Assessing the Ability of the Variable Length Block Bootstrapping Model for the Generation of Multiple Stochastic Hydrometric Data Types

Stochastic inputs are essential for incorporating hydrological variability in water resources assessment, planning, and management. However, most studies focus on the generation of precipitation and temperature, precipitation and streamflow, and precipitation and evaporation, with limited incorporation of groundwater levels. This study assessed the ability of the Variable Length Block (VLB) bootstrapping model for simultaneously generating stochastic sequences of rainfall, evaporation, and groundwater levels. The performance of the model was assessed by comparing single statistics of historical time series located within the box plots of 100 annual and monthly stochastically generated time series. The model preserved eight of the nine statistics adequately, except for skewness, across all variables, with historical values for evaporation and groundwater levels falling below and above the interquartile range for 12 months. All the historic statistics for rainfall, evaporation, and groundwater levels were within the interquartile ranges of the box plots for 83, 71, and 71% of the time, respectively. The historic statistics for rainfall, evaporation, and groundwater levels were within the box plot ranges for 100, 98, and 99% of the time, respectively. These findings indicated reasonably successful generation, and the VLB generator was therefore considered applicable for the stochastic generation of multiple hydrometric data types.