2026-10-15T17:09:40Z https://data.mendeley.com/oai

oai:data.mendeley.com/pgszxc3s8y.1 2026-09-30T09:12:02Z

Corimanya-Yucra, Erick Mauricio Data and code for prioritizing hydropower catchments for drought monitoring in Brazil Mendeley Data This dataset accompanies the study “Prioritizing hydropower catchments for drought monitoring in Brazil using conditional risk and external evidence”. It links 204 hydropower entities to 109 upstream catchments and combines monthly generation records for 2000–2025 with corrected ERA5-Land runoff for 1991–2025. The package contains frozen analytical inputs, the complete catchment atlas, the reconciled entity inventory, reference tables and Python code. The analyses estimate runoff–generation associations, reconstruct conditional-risk magnitudes and rankings, assess sensitivity to hydrological periods and response specifications, compare runoff with ONS natural energy inflow and ANA gauge observations, and evaluate the contribution of prior stored energy to retrospective generation-deficit concordance. Quality-control records document source corrections, catchment assignments and the treatment of initial zero-valued ENA records. A Google Colab notebook provides an entry point for running the analytical reproduction. The scripts re-estimate the retained models, reconstruct numerical results and selected figures, and compare regenerated outputs with the supplied reference tables. Documentation includes execution instructions, dependency versions, variable definitions, file descriptions and source checksums. Reproduction starts from the supplied analytical inputs. Original source acquisition, initial gridded-data processing and the complete raw provider archives are outside the package. The documentation specifies which outputs are regenerated and which upstream controls are retained as archived records. Hydrology Drought Hydroelectric Power Generation Integrated Water Resources Management Moretto, Evandro Dataset doi:10.17632/pgszxc3s8y.1 oai:data.mendeley.com/pgszxc3s8y.1 Creative Commons Attribution 4.0 International http://creativecommons.org/licenses/by/4.0 https://data.mendeley.com/datasets/pgszxc3s8y 2026-09-30T09:12:02Z