Understanding hydrological processes with scarce data in a mountain environment

Performance of process‐based hydrological models is usually assessed through comparison between simulated and measured streamflow. Although necessary, this analysis is not sufficient to estimate the quality and realism of the modelling since streamflow integrates all processes of the water cycle, including intermediate production or redistribution processes such as snowmelt or groundwater flow. Assessing the performance of hydrological models in simulating accurately intermediate processes is often difficult and requires heavy experimental investments. In this study, conceptual hydrological modelling (using SWAT) of a semi‐arid mountainous watershed in the High Atlas in Morocco is attempted. Our objective is to analyse whether good intermediate processes simulation is reached when global‐satisfying streamflow simulation is possible. First, parameters presenting intercorrelation issues are identified: from the soil, the groundwater and, to a lesser extent, from the snow. Second, methodologies are developed to retrieve information from accessible intermediate hydrological processes. A geochemical method is used to quantify the contribution of a superficial and a deep reservoir to streamflow. It is shown that, for this specific process, the model formalism is not adapted to our study area and thus leads to poor simulation results. A remote‐sensing methodology is proposed to retrieve the snow surfaces. Comparison with the simulation shows that this process can be satisfyingly simulated by the model. The multidisciplinary approach adopted in this study, although supported by the hydrological community, is still uncommon. Copyright © 2007 John Wiley & Sons, Ltd.     

Linking hydrologic signatures to hydrologic processes: A review

Hydrologic signatures are metrics that quantify aspects of streamflow response. Linking signatures to underlying processes enables multiple applications, such as selecting hydrologic model structure, analysing hydrologic change, making predictions in ungauged basins, and classifying watershed function. However, many lists of hydrologic signatures are not process-based, and knowledge about signature-process links has been scattered among studies from experimental watersheds and model selection experiments. This review brings together those studies to catalogue more than 50 signatures representing evapotranspiration, snow storage and melt, permafrost, infiltration excess, saturation excess, groundwater, baseflow, connectivity, channel processes, partitioning, and human alteration. The review shows substantial variability in the number, type, and timescale of signatures available to represent each process. Many signatures provide information about groundwater storage, partitioning, and connectivity, whereas snow processes and human alteration are underrepresented. More signatures are related to the seasonal scale than the event timescale, and land surface processes (ET, snow, and overland flow) have no signatures at the event scale. There are limitations in some signatures that test for occurrence but cannot quantify processes, or are related to multiple processes, making automated analysis more difficult. This review will be valuable as a reference for hydrologists seeking to use streamflow records to investigate a particular hydrologic process or to conduct large-sample analyses of patterns in hydrologic processes.     

Estimating impacts of wildfire and climate variability on streamflow in Victoria,Australia

Wildfires are common in Australia and can cause vegetation loss and affect hydrological processes such as interception, evapotranspiration, soil water storage and streamflow. This study investigates wildfire impacts on catchment mean annual streamflow for 14 Australian catchments that have been severely impacted by the 2009 Victoria wildfire, the second-worst wildfire disaster in Australia. A statistical approach based on sensitivity coefficients was used for quantifying the climate variability impacts on streamflow and the time trend analysis method was used to estimate the annual streamflow changes due to wildfire respectively. Our results show that wildfire has caused a noticeable increase in mean annual streamflow in the catchments with a burnt area above 70% for an immediate post-wildfire period (2009–2015) and the wildfire impact on streamflow is evidently larger than the climate change impact in the majority of burnt catchments. Furthermore, the wildfire impact on mean annual streamflow strongly increases with the burnt percentage area, indicated by R² = 0.73 between the two. The results also illustrate that catchments with high burnt percentage areas can have more potential to gain increased streamflow due to wildfires compared with that due to climate variability and can have significant streamflow change after wildfires above the 70% threshold of burnt area. These results provide evidence for evaluating large-scale wildfire impact on streamflow at small to medium-sized catchments, and guidance for process-based hydrological models for simulating wildfire impacts on hydrological processes for the immediate period after the wildfire.     

Surface and subsurface water contributions to streamflow from a mesoscale watershed in complex mountain terrain

An understanding of surface and subsurface water contributions to streamflow is essential for accurate predictions of water supply from mountain watersheds that often serve as water towers for downstream communities. As such, this study used the end‐member mixing analysis technique to investigate source water contributions and hydrologic flow paths of the 264 km² Boulder Creek Watershed, which drains the Colorado Front Range, USA. Four conservative hydrochemical tracers were used to describe this watershed as a 3 end‐member system, and tracer concentration reconstruction suggested that the application of end‐member mixing analysis was robust. On average from 2009 to 2011, snowmelt and rainwater from the subalpine zone and groundwater sampled from the upper montane zone contributed 54%, 22%, and 24% of the annual streamflow, respectively. These values demonstrate increased rainwater and decreased snow water contributions to streamflow relative to area‐weighted mean values derived from previous work at the headwater scale. Young water (2.3 ± 0.8 months) fractions of streamflow decreased from 18–22% in the alpine catchment to 8–10% in the lower elevation catchments and the watershed outlet with implications for subsurface storage and hydrological connectivity. These results contribute to a process‐based understanding of the seasonal source water composition of a mesoscale watershed that can be used to extrapolate headwater streamflow generation predictions to larger spatial scales.     

Modelling the interaction of climate,forest ecosystem,and hydrology to estimate catchment dissolved organic carbon export

The potential for increased loads of dissolved organic carbon (DOC) in streams and rivers is a concern for regulating the water quality in water supply watersheds. With increasing hydroclimatic variability related to global warming and shifts in forest ecosystem community and structure, understanding and predicting the magnitude and variability of watershed supply and transport of DOC over multiple time scales have become important research and management goals. In this study, we use a distributed process‐based ecohydrological model (Regional Hydro‐Ecological Simulation System [RHESSys]) to explore controls and predict streamflow DOC loads in Biscuit Brook. Biscuit Brook is a forested headwater catchment of the Neversink Reservoir, part of the New York City water supply system in the Catskill Mountains. Three different model structures of RHESSys were proposed to explore and evaluate hypotheses addressing how vegetation phenology and hydrologic connectivity between deep groundwater and riparian zones influence streamflow and DOC loads. Model results showed that incorporating dynamic phenology improved model agreement with measured streamflow in spring, summer, and fall and fall DOC concentration, compared with a static phenology. Additionally, the connectivity of deep groundwater flux through riparian zones with dynamic phenology improved streamflow and DOC flux in low flow conditions. Therefore, this study suggests the importance of inter‐annual vegetation phenology and the connectivity of deep groundwater drainage through riparian zones in the hydrology and stream DOC loading in this forested watershed and the ability of process‐based ecohydrological models to simulate these dynamics. The advantage of a process‐based modelling approach is specifically seen in the sensitivity to forest ecosystem dynamics and the interactions of hydroclimate variability with ecosystem processes controlling the supply and distribution of DOC. These models will be useful to evaluate different forest management approaches toward mitigating water quality concerns.     

System dynamics model for predicting floods from snowmelt in North American prairie watersheds

This study uses a system dynamics approach to explore hydrological processes in the geographic locations where the main contribution to flooding is coming from the snowmelt. Temperature is identified as a critical factor that affects watershed hydrological processes. Based on the dynamic processes of the hydrologic cycle occurring in a watershed, the feedback relationships linking the watershed structure, as well as the climate factors, to the streamflow generation were identified prior to the development of a system dynamics model. The model is used to simulate flood patterns generated by snowmelt under temperature change in the spring. Model structure captures a vertical water balance using five tanks representing snow, interception, surface, subsurface and groundwater storage. Calibration and verification results show that temperature change and snowmelt play a key role in flood generation. Results indicate that simulated values match observed data very well. The goodness‐of‐fit between simulated and observed peak flow data is measured using coefficient of efficiency, coefficient of determination and square of the residual mass curve coefficient. For the Assiniboine River all three measures were in the interval between 0·92 and 0·96 and for the Red River between 0·89 and 0·97. The model is capable of capturing the essential dynamics of streamflow formation. Model input requires a set of initial values for all state variables and the time series of daily temperature and precipitation information. Data from the Red River Basin, shared by Canada and the USA, are used in the model development and testing. Copyright © 2002 John Wiley & Sons, Ltd.     

A comprehensive assessment framework for attributing trends in streamflow and groundwater storage to climatic and anthropogenic changes: A case study in the typical semi-arid catchments of southern India

The clearest signs of hydrologic change can be observed from the trends in streamflow and groundwater levels in a catchment. During 1980–2007, significant declines in streamflow (−3.03 mm/year) and groundwater levels (−0.22 m/year) were observed in Himayat Sagar (HS) catchment, India. We examined the degree to which hydrologic changes observed in the HS catchment can be attributed to various internal and external drivers of change (climatic and anthropogenic changes). This study used an investigative approach to attribute hydrologic changes. First, it involves to develop a model and test its ability to predict hydrologic trends in a catchment that has undergone significant changes. Second, it examines the relative importance of different causes of change on the hydrologic response. The analysis was carried out using Modified Soil and Water Assessment Tool (SWAT), a semi-distributed rainfall-runoff model coupled with a lumped groundwater model for each sub- catchment. The model results indicated that the decline in potential evapotranspiration (PET) appears to be partially offset by a significant response to changes in rainfall. Measures that enhance recharge, such as watershed hydrological structures, have had limited success in terms of reducing impacts on the catchment-scale water balance. Groundwater storage has declined at a rate of 5 mm/y due to impact of land use changes and this was replaced by a net addition of 2 mm/y by hydrological structures. The impact of land use change on streamflow is an order of magnitude larger than the impact of hydrological structures and about is 2.5 times higher in terms of groundwater impact. Model results indicate that both exogenous and endogenous changes can have large impacts on catchment hydrology and should be considered together. The proposed comprehensive framework and approach demonstrated here is valuable in attributing trends in streamflow and groundwater levels to catchment climatic and anthropogenic changes.     

Sensitivity of streamflow from a Himalayan catchment to plausible changes in land cover and climate

Global climate change will likely increase temperature and variation in precipitation in the Himalayas, modifying both supply of and demand for water. This study assesses combined impacts of land‐cover and climate changes on hydrological processes and a rainfall‐to‐streamflow buffer indicator of watershed function using the Soil Water Assessment Tool (SWAT) in Kejie watershed in the eastern Himalayas. The Hadley Centre Coupled Model Version 3 (HadCM3) was used for two Intergovernmental Panel on Climate Change (IPCC) emission scenarios (A2 and B2), for 2010–2099. Four land‐cover change scenarios increase forest, grassland, crops, or urban land use, respectively, reducing degraded land. The SWAT model predicted that downstream water resources will decrease in the short term but increase in the long term. Afforestation and expansion in cropland will probably increase actual evapotranspiration (ET) and reduce annual streamflow but will also, through increased infiltration, reduce the overland flow component of streamflow and increase groundwater release. An expansion in grassland will decrease actual ET, increase annual streamflow and groundwater release, while decreasing overland flow. Urbanization will result in increases in streamflow and overland flow and reductions in groundwater release and actual ET. Land‐cover change dominated over effects on streamflow of climate change in the short and middle terms. The predicted changes in buffer indicator for land‐use plus climate‐change scenarios reach up to 50% of the current (and future) range of inter‐annual variability. Copyright © 2010 John Wiley & Sons, Ltd.     

Changes in streamflow regimes and their responses to different soil and water conservation measures in the Loess Plateau watersheds,China

Investigating the changes in streamflow regimes in response to various influencing factors contributes to our understanding of the mechanisms of hydrological processes in different watersheds and to water resource management strategies. This study examined streamflow regime changes by applying the indicators of hydrologic alteration method and eco-flow metrics to daily runoff data (1965–2016) from the Sandu, Hulu and Dali Rivers on the Chinese Loess Plateau, and then determined their responses to terracing, afforestation and damming. The Budyko water balance equation and the double mass curve method were used to separate the impacts of climate change and human activities on the mean discharge changes. The results showed that the terraced and dammed watersheds exhibited significant decreases in annual runoff. All hydrologic metrics indicated that the highest degree of hydrologic alteration was in the Sandu River watershed (terraced), where the monthly and extreme flows reduced significantly. In contrast, the annual eco-deficit increased significantly, indicating the highest reduction in streamflow among the three watersheds. The regulation of dams and reservoirs in the Dali River watershed has altered the flow regime, and obvious decreases in the maximum flow and slight increases in the minimum flow and baseflow indices were observed. In the Hulu River watershed (afforested), the monthly flow and extreme flows decreased slightly and were categorized as low-degree alteration, indicating that the long-term delayed effects of afforestation on hydrological processes. The magnitude of the eco-flow metrics varied with the alteration of annual precipitation. Climate change contributed 67.47% to the runoff reduction in the Hulu River watershed, while human activities played predominant roles in reducing runoff in the Sandu and Dali River watersheds. The findings revealed distinct patterns and causes of streamflow regime alteration due to different conservation measures, emphasizing the need to optimize the spatial allocation of measures to control soil erosion and utilize water resources on the Loess Plateau.     

Assessing effects of model complexity and structure on predictions of hydrological responses using serial and parallel model design

By utilizing functional relationships based on observations at plot or field scales, water quality models first compute surface runoff and then use it as the primary governing variable to estimate sediment and nutrient transport. When these models are applied at watershed scales, this serial model structure, coupling a surface runoff sub-model with a water quality sub-model, may be inappropriate because dominant hydrological processes differ among scales. A parallel modeling approach is proposed to evaluate how best to combine dominant hydrological processes for predicting water quality at watershed scales. In the parallel scheme, dominant variables of water quality models are identified based entirely on their statistical significance using time series analysis. Four surface runoff models of different model complexity were assessed using both the serial and parallel approaches to quantify the uncertainty on forcing variables used to predict water quality. The eight alternative model structures were tested against a 25-year high-resolution data set of streamflow, suspended sediment discharge, and phosphorous discharge at weekly time steps. Models using the parallel approach consistently performed better than serial-based models, by having less error in predictions of watershed scale streamflow, sediment and phosphorus, which suggests model structures of water quantity and quality models at watershed scales should be reformulated by incorporating the dominant variables. The implication is that hydrological models should be constructed in a way that avoids stacking one sub-model with one set of scale assumptions onto the front end of another sub-model with a different set of scale assumptions.     

Conceptual modelling to assess the influence of hydro-climatic variability on runoff processes in data scarce semi-arid Andean catchments

Using hydro-meteorological time series of 50 years and in situ measurements, the dominant runoff processes in perennial Andean headwater catchments in Chile were determined using the hydrological model HBV light. First, cluster analysis was used to identify dry, wet and intermediate years. From these, sub-periods were identified with contrasting seasonal climatic influences on streamflow. By calibrating the model across different periods, impacts on model performance, parameter sensitivity and identifiability were investigated, providing insights into differences in hydrological processes. The modelling approach suggested that, independently of a dry or wet period of calibration, the streamflow response is mostly consistent with flux from groundwater storage, while only a small fraction comes from direct routing of snowmelt. The variation of model parameters, such as the groundwater rate coefficient, was found to be consistent with differing recharge in wet and dry years. The resulting snowmelt–groundwater model is a realistic hypothesis of the hydrological operation of such complex, data scarce and semi-arid Andean catchments. This model may also be a useful tool for predictions of seasonal water availability and a basis for further field studies.     

Hydrological analysis of the Upper Tiber River Basin,Central Italy: a watershed modelling approach

The quantification of the various components of hydrological processes in a watershed remains a challenging topic as the hydrological system is altered by internal and external drivers. Watershed models have become essential tools to understand the behaviour of a catchment under dynamic processes. In this study, a physically based watershed model called Soil Water Assessment Tool was used to understand the hydrologic behaviour of the Upper Tiber River Basin, Central Italy. The model was successfully calibrated and validated using observed weather and flow data for the period of 1963–1970 and 1971–1978, respectively. Eighteen parameters were evaluated, and the model showed high relative sensitivity to groundwater flow parameters than the surface flow parameters. An analysis of annual hydrological water balance was performed for the entire upper Tiber watershed and selected subbasins. The overall behaviour of the watershed was represented by three categories of parameters governing surface flow, subsurface flow and whole basin response. The base flow contribution has shown that 60% of the streamflow is from shallow aquifer in the subbasins. The model evaluation statistics that evaluate the agreement between the simulated and the observed streamflow at the outlet of a watershed and other three different subbasins has shown a coefficient of determination (R²) from 0.68 to 0.81 and a Nash–Sutcliffe efficiency (E_NS) between 0.51 and 0.8 for the validation period. The components of the hydrologic cycle showed variation for dry and wet periods within the watershed for the same parameter sets. On the basis of the calibrated parameters, the model can be used for the prediction of the impact of climate and land use changes and water resources planning and management. Copyright © 2012 John Wiley & Sons, Ltd.     

Hydrological Outlook UK: an operational streamflow and groundwater level forecasting system at monthly to seasonal time scales

This paper describes the development of the first operational seasonal hydrological forecasting service for the UK, the Hydrological Outlook UK (HOUK). Since June 2013, this service has delivered monthly forecasts of streamflow and groundwater levels, with an emphasis on forecasting hydrological conditions over the next three months, accompanied by outlooks over longer time horizons. This system is based on three complementary approaches combined to produce the outlooks: (i) national-scale modelling of streamflow and groundwater levels based on dynamic seasonal rainfall forecasts, (ii) catchment-scale modelling where streamflow and groundwater level models are driven by historical meteorological forcings (i.e. the Ensemble Streamflow Prediction, ESP, approach), and (iii) a catchment-scale statistical method based on persistence and historical analogues. This paper provides the background to the Hydrological Outlook, describes the various component methods in detail and then considers the impact and usefulness of the product. As an example of a multi-method, operational seasonal hydrological forecasting system, it is hoped that this overview provides useful information and context for other forecasting initiatives around the world.     

Space–time changes in hydrological processes in response to human activities and climatic change in the south China

Due to the influence of climate change and human activities, more and more regions around the world are nowadays facing serious water shortages. This is particularly so with the Guangdong province, an economically prosperous region in China. This study aims at understanding the abrupt behavior of hydrological processes by analyzing monthly precipitation series from 257 rain gauging stations and monthly streamflow series from 25 hydrological stations using the likelihood ratio statistic and schwarz information criterion (SIC). The underlying causes of the changing properties of hydrological processes are investigated by analyzing precipitation changes and information of water reservoirs. It is found that (1) streamflow series in dry season seems to exhibit abrupt changes when compared to that in the flood season; (2) abrupt changes in the values of mean and variance of hydrological variables in the dry season are more common than those in the streamflow series in the flood season, which implies that streamflow in the dry season is more sensitive to human activities and climate change than that in the flood season; (3) no change points are identified in the annual precipitation and precipitation series in the flood season. Annual streamflow and streamflow in the flood season exhibit no abrupt changes, showing the influence of precipitation on streamflow changes in the flood season. However, streamflow changes in the dry season seem to be heavily influenced by hydrological regulations of water reservoirs. The results of this study are of practical importance for regional water resource management in the Guangdong province.     

Response of hydrology to climate change in the southern Appalachian Mountains using Bayesian inference

Predicting long‐term consequences of climate change on hydrologic processes has been limited due to the needs to accommodate the uncertainties in hydrological measurements for calibration, and to account for the uncertainties in the models that would ingest those calibrations and uncertainties in climate predictions as basis for hydrological predictions. We implemented a hierarchical Bayesian (HB) analysis to coherently admit multiple data sources and uncertainties including data inputs, parameters, and model structures to identify the potential consequences of climate change on soil moisture and streamflow at the head watersheds ranging from low to high elevations in the southern Appalachian region of the United States. We have considered climate change scenarios based on three greenhouse gas emission scenarios of the Interovernmental Panel on Climate Change: A2, A1B, and B1 emission scenarios. Full predictive distributions based on HB models are capable of providing rich information and facilitating the summarization of prediction uncertainties. With predictive uncertainties taken into account, the most pronounced change in soil moisture and streamflow would occur under the A2 scenario at both low and high elevations, followed by the A1B scenario and then by the B1 scenario. Uncertainty in the change of soil moisture is less than that of streamflow for each season, especially at high elevations. A reduction of soil moisture in summer and fall, a reduction or slight increase of streamflow in summer, and an increase of streamflow in winter are predicted for all three scenarios at both low and high elevations. The hydrological predictions with quantified uncertainties from a HB model could aid more‐informed water resource management in developing mitigation plans and dealing with water security under climate change. Copyright © 2012 John Wiley & Sons, Ltd.     

Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins

Approaches to modeling the continuous hydrologic response of ungauged basins use observable physical characteristics of watersheds to either directly infer values for the parameters of hydrologic models, or to establish regression relationships between watershed structure and model parameters. Both these approaches still have widely discussed limitations, including impacts of model structural uncertainty. In this paper we introduce an alternative, model independent, approach to streamflow prediction in ungauged basins based on empirical evidence of relationships between watershed structure, climate and watershed response behavior. Instead of directly estimating values for model parameters, different hydrologic response behaviors of the watershed, quantified through model independent streamflow indices, are estimated and subsequently regionalized in an uncertainty framework. This results in expected ranges of streamflow indices in ungauged watersheds. A pilot study using 30 UK watersheds shows how this regionalized information can be used to constrain ensemble predictions of any model at ungauged sites. Dominant controlling characteristics were found to be climate (wetness index), watershed topography (slope), and hydrogeology. Main streamflow indices were high pulse count, runoff ratio, and the slope of the flow duration curve. This new approach provided sharp and reliable predictions of continuous streamflow at the ungauged sites tested.     

Model calibration using hydropedological insights to improve the simulation of internal hydrological processes using SWAT+

Soils affect the distribution of hydrological processes by partitioning precipitation into different components of the water balance. Therefore, understanding soil-water dynamics at a catchment scale remains imperative to future water resource management. In this study, the value of hydropedological insights was examined to calibrate a processes-based model. Soil morphology was used as soft data to assist in the calibration of the Soil Water Assessment Tool (SWAT+) model at five different catchment scales (48, 56, 174, 674, and 2421 km²) in the Sabie River catchment, South Africa. The aim of this study was to calibrate the SWAT+ model to accurately simulate long-term monthly streamflow predictions as well as to reflect internal soil hydrological processes using a procedure focusing on hydropedology as a calibration tool in a multigauge system. Results indicated that calibration improved streamflow predictions where R² improved by 2%–8%. Nash-Sutcliffe Efficiency (NSE) improved from negative correlations to values exceeding 0.5 at four of the five catchment scales compared to the uncalibrated model. Results confirm that soil mapping units can be calibrated individually within SWAT+ to improve the representation of hydrological processes. Particularly, the spatial linkage between hydropedology and hydrological processes, which is captured within the soil map of the catchment, can be adequately reflected within the model simulations after calibration. This research will lead to an improved understanding of hydropedology as soft data to improve hydrological modelling accuracy.     

Quantifying the impacts of climate change and land use on hydrological processes: A comparison between mountain and lowland agricultural watersheds

Mountain and lowland watersheds are two distinct geographical units with considerably different hydrological processes. Understanding their hydrological processes in the context of future climate change and land use scenarios is important for water resource management. This study investigated hydrological processes and their driving factors and eco-hydrological impacts for these two geographical units in the Xitiaoxi watershed, East China, and quantified their differences through hydrological modelling. Hydrological processes in 24 mountain watersheds and 143 lowland watersheds were simulated based on a raster-based Xin'anjiang model and a Nitrogen Dynamic Polder (NDP) model, respectively. These two models were calibrated and validated with an acceptable performance (Nash-Sutcliffe efficiency coefficients of 0.81 and 0.50, respectively) for simulating discharge for mountain watersheds and water level for lowland watersheds. Then, an Indicators of Hydrological Alteration (IHA) model was used to help quantify the alterations to the hydrological process and their resulting eco-hydrological impacts. Based on the validated models, scenario analysis was conducted to evaluate the impacts of climate and land use changes on the hydrological processes. The simulation results revealed that (a) climate change would cause a larger increase in annual runoff than that under land use scenario in the mountain watersheds, with variations of 19.9 and 10.5% for the 2050s, respectively. (b) Land use change was more responsible for the streamflow increment than climate change in the lowland watersheds, causing an annual runoff to increase by 27.4 and 16.2% for the 2050s, respectively. (c) Land use can enhance the response of streamflow to the climatic variation. (d) The above-mentioned hydrological variations were notable in flood and dry season in the mountain watersheds, and they were significant in rice season in the lowland watersheds. (e) Their resulting degradation of ecological diversity was more susceptible to future climate change in the two watersheds. This study demonstrated that mountain and lowland watersheds showed distinct differences in hydrological processes and their responses to climate and land use changes.     

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 (? _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 ? _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.