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Filters: Author is Ashley Wright
Guidelines on the optimal use of remote sensing data to improve the accuracy of hydrologic and hydraulic models. (Bushfire and Natural Hazards CRC, 2020).
Improving flood forecast skill using remote sensing data – final project report. (Bushfire and Natural Hazards CRC, 2020).
Improving flood forecast using remote sensing data - annual report 2018-2019. (Bushfire and Natural Hazards CRC, 2019).
Improving flood forecasting skill using remotely sensed data. Bushfire and Natural Hazards CRC Research Day AFAC19 (2019). at <https://knowledge.aidr.org.au/resources/australian-journal-of-emergency-management-monograph-series/>
Identification of hydrologic models, optimized parameteres, and rainfall inputs consistent with in situ streamflow and rainfall and remotely sensed soil moisture. Journal of Hydrometeorology 19, (2018).
A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction. Hydrology and Earth System Sciences (2017). doi:10.5194/hess-21-3827-2017
Estimating areal rainfall time series using input data reduction, model inversion, and data assimilation. Monash University 146 (2017). at <http://users.monash.edu.au/~jpwalker/theses/AshleyWright.pdf>
Estimating rainfall time series and model parameter distributions using model data reduction and inversion techniques. AGU (2017). at <https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017WR020442>
Improving flood forecast skill using remote sensing data. AFAC17 (Bushfire and Natural Hazards CRC, 2017).
Improving flood forecast skill using remote sensing data: annual report 2016-17. (Bushfire and Natural Hazards CRC, 2017).
Improving flood forecast skill using remote sensing: Annual project report 2015-2016. (Bushfire and Natural Hazards CRC, 2016).
Improving flood forecast skill using remote sensing data. AFAC16 (Bushfire and Natural Hazards CRC, 2016).
Combining hydrologic and hydraulic models for real time flood forecasting - non peer reviewed extended abstract. Adelaide Conference 2015 (2015).
Improving flood forecast skill using remote sensing data: Annual project report 2014-2015. (Bushfire and Natural Hazards CRC, 2015).