Francis H. S. Chiew

Preferred states in spatial soil moisture patterns: Local and nonlocal controls

In this paper we develop a conceptual and observational case in which soil water patterns in temperate regions of Australia switch between two preferred states. The wet state is dominated by lateral water movement through both surface and subsurface paths, with catchment terrain leading to organization of wet areas along drainage lines. We denote this as nonlocal control. The dry state is dominated by vertical fluxes, with soil properties and only local terrain (areas of high convergence) influencing spatial patterns. We denote this as local control. The switch is described in terms of the dominance of lateral over vertical water fluxes and vice versa. When evapotranspiration exceeds rainfall, the soil dries to the point where hydraulic conductivity is low and any rainfall that occurs essentially wets up the soil uniformly and is evapotranspired before any significant lateral redistribution takes place. As evapotranspiration decreases and/or rainfall increases, areas of high local convergence become wet, and runoff that is generated moves downslope, rapidly wetting up the drainage lines. In the wet to dry transitional period a rapid increase in potential evapotranspiration (and possibly a decrease in rainfall) causes drying of the soil and “shutting down” of lateral flow. Vertical fluxes dominate and the “dry” pattern is established. Three data sets from two catchments are presented to support the notion of preferred states in soil moisture, and the results of a modeling exercise on catchments from a range of climatic conditions illustrate that the conclusions from the field studies may apply to other areas. The implications for hydrological modeling are discussed in relation to methods for establishing antecedent moisture conditions for event models, for distribution models, and for spatially distributing bulk estimates of catchment soil moisture using indices.

El Nino/Southern Oscillation and Australian rainfall, streamflow and drought: Links and potential for forecasting

Abstract El Nino/Southern Oscillation (ENSO) has been linked to climate anomalies throughout the world. This paper presents an overview of the relationship between ENSO and rainfall, drought and streamflow in Australia. The teleconnection between ENSO and the hydroclimate of Australia is investigated using the empirical method of Ropelewski and Halpert and the potential for forecasting the hydroclimate variables are investigated by assessing the lag correlations between rainfall and streamflow and the indicators of ENSO several months earlier. The analyses show that dry conditions in Australia tend to be associated with El Nino. The link between rainfall and streamflow and ENSO is statistically significant in most parts of Australia, but it is not sufficiently strong to consistently predict rainfall and streamflow accurately. The teleconnection is stronger in the latter part of the year, and the analyses suggest that the indicators of ENSO can be used with some success to forecast spring rainfall in eastern Australia and summer rainfall in north-east Australia several months in advance. The ENSO indicators can also be used to help forecast spring runoff in south-east Australia and summer runoff in the north-east and east coasts of Australia. Unlike rainfall, the serial correlation in the streamflow data is generally similar or higher than the lag streamflow-ENSO correlation, and it must be used together with the ENSO indicators in developing streamflow forecast models. The seasonal forecasts of rainfall and streamflow are invaluable to the management of land and water resources, particularly in Australia, where the streamflow variability is higher than in most parts of the world.

Experimental study of pollutant accumulation on an urban road surface

An understanding of pollutant characteristics on impervious surfaces is essential to estimate pollutant washoff characteristics and to design methods to minimise the impacts of pollutants on the environment. This paper presents data on surface pollutant characteristics on an urban road surface in Melbourne, Australia, from samples collected over a 36 day period. The data indicate that buildup over the dry days occurs relatively quickly after a rain event, but slows down after several days as redistribution occurs. The surface pollutant also becomes finer over the dry days as it is disintegrated. The washoff of surface pollutant is dependent on the rainfall and runoff characteristics, but the results here show that common storms only remove a small proportion of the total surface pollutant load. The data also show that street sweeping may have an adverse impact on pollutant washoff because the street sweeper releases the finer material but only removes some of them, making the fine sediment available for washoff by the next storm. The data also show that most of the nutrients are attached to the finer sediments, and to effectively reduce nutrient loads in particulates, treatment facilities must be able to remove the finer particles (down to 50 μm for TP and down to 10 μm for TN), and not just the total sediment or suspended solid load.

Estimation of rainfall elasticity of streamflow in Australia

Abstract Estimates of rainfall elasticity of streamflow in 219 catchments across Australia are presented. The rainfall elasticity of streamflow is defined here as the proportional change in mean annual streamflow divided by the proportional change in mean annual rainfall. The elasticity is therefore a simple estimate of the sensitivity of long-term streamflow to changes in long-term rainfall, and is particularly useful as an initial estimate of climate change impact in land and water resources projects. The rainfall elasticity of streamflow is estimated here using a hydrological modelling approach and a nonparametric estimator. The results indicate that the rainfall elasticity of streamflow (ϵ P ) in Australia is about 2.0–3.5 (observed in about 70% of the catchments), that is, a 1% change in mean annual rainfall results in a 2.0–3.5% change in mean annual streamflow. The rainfall elasticity of streamflow is strongly correlated to runoff coefficient and mean annual rainfall and streamflow, where streamflow is more sensitive to rainfall in drier catchments, and those with low runoff coefficients. There is a clear relation-ship between the ϵ P values estimated using the hydrological modelling approach and those estimated using the nonparametric estimator for the 219 catchments, although the values estimated by the hydrological modelling approach are, on average, slightly higher. The modelling approach is useful where a detailed study is required and where there are sufficient data to reliably develop and calibrate a hydrological model. The nonparametric estimator is useful where consistent estimates of the sensitivity of long-term streamflow to climate are required, because it is simple to use and estimates the elasticity directly from the historical data. The nonparametric method, being model independent, can also be easily applied in comparative studies to data sets from many catchments across large regions.

Comparison of six rainfall-runoff modelling approaches

Abstract Six rainfall-runoff modelling approaches — simple polynomial equation, simple process equation (tanh equation), simple time-series equation (Tsykin equation), complex time-series model (IHACRES), simple conceptual model (SFB) and complex conceptual model (MODHYDROLOG) — are compared in this paper with the models used to simulate daily, monthly and annual flows in eight unregulated catchments. The complex conceptual model gives, by far, the best simulation of daily high and low flows, and can estimate adequately daily flows for the wetter catchments. It can provide satisfactory estimates of monthly and annual catchment yields in almost all catchments. However, the time-series approaches and the simple conceptual model can also provide adequate estimates of monthly and annual yields in the wetter catchments. As it is much easier to use these approaches than the complex conceptual model, the simpler methods may be used to estimate monthly and annual runoff in the wetter catchments.

Influence of Rainfall Scenario Construction Methods on Runoff Projections

Abstract The future rainfall series used to drive hydrological models in most climate change impact studies is informed by global climate models (GCMs). This paper compares future runoff projections in ∼11 000 0.25° grid cells across Australia from a daily rainfall–runoff model driven with future daily rainfall series obtained using three simple scaling methods, informed by 14 GCMs. In the constant scaling and daily scaling methods, the historical daily rainfall series is scaled by the relative difference between GCM simulations for the future and historical climates. The constant scaling method scales all the daily rainfall by the same factor, and the daily scaling method takes into account changes in the daily rainfall distribution by scaling the different daily rainfall amounts differently. In the daily translation method, the GCM future daily rainfall series is translated to a 0.25° gridcell rainfall series using the relationship established between the historical GCM-scale rainfall and 0.25° gridcell...

Seasonal streamflow forecasting in eastern Australia and the El Niño–Southern Oscillation

Previous studies have identified a strong link between climate variability in Australia and the El Nino–Southern Oscillation (ENSO). This paper describes the development and use of a seasonal streamflow forecast model based on an optimal linear combination of forecasts derived from climatology, persistence, the Southern Oscillation index (SOI), and equatorial Pacific sea surface temperatures (SST). The model builds on the work of the Australian Bureau of Meteorology and that of other researchers who have investigated southeast Australian rivers. The model is tested using 66 years of unimpaired streamflow data from 10 eastern Australian catchments. Results from testing the model further support the ENSO-hydroclimate link, showing that eastern Australia generally receives below normal streamflow during El Nino conditions and above normal streamflow during La Nina conditions. In southeast Australia the SOI is a better predictor for July–September and October–December streamflow and the SST a better predictor of January–March and April–June streamflow. For many of the seasons and stations, the skill associated with the cross-validation forecast is better than that drawn from the baseline condition of climatology.

Simulation of the impacts of climate change on runoff and soil moisture in Australian catchments

Abstract The impacts of climate change on runoff and soil moisture in 28 Australian catchments are simulated using a hydrologic daily rainfall-runoff model. Two methods are used to provide the climate change scenarios. First, a range of arbitrary changes in temperature and precipitation are applied to the calibrated rainfall-runoff model to study the sensitivity of runoff and soil moisture to potential changes in the climate. Second, results from five global climate model (GCM) enhanced greenhouse experiments are analysed to provide regional climate change scenarios to estimate the range of plausible changes in runoff and soil moisture by the years 2030 and 2070. The sensitivity analyses indicate that changes in rainfall are always amplified in runoff with the amplification factor for runoff being higher in drier catchments. The change in rainfall has little effect on the soil moisture in wet catchments but in drier catchments, the percentage change in soil moisture levels can be greater than the percentage change in rainfall. Compared to precipitation, temperature increases alone have negligible impacts on the runoff and soil moisture. The simulations using the GCM scenarios indicate increases in annual runoff of up to 25% by the year 2030 in the wet tropical catchments near the north-east coast of Australia. The GCMs do not agree in the direction of rainfall change in south-east Australia, and the simulations show runoff changes of up to ±20% by 2030. For Tasmanian catchments, up to 10% increase in runoff is simulated whereas for catchments in the South Australian Gulf, up to 35% decrease in annual runoff is simulated for 2030. Near the western coast of Australia, the simulations show runoff changes of up to ±50%. These results show the potential for climate change to bring about runoff modifications that may require a significant planning response. They are also indicative of the fact that hydrological impacts affecting water supply and flood studies may be important in considering the cost and benefits of potential climate change.

Global ENSO-streamflow teleconnection, streamflow forecasting and interannual variability

Abstract El Niño Southern Oscillation (ENSO) has been linked to climate anomalies throughout the world. This paper presents an overview of global ENSO-streamflow teleconnection and identifies regions where the relationship may be exploited to forecast streamflow several months ahead. The teleconnection is investigated by fitting a first harmonic to 24-month El Niño streamflow composites from 581 catchments worldwide and the potential for forecasting is investigated by calculating the lag correlation between streamflow and two indicators of ENSO. The analyses indicate clear ENSO-streamflow teleconnections in many catchments, some of which are consistent across large geographical regions. Strong and regionally consistent ENSO-streamflow teleconnections are identified in Australia and New Zealand, South and Central America, and weaker signals are identified in some parts of Africa and North America. The results suggest that the ENSO-streamflow relationship and the serial correlation in streamflow can be used to successfully forecast streamflow. The streamflow forecasts can be used to help manage water resources, particularly in systems with high interannual variability in Australia, southern and drier parts of Africa and some areas of North America.

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–...