Abstract: Climate variability, as an element of uncertainty in water management, affects community, sectoral, and individual decision-making. Long-range prediction models are tools that offer the potential for integration and joint analysis with the hydrological, hydrodynamic, and management response of the socio-ecological systems to which they are linked. The main objective of this article is to present a seasonal climate prediction model, the open-source algorithm SIE-Climate, whose application consists of three phases (exploration, development, and evaluation), and to describe its application to the Lake Sochagota socio-ecological system (Paipa, Boyacá, Colombia). The K-nearest neighbours method is used when defining a target matrix that represents and integrates macro- and micro-climatic phenomena (Oceanic Niño Index, local temperature, and local rainfall) to identify periods of similar climatic behaviour. Considering a 1-year horizon and management purposes the tool is calibrated and validated in periods with and without climatic anomalies (2000-2018), giving reliable adjustment results (RSME:4.86; R2: 0.95; PBIAS: -8.89%; EFF: 0.85). SIE-Climate can be adapted to various contexts, variables of interest, and temporal and spatial scales, with an appropriate technological and computational cost for regional water management.
Authorship: Sierra-Cárdenas E., Usaquén-Perilla O., Fonseca-Molano M., Ochoa-Echeverría M., Díaz-Gómez J., del Jesus M.,
Fuente: International Journal of Climatology, 2022, 42(2), 868-888
Publisher: John Wiley and Sons Ltd
Publication date: 27/06/2022
No. of pages: 21
Publication type: Article
DOI: 10.1002/joc.7277
ISSN: 0899-8418,1097-0088
Spanish project: FP44842-293-2018
Publication Url: https://doi.org/10.1002/joc.7277