Sources of dissolved organic carbon during stormflow in a headwater agricultural catchment

Increasing dissolved organic carbon (DOC) concentrations have been reported during the last 15 years in streams from the United Kingdom, Northern Europe and North America. Identifying the sources of DOC and the controls of the delivery to the stream is important to understand the significance of these trends. This relies on the availability of observations of DOC dynamics during storm events, since much of the DOC export from soils to streams occurs during high flows. This study analyses DOC data for eight storm events during winter 2005–2006 in a small agricultural experimental catchment—the Kervidy‐Naizin experimental catchment—located in Western France. A four end‐member mixing approach was applied to the eight monitored storm events to identify DOC sources and quantify their respective contribution to DOC stream fluxes, using DOC, nitrate, sulphate and chloride as tracers. The results show that DOC concentrations in the stream at the outlet of this catchment increase markedly during storm events. The slope of the linear regression between DOC concentration and discharge was not constant for the eight events and depended on pre‐event hydrological conditions. Between 64 and 86% of the DOC that enter the stream during storms originated from the upper layers of the riparian wetland soils. The variation of the delivery of DOC seems to be controlled by hydrological processes only, the wetland soils acting as a non‐limiting store. Copyright © 2009 John Wiley & Sons, Ltd.     

Development of a one-parameter variable source area runoff model for ungauged basins

This research develops a one-parameter model of saturated source area dynamics and the spatial distribution of soil moisture. The single required parameter is the maximum soil moisture deficit within the catchment. The concept behind the development of the model comes from the fact that the complexity of topographically-driven runoff generation can be reduced through the use of geomorphological scaling relations. The scaling formulation allows the prediction of the dynamics of saturated source areas as a function of basin-wide soil moisture state. This model offers a number of potential advantages. Firstly, the model parameter is independent of topographic index distribution and its associated scale effects. Secondly, it may be possible to measure this single parameter using field measurements or perhaps remote sensing, which gives the model significant potential for application in ungauged basins. Finally, the fact that this parameter is a physical characteristic of the basin, estimation of this parameter avoids regionalization and parameter transferability problems. The model is tested using rainfall–runoff data from the 10.4 ha experimental catchment known as Tarrawara in Australia, the 37 km² Town Creek catchment in U.S.A., and the 620 km² Balaphi and the 850 km² Likhu sub-catchments of the Koshi river in Nepal. In sub-catchments of Koshi river, the simulation results compare favorably against the calibrated TOPMODEL both in terms of direct runoff and the spatial distribution of soil moisture state. In the Tarrawara and Town Brook catchments, simulation results compare favorably against observed storm runoff using all observed data, without calibration.     

A stochastic integral equation analog of rainfall-runoff processes for evaluating modeling uncertainty

In this paper a very general rainfall-runoff model structure (described below) is shown to reduce to a unit hydrograph model structure. For the general model, a multi-linear unit hydrograph approach is used to develop subarea runoff, and is coupled to a multi-linear channel flow routing method to develop a link-node rainfall-runoff model network. The spatial and temporal rainfall distribution over the catchment is probabilistically related to a known rainfall data source located in the catchment in order to account for the stochastic nature of rainfall with respect to the rain gauge measured data. The resulting link node model structure is a series of stochastic integral equations, one equation for each subarea. A cumulative stochastic integral equation is developed as a sum of the above series, and includes the complete spatial and temporal variabilities of the rainfall over the catchment. The resulting stochastic integral equation is seen to be an extension of the well-known single area unit hydrograph method, except that the model output of a runoff hydrograph is a distribution of outcomes (or realizations) when applied to problems involving prediction of storm runoff; that is, the model output is a set of probable runoff hydrographs, each outcome being the results of calibration to a known storm event.     

A stochastic integral equation analog of rainfall-runoff processes for evaluating modeling uncertainty

In this paper a very general rainfall-runoff model structure (described below) is shown to reduce to a unit hydrograph model structure. For the general model, a multi-linear unit hydrograph approach is used to develop subarea runoff, and is coupled to a multi-linear channel flow routing method to develop a link-node rainfall-runoff model network. The spatial and temporal rainfall distribution over the catchment is probabilistically related to a known rainfall data source located in the catchment in order to account for the stochastic nature of rainfall with respect to the rain gauge measured data. The resulting link node model structure is a series of stochastic integral equations, one equation for each subarea. A cumulative stochastic integral equation is developed as a sum of the above series, and includes the complete spatial and temporal variabilities of the rainfall over the catchment. The resulting stochastic integral equation is seen to be an extension of the well-known single area unit hydrograph method, except that the model output of a runoff hydrograph is a distribution of outcomes (or realizations) when applied to problems involving prediction of storm runoff; that is, the model output is a set of probable runoff hydrographs, each outcome being the results of calibration to a known storm event.     

Shifts in discharge‐concentration relationships as a small catchment recover from severe drought

This paper provides evidence of the recovery of a small, moorland catchment to a severe drought, the most extreme on record in the UK. We present a detailed water quality time series for the post‐drought recovery period, from the first significant storm event at the end of the drought through three very wet months during which time the catchment fully wetted up. High‐frequency observations were obtained using pump water samplers, at 15‐min intervals for storm events and 2 hourly at other times. There are significant shifts in discharge‐concentration response as the catchment wets up; initial behaviour is very different to later storms. Extreme drought may become more common in a warmer world, so it is increasingly important to understand water quality response during and after such episodes, if their impact on water resources and in‐stream ecology is to be better anticipated. Copyright © 2014 John Wiley & Sons, Ltd.     

A modelling framework for evaluation of the hydrological impacts of nature‐based approaches to flood risk management,with application to in‐channel interventions across a 29‐km2 scale catchment in the United Kingdom

Nature‐based approaches to flood risk management are increasing in popularity. Evidence for the effectiveness at the catchment scale of such spatially distributed upstream measures is inconclusive. However, it also remains an open question whether, under certain conditions, the individual impacts of a collection of flood mitigation interventions could combine to produce a detrimental effect on runoff response. A modelling framework is presented for evaluation of the impacts of hillslope and in‐channel natural flood management interventions. It couples an existing semidistributed hydrological model with a new, spatially explicit, hydraulic channel network routing model. The model is applied to assess a potential flood mitigation scheme in an agricultural catchment in North Yorkshire, United Kingdom, comprising various configurations of a single variety of in‐channel feature. The hydrological model is used to generate subsurface and surface fluxes for a flood event in 2012. The network routing model is then applied to evaluate the response to the addition of up to 59 features. Additional channel and floodplain storage of approximately 70,000 m³ is seen with a reduction of around 11% in peak discharge. Although this might be sufficient to reduce flooding in moderate events, it is inadequate to prevent flooding in the double‐peaked storm of the magnitude that caused damage within the catchment in 2012. Some strategies using features specific to this catchment are suggested in order to improve the attenuation that could be achieved by applying a nature‐based approach.     

The influence of storm characteristics and catchment conditions on extreme flood response : A case study based on the brue river basin,U.K.

Methods for estimating the magnitude of extreme floods are reviewed. A method which combines a probabilistic storm transposition technique with a physically-based distributed rainfallrunoff model is described. Synthetic storms with detailed spatial and temporal distributions are generated and applied to the calibrated model of the Brue river basin, U.K. (area 135 km²). The variability of catchment response due to storm characteristics (storm area, storm duration, storm movement, storm shape and within storm variation) and initial catchment wetness conditions is investigated. A probabilistic approach to estimating the return periods of extreme catchment responses is suggested.     

Remote sensing analysis of physical complexity of North Pacific Rim rivers to assist wild salmon conservation

Salmon populations are highly variable in both space and time. Accurate forecasting of the productivity of salmon stocks makes effective management and conservation of the resource extremely challenging. Furthermore, widespread and consistent data on the productivity of species‐specific and total salmon stocks in a river are almost nonexistent. Ranking rivers based on physical complexity derived from remote sensing allows rivers to be objectively compared. Our approach considered rivers with great geomorphic complexity (e.g. having expansive, multichanneled floodplains and/or on‐channel lakes) as likely to have greater productivity of salmon than rivers flowing in constrained or canyon‐bound channels. Our objective was to develop a database of landscape metrics that could be used to rank the rivers in relation to potential salmon productivity. We then examined the rankings in relation to existing empirical (monitoring) data describing productivity of salmon stocks. To extract the metrics for each river basin we used a digital elevation model and multispectral satellite imagery. We developed procedures to extract channel networks, floodplains, on‐channel lakes and other catchment features; variables such as catchment area, channel elevation, main channel length, floodplain area, and density of hydrojunctions (nodes) were measured. We processed 1509 catchments in the North Pacific Rim including the Kamchatka Peninsula in Russia and western North America. Overall, catchments were most physically complex in western Kamchatka and western Alaska, and particularly on the Arctic North Slope of Alaska. We could not directly examine coherence between potential and measured productivity except for a few rivers, but the expected relationship generally held. The resulting database and systematic ranking are objective tools that can be used to address questions about landscape structure and biological productivity at regional to continental extents, and provide a way to begin to efficiently prioritize the allocation of funding and resources towards salmon management and conservation. Copyright © 2010 John Wiley & Sons, Ltd.     

Hydrological processes of a closed catchment‐lake system in a semi‐arid Mediterranean environment

Data collected in 4 years of field observations were used in conjunction with continuous simulation models to study, at the small‐basin scale, the water balance of a closed catchment‐lake system in a semi‐arid Mediterranean environment. The open water evaporation was computed with the Penman equation, using the data set collected in the middle of the lake. The surface runoff was partly measured at the main tributary and partly simulated using a distributed, catchment, hydrological model, calibrated with the observed discharge. The simplified structure of the developed modelling mainly concerns soil moisture dynamics and bedrock hydraulics, whereas the flow components are physically based. The calibration produced high efficiency coefficients and showed that surface runoff is greatly affected by soil water percolation into fractured bedrock. The bedrock reduces the storm‐flow peaks and the interflow and has important multi‐year effects on the annual runoff coefficients. The net subsurface outflow from the lake was calculated as the residual of the lake water balance. It was almost constant in the dry seasons and increased in the wet seasons, because of the moistening of the unsaturated soil. During the years of observation, rainfall 30% higher than average caused abundant runoff and a continuous rise in the lake water levels. The analysis allows to predict that, in years with lower than the average rainfall, runoff will be drastically reduced and will not be able to compensate for negative balance between precipitation and lake evaporation. Such highly unsteady situations, with great fluctuations in lake levels, are typical of closed catchment‐lake systems in the semi‐arid Mediterranean environment. Copyright © 2012 John Wiley & Sons, Ltd.     

The use of agent based modelling techniques in hydrology: determining the spatial and temporal origin of channel flow in semi‐arid catchments

Information on the spatial and temporal origin of runoff entering the channel during a storm event would be valuable in understanding the physical dynamics of catchment hydrology; this knowledge could be used to help design flood defences and diffuse pollution mitigation strategies. The majority of distributed hydrological models give information on the amount of flow leaving a catchment and the pattern of fluxes within the catchment. However, these models do not give any precise information on the origin of runoff within the catchment. The spatial and temporal distribution of runoff sources is particularly intricate in semi‐arid catchments, where there are complex interactions between runoff generation, transmission and re‐infiltration over short temporal scales. Agents are software components that are capable of moving through and responding to their local environment. In this application, the agents trace the path taken by water through the catchment. They have information on their local environment and on the basis of this information make decisions on where to move. Within a given model iteration, the agents are able to stay in the current cell, infiltrate into the soil or flow into a neighbouring cell. The information on the current state of the hydrological environment is provided by the environment generator. In this application, the Connectivity of Runoff Model (CRUM) has been used to generate the environment. CRUM is a physically based, distributed, dynamic hydrology model, which considers the hydrological processes relevant for a semi‐arid environment at the temporal scale of a single storm event. During the storm event, agents are introduced into the model across the catchment; they trace the flows of water and store information on the flow pathways. Therefore, this modelling approach is capable of giving a novel picture of the temporal and spatial dynamics of flow generation and transmission during a storm event. This is possible by extracting the pathways taken by the agents at different time slices during the storm. The agent based modelling approach has been applied to two small catchments in South East Spain. The modelling approach showed that the two catchments responded differently to the same rainfall event due to the differences in the runoff generation and overland flow connectivity between the two catchments. The model also showed that the time of travel to the nearest flow concentration is extremely important for determining the connectivity of a point in the landscape with the catchment outflow. Copyright © 2007 John Wiley & Sons, Ltd.     

Heavy metal release by peat erosion in the Peak District,southern Pennines,UK

Upper North Grain (UNG) is a heavily eroding blanket peat catchment in the Peak District, southern Pennines, UK. Concentrations of lead in the near‐surface peat layer at UNG are in excess of 1000 mg kg⁻¹. For peatland environments, these lead concentrations are some of the highest globally. High concentrations of industrially derived, atmospherically transported magnetic spherules are also stored in the near‐surface peat layer. Samples of suspended sediment taken during a storm event that occurred on 1 November 2002 at UNG, and of the potential catchment sources for suspended sediments, were analysed for lead content and the environmental magnetic properties of anhysteretic remanent magnetization (ARM) and saturation isothermal remanent magnetization (SIRM). At the beginning of the storm event, there is a peak in both suspended sediment and associated lead concentration. SIRM/ARM values for suspended sediment samples throughout the storm reveal that the initial ‘lead flush’ is associated with a specific sediment source, namely that of organic sediment eroded from the upper peat layer. Using the magnetic ‘fingerprinting’ approach to discrimination of sediment sources, this study reveals that erosion of the upper peat layer at UNG is releasing high concentrations of industrially derived lead (and, by inference, other toxic heavy metals associated with industrial particulates) into the fluvial systems of the southern Pennines. Climate‐change scenarios for the UK, involving higher summer temperatures and stormier winters, may result in an increased flux both of sediment‐associated and dissolved heavy metals from eroding peatland catchments in the southern Pennines, adversely affecting the quality of sediment and water entering reservoirs of the region. Copyright © 2005 John Wiley & Sons, Ltd.     

Impact of road‐generated storm runoff on a small catchment response

The impact of road‐generated runoff on the hydrological response of a zero‐order basin was monitored for a sequence of 24 storm events. The study was conducted in a zero‐order basin (C1; 0·5ha) with an unpaved mountain road; an adjacent unroaded zero‐order basin (C2; 0·2 ha) with similar topography and lithology was used to evaluate the hydrological behaviour of the affected zero‐order basin prior to construction of the road. The impact of the road at the zero‐order basin scale was highly dependent on the antecedent soil‐moisture conditions, total storm precipitation, and to some extent rainfall intensity. At the beginning of the monitoring period, during dry antecedent conditions, road runoff contributed 50% of the total runoff and 70% of the peak flow from the affected catchment (C1). The response from the unroaded catchment was almost insignificant during dry antecedent conditions. As soil moisture increased, the road exerted less influence on the total runoff from the roaded catchment. For very wet conditions, the influence of road‐generated runoff on total outflow from the roaded catchment diminished to only 5·4%. Both catchments, roaded and unroaded, produced equivalent amount of outflow during very wet antecedent conditions on a unit area basis. The lag time between the rainfall and runoff peaks observed in the unroaded catchment during the monitoring period ranged from 0 to 4 h depending on the amount of precipitation and antecedent conditions, owing mainly to much slower subsurface flow pathways in the unroaded zero‐order basin. In contrast, the lag time in the roaded zero‐order basin was virtually nil during all storms. Copyright © 2009 John Wiley & Sons, Ltd.     

Towards the representation of groundwater in the Joint UK Land Environment Simulator

Groundwater is an important component of the hydrological cycle with significant interactions with soil hydrological processes. Recent studies have demonstrated that incorporating groundwater hydrology in land surface models (LSMs) considerably improves the prediction of the partitioning of water components (e.g., runoff and evapotranspiration) at the land surface. However, the Joint UK Land Environment Simulator (JULES), an LSM developed in the United Kingdom, does not yet have an explicit representation of groundwater. We propose an implementation of a simplified groundwater flow boundary parameterization (JULES-GFB), which replaces the original free drainage assumption in the default model (JULES-FD). We tested the two approaches under a controlled environment for various soil types using two synthetic experiments: (1) single-column and (2) tilted-V catchment, using a three-dimensional (3-D) hydrological model (ParFlow) as a benchmark for JULES’ performance. In addition, we applied our new JULES-GFB model to a regional domain in the UK, where groundwater is the key element for runoff generation. In the single-column infiltration experiment, JULES-GFB showed improved soil moisture dynamics in comparison with JULES-FD, for almost all soil types (except coarse soils) under a variety of initial water table depths. In the tilted-V catchment experiment, JULES-GFB successfully represented the dynamics and the magnitude of saturated and unsaturated storage against the benchmark. The lateral water flow produced by JULES-GFB was about 50% of what was produced by the benchmark, while JULES-FD completely ignores this process. In the regional domain application, the Kling-Gupta efficiency (KGE) for the total runoff simulation showed an average improvement from 0.25 for JULES-FD to 0.75 for JULES-GFB. The mean bias of actual evapotranspiration relative to the Global Land Evaporation Amsterdam Model (GLEAM) product was improved from −0.22 to −0.01 mm day⁻¹. Our new JULES-GFB implementation provides an opportunity to better understand the interactions between the subsurface and land surface processes that are dominated by groundwater hydrology.     

Non-linear quickflow response as indicators of runoff generation mechanisms

Linking quickflow response to subsurface state can improve our understanding of runoff processes that drive emergent catchment behaviour. We investigated the formation of non-linear quickflows in three forested headwater catchments and also explored unsaturated and saturated storage dynamics, and likely runoff generation mechanisms that contributed to threshold formation. Our analyses focused on two reference watersheds at the Coweeta Hydrologic Laboratory (CHL) in western North Carolina, USA, and one reference watershed at the Susquehanna Shale Hills Critical Zone Observatory (SHW) in Central Pennsylvania, USA, with available hourly soil moisture, groundwater, streamflow, and precipitation time series over several years. Our study objectives were to characterise (a) non-linear runoff response as a function of storm characteristics and antecedent conditions, (b) the critical levels of shallow unsaturated and saturated storage that lead to hourly flow response, and (c) runoff mechanisms contributing to rapidly increasing quickflow using measurements of soil moisture and groundwater. We found that maximum hourly rainfall did not significantly contribute to quickflow production in our sites, in contrast to prior studies, due to highly conductive forest soils. Soil moisture and groundwater dynamics measured in hydrologically representative areas of the hillslope showed that variable subsurface states could contribute to non-linear runoff behaviour. Quickflow generation in watersheds at CHL were dominated by both saturated and unsaturated pathways, but the relative contributions of each pathway varied between catchments. In contrast, quickflow was almost entirely related to groundwater fluctuations at SHW. We showed that co-located measurements of soil moisture and groundwater supplement threshold analyses providing stronger prediction and understanding of quickflow generation and indicate dominant runoff processes.     

The effect of storm movement on infiltration,runoff and soil erosion in a semi-arid catchment

Rainfall characteristics are key factors influencing infiltration and runoff generation in catchment hydrology, particularly for arid and semiarid catchments. Although the effect of storm movement on rainfall-runoff processes has been evaluated and emphasized since the 1960s, the effect on the infiltration process has barely been considered. In this study, a physically based distributed hydrological model (InHM) was applied to a typical semi-arid catchment (Shejiagou, 4.26 km²) located in the Loess Plateau, China, to investigate the effect of storm movement on infiltration, runoff and soil erosion at the catchment scale. Simulations of 84 scenarios of storm movement were conducted, including storms moving across the catchment in both the upstream and downstream directions along the main channel, while in each direction considering four storm moving speeds, three rainfall depths and two storm ranges. The simulation results showed that, on both the hillslopes facing downstream (facing south) and in the main channel, the duration of the overland flow process under the upstream-moving storms was longer than that under the downstream-moving storms. Thus, the duration and volume of infiltration under upstream-moving storms were larger in these areas. For the Shejiagou catchment, as there are more hillslopes facing downstream, more infiltration occurred under the upstream-moving storms than the downstream-moving storms. Therefore, downstream-moving storms generated up to 69% larger total runoff and up to 351% more soil loss in the catchment than upstream-moving storms. The difference in infiltration between the storms moving upstream and downstream decreased as the storm moving speed increased. The relative difference in total runoff and sediment yield between the storms moving upstream and downstream decreased with increasing rainfall depth and storm speed. The results of this study revealed that the infiltration differences under moving storms largely influenced the total runoff and sediment yield at the catchment scale, which is of importance in runoff prediction and flood management. The infiltration differences may be a potential factor leading to different groundwater, vegetation cover and ecology conditions for the different sides of the hillslopes.     

Sensitivity of runoff and soil erosion to climate change in two Mediterranean watersheds. Part II: assessing impacts from changes in storm rainfall,soil moisture and vegetation cover

The impacts of climate change on storm runoff and erosion in Mediterranean watersheds are difficult to assess due to the expected increase in storm frequency coupled with a decrease in total rainfall and soil moisture, added to positive or negative changes to different types of vegetation cover. This report, the second part of a two‐part article, addresses this issue by analysing the sensitivity of runoff and erosion to incremental degrees of change (from ? 20 to + 20%) to storm rainfall, pre‐storm soil moisture, and vegetation cover, in two Mediterranean watersheds, using the MEFIDIS model. The main results point to the high sensitivity of storm runoff and peak runoff rates to changes in storm rainfall (2·2% per 1% change) and, to a lesser degree, to soil water content (?1·2% per 1% change). Catchment sediment yield shows a greater sensitivity than within‐watershed erosion rates to both parameters: 7·8 versus 4·0% per 1% change for storm rainfall, and ? 4·9 versus ? 2·3% per 1% change for soil water content, indicating an increase in sensitivity with spatial scale due to changes to sediment connectivity within the catchment. Runoff and erosion showed a relatively low sensitivity to changes in vegetation cover. Finally, the shallow soils in one of the catchments led to a greater sensitivity to changes in storm rainfall and soil moisture. Overall, the results indicate that decreasing soil moisture levels caused by climate change could be sufficient to offset the impact of greater storm intensity in Mediterranean watersheds. Copyright © 2009 John Wiley & Sons, Ltd.     

Bayesian dynamic modelling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification

Forecasting of hydrologic time series, with the quantification of uncertainty, is an important tool for adaptive water resources management. Nonstationarity, caused by climate forcing and other factors, such as change in physical properties of catchment (urbanization, vegetation change, etc.), makes the forecasting task too difficult to model by traditional Box–Jenkins approaches. In this paper, the potential of the Bayesian dynamic modelling approach is investigated through an application to forecast a nonstationary hydroclimatic time series using relevant climate index information. The target is the time series of the volume of Devil's Lake, located in North Dakota, USA, for which it was proved difficult to forecast and quantify the associated uncertainty by traditional methods. Two different Bayesian dynamic modelling approaches are discussed, namely, a constant model and a dynamic regression model (DRM). The constant model uses the information of past observed values of the same time series, whereas the DRM utilizes the information from a causal time series as an exogenous input. Noting that the North Atlantic Oscillation (NAO) index appears to co‐vary with the time series of Devil's Lake annual volume, its use as an exogenous predictor is explored in the case study. The results of both the Bayesian dynamic models are compared with those from the traditional Box–Jenkins time series modelling approach. Although, in this particular case study, it is observed that the DRM performs marginally better than traditional models, the major strength of Bayesian dynamic models lies in the quantification of prediction uncertainty, which is of great value in hydrology, particularly under the recent climate change scenario. Copyright © 2008 John Wiley & Sons, Ltd.     

Model study of the effect of temporal storm distributions on peak discharges and volumes

ABSTRACT

A series of synthetic five-year return period storms having rectangular, triangular and bimodal (triangular) temporal profiles was compiled from depthduration-frequency (D-D-F) relationships based on (a) standard sorted clock time depths and (b) complete storms only. These were used as inputs to a catchment runoff model to simulate the peaks and volumes of runoff from an actual and a hypothetical catchment respectively. The hypothetical catchment was used to prove the adequacy of the simplified hyetographs and the real catchment to demonstrate the difference in runoff hydrographs for the various hyetographs. The results were compared to establish the effect of storm profiles on peak and volume of runoff as well as to indicate the shortcomings of D-D-F relationships derived by conventional methods. In general, on the assumption that the model correctly converts storm input to runoff, triangular, and in particular bimodal, profiles were shown to reproduce adequately runoff peaks and volumes.     

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.