ASSESSING EFFECT OF WET AND DRY YEAR DATA ON OPTIMAL MODEL PARAMETERS OF A CONCEPTUAL RAINFALL- RUNOFF MODEL
By: Venkatesh, B
.
Contributor(s): Jayasree, V.
Publisher: Roorkee Indian Water Resources Society 2019Edition: Vol.39(4), Oct.Description: 42-50p.Subject(s): Civil EngineeringOnline resources: Click here
In:
Journal of indian water resource societySummary: The rainfall-runoff models are essential tools for the prediction of river flows over a wide range of climatic conditions. Changing climatic situations have
greater influence on the model parameters and thus also on the prediction ability of the model. Potentially, there will be large uncertainties in the model
simulations. Therefore, it is important to have a reliable prediction from hydrological models to develop tools for water resources management in the future.
igates the effect of the wet and dry period data on the hydrological model parameters and on catchment hydrological
Runoff model to Malaprabha sub-basin of Krishna basin using time series of rainfall, discharge and
available for 21 year period. The wet and dry periods were identified through available long-termrainfall data using differential split
were used for calibration andvalidation of ARNO model. The results indicate that,the model parameters show no significant variations under the changing
climatic conditions. It was also noticed that, the transfer of model parameters (Wet to dry and Dry to wet) have smaller infl
alibration of model on wet/dry year and validation on dry/wet climate show over-estimation of mean stimulated runoff (volumes)
for few occasions. These results are indicative of applicability of ARNO model for prediction of hydrological responses unde
Hydrological model, ARNO, Rainfall, Runoff, Malaprabha River
Visvesvaraya...
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Articles Abstract Database
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School of Engineering & Technology (PG) Archieval Section | Not for loan | 2021-2022131 |
The rainfall-runoff models are essential tools for the prediction of river flows over a wide range of climatic conditions. Changing climatic situations have
greater influence on the model parameters and thus also on the prediction ability of the model. Potentially, there will be large uncertainties in the model
simulations. Therefore, it is important to have a reliable prediction from hydrological models to develop tools for water resources management in the future.
igates the effect of the wet and dry period data on the hydrological model parameters and on catchment hydrological
Runoff model to Malaprabha sub-basin of Krishna basin using time series of rainfall, discharge and
available for 21 year period. The wet and dry periods were identified through available long-termrainfall data using differential split
were used for calibration andvalidation of ARNO model. The results indicate that,the model parameters show no significant variations under the changing
climatic conditions. It was also noticed that, the transfer of model parameters (Wet to dry and Dry to wet) have smaller infl
alibration of model on wet/dry year and validation on dry/wet climate show over-estimation of mean stimulated runoff (volumes)
for few occasions. These results are indicative of applicability of ARNO model for prediction of hydrological responses unde
Hydrological model, ARNO, Rainfall, Runoff, Malaprabha River
Visvesvaraya...
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