Towards operational hydrological model calibration using streamflow and soil moisture measurements

Yuxi Zhang, Yuan Li, Jeffrey Walker, Valentijn Rachel Noel Pauwels, Mahshid Shahrban

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

Timely and reliable flood forecasting is critical for flood warning delivery and emergency response. As core components of an operational forecasting system, hydrological models are typically calibrated using streamflow measurements to minimize parameter uncertainties. The rapid development of earth observation techniques provides opportunities to obtain soil moisture information. As catchment discharge is strongly related to soil moisture, there is a possibility to improve streamflow forecasts by using soil moisture measurements for model calibration. The use of soil moisture observations has attracted
increasing attention, however, there have been a limited number of studies.
This study aims to assess the impact of integrating soil moisture measurements for model calibration on the forecast skills of hydrological models. Experiments were implemented in the Adelong Creek (157 km2) and the Upper Kyeamba Creek (190 km2) catchments of the Murrumbidge Basin using a lumped rainfall-runoff model named GRKAL (modèle du Génie Rural Kal). Two calibration scenarios are performed: 1) a traditional streamflow-only-calibration; 2) a joint-calibration using both streamflow and in-situ soil moisture measurements. Outcomes are evaluated in a hind-casting mode for both a calibration and independent validation period. Results show that, for the Adelong catchment, the joint-calibration led to a slightly worse match between the simulated and observed streamflow with a Nash-Sutcliffe (NS) value of 0.8173, as compared to the streamflow-calibration scheme (achieved a NS value of 0.8443) alone in calibration period. During the validation period, the joint-calibration achieved a NS value of 0.7952, performing better than the streamflowcalibration
scheme which gives a NS value of 0.7586. This result indicates that although introducing the soil moisture measurements to the objective function lead to a sub-optimal match of simulated streamflow to the observed data during the calibration period, there exists the possibility that joint calibration potentially
optimized the model parameters to be more realistic, resulting a more precise prediction in the validation period. However, for the Kyeamba catchment, the results tend to be worse: NS values derived from jointcalibration was less than that obtained by streamflow-calibration in both calibration and validation period. This may relate to the unphysically based model structure, equal-weighted objective function, and various sources of uncertainties. In terms of the soil moisture prediction, it is consistent in both catchments that the joint-calibration illustrates a marginally better match to the observed value than the streamflow calibration during most of the study period. It is concluded that while the joint-calibration will typically lead to poorer streamflow forecast results during the calibration period, it could lead to a more robust result in the validation/forecasting period. As this was not consistently the case, more objective functions (such as unequal-weighted NS and a combination of several frequently-used objective functions) need to be investigated to identify the best calibration strategy for using soil moisture information.
Original languageEnglish
Title of host publicationMODSIM2015, 21st International Congress on Modelling and Simulation
EditorsT Weber, M J McPhee, R S Anderssen
Place of PublicationCanberra ACT Australia
PublisherModelling and Simulation Society of Australia and New Zealand (MSSANZ)
Pages2089 - 2095
Number of pages7
ISBN (Print)9780987214355
Publication statusPublished - 2015
EventInternational Congress on Modelling and Simulation 2015: Partnering with industry and the community for innovation and impact through modelling - Gold Coast Convention and Exhibition Centre, Broadbeach, Australia
Duration: 29 Nov 20154 Dec 2015
Conference number: 21st
https://web.archive.org/web/20150627050926/http://www.mssanz.org.au:80/modsim2015/
https://web.archive.org/web/20150626200712/http://mssanz.org.au:80/modsim2015/index.html

Conference

ConferenceInternational Congress on Modelling and Simulation 2015
Abbreviated titleMODSIM2015
CountryAustralia
CityBroadbeach
Period29/11/154/12/15
OtherThe 21st International Congress on Modelling and Simulation (MODSIM2015) was held at the Gold Coast Convention and Exhibition Centre, Broadbeach, Queensland, Australia from Sunday 29 November to Friday 4 December 2015.

It was held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium (DORS 2015).

The theme for this event was Partnering with industry and the community for innovation and impact through modelling.

21st International Congress on Modelling and Simulation: Partnering with Industry and the Community for Innovation and Impact through Modelling, MODSIM 2015 - Held jointly with the 23rd National Conference of the Australian Society for Operations Research and the DSTO led Defence Operations Research Symposium, DORS 2015
Internet address

Cite this

Zhang, Y., Li, Y., Walker, J., Pauwels, V. R. N., & Shahrban, M. (2015). Towards operational hydrological model calibration using streamflow and soil moisture measurements. In T. Weber, M. J. McPhee, & R. S. Anderssen (Eds.), MODSIM2015, 21st International Congress on Modelling and Simulation (pp. 2089 - 2095). Modelling and Simulation Society of Australia and New Zealand (MSSANZ).