Jin Teng

Impact of DEM accuracy and resolution on topographic indices

Topography is an important land-surface characteristic that affects most aspects of the water balance in a catchment, including the generation of surface and sub-surface runoff; the flow paths followed by water as it moves down and through hillslopes and the rate of water movement. All of the spatially explicit fully distributed hydraulic and hydrological models use topography (represented by the DEM of the area modelled) to derive bathymetry. DEM is also used to derive some other key information critical in fully distributed hydraulic and hydrological models. With high-resolution DEMs such as LiDAR (Light Detection and Ranging) becoming more readily available and also with the advancements in computing facilities which can handle these large data sets, there is a need to quantify the impact of using different resolution DEMs (e.g. 1 m against 10 m or 25 m) on hydrologically important variables and the loss of accuracy and reliability of the results as we move from high resolution to coarser resolution. The results from statistical analysis carried out to compare field survey elevations with the LiDAR DEM-derived elevations, show that there are small differences between the two data sets but LiDAR DEM is a reasonably good representation of the actual ground surface compared to other commonly used DEMs derived from contour maps. The results from the analysis clearly show that the accuracy and resolution of the input DEM have serious implications on the values of the hydrologically important spatial indices derived from the DEM. The result also indicates that the loss of details by re-sampling the higher resolution DEM to coarser resolution are much less compared to the details captured in the commonly available coarse resolution DEM derived from contour maps. Topographic indices based on contour derived DEMs should be used with caution and where available, the higher resolution DEM should be used instead of the coarse resolution one.

Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

AbstractThis paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–...

An integrated modelling framework for regulated river systems

Management of regulated water systems has become increasingly complex due to rapid socio-economic growth and environmental changes in river basins over recent decades. This paper introduces the Source Integrated Modelling System (IMS), and describes the individual modelling components and how they are integrated within it. It also describes the methods employed for tracking and assessment of uncertainties, as well as presenting outcomes of two case study applications. Traditionally, the mathematical tools for water resources planning and management were generally designed for sectoral applications with, for example, groundwater being modelled separately from surface water. With the increasing complexity of water resources management in the 21st century those tools are becoming outmoded. Water management organisations are increasingly looking for new generation tools that allow integration across domains to assist their decision making processes for short-term operations and long-term planning; not only to meet current needs, but those of the future as well. In response to the need for an integrated tool in the water industry in Australia, the eWater Cooperative Research Centre (CRC) has developed a new generation software package called the Source IMS. The Source IMS is an integrated modelling environment containing algorithms and approaches that allow defensible predictions of water flow and constituents from catchment sources to river outlets at the sea. It is designed and developed to provide a transparent, robust and repeatable approach to underpin a wide range of water planning and management purposes. It can be used to develop water sharing plans and underpin daily river operations, as well as be used for assessments on water quantity and quality due to changes in: i) land-use and climate; ii) demands (irrigation, urban, ecological); iii) infrastructure, such as weirs and reservoirs; iv) management rules that might be associated with these; and v) the impacts of all of the above on various ecological indices. The Source IMS integrates the existing knowledge and modelling capabilities used by different state and federal water agencies across Australia and has additional functionality required for the river system models that will underpin the next round of water sharing plans in the country. It is built in a flexible modelling environment to allow stakeholders to incorporate new scientific knowledge and modelling methods as they evolve, and is designed as a generic tool suitable for use across different jurisdictions. Due to its structure, the platform can be extended/customised for use in other countries and basins, particularly where there are boundary issues.

Rainfall-runoff Modelling across Southeast Australia: Datasets, Models and Results

Abstract This study describes a daily rainfall, potential evaporation and streamflow data set compiled for the important water resources region of southeast Australia, and the application of six commonly used lumped conceptual rainfall-runoff models to estimate daily runoff across the region. The daily climate data set and the daily modelled runoff are available from 1895 to 2008 at 0.05° grid resolution across the region. The modelling exercise indicates that the rainfall-runoff models can generally be calibrated to reproduce the daily observed streamflow (for 232 catchments in the high runoff generation areas), and the regionalisation results indicate that the use of optimised parameter values from a gauged catchment nearby can model runoff reasonably well in the ungauged areas. There are differences between the six models, but they are relatively small when used to describe aggregated results across large regions.

Flood inundation modelling

This paper reviews state-of-the-art empirical, hydrodynamic and simple conceptual models for determining flood inundation. It explores their advantages and limitations, highlights the most recent advances and discusses future directions. It addresses how uncertainty is analysed in this field with the various approaches and identifies opportunities for handling it better. The aim is to inform scientists new to the field, and help emergency response agencies, water resources managers, insurance companies and other decision makers keep up-to-date with the latest developments. Guidance is provided for selecting the most suitable method/model for solving practical flood related problems, taking into account the specific outputs required for the modelling purpose, the data available and computational demands. Multi-model, multi-discipline approaches are recommended in order to further advance this research field. This paper reviews state-of-the-art flood inundation models.It explores their advantages and limitations.It highlights the most recent advances and discusses future directions.It addresses how uncertainty is analysed and identifies opportunities for handling it better.

Observed hydrologic non-stationarity in far south-eastern Australia: implications for modelling and prediction

The term ‘hydrologic non-stationarity’ has been used to describe many things, ranging from different climate-runoff relationships evident in different periods within a long hydroclimate time series to changes in hydroclimate characteristics and dominant hydrological processes in an increasingly warmer and higher CO2 world. This paper presents several examples of observed ‘hydrologic non-stationarity’ in far south-eastern Australia exposed by the prolonged 1997–2009 “Millennium” drought, focussing on the implications of this hydrologic non-stationarity on hydrological modelling and prediction. The runoff decline during the drought was unprecedented in the instrumental historical record. It was caused not only by the lower annual rainfall, but also by changes in other climate characteristics (lack of any high rainfall years, change in rainfall seasonality and higher temperatures) and dominant hydrological processes (reduced surface–groundwater connection and farm dams intercepting proportionally more water during dry periods). Hydrological models developed and calibrated against pre-1997 data cannot predict adequately the flow volumes and runoff characteristics during the drought. However, as the Millennium drought has exposed these extreme conditions, models can now be developed and calibrated to represent these, as well other conditions observed in the instrumental historical records (i.e., hydrologic non-stationarity that has already been observed). Such models should be able to satisfactorily predict the near-term runoff which will be influenced mainly by the rainfall inputs. However, further into the future, runoff will be increasingly influenced by higher temperatures and changed ecohydrological processes under higher CO2. Reliably modelling these is difficult because of the complex interactions and feedbacks between many variables and processes in a future environment not seen in the past (i.e., hydrologic non-stationarity that has not been observed).

Evaluating rainfall patterns using physics scheme ensembles from a regional atmospheric model

This study evaluated the ability of Weather Research and Forecasting (WRF) multi-physics ensembles to simulate storm systems known as East Coast Lows (ECLs). ECLs are intense low-pressure systems that develop off the eastern coast of Australia. These systems can cause significant damage to the region. On the other hand, the systems are also beneficial as they generate the majority of high inflow to coastal reservoirs. It is the common interest of both hazard control and water management to correctly capture the ECL features in modeling, in particular, to reproduce the observed spatial rainfall patterns. We simulated eight ECL events using WRF with 36 model configurations, each comprising physics scheme combinations of two planetary boundary layer (pbl), two cumulus (cu), three microphysics (mp), and three radiation (ra) schemes. The performance of each physics scheme combination and the ensembles of multiple physics scheme combinations were evaluated separately. Results show that using the ensemble average gives higher skill than the median performer within the ensemble. More importantly, choosing a composite average of the better performing pbl and cu schemes can substantially improve the representation of high rainfall both spatially and quantitatively.

Estimation of Climate Change Impact on Mean Annual Runoff across Continental Australia Using Budyko and Fu Equations and Hydrological Models

AbstractThis paper presents the climate change impact on mean annual runoff across continental Australia estimated using the Budyko and Fu equations informed by projections from 15 global climate models and compares the estimates with those from extensive hydrological modeling. The results show runoff decline in southeast and far southwest Australia, but elsewhere across the continent there is no clear agreement between the global climate models in the direction of future precipitation and runoff change. Averaged across large regions, the estimates from the Budyko and Fu equations are reasonably similar to those from the hydrological models. The simplicity of the Budyko equation, the similarity in the results, and the large uncertainty in global climate model projections of future precipitation suggest that the Budyko equation is suitable for estimating climate change impact on mean annual runoff across large regions. The Budyko equation is particularly useful for data-limited regions, for studies where o...

Conceptual Rainfall–Runoff Model Performance with Different Spatial Rainfall Inputs

AbstractDifferent methods have been used to obtain the daily rainfall time series required to drive conceptual rainfall–runoff models, depending on data availability, time constraints, and modeling objectives. This paper investigates the implications of different rainfall inputs on the calibration and simulation of 4 rainfall–runoff models using data from 240 catchments across southeast Australia. The first modeling experiment compares results from using a single lumped daily rainfall series for each catchment obtained from three methods: single rainfall station, Thiessen average, and average of interpolated rainfall surface. The results indicate considerable improvements in the modeled daily runoff and mean annual runoff in the model calibration and model simulation over an independent test period with better spatial representation of rainfall. The second experiment compares modeling using a single lumped daily rainfall series and modeling in all grid cells within a catchment using different rainfall inp...

A GIS‐Based Tool for Spatial and Distributed Hydrological Modelling: CLASS Spatial Analyst

CLASS Spatial Analyst is a GIS tool which can be used to support spatially distributed hydrological modelling. The tool generates a number of spatial layers that can be used for many practical applications. These include climate zoning, multi-resolution DEMs, Compound Topographic Index (CTI) (also referred to as Topographic Wetness Index, TWI), lateral multiple flow paths, accumulation and dispersion of water and solutes from hazard areas, estimation of soil depth, soil material/horizon distribution and soil moisture storage capacity in different parts of the landscape. Although each of these tasks can be undertaken separately using spatial software packages such as ArcGIS, GRASS, TIME, and MapInfo, this tool puts together all these tasks into a single application which provides the user with an option of undertaking some or all of them within this application. The technology used in this tool is supported by various peer-reviewed publications (e.g. Tarboton 1997, Gallant and Dowling 2003).