12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > Constraining Dynamic TOPMODEL responses for imp...
View graph of relations

« Back

Constraining Dynamic TOPMODEL responses for imprecise water table information using fuzzy rule based performance measures.

Research output: Contribution to journalJournal article

Published

Journal publication date1/06/2004
JournalJournal of Hydrology
Journal number3-4
Volume291
Number of pages24
Pages254-277
Original languageEnglish

Abstract

Dynamic TOPMODEL is applied to the Maimai M8 catchment (3.8 ha), New Zealand using rainfall–runoff and water table information in model calibration. Different parametric representations of hillslope and valley bottom landscape units (LU's) were used to improve the spatial representation of the model structure. The continuous time series water table information is obtained from tensiometric observations from both near stream (NS) and hillslope (P5) locations having different responses to rainfall events. For each location, and within an area equivalent to an effective model gridscale (25 m2), a number of tensiometer readings at different depths were available (11 for the NS site and nine for the P5 site). Using this information a distribution of water table elevations for each time step at each location was calculated. The distribution of water table elevations was used to derive fuzzy estimates of the water table depth for the whole time series that includes the temporal variability of the uncertainty in the observations. These data were used to constrain the spatial representation of the model having previously conditioned the model using the rainfall–runoff data. Model conditioning was assessed using the Generalised Likelihood Uncertainty Estimation procedure. Results show that many combinations of parameter values for the two LU's were able to simulate the rainfall–runoff data. Further constraining of the model responses using the fuzzy water table elevations at both locations considerably reduced the number of behavioural parameter sets. An evaluation of the distributions of behavioural parameter sets showed that improvements to the model structure for the two LU's were required, especially for simulations of the response at the hillslope location.

Bibliographic note

JEF supervised the MSc thesis of HMcM, which used the thesis data collected by JJMcD in Maimai, New Zealand. The first paper to include the use of fuzzy performance measures in GLUE for time series data to express the variability in the information content of data over different events. RAE_import_type : Journal article RAE_uoa_type : Earth Systems and Environmental Sciences