Multivariate Analysis of Climatological and Hydrological Low Water Drivers in Bavaria (Statistical Internship)

Data

Simulated and measured data at 3 river gauges in hydrological Bavaria between 1990 and 2020. The target variable NM7Q: lowest 7-day runoff mean of a year (typical low water characteristic)

Research Interests

• How can the occurrence of low water events be explained/predicted?
• Which drivers are relevant?
• Are drivers of an extreme event themselves extreme? Or is it a combination of moderately pronounced drivers that leads to extreme low water?

Findings

• How can the occurrence of low water events be explained/predicted?

  • GAMs with binomial distribution assumption
  • Modeling drivers as splines and individual explanatory interactions
  • Variable-specific quantile distribution analysis

• Which drivers are relevant?

  • Groundwater level, precipitation group, and soilwater appear important
  • Clear differences between north and south, e.g., in influence of snow and air temperature
  • Grouping of southern and northern areas seems reasonable

• Are drivers of an extreme event themselves extreme? Or is it a combination of moderately pronounced drivers that leads to extreme low water?

  • Differences between variables
  • Extreme events seem relevant for: Precipitation, relative near-surface soil moisture, infiltration, and groundwater level.

Authors

• Christian Hobelsberger
• Max Lang
• Jonas Schernich
• Lisa Kleinlein