Murray C. Peel

Hydrological modelling in a changing world

Changing hydrological conditions due to climate, land use and infrastructure pose significant ongoing challenges to the hydrological research and water management communities. While, traditionally, hydrological models have assumed stationary conditions, there has been much progress since 2005 on model parameter estimation under unknown or changed conditions and on techniques for modelling in those conditions. There is an analogy between extrapolation in space (termed Prediction in Ungauged Basins, PUB), and extrapolation in time (termed Prediction in Ungauged Climates, PUC) that can be exploited for estimating model parameters. Methods for modelling changing hydrological conditions need to progress beyond the current scenario approach, which is reliant upon precalibrated models. Top-down methods and analysis of spatial gradients of a variable of interest, instead of temporal gradients (a method termed ‘Trading space for time’) show much promise for validating more complex model projections. Understanding hydrological processes and how they respond to change, along with quantification of parameter estimation and modelling process uncertainty will continue to be active areas of research within hydrology. Contributions from these areas will not only help inform future climate change impact studies about what will change and by how much, but also provide insight into why any changes may occur, what changes we are able to predict in a realistic manner, and what changes are beyond the current predictability of hydrological systems.

Identification and explanation of continental differences in the variability of annual runoff

Continental differences in the variability of annual runoff were investigated using an expanded and improved database to that used in previous work. A statistical analysis of the data, divided by continent and Koppen climate type, revealed that continental differences exist in the variability of annual runoff. The variability of annual runoff for temperate Australia, arid southern Africa and possibly temperate southern Africa were noted to be generally higher than that of other continents with data in the same climate type. A statistical analysis of annual precipitation by continent and Koppen climate type revealed that differences in the variability of annual precipitation could account for some but not all the observed differences in the variability of annual runoff. A literature review of potential causes of continental differences in evapotranspiration resulted in the hypothesis that the significantly higher variability of annual runoff in temperate Australia and possibly temperate southern Africa may be due to the distribution of evergreen and deciduous vegetation. The process model Macaque was used to test this hypothesis. The model results indicate that the variability of annual runoff may be between 1 and 99% higher for catchments covered in evergreen vegetation as opposed to deciduous vegetation, depending on mean annual precipitation and the seasonality of precipitation. It is suggested that the observed continental differences in the variability of annual runoff are largely caused by continental differences in the variability of annual precipitation and in temperate regions the distribution of evergreen and deciduous vegetation in conjunction with the distribution of mean annual precipitation and precipitation seasonality.

The utility of L-moment ratio diagrams for selecting a regional probability distribution

Abstract L-moment ratio diagrams are increasingly being used in the literature for selecting a probability distribution function for regional frequency analysis. Two graphical methods are often used in the distribution selection process, the sample average and a line of best-fit through the sample L-moment ratios. Examples of homogeneous and heterogeneous regional samples are simulated to illustrate the utility of the two distribution selection methods. Distribution selection for homogeneous regional data is best based on the sample average and not on a line of best-fit through the data points. For very heterogeneous regional data, exhibiting a large range in the distributions shape parameter, the line of best-fit is useful for distribution selection. These results emphasize the importance of using heterogeneity tests in conjunction with L-moment ratio diagrams.

Empirical mode decomposition using rational splines: an application to rainfall time series

Empirical mode decomposition (EMD), a relatively new form of time-series decomposition, has the feature of not assuming that a time series is linear or stationary, as is implicitly done in Fourier analysis. In natural time series such as records of rainfall, streamflow, temperature, etc., where most variables exhibit nonlinear and non-stationary behaviour, this feature is particularly useful, allowing more meaningful quantification of the proportion of variance in a time series due to fluctuations at different time scales, than previous spectral analysis techniques. However, in its original form, the EMD algorithm relies on cubic spline interpolation of the extrema, which often inflate the variance of the resultant components (intrinsic mode functions) and residual. In this paper, a suggested improvement to the EMD algorithm, using rational splines and flexible treatment of the end conditions, is outlined and the consequent effect on three exemplary annual rainfall time series is assessed as a proof of concept. It is recognized that many more examples are needed for the fine tuning of the ideas before it can be widely recommended and this work is currently underway.

Continental Runoff: A quality-controlled global runoff data set

Arising from: N. Gedney et al. 439, 835–838 (2006); Gedney et al. replyGedney et al. attribute an increase in the twentieth-century continental runoff to the suppression of plant transpiration by CO2-induced stomatal closure, by replicating a continental runoff data set. However, we have concerns about this data set and the methods used to construct it, in addition to those already raised, which we believe may undermine their conclusions.

Decadal Trends in Evaporation from Global Energy and Water Balances

AbstractSatellite and gridded meteorological data can be used to estimate evaporation (E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in “wet” regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman–Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation an...

Hydrology: catchment vegetation and runoff

The interactions between catchment vegetation and runoff continue to be a staple area of hydrological research. Drawing mainly upon material published since 2002, this report briefly reviews progress in this area with specific reference to: (1) paired and single catchment studies; (2) top-down models; and (3) the likely impact of climate change. Results from a wider range of paired and single catchments studies are revealing the complex relationship between catchment vegetation and runoff and prompting a reassessment of the methodologies used to generalize this relationship. Vegetation appears to have a significant influence on runoff at small scales, which reduces to a second-order influence, relative to aridity, at larger scales. Top-down models of catchment behaviour generally reflect this second-order influence at the large scale. As vegetation responds to CO2 enrichment under climate change, the magnitude and direction of associated changes in runoff remains uncertain. A key element in quantifying the hydrological impact of climate change is the relationship between catchment vegetation and runoff, which continues to be a productive area of research within hydrology.

Chapter 4 – The Hydrology of the Mekong River

Publisher Summary The Mekong rises on the Tibetan Plateau at an altitude of about 5200 m and flows 4800 km southeast to the South China Sea, through six developing countries: China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. The Mekong catchment has an unusual shape. Most catchments tend to have a dendritic form, with the width of the catchment gradually decreasing downstream, producing a characteristic teardrop shape. The Mekong catchment, by contrast, progressively widens down valley so that its widest point is immediately upstream of its delta. The hydrology of the Mekong River is characterized by a huge mean annual discharge; concentrated in an extremely regular wet-season peak. The size of the wet-season peak and its highly predictable timing are the defining characteristics of large tropical monsoonal rivers. In the upper part of the Lower Mekong system, at Vientiane, the flow originating from China and Burma, the so-called Yunnan Component, not only provides most of the dry-season flows, but in addition, most of the floodwater during the majority of years. Even though floods can cause major devastation along the Mekong River, the peak discharge of the largest floods tends to be only about double the size of the bankfull discharge.

The influence of multiyear drought on the annual rainfall‐runoff relationship: An Australian perspective

Most current long-term (decadal and longer) hydrological predictions implicitly assume that hydrological processes are stationary even under changing climate. However, in practice, we suspect that changing climatic conditions may affect runoff generation processes and cause changes in the rainfall-runoff relationship. In this article, we investigate whether temporary but prolonged (i.e., of the order of a decade) shifts in rainfall result in changes in rainfall-runoff relationships at the catchment scale. Annual rainfall and runoff records from south-eastern Australia are used to examine whether interdecadal climate variability induces changes in hydrological behavior. We test statistically whether annual rainfall-runoff relationships are significantly different during extended dry periods, compared with the historical norm. The results demonstrate that protracted drought led to a significant shift in the rainfall-runoff relationship in ∼44% of the catchment-dry periods studied. The shift led to less annual runoff for a given annual rainfall, compared with the historical relationship. We explore linkages between cases where statistically significant changes occurred and potential explanatory factors, including catchment properties and characteristics of the dry period (e.g., length, precipitation anomalies). We find that long-term drought is more likely to affect transformation of rainfall to runoff in drier, flatter, and less forested catchments. Understanding changes in the rainfall-runoff relationship is important for accurate streamflow projections and to help develop adaptation strategies to deal with multiyear droughts.

Modelling the long term water yield impact of wildfire and other forest disturbance in Eucalypt forests

Disturbance of forested catchments by fire, logging, or other natural or human induced events that alter the evapotranspiration regime may be a substantial threat to domestic, environmental and industrial water supplies. This paper describes the physically-based modelling of the long term changes in water yield from two wildfire affected catchments in north-eastern Victoria, Australia, and of fire and climate change scenarios in Melbournes principal water supply catchment. The effect of scale, data availability and quality, and of forest species parameterisation are explored. The modelling demonstrates the importance of precipitation inputs, with Nash and Sutcliffe Coefficients of Efficiency of predicted versus observed monthly flows increasing from 0.5 to 0.8 with a higher density of rainfall stations, and where forest types are well parameterised. Total predicted flow volumes for the calibrations were within 1% of the observed for the Mitta Mitta River catchment and <4% for the Thomson River, but almost -10% for the less well parameterised Tambo River. Despite the issues of data availability simulations demonstrated the potential for significant impacts to water supply in SE Australia from wildfire and climate change. For example, for the catchments modelled the moderate climate change impact on water yield was more pronounced than the worst fire scenario. Both modelled cases resulted in long term water yield declines exceeding 20%, with the climate change impact nearing 30%. A simulation using observed data for the first four post-fire years at the Mitta Mitta River catchment showed Macaque was able to accurately predict total flow.