Stochastic Methods in Hydrology (250MAG008) – Course 2025/26 PDF
Contents
Course introduction; Review of basic probability and statistics: distributions, means, standard deviation, percentiles; Sampling, measurement errors and statistical inference: estimation and hypothesis testing.
Dedication
3h Large group + 5h 20m Self StudyPython setup and environment: Jupyter, scientific packages (NumPy, SciPy, Pandas, Matplotlib); Data manipulation with Pandas: import, cleaning, grouping and summarizing; Descriptive statistics and correlations: metric calculation, correlation matrices; Data visualization: line plots, scatter plots, histograms, maps and customization.
Dedication
9h Large group + 16h Self StudyAnalysis of hydrological time series: seasonality, trends, autocorrelation, spectral analysis; Return periods: extreme value distributions, fitting and validation; Hydrological and rainfall forecasting models: regression, ARIMA, introduction to machine learning techniques; Principal component analysis (PCA) in hydrogeochemistry: dimensionality reduction, result interpretation.
Dedication
15h Large group + 26h 40m Self StudyBasic concepts and regionalized variables; Stationary and second-order random functions; Semivariogram and its relation to covariance; Variogram inference: sample semivariogram computation and interpretation; Theoretical variogram models: exponential, spherical, Gaussian and nugget effect; Spatial structure analysis: variability scales, anisotropy and nugget effect; Ordinary kriging: formulation and application; Universal kriging and residual kriging; Cokriging and kriging with external drift; Co-located cokriging and practical applications; Introduction to geostatistical simulation; Sequential simulation and Monte Carlo method; Applications to mapping of hydrogeological variables.
Dedication
18h Large group + 32h Self Study