TY  - JOUR
A1  - Pathiraja, Sahani Darschika
A1  - Anghileri, Daniela
A1  - Burlando, P.
A1  - Sharma, A.
A1  - Marshall, L.
A1  - Moradkhani, H.
T1  - Insights on the impact of systematic model errors on data assimilation performance in changing catchments
JF  - Advances in water resources
N2  - The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.
Y1  - 2017
U6  - https://doi.org/10.1016/j.advwatres.2017.12.006
SN  - 0309-1708
SN  - 1872-9657
VL  - 113
SP  - 202
EP  - 222
PB  - Elsevier
CY  - Oxford
ER  - 
TY  - JOUR
A1  - Pathiraja, Sahani Darschika
A1  - Anghileri, Daniela
A1  - Burlando, Paolo
A1  - Sharma, Ashish
A1  - Marshall, Lucy
A1  - Moradkhani, Hamid
T1  - Time-varying parameter models for catchments with land use change
BT  - the importance of model structure
JF  - Hydrology and earth system sciences : HESS
N2  - Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km(2)) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.
Y1  - 2018
U6  - https://doi.org/10.5194/hess-22-2903-2018
SN  - 1027-5606
SN  - 1607-7938
VL  - 22
IS  - 5
SP  - 2903
EP  - 2919
PB  - Copernicus
CY  - Göttingen
ER  -