%0 Journal Article %1 doi:10.1029/2017WR022466 %A Keirnan, Fowler %A Murray, Peel %A Andrew, Western %A Lu, Zhang %D 2018 %J Water Resources Research %K calibration, climate\_change, drought hydrological\_modelling, rainfall-runoff, trend %N 5 %P 3392-3408 %R 10.1029/2017WR022466 %T Improved Rainfall-Runoff Calibration for Drying Climate: Choice of Objective Function %U https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022466 %V 54 %X Abstract It has been widely shown that rainfall-runoff models often provide poor and biased simulations after a change in climate, but evidence suggests existing models may be capable of better simulations if calibration strategies are improved. Common practice is to use “least squares”-type objective functions, which focus on hydrological behavior during high flows. However, simulation of a drying climate may require a more balanced consideration of other parts of the flow regime, including mid-low flows and drier years in the calibration period, as a closer analogue of future conditions. Here we systematically test eight objective functions over 86 catchments and five conceptual model structures in southern and eastern Australia. We focus on performance when evaluated over multiyear droughts. The results show significant improvements are possible compared to least squares calibration. In particular, the Refined Index of Agreement (based on sum of absolute error, not sum of squared error) and a new objective function called the Split KGE (which gives equal weight to each year in the calibration series) give significantly better split-sample results than least squares approaches. This improvement held for all five model structures, regardless of basin characteristics such as slope, vegetation, and across a range of climatic conditions (e.g., mean precipitation between 500 and 1,500 mm/yr). We recommend future studies to avoid least squares approaches (e.g., optimizing NSE or KGE with no prior transformation on streamflow) and adopt these alternative methods, wherever simulations in a drying climate are required.

@article{doi:10.1029/2017WR022466, abstract = {Abstract It has been widely shown that rainfall-runoff models often provide poor and biased simulations after a change in climate, but evidence suggests existing models may be capable of better simulations if calibration strategies are improved. Common practice is to use “least squares”-type objective functions, which focus on hydrological behavior during high flows. However, simulation of a drying climate may require a more balanced consideration of other parts of the flow regime, including mid-low flows and drier years in the calibration period, as a closer analogue of future conditions. Here we systematically test eight objective functions over 86 catchments and five conceptual model structures in southern and eastern Australia. We focus on performance when evaluated over multiyear droughts. The results show significant improvements are possible compared to least squares calibration. In particular, the Refined Index of Agreement (based on sum of absolute error, not sum of squared error) and a new objective function called the Split KGE (which gives equal weight to each year in the calibration series) give significantly better split-sample results than least squares approaches. This improvement held for all five model structures, regardless of basin characteristics such as slope, vegetation, and across a range of climatic conditions (e.g., mean precipitation between 500 and 1,500 mm/yr). We recommend future studies to avoid least squares approaches (e.g., optimizing NSE or KGE with no prior transformation on streamflow) and adopt these alternative methods, wherever simulations in a drying climate are required.}, added-at = {2018-07-11T10:31:24.000+0200}, author = {Keirnan, Fowler and Murray, Peel and Andrew, Western and Lu, Zhang}, biburl = {https://www.bibsonomy.org/bibtex/2e34d1c56735c8fdba87ffe0a0875a85e/rutgerdankers}, doi = {10.1029/2017WR022466}, eprint = {https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2017WR022466}, interhash = {360175a463a0f74b002474e77707f4b2}, intrahash = {e34d1c56735c8fdba87ffe0a0875a85e}, journal = {Water Resources Research}, keywords = {calibration, climate\_change, drought hydrological\_modelling, rainfall-runoff, trend}, number = 5, pages = {3392-3408}, timestamp = {2018-07-11T10:31:24.000+0200}, title = {Improved Rainfall-Runoff Calibration for Drying Climate: Choice of Objective Function}, url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2017WR022466}, volume = 54, year = 2018 }