{"query_echo":{"q":"","filters":{"analysis_type":["model calibration"]},"warnings":[{"code":"facet_value_not_in_vocabulary","message":"Value 'model calibration' for facet 'analysis_type' is not in the controlled vocabulary."}]},"total":{"value":2,"relation":"eq"},"page":1,"page_size":20,"self":"https://climateinsightsdirectory.org/api/v1/search?analysis_type=model+calibration","stability":"beta","ai_marking":{"digital_source_type":{"uri":"http://cv.iptc.org/newscodes/digitalsourcetype/trainedAlgorithmicMedia","name":"Created using Generative AI"},"notice":"Summary and key insights are generated using artificial intelligence."},"results":[{"id":"sei-001859","url":"https://climateinsightsdirectory.org/document/sei-001859","title":"Modelación del recurso hídrico en la cuenca del río La Vieja en Colombia","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"fact sheet","language":"es","date_published":"2014","source_url":"https://www.sei.org/mediamanager/documents/Publications/Water-sanitation/SEI-USAID-FS-2014-Modelacion-recurso-hidrico-rio-La-Vieja-Colombia.pdf","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","geography_discussed","analysis_type"],"summary":{"text":"The document details the application of the Water Evaluation And Planning (WEAP) system to model the La Vieja river basin, covering an area of approximately 2,880 km2 across the departments of Quindío, Valle del Cauca, and Risaralda. The model incorporates 37 watercourses, 16 human consumption demands, and 4 hydroelectric demands. By utilizing a soil moisture rain-runoff method and calibrating parameters such as runoff resistance and hydraulic conductivity, the project established a framework to evaluate 1,728 scenarios involving climate variability and demographic changes. This process aims to support regional environmental authorities in formulating adaptation strategies for water resource planning through 2050.","ai_generated":true,"unit":"sei-001859#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The hydrological model of the La Vieja river basin was developed using the WEAP tool, incorporating 37 direct and indirect tributary watercourses, 16 water demands for human consumption, and 4 demands for hydroelectric generation on the Quindío river.","ai_generated":true,"unit":"sei-001859#insight-1","date_modified":"2026-10-23"},{"text":"The study area of the La Vieja river basin covers approximately 2,880 km2, distributed across the departments of Quindío (68%), Valle del Cauca (22%), and Risaralda (10%), with a general water yield of 34.34 l/s/km2 and an annual water supply of 2,975.74 Mm3.","ai_generated":true,"unit":"sei-001859#insight-2","date_modified":"2026-10-23"},{"text":"The modeling utilized a quasi-physical one-dimensional soil moisture rain-runoff method, which represents the soil matrix as two buckets to simulate hydrological phenomena.","ai_generated":true,"unit":"sei-001859#insight-3","date_modified":"2026-10-23"},{"text":"Model calibration at the Cartago station of the La Vieja River showed a good correlation between simulated and observed flows, with statistical indices of Nash=0.78 and BIAS=2.88.","ai_generated":true,"unit":"sei-001859#insight-4","date_modified":"2026-10-23"},{"text":"The most influential parameters for adjusting flow responses in the model are the runoff resistance factor (RRF), which ranged from 3.00 to 6.50, and the root zone hydraulic conductivity (Ks), which ranged from 90mm to 180mm.","ai_generated":true,"unit":"sei-001859#insight-5","date_modified":"2026-10-23"},{"text":"A hypothesis was formulated regarding a potential interaction between the river and the 'Glacis del Quindío' aquifer system, suggesting the river may be losing water to the aquifer, which could explain poor correlations at the bocatoma EPA measuring station.","ai_generated":true,"unit":"sei-001859#insight-6","date_modified":"2026-10-23"},{"text":"Using the XLRM analytical methodology, the project defined 1,728 scenarios to evaluate uncertainties—including climate, demographics, per capita consumption, water loss, and agricultural dynamics—and adaptation strategies such as wastewater treatment plants and multipurpose reservoirs.","ai_generated":true,"unit":"sei-001859#insight-7","date_modified":"2026-10-23"}],"climate_tags":["water management","climate change adaptation","water-supply management","hydroelectricity"],"geography_discussed":["Quindío Department","Valle del Cauca Department","Risaralda Department","Armenia","Pereira"],"frame_perspective":[],"analysis_type":["hydrological simulation","scenario analysis","model calibration"]},{"id":"sei-000475","url":"https://climateinsightsdirectory.org/document/sei-000475","title":"A water system model for exploring electric energy alternatives in southeastern U.S. basins","publisher":{"name":"Stockholm Environment Institute","organization":"stockholm-environment-institute"},"document_type":"research paper","language":"en","date_published":"2013-09-13","source_url":"https://www.sei.org/publications/a-water-system-model-for-exploring-electric-energy-alternatives-in-southeastern-u-s-basins/","generator":"Climate Insights Directory","generated_fields":["summary","key_insights","climate_tags","analysis_type"],"summary":{"text":"The document describes a water resource systems model for the Apalachicola–Chattahoochee–Flint, Alabama–Coosa–Tallapoosa, and Tombigbee River basins. The model integrates electricity generation, agricultural, and municipal water use to assess impacts on streamflow and water temperatures, specifically addressing thermal pollution from power plant cooling. Validation against 1980–2010 data shows the model robustly represents monthly average streamflow and water temperatures.","ai_generated":true,"unit":"sei-000475#summary","date_modified":"2026-10-23"},"key_insights":[{"text":"The developed model represents various water users, including municipal users, agricultural users, and power plants, while incorporating data on local population, per-capita use estimates, and population growth.","ai_generated":true,"unit":"sei-000475#insight-1","date_modified":"2026-10-23"},{"text":"The model was calibrated and validated using observed managed flows in the three target basins, with flow calibration based on hydraulic conductivity of soil horizons, water capacity, and land cover, while temperature calibration focused on slope properties and channel width.","ai_generated":true,"unit":"sei-000475#insight-2","date_modified":"2026-10-23"},{"text":"Based on goodness-of-fit statistics, the model accurately represents water temperatures and monthly average streamflow under water use levels observed between 1980 and 2010.","ai_generated":true,"unit":"sei-000475#insight-3","date_modified":"2026-10-23"}],"climate_tags":["electricity generation"],"geography_discussed":[],"frame_perspective":[],"analysis_type":["model development","model calibration","model validation"]}]}