Timely spatially explicit warning of areas with high fire occurrence probability is an important component of strategic plans to prevent and monitor fires within South American (SA) Protected Areas (PAs). In this study, we present a five\uffe2\uff80\uff90level alert system, which combines both climatological and anthropogenic factors, the two main drivers of fires in SA. The alert levels are: High Alert, Alert, Attention, Observation and Low Probability. The trend in the number of active fires over the past three years and the accumulated number of active fires over the same period were used as indicators of intensification of human use of fire in that region, possibly associated with ongoing land use/land cover change (LULCC). An ensemble of temperature and precipitation gridded output from the GloSea5 Seasonal Forecast System was used to indicate an enhanced probability of hot and dry weather conditions that combined with LULCC favour fire occurrences. Alerts from this system were first issued in August 2020, for the period ranging from August to October (ASO) 2020. Overall, 50% of all fires observed during the ASO 2017\uffe2\uff80\uff932019 period and 40% of the ASO 2020 fires occurred in only 29 PAs were all categorized in the top two alert levels. In categories mapped as High Alert level, 34% of the PAs experienced an increase in fires compared with the 2017\uffe2\uff80\uff932019 reference period, and 81% of the High Alert false alarm registered fire occurrence above the median. Initial feedback from stakeholders indicates that these alerts were used to inform resource management in some PAs. We expect that these forecasts can provide continuous information aiming at changing societal perceptions of fire use and consequently subsidize strategic planning and mitigatory actions, focusing on timely responses to a disaster risk management strategy. Further research must focus on the model improvement and knowledge translation to stakeholders.
", "keywords": ["0106 biological sciences", "Atmospheric Science", "Land cover", "Flood Risk", "Precipitation", "01 natural sciences", "Environmental science", "Impact of Climate Change on Forest Wildfires", "Global Flood Risk Assessment and Management", "Meteorology", "Engineering", "Machine learning", "False alarm", "Civil engineering", "0105 earth and related environmental sciences", "Climatology", "Global and Planetary Change", "Tropical Cyclone Intensity and Climate Change", "Geography", "Warning system", "Geology", "FOS: Earth and related environmental sciences", "15. Life on land", "Computer science", "Earth and Planetary Sciences", "13. Climate action", "Environmental Science", "Physical Sciences", "Land use", "Telecommunications", "FOS: Civil engineering"]}, "links": [{"href": "https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/cli2.19"}, {"href": "https://doi.org/10.1002/cli2.19"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Climate%20Resilience%20and%20Sustainability", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1002/cli2.19", "name": "item", "description": "10.1002/cli2.19", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1002/cli2.19"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-10-20T00:00:00Z"}}, {"id": "10.5194/hess-19-4201-2015", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:21:34Z", "type": "Journal Article", "created": "2015-10-20", "title": "Multidecadal Change In Streamflow Associated With Anthropogenic Disturbances In The Tropical Andes", "description": "Abstract. Andean headwater catchments are an important source of freshwater for downstream water users. However, few long-term studies exist on the relative importance of climate change and direct anthropogenic perturbations on flow regimes in these catchments. In this paper, we assess change in streamflow based on long time series of hydrometeorological data (1974\uffe2\uff80\uff932008) and land cover reconstructions (1963\uffe2\uff80\uff932009) in the Pangor catchment (282 km2) located in the tropical Andes. Three main land cover change trajectories can be distinguished during the period 1963\uffe2\uff80\uff932009: (1) expansion of agricultural land by an area equal to 14 % of the catchment area (or 39 km2) in 46 years' time, (2) deforestation of native forests by 11 % (or \uffe2\uff88\uff9231 km2) corresponding to a mean rate of 67 ha yr\uffe2\uff88\uff921, and (3) afforestation with exotic species in recent years by about 5 % (or 15 km2). Over the time period 1963\uffe2\uff80\uff932009, about 50 % of the 64 km2 of native forests was cleared and converted to agricultural land. Given the strong temporal variability of precipitation and streamflow data related to El Ni\uffc3\uffb1o\uffe2\uff80\uff93Southern Oscillation, we use empirical mode decomposition techniques to detrend the time series. The long-term increasing trend in rainfall is remarkably different from the observed changes in streamflow, which exhibit a decreasing trend. Hence, observed changes in streamflow are not the result of long-term change in precipitation but very likely result from anthropogenic disturbances associated with land cover change.
", "keywords": ["Technology", "Period (music)", "0208 environmental biotechnology", "Urban Flooding", "Precipitation", "02 engineering and technology", "Oceanography", "Environmental technology. Sanitary engineering", "land-use change", "Geography. Anthropology. Recreation", "Climate change", "GE1-350", "TD1-1066", "Water Science and Technology", "Climatology", "2. Zero hunger", "Global and Planetary Change", "Geography", "Ecology", "T", "Physics", "Hydrology (agriculture)", "Geology", "Programming language", "Hydrological Modeling and Water Resource Management", "Physical Sciences", "Cartography", "Land cover", "1443", "Hydrometeorology", "Drainage basin", "0207 environmental engineering", "Streamflow", "Environmental science", "G", "Global Flood Risk Assessment and Management", "Meteorology", "Afforestation", "Agroforestry", "Biology", "Land use", " land-use change and forestry", "FOS: Earth and related environmental sciences", "Acoustics", "15. Life on land", "Computer science", "Environmental sciences", "Geotechnical engineering", "Deforestation (computer science)", "13. Climate action", "FOS: Biological sciences", "Environmental Science", "Global Drought Monitoring and Assessment", "Land use"]}, "links": [{"href": "https://doi.org/10.5194/hess-19-4201-2015"}, {"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-19-4201-2015", "name": "item", "description": "10.5194/hess-19-4201-2015", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/hess-19-4201-2015"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-10-20T00:00:00Z"}}, {"id": "10.5194/hess-26-3921-2022", "type": "Feature", "geometry": null, "properties": {"updated": "2026-05-23T16:21:35Z", "type": "Journal Article", "created": "2021-12-23", "title": "High-resolution satellite products improve hydrological modeling in northern Italy", "description": "Abstract. Satellite Earth observations (EO) are an accurate and reliable data source for atmospheric and environmental science. Their increasing spatial and temporal resolution, as well as the seamless availability over ungauged regions, make them appealing for hydrological modeling. This work shows recent advances in the use of high-resolution satellite-based Earth observation data in hydrological modelling. In a set of experiments, the distributed hydrological model Continuum is set up for the Po River Basin (Italy) and forced, in turn, by satellite precipitation and evaporation, while satellite-derived soil moisture and snow depths are ingested into the model structure through a data-assimilation scheme. Further, satellite-based estimates of precipitation, evaporation and river discharge are used for hydrological model calibration, and results are compared with those based on ground observations. Despite the high density of conventional ground measurements and the strong human influence in the focus region, all satellite products show strong potential for operational hydrological applications, with skillful estimates of river discharge throughout the model domain. Satellite-based evaporation and snow depths marginally improve (by 2 % and 4 %) the mean Kling-Gupta efficiency (KGE) at 27 river gauges, compared to a baseline simulation (KGEmean = 0.51) forced by high-quality conventional data. Precipitation has the largest impact on the model output, though the satellite dataset on average shows poorer skills compared to conventional data. Interestingly, a model calibration heavily relying on satellite data, as opposed to conventional data, provides a skillful reconstruction of river discharges, paving the way to fully satellite-driven hydrological applications.
", "keywords": ["Technology", "DATA", "ASSIMILATION", "Po River", "FLOOD RISK", "0211 other engineering and technologies", "0207 environmental engineering", "UNCERTAINTY", "02 engineering and technology", "high resolution satellite products", "Environmental technology. Sanitary engineering", "01 natural sciences", "G", "Geography. Anthropology. Recreation", "EARTH", "GE1-350", "continuum hydrological model", "RAINFALL", "TD1-1066", "0105 earth and related environmental sciences", "T", "RADAR ALTIMETRY DATA", "LAND-SURFACE", "6. Clean water", "Environmental sciences", "13. 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Indicative Flood Risk Areas are provided by the Environment Agency for use by Lead Local Flood Authorities in England in their review during 2017 of Preliminary Flood Risk Assessments and Flood Risk Areas under the Flood Risk Regulations.\nThe Indicative Flood Risk Areas are primarily based on an aggregated 1km square grid Updated Flood Map for Surface Water (1 in 100 and 1000 annual probability rainfall), informally referred to as the \u201cblue square map\u201d. These are 1km grids across England and consist of the following data layers:\n\u2022\tSurface Water Flood Risk Exposure Grid \u2013 1km square grid that shows places above the flood risk threshold defined, using the 1 in 100 and 1000 annual probability (deep) Flood Map for Surface Water.\n\u2022\tFlood risk thresholds used to generate the \u201cblue Squares\u201d:\n-\tNumber of people > 200\n-\tNumber of critical services, including electricity and water > 1\n-\tNumber of non-residential properties > 20 \n\u2022\tCluster Maps \u2013 are aggregations of 3km by 3km squares that each contain at least 5 touching \"blue squares\" (i.e. 1km grid squares where one of the thresholds above is exceeded)\n\u2022\tCommunities at Risk by Lead Local Flooding Authority\n\u2022\tPeople Sensitivity Map by Lead Local Flood Authority. Attribution statement: \u00a9 Environment Agency copyright and/or database right 2016. All rights reserved.\nContains public sector information licensed under the Open Government Licence", "formats": [{"name": "DSP:ESRI"}, {"name": "http:"}, {"name": "canonical"}], "keywords": ["EJP Country survey", "National", "Country Stocktake", "UK", "Indicative Flood Risk Area", "OpenData", "flood"], "contacts": [{"name": null, "organization": "Environment Agency", "position": null, "roles": ["pointOfContact"], "phones": [{"value": null}], "emails": [{"value": "metadata@environment-agency.gov.uk"}], "addresses": [{"deliveryPoint": [null], "city": null, "administrativeArea": null, "postalCode": "None", "country": "UK"}], "links": [{"href": {"url": null, "protocol": null, "protocol_url": "", "name": null, "name_url": "", "description": null, "description_url": "", "applicationprofile": null, "applicationprofile_url": "", "function": null}}]}]}, "links": [{"href": "https://environment.data.gov.uk/DefraDataDownload/?mapService=EA/IndicativeFloodRiskAreas&Mode=spatial", "name": "Indicative_Flood_Risk_Shapefiles_Download", "description": "Indicative Flood Risk Shapefiles Download on the Data Services Platform", "protocol": "DSP:ESRI", "rel": null}, {"href": "https://support.environment.data.gov.uk/hc/en-gb", "name": "DSP_CUSTOMER_FORUM", "description": "DEFRA Data Services Platform Customer Forum", "protocol": "http:", "rel": null}, {"href": "https://github.com/ejpsoil/ejpsoildatahub/tree/main/datasets/countries/UK/Indicative-Flood-Risk-Areas-for-.yml", "name": "Source of the record", "protocol": "canonical", "rel": "canonical"}, {"rel": "self", "type": "application/geo+json", "title": "6a41cbab-6d8a-4af6-a622-bc0f6dcd8372", "name": "item", "description": "6a41cbab-6d8a-4af6-a622-bc0f6dcd8372", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/6a41cbab-6d8a-4af6-a622-bc0f6dcd8372"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"interval": ["2016-01-01T00:00:00Z", "2016-12-31T00:00:00Z"]}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Flood+Risk&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=Flood+Risk&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=Flood+Risk&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=Flood+Risk&offset=4", "hreflang": "en-US"}], "numberMatched": 4, "numberReturned": 4, "distributedFeatures": [], "timeStamp": "2026-05-25T06:19:02.524508Z"}