctly reproduced the B and FY with NRMSE value of 8.8%. The estimated average value of FY (14.56\u00a0t/ha) for both seasons are in the range of the potential yield (14\u201318\u00a0t/ha) of table grapes in the irrigated Costa de Hermosillo in northwest Mexico.  After the validation of the AquaCrop model, it was used to evaluate the irrigation scheduling by the farmer as well as to assess the water productivity computed as the ratio of crop production to crop water use. The results showed that, the recommended irrigation by the model was about 547\u00a0mm and 509\u00a0mm, which it is about half of that applied by the farmer (1006\u00a0mm and 929\u00a0mm) during 2005 and 2006, respectively. This large difference, which represents approximately 54% and 57% of the irrigation supply, is lost through deep percolation and could be saved without vegetation suffering from water stress while maintaining the same yield. The high loss of water by percolation affects significantly the water productivity (WP), which decreases from 3.22 to 1.74\u00a0kg/m3 if we consider the transpiration (WPTr), and the sum of ETa and Percolation (WPETa+Pr) for WP computations, respectively. Consequently, the AquaCrop model can be used as an operational tool by decision makers and growers to improve irrigation management. This is of crucial importance in arid and semi-arid regions where water is becoming increasingly scarce.", "keywords": ["0106 biological sciences", "2. Zero hunger", "550", "Evapotranspiration", "Water productivity", "[SPI] Engineering Sciences [physics]", "Percolation", "04 agricultural and veterinary sciences", "15. Life on land", "Tablegrapes (Vitisvinifera L. cvs. Perletteand Superior)", "01 natural sciences", "630", "Irrigation scheduling", "AquaCrop", "[SPI]Engineering Sciences [physics]", "Vitisvinifera L cvs Perletteand Superior", "0401 agriculture", " forestry", " and fisheries", "Tablegrapes"]}, "links": [{"href": "https://doi.org/10.1016/j.agwat.2020.106585"}, {"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.2020.106585", "name": "item", "description": "10.1016/j.agwat.2020.106585", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.agwat.2020.106585"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-02-01T00:00:00Z"}}, {"id": "10.13031/2013.41521", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:18:11Z", "type": "Journal Article", "created": "2013-10-22", "title": "Large-Scale On-Farm Implementation Of Soil Moisture-Based Irrigation Management Strategies For Increasing Maize Water Productivity", "description": "Irrigated maize is produced on about 3.5 Mha in the U.S. Great Plains and western Corn Belt. Most irrigation water comes from groundwater. Persistent drought and increased competition for water resources threaten long-term viability of groundwater resources, which motivated our research to develop strategies to increase water productivity without noticeable reduction in maize yield. Results from previous research at the University of Nebraska-Lincoln (UNL) experiment stations in 2005 and 2006 found that it was possible to substantially reduce irrigation amounts and increase irrigation water use efficiency (IWUE) and crop water use efficiency (CWUE) (or crop water productivity) with little or no reduction in yield using an irrigation regime that applies less water during growth stages that are less sensitive to water stress. Our hypothesis was that a soil moisture-based irrigation management approach in research fields would give similar results in large production-scale, center-pivot irrigated fields in Nebraska. To test this hypothesis, IWUE, CWUE, and grain yields were compared in extensive on-farm research located at eight locations over two years (16 site-years), representing more than 600 ha of irrigated maize area. In each site-year, two contiguous center-pivot irrigated maize fields with similar topography, soil properties, and crop management practices received different irrigation regimes: one was managed by UNL researchers, and the other was managed by the farmer at each site. Irrigation management in farmer-managed fields relied on the farmers\u2019 traditional visual observations and personal expertise, whereas irrigation timing in the UNL-managed fields was based on pre-determined soil water depletion thresholds measured using soil moisture sensors, as well as crop phenology predicted by a crop simulation model using a combination of real-time (in-season) and historical weather data. The soil moisture-based irrigation regime resulted in greater soil water depletion, which decreased irrigation requirements and enabled more timely irrigation management in the UNL-managed fields in both years (34% and 32% less irrigation application compared with farmer-managed fields in 2007 and 2008, respectively). The average actual crop evapotranspiration (ETC) for the UNL- and farmer-managed fields for all sites in 2007 was 487 and 504 mm, respectively. In 2008, the average UNL and average farmer-managed field had seasonal ETC of 511 and 548 mm, respectively. Thus, when the average of all sites is considered, the UNL-managed fields had 3% and 7% less ETC than the farmer-managed fields in 2007 and 2008, respectively, although the percentage was much higher for some of the farmer-managed fields. In both years, differences in grain yield between the UNL and farmer-managed fields were not statistically significant (p = 0.75). On-farm implementation of irrigation management strategies resulted in a 38% and 30% increase in IWUE in the UNL-managed fields in 2007 and 2008, respectively. On average, the CWUE value for the UNL-managed fields was 4% higher than those in the farmer-managed fields in both years. Reduction in irrigation water withdrawal in UNL-managed fields resulted in $32.00 to $74.10 ha-1 in 2007 and $44.46 to $66.50 ha-1 in 2008 in energy saving and additional net return to the farm income. The results from this study can have significant positive implications in future irrigation management of irrigated maize systems in regions with similar soil and crop management practices.", "keywords": ["Civil and Environmental Engineering", "0106 biological sciences", "571", "Environmental Engineering", "550", "Other Civil and Environmental Engineering", "2204 Biomedical Engineering", "1107 Forestry", "01 natural sciences", "630", "Engineering", "1102 Agronomy and Crop Science", "1106 Food Science", "1111 Soil Science", "2. Zero hunger", "Evapotranspiration", "Bioresource and Agricultural Engineering", "Water productivity", "Water use efficiency", "04 agricultural and veterinary sciences", "15. Life on land", "6. Clean water", "Maize", "Irrigation management", "0401 agriculture", " forestry", " and fisheries", "Soil moisture"], "contacts": [{"organization": "Irmak, S., Burgert, M. J., Yang, H. S., Cassman, K. G., Walters, D. T., Rathje, W. R., Payero, J. O., Grassini, P., Kuzila, M. S., Brunkhorst, K. J., Eisenhauer, D. E., Kranz, W. L., VanDeWalle, B., Rees, J. M., Zoubek, G. L., Shapiro, C. A., Teichmeier, G. J.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.13031/2013.41521"}, {"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": "10.13031/2013.41521", "name": "item", "description": "10.13031/2013.41521", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.13031/2013.41521"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2012-01-01T00:00:00Z"}}, {"id": "10.13031/trans.56.10215", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:18:12Z", "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": "10.3389/fpls.2021.608967", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:17Z", "type": "Journal Article", "created": "2021-03-10", "title": "Remote Sensing Energy Balance Model for the Assessment of Crop Evapotranspiration and Water Status in an Almond Rootstock Collection", "description": "<p>One of the objectives of many studies conducted by breeding programs is to characterize and select rootstocks well-adapted to drought conditions. In recent years, field high-throughput phenotyping methods have been developed to characterize plant traits and to identify the most water use efficient varieties and rootstocks. However, none of these studies have been able to quantify the behavior of crop evapotranspiration in almond rootstocks under different water regimes. In this study, remote sensing phenotyping methods were used to assess the evapotranspiration of almond cv. \uffe2\uff80\uff9cMarinada\uffe2\uff80\uff9d grafted onto a rootstock collection. In particular, the two-source energy balance and Shuttleworth and Wallace models were used to, respectively, estimate the actual and potential evapotranspiration of almonds grafted onto 10 rootstock under three different irrigation treatments. For this purpose, three flights were conducted during the 2018 and 2019 growing seasons with an aircraft equipped with a thermal and multispectral camera. Stem water potential (\uffce\uffa8stem) was also measured concomitant to image acquisition. Biophysical traits of the vegetation were firstly assessed through photogrammetry techniques, spectral vegetation indices and the radiative transfer model PROSAIL. The estimates of canopy height, leaf area index and daily fraction of intercepted radiation had root mean square errors of 0.57 m, 0.24 m m\uffe2\uff80\uff931 and 0.07%, respectively. Findings of this study showed significant differences between rootstocks in all of the evaluated parameters. Cadaman\uffc2\uffae and Garnem\uffc2\uffae had the highest canopy vigor traits, evapotranspiration, \uffce\uffa8stem and kernel yield. In contrast, Rootpac\uffc2\uffae 20 and Rootpac\uffc2\uffae R had the lowest values of the same parameters, suggesting that this was due to an incompatibility between plum-almond species or to a lower water absorption capability of the rooting system. Among the rootstocks with medium canopy vigor, Adesoto and IRTA 1 had a lower evapotranspiration than Rootpac\uffc2\uffae 40 and Ishtara\uffc2\uffae. Water productivity (WP) (kg kernel/mm water evapotranspired) tended to decrease with \uffce\uffa8stem, mainly in 2018. Cadaman\uffc2\uffae and Garnem\uffc2\uffae had the highest WP, followed by INRA GF-677, IRTA 1, IRTA 2, and Rootpac\uffc2\uffae 40. Despite the low \uffce\uffa8stem of Rootpac\uffc2\uffae R, the WP of this rootstock was also high.</p>", "keywords": ["stem water potential", "2. Zero hunger", "Plant culture", "field phenotyping", "633", "Plant Science", "04 agricultural and veterinary sciences", "15. Life on land", "TSEB model", "6. Clean water", "thermal", "SB1-1110", "631", "crown area", "water productivity", "0401 agriculture", " forestry", " and fisheries"]}, "links": [{"href": "https://doi.org/10.3389/fpls.2021.608967"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Plant%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/fpls.2021.608967", "name": "item", "description": "10.3389/fpls.2021.608967", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/fpls.2021.608967"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-03-10T00:00:00Z"}}, {"id": "10.3390/w11091918", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:19:33Z", "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": "10261/277923", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:04Z", "type": "Journal Article", "created": "2022-07-18", "title": "Net irrigation requirement under different climate scenarios using AquaCrop over Europe", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.</p></article>", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. 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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": "10396/18990", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:08Z", "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": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:38Z", "type": "Journal Article", "created": "2022-07-18", "title": "Net irrigation requirement under different climate scenarios using AquaCrop over Europe", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Global soil water availability is challenged by the effects of climate change and a growing population. On average, 70\u2009% of freshwater extraction is attributed to agriculture, and the demand is increasing. In this study, the effects of climate change on the evolution of the irrigation water requirement to sustain current crop productivity are assessed by using the Food and Agriculture Organization (FAO) crop growth model AquaCrop version 6.1. The model is run at 0.5\u2218lat\u00d70.5\u2218long resolution over the European mainland, assuming a general C3-type of crop, and forced by climate input data from the Inter-Sectoral Impact Model Intercomparison Project phase three (ISIMIP3). First, the AquaCrop surface soil moisture (SSM) forced with two types of ISIMIP3 historical meteorological datasets is evaluated with satellite-based SSM estimates in two ways. When driven by ISIMIP3a reanalysis meteorology, daily simulated SSM values have an unbiased root mean square difference of 0.08 and 0.06\u2009m3\u2009m\u22123, with SSM retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, respectively, for the years 2015\u20132016 (2016 is the end year of the reanalysis data). When forced with ISIMIP3b meteorology from five global climate models (GCMs) for the years 2015\u20132020, the historical simulated SSM climatology closely agrees with the satellite-based SSM climatologies. Second, the evaluated AquaCrop model is run to quantify the future irrigation requirement, for an ensemble of five GCMs and three different emission scenarios. The simulated net irrigation requirement (Inet) of the three summer months for a near and far future climate period (2031\u20132060 and 2071\u20132100) is compared to the baseline period of 1985\u20132014 to assess changes in the mean and interannual variability of the irrigation demand. Averaged over the continent and the model ensemble, the far future Inet is expected to increase by 22\u2009mm per month (+30\u2009%) under a high-emission scenario Shared Socioeconomic Pathway (SSP) 3\u20137.0. Central and southern Europe are the most impacted, with larger Inet increases. The interannual variability in Inet is likely to increase in northern and central Europe, whereas the variability is expected to decrease in southern regions. Under a high mitigation scenario (SSP1\u20132.6), the increase in Inet will stabilize at around 13\u2009mm per month towards the end of the century, and interannual variability will still increase but to a smaller extent. The results emphasize a large uncertainty in the Inet projected by various GCMs.                     </p></article>", "keywords": ["IMPACTS", "LAND", "Technology", "Environmental Engineering", "AGRICULTURE", "DEFICIT IRRIGATION", "SIMULATE YIELD RESPONSE", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "CROP WATER PRODUCTIVITY", "Environmental technology. Sanitary engineering", "01 natural sciences", "0905 Civil Engineering", "G", "DATA ASSIMILATION", "Geography. Anthropology. Recreation", "GE1-350", "Geosciences", " Multidisciplinary", "TD1-1066", "0105 earth and related environmental sciences", "2. Zero hunger", "Science & Technology", "3707 Hydrology", "T", "Geology", "15. Life on land", "TRENDS", "6. Clean water", "MODEL", "Environmental sciences", "0907 Environmental Engineering", "13. Climate action", "Physical Sciences", "Water Resources", "4013 Geomatic engineering", "0406 Physical Geography and Environmental Geoscience", "3709 Physical geography and environmental geoscience"]}, "links": [{"href": "https://hess.copernicus.org/articles/26/3731/2022/hess-26-3731-2022.pdf"}, {"href": "https://doi.org/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Hydrology%20and%20Earth%20System%20Sciences", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "name": "item", "description": "20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/20.500.14017/81a6df94-d40c-4db1-86dc-539a3cb8aaf8"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-01-12T00:00:00Z"}}, {"id": "2972466247", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:58Z", "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": "2981757634", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:22:59Z", "type": "Journal Article", "created": "2019-10-23", "title": "Evaluating the performance of SALTMED model under alternate irrigation using saline and fresh water strategies to winter wheat in the North China Plain", "description": "The effective water management in the North China Plain (NCP) needs a tool to predict winter wheat production due to water quality. A large quantity of brackish water is stored underground in this region, and whether this water can be used properly in agriculture is becoming a crucial issue that is about to be resolved. The SALTMED model is a generic modeling tool for efficient irrigation management strategies, especially for cyclic use of saline and fresh water as well as different water qualities, and it still needs further investigation for alternate irrigation using saline and fresh water at different growth stages of winter wheat. Therefore, the aim of this investigation was to evaluate the performance of SALTMED model and simulate the production of winter wheat grown under different irrigation strategies. Irrigation strategies comprised rain-fed cultivation (NI), fresh and saline water irrigation (FS), saline and fresh water irrigation (SF), saline water irrigation (SS), and fresh water irrigation (FF). Three-year observed data were used for the validations of SALTMED model. The values of evaluation indices of relative error, RMSE, NRMSE, index of agreement (D-index), and R2 between simulated and observed grain yield were 6.8%, 0.8, 10.7, 0.9, and 0.9, respectively. The model results supported and matched the observed data and indicated similar differences among the irrigated and rain-fed treatments. It is concluded that the SALTMED model is able to predict grain yield of winter wheat and its productivity under the alternate irrigation using saline and fresh water and their interaction in the climate condition of the NCP", "keywords": ["2. Zero hunger", "0106 biological sciences", "China", "Agricultural Irrigation", "Fresh water", "Water productivity", "Rain", "Water", "Agriculture", "Fresh Water", "15. Life on land", "01 natural sciences", "6. Clean water", "Winter wheat", "Model - Saline water", "Biomass", "Seasons", "Grain yield", "Edible Grain", "Triticum"]}, "links": [{"href": "https://doi.org/2981757634"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "2981757634", "name": "item", "description": "2981757634", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2981757634"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-23T00:00:00Z"}}, {"id": "31646419", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-21T16:23:11Z", "type": "Journal Article", "created": "2019-10-23", "title": "Evaluating the performance of SALTMED model under alternate irrigation using saline and fresh water strategies to winter wheat in the North China Plain", "description": "The effective water management in the North China Plain (NCP) needs a tool to predict winter wheat production due to water quality. A large quantity of brackish water is stored underground in this region, and whether this water can be used properly in agriculture is becoming a crucial issue that is about to be resolved. The SALTMED model is a generic modeling tool for efficient irrigation management strategies, especially for cyclic use of saline and fresh water as well as different water qualities, and it still needs further investigation for alternate irrigation using saline and fresh water at different growth stages of winter wheat. Therefore, the aim of this investigation was to evaluate the performance of SALTMED model and simulate the production of winter wheat grown under different irrigation strategies. Irrigation strategies comprised rain-fed cultivation (NI), fresh and saline water irrigation (FS), saline and fresh water irrigation (SF), saline water irrigation (SS), and fresh water irrigation (FF). Three-year observed data were used for the validations of SALTMED model. The values of evaluation indices of relative error, RMSE, NRMSE, index of agreement (D-index), and R2 between simulated and observed grain yield were 6.8%, 0.8, 10.7, 0.9, and 0.9, respectively. The model results supported and matched the observed data and indicated similar differences among the irrigated and rain-fed treatments. It is concluded that the SALTMED model is able to predict grain yield of winter wheat and its productivity under the alternate irrigation using saline and fresh water and their interaction in the climate condition of the NCP", "keywords": ["0106 biological sciences", "2. Zero hunger", "China", "Agricultural Irrigation", "Fresh water", "Water productivity", "Rain", "Water", "Agriculture", "Fresh Water", "15. Life on land", "01 natural sciences", "6. Clean water", "Winter wheat", "Model - Saline water", "Biomass", "Seasons", "Grain yield", "Edible Grain", "Triticum"]}, "links": [{"href": "https://doi.org/31646419"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Environmental%20Science%20and%20Pollution%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "31646419", "name": "item", "description": "31646419", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/31646419"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-10-23T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Water+productivity&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=Water+productivity&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=Water+productivity&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Water+productivity&offset=14", "hreflang": "en-US"}], "numberMatched": 14, "numberReturned": 14, "distributedFeatures": [], "timeStamp": "2026-09-22T10:59:54.146419Z"}