A5015096383- Soil Moisture and Remote Sensing
- Hydrology and Watershed Management Studies
- Meteorological Phenomena and Simulations
- Soil and Unsaturated Flow
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
- Precipitation Measurement and Analysis
- Climate change and permafrost
- Hydrological Forecasting Using AI
- Geophysics and Gravity Measurements
- Flood Risk Assessment and Management
- Reservoir Engineering and Simulation Methods
- Cryospheric studies and observations
- Geophysical Methods and Applications
- Atmospheric aerosols and clouds
- Hydrology and Drought Analysis
- Infrastructure Maintenance and Monitoring
Bureau of Meteorology
2019-2022
The University of Melbourne
2007-2015
This paper describes a soil moisture data set from the 82,000 km 2 Murrumbidgee River Catchment in southern New South Wales, Australia. Data have been archived Soil Moisture Monitoring Network (MSMMN) since its inception September 2001. The represents range of conditions typical much temperate Australia, with climate ranging semiarid to humid and land use including dry irrigated agriculture, remnant native vegetation, urban areas. There are total 38 moisture‐monitoring sites across...
In providing uniform spatial coverage, satellite-based rainfall estimates can potentially benefit hydrological modeling, particularly for flood prediction. Maximizing the value of information from such data requires knowledge its error. The most recent Tropical Rainfall Measuring Mission (TRMM) 3B42RT (TRMM-RT) satellite product version 7 (v7) was used examining evaluation procedures against in situ gauge across mainland Australia at a daily time step, over 9 year period. This provides...
Abstract. A simple and effective two-step data assimilation framework was developed to improve soil moisture representation in an operational large-scale water balance model. The first step is a Kalman-filter-type sequential state updating process that exploits temporal covariance statistics between modelled satellite-derived produce analysed estimates. second use surface estimates impart mass conservation constraints (mass redistribution) on related states fluxes of the model using tangent...
The water and energy fluxes at the land-atmosphere interface depend heavily on soil moisture content, which imposes a significant control evaporation, infiltration runoff.Nonetheless, temporal evolution is not easy to measure or monitor large scales due its spatial variability, largely driven by local variation in properties vegetation cover.As consequence, dynamics are generally estimated using land surface models, with model physics based lowresolution property maps, may include errors...
The quality of runoff/streamflow modelling is critically dependent on the rainfall forcing data and a quantitative understanding its uncertainty.More accurate with clearly defined uncertainty has implications for water resource management flood prediction.This important Lake Eyre Basin (LEB) in central Australia where landscape very flat hydrophobic soils are common.The LEB also interest terms climate given that it predominantly semi-arid/arid large north-south gradient.The north subject to...
The ability to quantify soil moisture content over depths including the root zone is important for predicting key hydrological processes a range of applications in agriculture, emergency planning, and weather prediction.Remote-sensing provides large amount spatially distributed information related water balance quantities.This includes brightness temperature data from passive microwave sensors such as Advanced Microwave Scanning Radiometer Earth Observing System (AMSR-E), which used estimate...
Abstract. A simple and effective two-step data assimilation framework was developed to improve soil moisture representation in an operational large-scale water balance model. The first step is the sequential state updating process that exploits temporal covariance statistics between modelled satellite-derived produce analysed estimates. second use surface estimates impart mass conservation constraints (mass redistribution) on related states fluxes of model a post-analysis adjustment after at...
Calibration is the process of estimating optimal parameters for a model to accurately reflect real system, using historical records system data.The calibration, however, frequently limited by availability, quality, quantity and nature ground observations.Lack streamflow observations in vast majority world, example, constrains calibration hydrologic land surface models.In this study, an attempt made calibrate satellite retrievals soil moisture evapotranspiration (ET), without relying on...
Abstract Accurate initial conditions play a critical role in improving predictive accuracy of hydrological models for quantities such as streamflow generation. Streamflow observations from situ gauging sites have been assimilated wide range past research to improve lumped catchment streamflow. However, spatio‐temporal state updating distributed through data assimilation (DA) remains challenge due the large dimensional disparity between model space and observation space. This study explores...
A simple and robust method for assimilating satellite soil moisture (SM) products into the Australian Water Resources Assessment (AWRA) model was developed tested via community modelling system, AWRA-CMS.The requires time series of two products, along with AWRA simulations upper-layer water storage an offline determination weights use in optimal merging models observations triple collocation (TC) technique.The candidate data sources were near real-time from Soil Moisture Active/Passive...
<p>Climate change is already impacting on Australian water resources with step changes in rainfall regimes, catchment functioning and drier, hotter conditions creating major challenges for resource management.  Water most parts of the country are influenced by high interannual variability. Thus Australia's operational management, as well policy infrastructure development decisions require resolution information that realistically defines this variability both past,...
Earth and Space Science Open Archive This preprint has been submitted to is under consideration at Geophysical Research Letters. ESSOAr a venue for early communication or feedback before peer review. Data may be preliminary.Learn more about preprints preprintOpen AccessYou are viewing the latest version by default [v1]Operational soil moisture data assimilation improved continental water balance predictionAuthors Siyuan Tian iD Luigi John Renzullo Robert C. Pipunic Julien Lerat Wendy...