Application of a rainfall-runoff model to three catchments in Iraq

Abstract

The capability of the Surface inFiltration Baseflow (SFB) conceptual rainfall-runoff model to simulate streamflow for three catchments selected from northern Iraq is investigated. These catchments differ in their climatic regimes and physical characteristics. Three versions of the model were tested: the original three-parameter model (SFB), the modified five-parameter model (SFB-5), and the modified six-parameter model (SFB-6). The available daily precipitation, potential evapotranspiration and runoff data were used in conjunction with a simulated annealing (SA) optimization technique to calibrate the various versions of the SFB model. A simple sensitivity analysis was then carried out to determine the relative importance of the model parameters. The study indicated that use of the original three parameter model was not adequate to simulate monthly streamflow in the selected catchments. The modified version (SFB-5) provided better runoff simulation than the original SFB model; overall a 19% increase was observed in the coefficient of determination (R²) between simulated and observed monthly runoff. The SFB-5 model performed with varying degrees of success among the catchments. The model performance in the validation stage was reasonable and comparable to that of the calibration stage. The sensitivity analysis of the SFB model for arid catchments revealed that the baseflow parameter (B) was the most sensitive one, while the S and F parameters were less sensitive than the B parameter.     

Calibration of snow parameters in SWAT: comparison of three approaches in the Upper Adige River basin (Italy)

The Soil and Water Assessment Tool (SWAT) model is generally applied in alpine catchments using a unique set of snow parameters for the entire basin, and calibration is based on discharge records only. This technical note presents three calibration procedures for snow parameters of SWAT considering snow water equivalent (SWE) values computed using a dense network of snow depth measurement stations available in the Upper Adige River basin, Italy. The first two procedures calibrate snow parameters according to the average sub-basin SWE: the first one defines a unique set of parameters for the entire basin, while the second allows for sub-basin variability. The last approach includes the elevation band SWE output in the calibration for each sub-basin and qualitatively compares it to the SWE computed from the available snow depth monitoring stations. This last method provides the best agreement between SWAT model results and SWE data.     

How informative are stream level observations in different geographic regions?

Simple runoff models with a low number of model parameters are generally able to simulate catchment runoff reasonably well, but they rely on model calibration, which makes their use in ungauged basins challenging. In a previous study it has been shown that a limited number of streamflow measurements can be quite informative for constraining runoff models. In practice, however, instead of performing such repeated flow measurements, it might be easier to install a stream level logger. Here, a dataset of 600+ gauged basins in the USA was used to study how well models perform when only stream level data, rather than streamflow data, are available. A runoff model (the HBV model) was calibrated assuming that only stream level observations were available, and the simulations were evaluated on the full observed streamflow record. The results indicate that stream level data alone can already provide surprisingly good model simulation results in humid catchments, whereas in arid catchments some form of quantitative information (e.g. a streamflow observation or a regional average value) is needed to obtain good results. These results are encouraging for hydrological observations in data scarce regions as level observations are much easier to obtain than streamflow measurements. Based on runoff modelling, it might even be possible to derive streamflow time series from the level data obtained from loggers, satellites or community‐based approaches. Copyright © 2016 John Wiley & Sons, Ltd.     

Model estimates of runoff in the closed,semiarid Estancia basin,central New Mexico,USA

Abstract

The 5000 km² topographically closed Estancia basin in central New Mexico has been the focus of several palaeoclimatic studies based on changes in the level of late Pleistocene Lake Estancia. A large, unknown volume of surface runoff and groundwater from adjacent mountains contributed to the hydrological balance during highstands and lowstands. The US Department of Agriculture hydrological model SWAT (Soil and Water Assessment Tool) and the US Geological Survey groundwater flow model MODFLOW, with the LAK2 package, were used in this study to estimate runoff and water balance under present climate. A Geographic Information Systems (GIS) interface was used for SWAT, digitized data were applied for soils and vegetation, and limited streamflow data were used to obtain an approximate calibration for the model. Simulated streamflow is generally within 30% of observed values, and simulated runoff for the entire basin is about 8% of the annual inflow volume needed to support lowstands of the former Lake Estancia. Results from the combined models suggest application to other palaeoclimate investigations in semiarid lake basins.     

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.     

SWAT-based runoff and sediment simulation in a small watershed,the loessial hilly-gullied region of China:capabilities and challenges

Model calibration and validation are necessary before applying it for scenario assessment and watershed management.This study presented the methodology of evaluating Soil and Water Assessment Tool(SWAT) and tested the feasibility of SWAT on runoff and sediment load simulation in the Zhifanggou watershed located in hilly-gullied region of China.Daily runoff and sediment event data from 1998-2008 were used in this study;data from 1998-2003 were used for calibration and 2004-2008 for validation.The evaluation statistics for the daily runoff simulation showed that the model results were acceptable,but the model underestimated the runoff for high-flow events.For sediment load simulation,the SWAT performed well in capturing the trend of sediment load,while the model tended to underestimate sediment load during both the calibration and validation periods. The disparity between observed and simulated data most likely resulted from limitations of the existing SCS-CN and MUSLE methods in the model.This study indicated that the modification of SWAT components is needed to take rainfall intensity and its duration into account to enhance the model performance on peak flow and sediment load simulation during heavy rainfall season.     

Parameter identification and uncertainty analysis for simulating streamflow in a river basin of Eastern India

Uncertainty is inherent in modelling studies. However, the quantification of uncertainties associated with a model is a challenging task, and hence, such studies are somewhat limited. As distributed or semi‐distributed hydrological models are being increasingly used these days to simulate hydrological processes, it is vital that these models should be equipped with robust calibration and uncertainty analysis techniques. The goal of the present study was to calibrate and validate the Soil and Water Assessment Tool (SWAT) model for simulating streamflow in a river basin of Eastern India, and to evaluate the performance of salient optimization techniques in quantifying uncertainties. The SWAT model for the study basin was developed and calibrated using Parameter Solution (ParaSol), Sequential Uncertainty Fitting Algorithm (SUFI‐2) and Generalized Likelihood Uncertainty Estimation (GLUE) optimization techniques. The daily observed streamflow data from 1998 to 2003 were used for model calibration, and those for 2004–2005 were used for model validation. Modelling results indicated that all the three techniques invariably yield better results for the monthly time step than for the daily time step during both calibration and validation. The model performances for the daily streamflow simulation using ParaSol and SUFI‐2 during calibration are reasonably good with a Nash–Sutcliffe efficiency and mean absolute error (MAE) of 0.88 and 9.70 m³/s for ParaSol, and 0.86 and 10.07 m³/s for SUFI‐2, respectively. The simulation results of GLUE revealed that the model simulates daily streamflow during calibration with the highest accuracy in the case of GLUE (R² = 0.88, MAE = 9.56 m³/s and root mean square error = 19.70 m³/s). The results of uncertainty analyses by SUFI‐2 and GLUE were compared in terms of parameter uncertainty. It was found that SUFI‐2 is capable of estimating uncertainties in complex hydrological models like SWAT, but it warrants sound knowledge of the parameters and their effects on the model output. On the other hand, GLUE predicts more reliable uncertainty ranges (R‐factor = 0.52 for daily calibration and 0.48 for validation) compared to SUFI‐2 (R‐factor = 0.59 for daily calibration and 0.55 for validation), though it is computationally demanding. Although both SUFI‐2 and GLUE appear to be promising techniques for the uncertainty analysis of modelling results, more and more studies in this direction are required under varying agro‐climatic conditions for assessing their generic capability. Copyright © 2015 John Wiley & Sons, Ltd.     

Modelling sediment and total phosphorus export from a lowland catchment: comparing sediment routing methods

Bank erosion is the main source of suspended sediment (SS) and diffuse total phosphorus (TP) in many lowland catchments. This study compared a physically based sediment routing method (Physical method), which distinguishes between stream bed and bank erosion, with the original sediment routing method (Original method) within the Soil and Water Assessment Tool (SWAT) version 2009, for simulating SS and TP losses from a lowland catchment. A SWAT model was set up for the lowland River Odense catchment in Denmark and calibrated against observed stream flow and phosphate (PO₄) loads. On the basis of an initial calibration of hydrological and PO₄ parameters, the SWAT model with the Original method (Original model) and the SWAT model with the Physical method (Physical model) were calibrated separately against observed SS and TP loads. The SWAT model simulated daily stream flow well but underestimated PO₄ loads. The Physical model simulated daily SS and TP better than the Original model. The simulated contribution of bank erosion to SS in the Physical model (99%) was close to the estimated contribution from in situ erosion measurements (90–94%). Compared with the Original method, the Physical method is not only more conceptually correct but also improves model performance. Copyright © 2014 John Wiley & Sons, Ltd.     

Modelling the rainfall–runoff process of the Mara River basin using the Soil and Water Assessment Tool

The delicate balance between human utilization and sustaining its pristine biodiversity in the Mara River basin (MRB) is being threatened because of the expansion of agriculture, deforestation, human settlement, erosion and sedimentation and extreme flow events. This study assessed the applicability of the Soil and Water Assessment Tool (SWAT) model for long‐term rainfall–runoff simulation in MRB. The possibilities of combining/extending gage rainfall data with satellite rainfall estimates were investigated. Monthly satellite rainfall estimates not only overestimated but also lacked the variability of observed rainfall to substitute gage rainfall in model simulation. Uncertainties related to the quality and availability of input data were addressed. Sensitivity and uncertainty analysis was reported for alternative model components and hydrologic parameters used in SWAT. Mean sensitivity indices of SWAT parameters in MRB varied with and without observed discharge data. The manual assessment of individual parameters indicated heterogeneous response among sub‐basins of MRB. SWAT was calibrated and validated with 10 years of discharge data at Bomet (Nyangores River), Mulot (Amala River) and Mara Mines (Mara River) stations. Model performance varied from satisfactory at Mara Mines to fair at Bomet and weak at Mulot. The (Nash–Sutcliff efficiency, coefficient of determination) results of calibration and validation at Mara Mines were (0.68, 0.69) and (0.43, 0.44), respectively. Two years of moving time window and flow frequency analysis showed that SWAT performance in MRB heavily relied on quality and abundance of discharge data. Given the 5.5% area contribution of Amala sub‐basin as well as uncertainty and scarcity of input data, SWAT has the potential to simulate the rainfall runoff process in the MRB. Copyright © 2012 John Wiley & Sons, Ltd.     

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

Abstract

The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage?discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.

Editor D. Koutsoyiannis; Associate editor D. Gerten

Citation Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M., 2013. Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds. Hydrological Sciences Journal, 58 (8), 1635?1657.     

Assessment of runoff and sediment yield in the Miyun Reservoir catchment by using SWAT model

The Soil and Water Assessment Tool (SWAT) was used to simulate the transport of runoff and sediment into the Miyun Reservoir, Beijing in this study. The main objective was to validate the performance of SWAT and the feasibility of using this model as a simulator of runoff and sediment transport processes at a catchment scale in arid and semi‐arid area in North China, and related processes affecting water quantity and soil erosion in the catchment were simulated. The investigation was conducted using a 6‐year historical streamflow and sediment record from 1986 to 1991; the data from 1986 to 1988 was used for calibration and that from 1989 to 1991 for validation. The SWAT generally performs well and could accurately simulate both daily and monthly runoff and sediment yield. The simulated daily and monthly runoff matched the observed values satisfactorily, with a Nash‐Sutcliffe coefficient of greater than 0·6, 0·9 and a coefficient of determination 0·75, 0·9 at two outlet stations (Xiahui and Zhangjiafen stations) during calibration. These values were 0·6, 0·85 and 0·6, 0·9 during validation. For sediment simulation, the efficiency is lower than that for runoff. Even so, the Nash‐Sutcliffe coefficient and coefficient of determination were greater than 0·48 and 0·6 for monthly sediment yield during calibration, and these values were greater than 0·84 and 0·95 during validation. Sensitivity analysis shows that sensitive parameters for the simulation of discharge and sediment yield include curve number, base flow alpha factor, soil evaporation compensation factor, soil available water capacity, soil profile depth, surface flow lag time and channel re‐entrained linear parameter, etc. Copyright © 2009 John Wiley & Sons, Ltd.     

Parameter uncertainty of the AWBM model when applied to an ungauged catchment

In this study, a quantitative assessment of uncertainty was made in connection with the calibration of Australian Water Balance Model (AWBM) for both gauged and ungauged catchment cases. For the gauged catchment, five different rainfall data sets, 23 different calibration data lengths and eight different optimization techniques were adopted. For the ungauged catchment case, the optimum parameter sets obtained from the nearest gauged catchment were transposed to the ungauged catchments, and two regional prediction equations were used to estimate runoff. Uncertainties were ascertained by comparing the observed and modelled runoffs by the AWBM on the basis of different combinations of methods, model parameters and input data. The main finding from this study was that the uncertainties in the AWBM modelling outputs could vary from ?1.3% to 70% owing to different input rainfall data, ?5.7% to 11% owing to different calibration data lengths and ?6% to 0.2% owing to different optimization techniques adopted in the calibration of the AWBM. The performance of the AWBM model was found to be dominated mainly by the selection of appropriate rainfall data followed by the selection of an appropriate calibration data length and optimization algorithm. Use of relatively short data length (e.g. 3 to 6 years) in the calibration was found to generate relatively poor results. Effects of different optimization techniques on the calibration were found to be minimal. The uncertainties reported here in relation to the calibration and runoff estimation by the AWBM model are relevant to the selected study catchments, which are likely to differ for other catchments. The methodology presented in this paper can be applied to other catchments in Australia and other countries using AWBM and similar rainfall–runoff models. Copyright © 2014 John Wiley & Sons, Ltd.     

MODELLING RAINFALL-RUNOFF FROM LARGE CATCHMENT TO BASIN SCALE: THE GOULBURN VALLEY,VICTORIA

A lumped parameter dynamic rainfall-runoff model, IHACRES, is applied to the large upland area (more than 4500 km²) of the Goulburn Valley Basin, Victoria, Australia to predict streamflow under different climatic conditions. This paper presents the first evaluation of a rainfall–runoff model at large catchment scale, which is comprehensive in terms of the number of catchments investigated and the number of calibration and simulation periods used. The basin is subdivided into 12 catchments (from 100 to 700 km²), each of which is calibrated separately. High values of model efficiency and low bias are consistently obtained for different calibration sub-periods for all catchments in the basin. Simulation or so-called validation tests are used to select the best models for each catchment. This allows simulation of the water regime during long historical (approximately 90 year) periods when only climatological (rainfall and temperature) data were available. This procedure is extremely important for the estimation of the effect of climate variability and of the possible impact of climate change on the hydrological regime in the region and, in particular, for supporting irrigation management of the basin. Analysis of a composite catchment (2417 km²) and its five separate subcatchments indicates that the information content in the rainfall–streamflow data is independent of catchment size. Dynamic modelling of the daily water balance at the macroscale is limited principally by the adequacy of the precipitation gauging network. When a good estimate of areal precipitation is available for a catchment, it is not necessary to consider subcatchment-scale variability for modelling if the only interest is the daily discharge and evaporation losses from the catchment.     

Glacier mass balance simulation using SWAT distributed snow algorithm

Application of a temperature-index melt model incorporated into the Soil and Water Assessment Tool (SWAT) is presented to simulate mass balance (MB) and equilibrium line altitude (ELA) of three glaciers. The snow accumulation/melt parameters were adjusted to glacierized and free glacier areas, respectively. The SWAT snow algorithm enabled us to consider spatial variation of snow parameters by elevation bands across the sub-basins, while in the previous studies using SWAT, the related parameters were constant for an entire basin. The results show slight improvement in runoff simulation and significant improvement in simulated MB when considering ELA in model calibration. The results showed that SWAT can be applied to simulate MB, vertical MB distribution and annual ELA, with light calibration efforts for data-scarce catchments. The accuracy of the results depends on the modelled area of ablation zone from which most of the meltwater is released.     

Simulating streamflow in the Upper Halda Basin of southeastern Bangladesh using SWAT model

ABSTRACT

Most catchments in tropical regions are ungauged and data deficient, complicating the simulation of water quantity and quality. Yet, developing and testing hydrological models in data-poor regions is vital to support water management. Here, we used the Soil and Water Assessment Tool (SWAT) to predict stream runoff in Halda Basin in Bangladesh. While the calibrated model’s performance was satisfactory (R² = 0.80, NSE = 0.71), the model was unable to track the extreme low flow peaks due to the temporal and spatial variability of rainfall which may not be fully captured by using data from one rainfall gauging station. Groundwater delay time, baseflow alpha factor and curve number were the most sensitive parameters influencing model performance. This study improves understanding of the key processes of a catchment in a data-poor, monsoon driven, small river basin and could serve as a baseline for scenario modelling for future water management and policy framework.     

Controls of streamflow generation in small catchments across the snow–rain transition in the Southern Sierra Nevada,California

Processes controlling streamflow generation were determined using geochemical tracers for water years 2004–2007 at eight headwater catchments at the Kings River Experimental Watersheds in southern Sierra Nevada. Four catchments are snow‐dominated, and four receive a mix of rain and snow. Results of diagnostic tools of mixing models indicate that Ca²⁺, Mg²⁺, K⁺ and Cl^? behaved conservatively in the streamflow at all catchments, reflecting mixing of three endmembers. Using endmember mixing analysis, the endmembers were determined to be snowmelt runoff (including rain on snow), subsurface flow and fall storm runoff. In seven of the eight catchments, streamflow was dominated by subsurface flow, with an average relative contribution (% of streamflow discharge) greater than 60%. Snowmelt runoff contributed less than 40%, and fall storm runoff less than 7% on average. Streamflow peaked 2–4 weeks earlier at mixed rain–snow than snow‐dominated catchments, but relative endmember contributions were not significantly different between the two groups of catchments. Both soil water in the unsaturated zone and regional groundwater were not significant contributors to streamflow. The contributions of snowmelt runoff and subsurface flow, when expressed as discharge, were linearly correlated with streamflow discharge (R² of 0.85–0.99). These results suggest that subsurface flow is generated from the soil–bedrock interface through preferential pathways and is not very sensitive to snow–rain proportions. Thus, a declining of the snow–rain ratio under a warming climate should not systematically affect the processes controlling the streamflow generation at these catchments. Copyright © 2012 John Wiley & Sons, Ltd.     

Predicting dry‐season flows with a monthly rainfall–runoff model: Performance for gauged and ungauged catchments

Hydrologic models are useful to understand the effects of climate and land‐use changes on dry‐season flows. In practice, there is often a trade‐off between simplicity and accuracy, especially when resources for catchment management are scarce. Here, we evaluated the performance of a monthly rainfall–runoff model (dynamic water balance model, DWBM) for dry‐season flow prediction under climate and land‐use change. Using different methods with decreasing amounts of catchment information to set the four model parameters, we predicted dry‐season flow for 89 Australian catchments and verified model performance with an independent dataset of 641 catchments in the United States. For the Australian catchments, model performance without catchment information (other than climate forcing) was fair; it increased significantly as the information to infer the four model parameters increased. Regressions to infer model parameters from catchment characteristics did not hold for catchments in the United States, meaning that a new calibration effort was needed to increase model performance there. Recognizing the interest in relative change for practical applications, we also examined how DWBM could be used to simulate a change in dry‐season flow following land‐use change. We compared results with and without calibration data and showed that predictions of changes in dry‐season flow were robust with respect to uncertainty in model parameters. Our analyses confirm that climate is a strong driver of dry‐season flow and that parsimonious models such as DWBM have useful management applications: predicting seasonal flow under various climate forcings when calibration data are available and providing estimates of the relative effect of land use on seasonal flow for ungauged catchments.     

Advancing understanding of runoff and sediment transfers in agricultural catchments through simultaneous observations across scales

Our understanding of the effect of scale on runoff and sediment transfers within catchments is currently limited by a lack of available data. A multi‐scale dataset of 17 rainfall events collected simultaneously at four spatial scales within a small agricultural catchment in 2005–2006 is presented. Analysis using exploratory techniques and a two‐step, zero‐inflated lognormal mixed‐effects regression model, has demonstrated that event responses, and event response characteristics representing runoff and sediment peaks and area‐normalized yields, are scale dependent, and hence cannot be transferred directly between scales. Runoff and sediment yields increase as scale increases, and it is proposed that this effect, which differs from that observed in the few other studies of scale effects undertaken, is due to increasing connectivity within the catchment, and the dominance of preferential flow pathways including through macropores and field drains. The processes contributing to scale dependence in the data, and the possibility that certain processes dominate at particular scales, are discussed. The data presented here help to improve our spatial understanding of runoff and sediment transport in small agricultural catchments, and provide examples of the type of spatial dataset and the type of analysis that are essential if we are to develop models which are able to predict runoff and soil erosion accurately, and allow us to manage runoff and sediment transport effectively across scales. Copyright © 2011 John Wiley & Sons, Ltd.     

Evaluating the effect of snow and ice melt in an Alpine headwater catchment and further downstream in the River Rhine

Abstract

The runoff regime of glacierized headwater catchments in the Alps is essentially characterized by snow and ice melt. High Alpine drainage basins influence distant downstream catchments of the Rhine River basin. In particular, during the summer months, low-flow conditions are probable with strongly reduced snow and ice melt under climate change conditions. This study attempts to quantify present and future contributions from snow and ice melt to summer runoff at different spatial scales. For the small Silvretta catchment (103 km²) in the Swiss Alps, with a glacierization of 7%, the HBV model and the glacio-hydrological model GERM are applied for calculating future runoff based on different regional climate scenarios. We evaluate the importance of snow and ice melt in the runoff regime. Comparison of the models indicates that the HBV model strongly overestimates the future contribution of glacier melt to runoff, as glaciers are considered as static components. Furthermore, we provide estimates of the current meltwater contribution of glaciers for several catchments downstream on the River Rhine during the month of August. Snow and ice melt processes have a significant direct impact on summer runoff, not only for high mountain catchments, but also for large transboundary basins. A future shift in the hydrological regime and the disappearance of glaciers might favour low-flow conditions during summer along the Rhine.

Citation Junghans, N., Cullmann, J. & Huss, M. (2011) Evaluating the effect of snow and ice melt in an Alpine headwater catchment and further downstream in the River Rhine. Hydrol. Sci. J. 56(6), 981–993.     

Understanding changes in annual runoff following land use changes: a systematic data‐based approach

A simple modelling framework for assessing the response of ungauged catchments to land use change in South‐Western Australia is presented. The framework uses knowledge of transpiration losses from native vegetation and pasture and then partitions the ‘excess’ water (resulting from reduced transpiration after land use change) between runoff and deep storage. The simple partitioning is achieved by using soft information (satellite imagery, previous mapping and field assessment) to delimit the spread of the permanently saturated area close to the stream. Runoff is then assumed to increase in proportion to the saturated area, with the residual difference going to deep storage. The model parameters to describe the annual water yield are obtained a priori and no calibration to streamflow is required. We tested the model using gauged records over 25 years from paired catchment experiments in South‐Western Australia. Very good estimates of runoff were obtained from high rainfall (>1100 mm yr⁻¹) catchments (R² > 0·9) and for low rainfall (<900 mm yr⁻¹) catchments after clearing (R² = 0·96) but results were poorer (R² = 0·55) for an uncleared low rainfall catchment, although overall balances were reasonable. In the drier uncleared catchments, the within‐year distributions of rainfall may exert a substantial influence on runoff response that is not completely captured by the presented model. Copyright © 2005 John Wiley & Sons, Ltd.