Transfer function noise modelling of groundwater level fluctuation using threshold rainfall-based binary-weighted parameter estimation approach
| Autor: | Suresh Kumar Govindarajan, Suresh Beniwal, MOHANASUNDARAM S, Mohanasundaram Shanmugam, Balaji Narasimhan |
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| Rok vydání: | 2016 |
| Předmět: |
Coefficient of determination
010504 meteorology & atmospheric sciences Estimation theory 0208 environmental biotechnology Binary number 02 engineering and technology Time step 01 natural sciences Transfer function 020801 environmental engineering Water level Statistics Groundwater 0105 earth and related environmental sciences Water Science and Technology Mathematics Water level rise |
| Zdroj: | Hydrological Sciences Journal. :1-14 |
| ISSN: | 2150-3435 0262-6667 |
| DOI: | 10.1080/02626667.2016.1171325 |
| Popis: | Considerable uncertainty occurs in the parameter estimates of traditional rainfall–water level transfer function noise (TFN) models, especially with the models built using monthly time step datasets. This is due to the equal weights assigned for rainfall occurring during both water level rise and water level drop events while estimating the TFN model parameters using the least square technique. As an alternative to this approach, a threshold rainfall-based binary-weighted least square method was adopted to estimate the TFN model parameters. The efficacy of this binary-weighted approach in estimating the TFN model parameters was tested on 26 observation wells distributed across the Adyar River basin in Southern India. Model performance indices such as mean absolute error and coefficient of determination values showed that the proposed binary-weighted approach of fitting independent threshold-based TFN models for water level rise and water level drop scenarios considerably improves the model accurac... |
| Databáze: | OpenAIRE |
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