It is challenging for rainfall-runoff modelling to simulate low-streamflow metrics right (). Firstly, since the daily flow rate at P01 can be many orders of magnitude smaller than the high daily flow rate at P99, it makes the AWRA-L model almost always over estimate the low-streamflow P01 when it is calibrated using the Nash–Sutcliffe efficiency based objective function using normal streamflow or using the Box-Cox transformed streamflow. As a result of over estimation of low flows the duration hydrological response variables such as ZFD, LFD, LFS and LLFS are under estimated. There are no widely accepted rules to determine the degree of transformation needed to help eliminate this problem ( ). used a number of flow transformation criteria and Nash–Sutcliffe efficiency to evaluate the efficiency of hydrological models and found that for most of the criteria high flows still make a significant contribution to the objective function value (see also ).
Secondly, the quality of the data gets degraded at the lower end of streamflow measurement due to uncertainty related to the rating curve as a result of frequent changes of channel bed geometry caused by floods and large flows. For example,investigated the rating curve uncertainties from the Namoi river basin, and found that most gauges showed significant deviations at low stages, affecting the determination of low streamflow.
In the 18.104.22.168, the selected 300 best parameters are used for the prediction providing suitable uncertainty bounds for the changes in hydrological response variables caused by .(BA), the effects of over estimation of low streamflow are lessened by taking outputs from 3000 simulations using unique parameter sets applied to both AWRA-L and AWRA-R. As discussed in Section
Furthermore, thedetermines the effects of additional coal resource development on the water resources given by the difference between and futures. As the errors introduced due to the uncertainty of model parameters are common to both baseline and CRDP, they cancel out when the net effect is calculated by taking the difference between the two pathways.
Product Finalisation date
- 22.214.171.124 Methods
- 126.96.36.199 Review of existing models
- 188.8.131.52 Model development
- 184.108.40.206 Calibration
- 220.127.116.11 Uncertainty
- 18.104.22.168 Prediction
- Currency of scientific results
- Contributors to the Technical Programme
- About this technical product