Geostatistical Discharge Estimation in Hydroelectric Canals: Integration Kriging, Conditional Simulation, and Sampling Design (software and derived data)
Abstract
Python software and derived data accompanying the article "Geostatistical Discharge Estimation in Hydroelectric Canals: Integration Kriging, Conditional Simulation, and Sampling Design" (Water Resources Research). Includes the integration-kriging and conditional-simulation pipeline, the validation code over 72 tests (36 Section A + 36 Section B), and the derived per-test results (discharge estimates, kriging and simulation coefficients of variation, and their ratio). Raw current-meter velocity data are governed by BC Hydro / CEATI agreements and are available on request; see the article's Data Availability Statement.
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 3 July 2026