{"type": "FeatureCollection", "features": [{"id": "10.1016/j.catena.2022.106181", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:16:21Z", "type": "Journal Article", "created": "2022-03-04", "title": "Sediment yields variation and response to the controlling factors in the Wei River Basin, China", "description": "Project Co-ordinators: Dr. Jose Alfonso G\u00f3mez Calero (Instituto de Agricultura Sostenible (IAS-CISC), Dr. Weifeng Xu (Fujian Agriculture and Forest University, FAFU). -- Trabajo desarrollado bajo la financiaci\u00f3n del proyecto \u201cSoil Hydrology research platform underpinning innovation to manage water scarcity in European and Chinese cropping Systems\u201d (773903), coordinado por Jos\u00e9 Alfonso G\u00f3mez Calero, investigador del Instituto de Agricultura Sostenible (IAS). Assessing regional sediment yield variation and their responses to the potential controlling factors are critical to develop specific strategies of soil conservation measures to adapt to future climate change. This study attempted to investigate the spatial\u2013temporal variation of sediment load in the Wei River basin in the midstream of the Yellow River during 1961\u20132015 at 15 hydrological stations. The results indicated that annual sediment load in the past six decades decreased significantly (P < 0.01) with the changing trends of \u22126.43 \u00d7 104, \u22123.86 \u00d7 104, \u22124.6 \u00d7 104 t/a at Xianyang, Zhangjiashan, and Zhuangtou stations, respectively. Annual sediment load exhibited abrupt changes in the mid-1990s, which were largely attributed to the strong effects of soil conservation measures in the study area. The spatial pattern of soil erosion were characterized by high sediment yield in the north with sparse vegetation cover and well-developed gullies, and low sediment yield in the south with flat plain and good vegetation cover in the Wei River basin. The results of the partial least squares-structural equation model (PLS-SEM) showed that vegetation changes and rainfall variability explained 62.3%, 47.3%, and 40.1% of the variation in runoff at Xianyang, Zhuangtou, and Zhangjiashan stations, respectively, whereas 59.4%, 17.6% and 48% of the variation in sediment load were explained by the combining effects of rainfall variability, changes of vegetation and runoff. This study provides a deep insight for understanding the effects of driving forces on sediment yield changes, and can be useful to regional soil conservation planning in the region. The study was funded by the National Science and Technology Basic Resource Investigation Program (2017FY100904), the Chinese National Natural Sciences Foundation (42177323; 42077076), the Horizon 2020 Project Shui which is co-funded by the Chinese MOST (2017YFE0118100) and the European Union Project (773903). Peer reviewed", "keywords": ["Controlling factors", "13. Climate action", "0208 environmental biotechnology", "Sediment yield", "0207 environmental engineering", "Correlation analysis", "Spatial and temporal variation", "02 engineering and technology", "15. Life on land", "6. Clean water", "Wei River Basin"]}, "links": [{"href": "https://doi.org/10.1016/j.catena.2022.106181"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1016/j.catena.2022.106181", "name": "item", "description": "10.1016/j.catena.2022.106181", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1016/j.catena.2022.106181"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-01T00:00:00Z"}}, {"id": "10.3390/w13162238", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:21:57Z", "type": "Journal Article", "created": "2021-08-18", "title": "Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from \u221217% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.</p></article>", "keywords": ["Step-wise calibration", "2. Zero hunger", "step-wise calibration", "Crop yields", "soil erosion model", "Sequential calibration", "Sediment yield", "0207 environmental engineering", "HOAL", "crop yields", "Streamflow", "SWATplusR", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "sediment yield", "6. Clean water", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "SWAT", "Soil erosion model", "streamflow", "Soil moisture", "soil moisture", "sequential calibration"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://doi.org/10.3390/w13162238"}, {"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/w13162238", "name": "item", "description": "10.3390/w13162238", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/w13162238"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-17T00:00:00Z"}}, {"id": "10.5281/zenodo.14036322", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:23:22Z", "type": "Dataset", "created": "2024-11-04", "title": "Geochemistry of soils and eroded suspended sediments from two large rural catchments in southern Brazil for studies on Suspended Sediment Fingerprinting", "description": "1. Introduction  This dataset comes from a research project entitled 'Water and pollutants, from cropfields to cities: evaluation and improved of soil management technologies in a catchment network ' supported by the Foundation for Research Support of the State of Rio Grande do Sul (FAPERGS) and National Council for Scientific and Technological Development (CNPq) (process n\u00b010/0034-0). The project was carried out between 2010 and 2014 under the coordination of Jos\u00e9 Miguel Reichert and Danilo Rheinheimer dos Santos, professors at the Federal University of Santa Maria. One of the aims of this project was to understand the main pollutant transfer process from hillslopes to fluvial systems in large rural catchments representative of the agricultural production system in Southern Brazil. In this context, the Suspended Sediment Fingerprinting (SSF) was extremely useful for quantifying the origin of the sediment yield monitored at the outlet of these catchments. Among the various works carried out in this project, we highlight Tales Tiecher's doctoral thesis (Tiecher, 2015) that explored the SSF in many catchments, including the Concei\u00e7\u00e3o and Guapor\u00e9 river basins.  2. Material and Methods  The catchments represent the magnitude of erosive and hydrological processes representative of Southern Brazil. The Concei\u00e7\u00e3o catchment has a drainage area of 804 km2 (28\u00b027\u203222\u2033S and 53\u00b058\u203224\u2033 W). According to K\u00f6ppen, the climate is Cfa type, with an annual rainfall between 1,750 and 2,000 mm. Geology is riodacithe basalt, with a formation of deep and highly weathered soils (Oxisols, Ultisols, and Alfisols). The relief is characterized by gentle slopes (6\u20139 %) on top and hillside slopes and higher steepness (10\u201314%) near the drainage channels. Farming based on the production of soybeans (Glycine max) in summer and wheat (Triticumspp.), oats (Avena strigosa), and ryegrass (Lolium multiflorum) in winter. The Guapor\u00e9 catchment has a drainage area of 1,980 km2 (28\u00b054\u203241\u2033S and 51\u00b057\u203210\u2033W), it covers part of the meridional plateau border. The climate is classified as Cfa, with annual rainfall varies between 1,400 and 2,000 mm. Geology is characterized by volcanic lava flows, and topography is undulating to hilly. Due to variations in landscape, several classes of soils (Entisols, Luvisol, Cambisol, Oxisol, Ultisol, and Chernosol). The land use is highly heterogeneous. In the upper third of the catchment, there is a predominance of soybean cultivated under no-tillage soil management. In the other two-thirds (middle and lower parts), land use and soil management are very heterogeneous. The main land uses are tobacco (Nicotiana tabacum) and maize (Zea mays) crops, Eucalyptus (Eucalyptus spp.), as well as pastures for dairy cattle. The contribution of unpaved roads is relevant to the sediment yield in both catchments (Didon\u00e9 et al., 2014). Composite samples of potential sediment sources (cropland, unpaved roads, and stream channel banks) were collected. Sediment source samples were taken from the surface soil layer (0\u20130.05 m) of cropland and unpaved roads and on exposed sites located along the river channel network. Each sample was composed of at least 10 subsamples. To obtain representative samples of suspended sediment transported in the catchment\u2019s outlet were used three strategies: (1) to collect flood suspended sediments (FSS) through the manual sampling (USDH-48) at different periods during the rising and falling stages of floods; (2) to deploy time-integrated suspended sediment samplers (TISS), by installing the device developed by Phillips et al. (2000) at different sites within the catchments; to collect fine-bed sediment (FBS) with a suction stainless sampler limiting the loss of fine material at the bed river. Source and sediment samples were oven\u2010dried at 50 \u00b0C, gently disaggregated using a pestle and mortar, and then sieved to 62,5 \u03bcm. The geochemical tracers evaluated were total organic carbon estimated by wet oxidation (K2Cr2O7 + H2SO4) and the total concentration of Al, Ba, Be, Ca, Co, Cr, Cu, Fe, K, La, Li, Mg, Mn, Na, Ni, P, Pb, Sr, Ti, V, and Zn using inductively coupled plasma optical emission spectrometry after microwave\u2010assisted digestion with concentrated HCl and HNO3 (ratio 3:1) for 9.5 min at 182 \u00b0C (Tiecher, 2015; Tiecher et al. 2017, 2018).  \u00a0 3. Final remarks  \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 The SSF results provided by this dataset (Tiecher, 2015) combined with sediment yield monitoring were very important for the assessment and modeling studies in these two catchments that took place after that (Didon\u00e9 et al., 2015; 2017). In addition, other studies have explored the same sample bank, expanding upon the array of tracer properties and increasing our understanding about the mechanisms of sediment and pollutant transfer in these catchments (Le Gall et al. 2017; Zafar et al., 2017; Ramon et al., 2020).  \u00a04. References  \u00a0Didon\u00e9, E. J., Minella, J. P. G., Reichert, J. M., Merten G. H., Dalbianco, L., Barros, C. A. P., Ramon, R. (2014) Impact of no-tillage agricultural systems on sediment yield in two large catchments in southern Brazil. J Soils Sediments 14:1287\u20131297.  Didon\u00e9, E.J., Minella, J.P.G., Evrard, O. (2017). Measuring and modelling soil erosion and sediment yields in a large cultivated catchment under no-till of Southern Brazil. Soil Tillage Res. 174, 24-33. https://doi.org/10.1016/j.still.2017.05.011  Didon\u00e9, E. J.; Minela, J. P. G.; Merten, G. H. (2015). Quantifying soil erosion and sediment yield in a catchment in southern Brazil and implications for land conservation. J. Soils Sediments 11, 2334-2346. https://doi.org/10.1007/s11368-015-1160-0  le Gall, M., Evrard, O., Dapoigny, A., Tiecher, T., Zafar, M., Minella, J. P. G., Laceby, J. P., & Ayrault, S. (2017). Tracing sediment sources in a subtropical agricultural catchment of southern Brazil cultivated with conventional and conservation farming practices. Land Degradation and Development, 28(4). https://doi.org/10.1002/ldr.2662  Ramon, R., Evrard, O., Laceby, J. P., Caner, L., Inda, A. v., Barros, C. A. P., Minella, J. P. G., & Tiecher, T. (2020). Combining spectroscopy and magnetism with geochemical tracers to improve the discrimination of sediment sources in a homogeneous subtropical catchment. Catena, 195, 104800. https://doi.org/10.1016/j.catena.2020.104800  Tiecher, T. (2015). Fingerprinting sediment sources in agricultural catchments in Southern Brazil. Doctoral Dissertation in Soil Science. Universidade Federal de Santa Maria, Santa Maria, RS.  Tiecher, T., Minella, J. P. G., Caner, L., Evrard, O., Zafar, M., Capoane, V., le Gall, M., & Santos, D. R. D. (2017). Quantifying land use contributions to suspended sediment in a large cultivated catchment of Southern Brazil (Guapor\u00e9 River, Rio Grande do Sul). Agriculture, Ecosystems and Environment, 237. https://doi.org/10.1016/j.agee.2016.12.004  Tiecher, T., Minella, J. P. G., Evrard, O., Caner, L., Merten, G. H., Capoane, V., Didon\u00e9, E. J., & dos Santos, D. R. (2018). Fingerprinting sediment sources in a large agricultural catchment under no-tillage in Southern Brazil (Concei\u00e7\u00e3o River). Land Degradation and Development, 29(4). https://doi.org/10.1002/ldr.2917.  Zafar, M., Tiecher, T., Capoane, V., Troian, A., dos Santos, D.R. (2017). Characteristics, lability and distribution of phosphorus in suspended sediment from a subtropical catchment under diverse anthropic pressure in Southern Brazil. Ecol. Eng. 100, 28\u201345.", "keywords": ["No-tiilage", "Fingerprinting approach", "Soil erosion", "Sediment yield", "Sediment quality", "Brazil"], "contacts": [{"organization": "Tiecher, Tales, Minella, Jean P G, Reichert, Jos\u00e9 Miguel, dos Santos, Danilo R, Bender, Marcos, Didon\u00e9, Elizeu, Barros, Cl\u00e1udia A., Dalbianco, Leandro, Ramon, Rafael, Capone, Viviane,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5281/zenodo.14036322"}, {"rel": "self", "type": "application/geo+json", "title": "10.5281/zenodo.14036322", "name": "item", "description": "10.5281/zenodo.14036322", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5281/zenodo.14036322"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2024-11-04T00:00:00Z"}}, {"id": "10261/277849", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:25:39Z", "type": "Journal Article", "created": "2022-03-04", "title": "Sediment yields variation and response to the controlling factors in the Wei River Basin, China", "description": "Open AccessPeer reviewed", "keywords": ["Controlling factors", "13. Climate action", "0208 environmental biotechnology", "Sediment yield", "0207 environmental engineering", "Correlation analysis", "Spatial and temporal variation", "02 engineering and technology", "15. Life on land", "6. Clean water", "Wei River Basin"]}, "links": [{"href": "https://doi.org/10261/277849"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/CATENA", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10261/277849", "name": "item", "description": "10261/277849", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/277849"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2022-06-01T00:00:00Z"}}, {"id": "10261/253007", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:25:38Z", "type": "Journal Article", "created": "2021-08-17", "title": "Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from \u221217% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.</p></article>", "keywords": ["Step-wise calibration", "2. Zero hunger", "step-wise calibration", "Crop yields", "soil erosion model", "Sequential calibration", "Sediment yield", "0207 environmental engineering", "HOAL", "crop yields", "Streamflow", "SWATplusR", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "sediment yield", "6. Clean water", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "SWAT", "Soil erosion model", "streamflow", "Soil moisture", "soil moisture", "sequential calibration"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://doi.org/10261/253007"}, {"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": "10261/253007", "name": "item", "description": "10261/253007", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10261/253007"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-17T00:00:00Z"}}, {"id": "3195029335", "type": "Feature", "geometry": null, "properties": {"updated": "2026-06-23T16:27:24Z", "type": "Journal Article", "created": "2021-08-18", "title": "Multi-Step Calibration Approach for SWAT Model Using Soil Moisture and Crop Yields in a Small Agricultural Catchment", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>The quantitative prediction of hydrological components through hydrological models could serve as a basis for developing better land and water management policies. This study provides a comprehensive step by step modelling approach for a small agricultural watershed using the SWAT model. The watershed is situated in Petzenkirchen in the western part of Lower Austria and has total area of 66 hectares. At present, 87% of the catchment area is arable land, 5% is used as pasture, 6% is forested and 2% is paved. The calibration approach involves a sequential calibration of the model starting from surface runoff, and groundwater flow, followed by crop yields and then soil moisture, and finally total streamflow and sediment yields. Calibration and validation are carried out using the r-package SWATplusR. The impact of each calibration step on sediment yields and total streamflow is evaluated. The results of this approach are compared with those of the conventional model calibration approach, where all the parameters governing various hydrological processes are calibrated simultaneously. Results showed that the model was capable of successfully predicting surface runoff, groundwater flow, soil profile water content, total streamflow and sediment yields with Nash-Sutcliffe efficiency (NSE) of greater than 0.75. Crop yields were also well simulated with a percent bias (PBIAS) ranging from \u221217% to 14%. Surface runoff calibration had the highest impact on streamflow output, improving NSE from 0.39 to 0.77. The step-wise calibration approach performed better for streamflow prediction than the simultaneous calibration approach. The results of this study show that the step-wise calibration approach is more accurate, and provides a better representation of different hydrological components and processes than the simultaneous calibration approach.</p></article>", "keywords": ["Step-wise calibration", "2. Zero hunger", "step-wise calibration", "Crop yields", "soil erosion model", "Sequential calibration", "Sediment yield", "0207 environmental engineering", "HOAL", "crop yields", "Streamflow", "SWATplusR", "04 agricultural and veterinary sciences", "02 engineering and technology", "15. Life on land", "sediment yield", "6. Clean water", "13. Climate action", "0401 agriculture", " forestry", " and fisheries", "SWAT", "Soil erosion model", "streamflow", "Soil moisture", "soil moisture", "sequential calibration"]}, "links": [{"href": "http://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://www.mdpi.com/2073-4441/13/16/2238/pdf"}, {"href": "https://doi.org/3195029335"}, {"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": "3195029335", "name": "item", "description": "3195029335", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/3195029335"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-08-17T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sediment+yield&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=Sediment+yield&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=Sediment+yield&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Sediment+yield&offset=6", "hreflang": "en-US"}], "numberMatched": 6, "numberReturned": 6, "distributedFeatures": [], "timeStamp": "2026-06-24T08:32:33.459803Z"}