A5024375859- Hydrology and Watershed Management Studies
- Hydrological Forecasting Using AI
- Cryospheric studies and observations
- Soil Geostatistics and Mapping
- Flood Risk Assessment and Management
- Mineral Processing and Grinding
- Precipitation Measurement and Analysis
- Groundwater flow and contamination studies
- Hydrology and Drought Analysis
- Climate variability and models
- Soil Moisture and Remote Sensing
The University of Sydney
2016-2017
We present one of the first climate change impact assessments on river runoff that utilises an ensemble global hydrological models (Glob-HMs) and catchment-scale (Cat-HMs), across multiple catchments: upper Amazon, Darling, Ganges, Lena, Mississippi, Niger, Rhine Tagus. Relative changes in simulated mean annual (MAR) four indicators high low extreme flows are compared between two ensembles. The median values with three different scenarios global-mean warming (1, 2 3 °C above pre-industrial...
An intercomparison of climate change impacts projected by nine regional-scale hydrological models for 12 large river basins on all continents was performed, and sources uncertainty were quantified in the framework ISIMIP project. The ECOMAG, HBV, HYMOD, HYPE, mHM, SWAT, SWIM, VIC WaterGAP3 applied following basins: Rhine Tagus Europe, Niger Blue Nile Africa, Ganges, Lena, Upper Yellow Yangtze Asia, Mississippi, MacKenzie Amazon America, Darling Australia. model calibration validation done...
Abstract Remotely sensed (RS) data can add value to a hydrological model calibration. Among this, RS soil moisture (SM) have mostly been assimilated into conceptual models using various transformed variable or indices. In this study, raw surface SM is used as calibration in the Soil and Water Assessment Tool model. This means values were not another (e.g., water index root zone index). Using nested catchment, based only on optimizing parameters sensitive particle swarm optimization improved...
Abstract. Dryland salinity remains a major global natural resource management concern, and which is amplified in Australia. However, limited detailed space-time data sets with observations of stream groundwater has constrained deep understanding the range processes that can lead to dryland problems landscapes. The aim this study report on open dataset resulting from 14-year collection effort subcatchment Murrumbidgee catchment New South Wales, Over period series different sampling campaigns...
Identifying physical catchment processes from streamflow data, such as quick- and slow-flow paths, remains challenging. This study is designed to explore whether a flexible nonparametric regression model (generalized additive model, GAM) can be used infer different flow paths. assumes that the data relationship in data-driven models also reflection of processes. The GAM, using time-lagged covariates, was fitted synthetic rainfall–runoff simulated simple linear reservoirs. Partial plots...