{"type": "FeatureCollection", "features": [{"id": "10.1007/s100210000025", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:14:55Z", "type": "Journal Article", "created": "2002-07-25", "title": "Controls On Soil Carbon Dioxide And Methane Fluxes In A Variety Of Taiga Forest Stands In Interior Alaska", "description": "CO2 and CH4 fluxes were monitored over 4 years in a range of taiga forests along the Tanana River in interior Alaska. Floodplain alder and white spruce sites and upland birch/aspen and white spruce sites were examined. Each site had control, fertilized, and sawdust amended plots; flux measurements began during the second treatment year. CO2 emissions decreased with successional age across the sites (alder, birch/aspen, and white spruce, in order of succession) regardless of landscape position. Although CO2 fluxes showed an exponential relationship with soil temperature, the response of CO2 production to moisture fit an asymptotic model. Of the manipulations, only N fertilization had an effect on CO2 flux, decreasing flux in the floodplain sites but increasing it in the birch/aspen site. Landscape position was the best predictor of CH4 flux. The two upland sites consumed CH4 at similar rates (approximately 0.5 mg C m\u22122 d\u22121), whereas the floodplain sites had lower consumption rates (0\u20130.3 mg C m\u22122 d\u22121). N fertilization and sawdust both inhibited CH4 consumption in the upland birch/aspen and floodplain spruce sites but not in the upland spruce site. The biological processes driving CO2 fluxes were sensitive to temperature, moisture, and vegetation, whereas CH4 fluxes were sensitive primarily to landscape position and biogeochemical disturbances. Hence, climate change effects on C-gas flux in taiga forest soils will depend on the relationship between soil temperature and moisture and the concomitant changes in soil nutrient pools and cycles.", "keywords": ["landscape-ecology", "Betulaceae-: Dicotyledones-", "flux-", "soil-nutrient-pools", "Coniferopsida-: Gymnospermae-", "Vascular-Plants", "forests-", "Environmental-Sciences)", "carbon-dioxide", "nitrogen-fertilizers", "01 natural sciences", "carbon-dioxide: emissions-", "nitrogen-: fertilization-", "vegetation-", "birch- (Betulaceae-)", "124-38-9: CARBON DIOXIDE", "Spermatophytes-", "Spermatophyta-", "74-82-8: METHANE", "Plantae-", "white-spruce (Coniferopsida-)", "successional-age", "boreal-forests", "environmental-temperature", "0105 earth and related environmental sciences", "taiga-forest-stands", "Angiosperms-", "Gymnosperms-", "Angiospermae-", "Plants-", "sawdust-", "methane-", "15. Life on land", "North-America", "Nearctic-region)", "floodplains-", "mathematical-models", "13. Climate action", "alder- (Betulaceae-)", "upland-sites", "Alaska- (USA-", "climate-change", "Terrestrial-Ecology (Ecology-", "7727-37-9: NITROGEN", "Dicots-", "methane-: consumption-", "moisture-", "climatic-change", "temperature-"]}, "links": [{"href": "https://doi.org/10.1007/s100210000025"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Ecosystems", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1007/s100210000025", "name": "item", "description": "10.1007/s100210000025", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1007/s100210000025"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2000-05-10T00:00:00Z"}}, {"id": "10.3390/rs10060969", "type": "Feature", "geometry": null, "properties": {"updated": "2026-07-27T16:21:58Z", "type": "Journal Article", "created": "2018-06-18", "title": "Relation between Convective Rainfall Properties and Antecedent Soil Moisture Heterogeneity Conditions in North Africa", "description": "<p>Recent observational studies have demonstrated the relevance of soil moisture heterogeneity and the associated thermally-induced circulation on deep convection and rainfall triggering. However, whether this dynamical mechanism further influences rainfall properties\uffe2\uff80\uff94such as rain volume or timing\uffe2\uff80\uff94has yet to be confirmed by observational data. Here, we analyze 10 years of satellite-based sub-daily soil moisture and precipitation records and explore the potential of strong spatial gradients in morning soil moisture to influence the properties of afternoon rainfall in the North African region, at the 100-km scale. We find that the convective rain systems that form over locally drier soils and anomalously strong soil moisture gradients have a tendency to initiate earlier in the afternoon; they also yield lower volumes of rain, weaker intensity and lower spatial variability. The strongest sensitivity to antecedent soil conditions is identified for the timing of the rain onset; it is found to be correlated with the magnitude of the soil moisture gradient. Further analysis shows that the early initiation of rainfall over dry soils and strong surface gradients yet requires the presence of a very moist boundary layer on that day. Our findings agree well with the expected effects of thermally-induced circulation on rainfall properties suggested by theoretical studies and point to the potential of locally drier and heterogeneous soils to influence convective rainfall development. The systematic nature of the identified effect of soil moisture state on the onset time of rainstorms in the region is of particular relevance and may help foster research on rainfall predictability.</p>", "keywords": ["Science", "0207 environmental engineering", "UNITED-STATES", "EVIDENCE", "soil moisture-precipitation coupling", "02 engineering and technology", "01 natural sciences", "soil moisture-precipitation coupling; soil moisture heterogeneity; convective rainfall initiation; semi-arid Sahel", "Soilmoisture heterogeneity", "convective rainfall initiation", "LARGE-EDDY SIMULATIONS", "Soilmoisture-precipitation coupling", "WEST-AFRICA", "0105 earth and related environmental sciences", "Semi-arid Sahel", "PRECIPITATION FEEDBACK", "Convective rainfall initiation", "Q", "PASSIVE MICROWAVE", "15. Life on land", "LAND-SURFACE", "DIURNAL CYCLES", "semi-arid Sahel", "13. Climate action", "Earth and Environmental Sciences", "AMMA CAMPAIGN", "OBSERVATIONAL", "soil moisture heterogeneity", "BOUNDARY-LAYER INTERACTIONS"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/10/6/969/pdf"}, {"href": "https://doi.org/10.3390/rs10060969"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs10060969", "name": "item", "description": "10.3390/rs10060969", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs10060969"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-06-17T00:00:00Z"}}, {"id": "10.5194/hess-2018-94", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:50Z", "type": "Journal Article", "created": "2018-04-05", "title": "The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Soil moisture measurements are needed in a large number of applications such as climate change, watershed water balance and irrigation management. One of the main characteristics of this property is that soil moisture is highly variable with both space and time, hindering the estimation of a representative value. Deciding how to measure soil moisture before undertaking any type of study is therefore an important issue that needs to be addressed correctly. Nowadays, different kinds of methodologies exist for measuring soil moisture; Remote Sensing, soil moisture sensors or gravimetric measurements. This work is focused on how to measure soil moisture for irrigation scheduling, where soil moisture sensors are the main methodology for monitoring soil moisture. One of its disadvantages, however, is that soil moisture sensors measure a small volume of soil, and do not take into account the existing variability in the field. In contrast, Remote Sensing techniques are able to estimate soil moisture with a low spatial resolution, and thus it is not possible to apply these estimations to agricultural applications. In order to solve this problem, different kinds of algorithms have been developed for downscaling these estimations from low to high resolution. The DISPATCH algorithm downscales soil moisture estimations from 40\u2009km to 1\u2009km resolution using SMOS satellite soil moisture, NDVI and LST from MODIS sensor estimations. In this work, DISPATCH estimations are compared with soil moisture sensors and gravimetric measurements to validate the DISPATCH algorithm in two different hydrologic scenarios; (1) when wet conditions are maintained around the field for rainfall events, and (2) when it is local irrigation that maintains wet conditions. Results show that the DISPATCH algorithm is sensitive when soil moisture is homogenized during general rainfall events, but not when local irrigation generates occasional heterogeneity. In order to explain these different behaviours, we have examined the spatial variability scales of NDVI and LST data, which are the variables involved in the downscaling process provided by the MODIS sensor. Sample variograms show that the spatial scales associated with the NDVI and LST properties are too large to represent the variations of the average water content at the site, and this could be a reason for why the DISPATCH algorithm is unable to detect soil moisture increments caused by local irrigation.                         </p></article>", "keywords": ["2. Zero hunger", "Technology", ":Enginyeria civil::Geologia::Hidrologia [\u00c0rees tem\u00e0tiques de la UPC]", "T", "15. Life on land", "Environmental technology. Sanitary engineering", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria civil::Geologia::Hidrologia", "01 natural sciences", "6. Clean water", "S\u00f2ls -- Humitat -- Mesurament", "G", "Environmental sciences", "13. Climate action", "Geography. Anthropology. Recreation", "GE1-350", "Soil moisture--Measurement--Remote sensing", "TD1-1066", "0105 earth and related environmental sciences"], "contacts": [{"organization": "M. Fontanet, M. Fontanet, M. Fontanet, D. Fern\u00e0ndez-Garcia, D. Fern\u00e0ndez-Garcia, F. Ferrer,", "roles": ["creator"]}]}, "links": [{"href": "https://hess.copernicus.org/articles/22/5889/2018/hess-22-5889-2018.pdf"}, {"href": "https://doi.org/10.5194/hess-2018-94"}, {"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": "10.5194/hess-2018-94", "name": "item", "description": "10.5194/hess-2018-94", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-2018-94"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-05T00:00:00Z"}}, {"id": "10.5194/hess-22-5889-2018", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:22:51Z", "type": "Journal Article", "created": "2018-04-05", "title": "The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields", "description": "<p>Abstract. Soil moisture measurements are needed in a large number of applications such as climate change, watershed water balance and irrigation management. One of the main characteristics of this property is that soil moisture is highly variable with both space and time, hindering the estimation of a representative value. Deciding how to measure soil moisture before undertaking any type of study is therefore an important issue that needs to be addressed correctly. Nowadays, different kinds of methodologies exist for measuring soil moisture; Remote Sensing, soil moisture sensors or gravimetric measurements. This work is focused on how to measure soil moisture for irrigation scheduling, where soil moisture sensors are the main methodology for monitoring soil moisture. One of its disadvantages, however, is that soil moisture sensors measure a small volume of soil, and do not take into account the existing variability in the field. In contrast, Remote Sensing techniques are able to estimate soil moisture with a low spatial resolution, and thus it is not possible to apply these estimations to agricultural applications. In order to solve this problem, different kinds of algorithms have been developed for downscaling these estimations from low to high resolution. The DISPATCH algorithm downscales soil moisture estimations from 40\uffe2\uff80\uff89km to 1\uffe2\uff80\uff89km resolution using SMOS satellite soil moisture, NDVI and LST from MODIS sensor estimations. In this work, DISPATCH estimations are compared with soil moisture sensors and gravimetric measurements to validate the DISPATCH algorithm in two different hydrologic scenarios; (1) when wet conditions are maintained around the field for rainfall events, and (2) when it is local irrigation that maintains wet conditions. Results show that the DISPATCH algorithm is sensitive when soil moisture is homogenized during general rainfall events, but not when local irrigation generates occasional heterogeneity. In order to explain these different behaviours, we have examined the spatial variability scales of NDVI and LST data, which are the variables involved in the downscaling process provided by the MODIS sensor. Sample variograms show that the spatial scales associated with the NDVI and LST properties are too large to represent the variations of the average water content at the site, and this could be a reason for why the DISPATCH algorithm is unable to detect soil moisture increments caused by local irrigation.                         </p>", "keywords": ["2. Zero hunger", "Technology", ":Enginyeria civil::Geologia::Hidrologia [\u00c0rees tem\u00e0tiques de la UPC]", "T", "15. Life on land", "Environmental technology. Sanitary engineering", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria civil::Geologia::Hidrologia", "01 natural sciences", "6. Clean water", "S\u00f2ls -- Humitat -- Mesurament", "G", "Environmental sciences", "13. Climate action", "Geography. Anthropology. Recreation", "GE1-350", "Soil moisture--Measurement--Remote sensing", "TD1-1066", "0105 earth and related environmental sciences"], "contacts": [{"organization": "M. Fontanet, M. Fontanet, M. Fontanet, D. Fern\u00e0ndez-Garcia, D. Fern\u00e0ndez-Garcia, F. Ferrer,", "roles": ["creator"]}]}, "links": [{"href": "https://hess.copernicus.org/articles/22/5889/2018/hess-22-5889-2018.pdf"}, {"href": "https://doi.org/10.5194/hess-22-5889-2018"}, {"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": "10.5194/hess-22-5889-2018", "name": "item", "description": "10.5194/hess-22-5889-2018", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-22-5889-2018"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-05T00:00:00Z"}}, {"id": "2117/127482", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:26:56Z", "type": "Journal Article", "created": "2018-04-05", "title": "The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Soil moisture measurements are needed in a large number of applications such as climate change, watershed water balance and irrigation management. One of the main characteristics of this property is that soil moisture is highly variable with both space and time, hindering the estimation of a representative value. Deciding how to measure soil moisture before undertaking any type of study is therefore an important issue that needs to be addressed correctly. Nowadays, different kinds of methodologies exist for measuring soil moisture; Remote Sensing, soil moisture sensors or gravimetric measurements. This work is focused on how to measure soil moisture for irrigation scheduling, where soil moisture sensors are the main methodology for monitoring soil moisture. One of its disadvantages, however, is that soil moisture sensors measure a small volume of soil, and do not take into account the existing variability in the field. In contrast, Remote Sensing techniques are able to estimate soil moisture with a low spatial resolution, and thus it is not possible to apply these estimations to agricultural applications. In order to solve this problem, different kinds of algorithms have been developed for downscaling these estimations from low to high resolution. The DISPATCH algorithm downscales soil moisture estimations from 40\u2009km to 1\u2009km resolution using SMOS satellite soil moisture, NDVI and LST from MODIS sensor estimations. In this work, DISPATCH estimations are compared with soil moisture sensors and gravimetric measurements to validate the DISPATCH algorithm in two different hydrologic scenarios; (1) when wet conditions are maintained around the field for rainfall events, and (2) when it is local irrigation that maintains wet conditions. Results show that the DISPATCH algorithm is sensitive when soil moisture is homogenized during general rainfall events, but not when local irrigation generates occasional heterogeneity. In order to explain these different behaviours, we have examined the spatial variability scales of NDVI and LST data, which are the variables involved in the downscaling process provided by the MODIS sensor. Sample variograms show that the spatial scales associated with the NDVI and LST properties are too large to represent the variations of the average water content at the site, and this could be a reason for why the DISPATCH algorithm is unable to detect soil moisture increments caused by local irrigation.</p></article>", "keywords": ["2. Zero hunger", "Technology", ":Enginyeria civil::Geologia::Hidrologia [\u00c0rees tem\u00e0tiques de la UPC]", "T", "15. Life on land", "Environmental technology. Sanitary engineering", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria civil::Geologia::Hidrologia", "01 natural sciences", "6. Clean water", "S\u00f2ls -- Humitat -- Mesurament", "G", "Environmental sciences", "13. Climate action", "Geography. Anthropology. Recreation", "GE1-350", "Soil moisture--Measurement--Remote sensing", "TD1-1066", "0105 earth and related environmental sciences"], "contacts": [{"organization": "M. Fontanet, M. Fontanet, M. Fontanet, D. Fern\u00e0ndez-Garcia, D. Fern\u00e0ndez-Garcia, F. Ferrer,", "roles": ["creator"]}]}, "links": [{"href": "https://hess.copernicus.org/articles/22/5889/2018/hess-22-5889-2018.pdf"}, {"href": "https://doi.org/2117/127482"}, {"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": "2117/127482", "name": "item", "description": "2117/127482", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2117/127482"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-05T00:00:00Z"}}, {"id": "2795809170", "type": "Feature", "geometry": null, "properties": {"license": "Open Access", "updated": "2026-07-27T16:27:13Z", "type": "Journal Article", "created": "2018-04-05", "title": "The value of satellite remote sensing soil moisture data and the DISPATCH algorithm in irrigation fields", "description": "<?xml version='1.0' encoding='UTF-8'?><article><p>Abstract. Soil moisture measurements are needed in a large number of applications such as climate change, watershed water balance and irrigation management. One of the main characteristics of this property is that soil moisture is highly variable with both space and time, hindering the estimation of a representative value. Deciding how to measure soil moisture before undertaking any type of study is therefore an important issue that needs to be addressed correctly. Nowadays, different kinds of methodologies exist for measuring soil moisture; Remote Sensing, soil moisture sensors or gravimetric measurements. This work is focused on how to measure soil moisture for irrigation scheduling, where soil moisture sensors are the main methodology for monitoring soil moisture. One of its disadvantages, however, is that soil moisture sensors measure a small volume of soil, and do not take into account the existing variability in the field. In contrast, Remote Sensing techniques are able to estimate soil moisture with a low spatial resolution, and thus it is not possible to apply these estimations to agricultural applications. In order to solve this problem, different kinds of algorithms have been developed for downscaling these estimations from low to high resolution. The DISPATCH algorithm downscales soil moisture estimations from 40\u2009km to 1\u2009km resolution using SMOS satellite soil moisture, NDVI and LST from MODIS sensor estimations. In this work, DISPATCH estimations are compared with soil moisture sensors and gravimetric measurements to validate the DISPATCH algorithm in two different hydrologic scenarios; (1) when wet conditions are maintained around the field for rainfall events, and (2) when it is local irrigation that maintains wet conditions. Results show that the DISPATCH algorithm is sensitive when soil moisture is homogenized during general rainfall events, but not when local irrigation generates occasional heterogeneity. In order to explain these different behaviours, we have examined the spatial variability scales of NDVI and LST data, which are the variables involved in the downscaling process provided by the MODIS sensor. Sample variograms show that the spatial scales associated with the NDVI and LST properties are too large to represent the variations of the average water content at the site, and this could be a reason for why the DISPATCH algorithm is unable to detect soil moisture increments caused by local irrigation.                         </p></article>", "keywords": ["2. Zero hunger", "Technology", ":Enginyeria civil::Geologia::Hidrologia [\u00c0rees tem\u00e0tiques de la UPC]", "T", "15. Life on land", "Environmental technology. Sanitary engineering", "\u00c0rees tem\u00e0tiques de la UPC::Enginyeria civil::Geologia::Hidrologia", "01 natural sciences", "6. Clean water", "S\u00f2ls -- Humitat -- Mesurament", "G", "Environmental sciences", "13. Climate action", "Geography. Anthropology. Recreation", "GE1-350", "Soil moisture--Measurement--Remote sensing", "TD1-1066", "0105 earth and related environmental sciences"], "contacts": [{"organization": "M. Fontanet, M. Fontanet, M. Fontanet, D. Fern\u00e0ndez-Garcia, D. Fern\u00e0ndez-Garcia, F. Ferrer,", "roles": ["creator"]}]}, "links": [{"href": "https://hess.copernicus.org/articles/22/5889/2018/hess-22-5889-2018.pdf"}, {"href": "https://doi.org/2795809170"}, {"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": "2795809170", "name": "item", "description": "2795809170", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/2795809170"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-04-05T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=moisture-&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=moisture-&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=moisture-&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=moisture-&offset=6", "hreflang": "en-US"}], "numberMatched": 6, "numberReturned": 6, "distributedFeatures": [], "timeStamp": "2026-07-27T20:55:33.306456Z"}