Flood Flow Modeling under Nonstationarity in the Urban Watersheds of Legazpi City, Philippines

  • Virgil B. Bilaro Agricultural and Biosystems Engineering Department, Bicol University, Guinobatan, Albay and Civil Engineering Graduate Program, Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines
  • Guillermo Q. Tabios, III Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Abstract

Abstract – Traditional flood frequency analysis assumes stationary conditions (i.e. the mean and other statistical properties are unchanging) prevail in the physical and climatological element driving the phenomenon. With climate change and rapid landcover change, this assumption must be reviewed, and new approaches considering nonstationarity may need to be adopted. Long-term rainfall and land cover data were used to reconstruct historical streamflow in three urban watersheds using deterministic and stochastic techniques. The streamflow models were developed with static and time-evolving built-up land cover area to mimic the effect of land cover change due to urbanization. Annual flood maximum series were developed from each streamflow data set and were tested for trends. The models with time-evolving built-up landcover area (deterministic models) and those with urbanization as co-predictors (stochastic models) were able to generate continuous streamflow time series that yielded flood extremes exhibiting nonstationarity. The annual flood maxima were fitted onto stationary and nonstationary Generalized Extreme Value distribution models using Bayesian approach and successively tested for goodness-of-fit and parsimony. All the annual flood series from both deterministic and stochastic models satisfactorily fit both the stationary and nonstationary Generalized Extreme Value distribution, with the stationary models exhibiting better fit for streamflow models of watersheds with static urbanization scenarios; and the nonstationary models exhibiting better fit for streamflow models of watersheds with evolving urbanization scenarios. In terms of parsimony, the stochastically generated flood models are better than those developed from deterministic models as evidenced by the lower Akaike Information Criterion and Bayesian Information Criterion values for all watersheds. The probability of exceedance of floods through some threshold magnitude increases under nonstationary conditions.


 


Keywords: extreme value distribution; flood frequency; nonstationarity; return period; urbanization; land cover change; streamflow model

Author Biographies

Virgil B. Bilaro, Agricultural and Biosystems Engineering Department, Bicol University, Guinobatan, Albay and Civil Engineering Graduate Program, Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Agricultural and Biosystems Engineering Department, Bicol University, Guinobatan, Albay, and;

Civil Engineering Graduate Program, Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Guillermo Q. Tabios, III, Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Institute of Civil Engineering, College of Engineering, University of the Philippines Diliman, Quezon City 1101, Philippines

Published
2024-12-26
Issue
Vol 45 No 02 (2024)
Section
Articles