Antecedent Flow Research Articles

The Application of Bayesian Neural Network in Rainfall Forecasting

The process of Rainfall Forecasting very complex and highly nonlinear and exhibits both temporal and spatial variability’s, In this article, a Rainfall Forecasting model using the Bayesian neural networks (BNN) is proposed for Rainfall Forecasting. The study uses the data from a coastal forest catchment. This article studies the accuracy of the short-term rainfall forecast obtained by BNN time-series analysis techniques and using antecedent rainfall depths and stream flow as the input information. The verification results from the proposed model indicate that the approach of BNN Rainfall Forecasting model presented in this paper shows a reasonable agreement in Rainfall Forecasting modeling with high accuracy.

River discharge and local‐scale physical habitat influence macroinvertebrate LIFE scores

Summary1. Methods are needed to relate changing river flows to ecological response, particularly those which do not require collection of extensive new data for river segments that lack historical data. Using time‐series of river biomonitoring data from wadeable lowland streams in Denmark and the East Midlands of the U.K., we describe how local‐scale habitat features (indexed through River Habitat Survey or Danish Habitat Quality Survey) and changing river flow (discharge) influence the response of a macroinvertebrate community index. The approach has broad applicability in developing regional flow‐ecological response models.2. We analysed the data using multilevel linear regression, combining sample‐level and site‐level characteristics as predictors. We focused on the potential for common responses across sites; hence for each sample, the macroinvertebrate community was summarised into an index, Lotic Invertebrate index for Flow Evaluation (LIFE), an average of abundance‐weighted flow groups which indicate the microhabitat preferences of each taxon for higher velocities and clean gravel/cobble substrata or slow/still velocities and finer substrata.3. For the Danish fauna, the LIFE score responded to three predictors in an additive manner: high flows in the preceding 4 months (positive), substratum composition and whether the channel was meandering or straight. The East Midlands fauna responded to three predictors: high and low flows in the preceding 6 months (positive) and the degree of resectioning of the channel (negative). In both cases, LIFE responded negatively to features associated with historical channel modification. We suggest that there are several mechanisms for these relationships, including the narrower tolerances of taxa preferring high velocity habitat; these taxa are also continually recovering from extreme flow events over an inter‐annual timescale.4. At the East Midlands sites, there was an interaction between degree of resectioning and antecedent low flow. At sites with a greater extent of resectioning, the LIFE‐discharge relationship was also steeper than at less modified sites. Consideration of the underlying data suggests that there are two mechanisms for this response. Firstly, in less modified sites, refugia are present during low flows for taxa preferring higher velocities such as riffle beetles, caseless caddis, mayflies and Gammarus pulex. Secondly, high flows are associated with decreasing abundances of taxa such as molluscs, flatworms and leeches at more resectioned sites, but with stable or increasing abundances at less modified sites.5. The LIFE index responded to both antecedent flow and habitat modification in two separate data sets from lowland wadeable streams. This is the first time that the combined importance of these two factors has been demonstrated using routine invertebrate biomonitoring data. These results complement other site‐specific studies that have shown how channel structure interacts with flow to create physical habitat, and should assist future work aiming to define flow‐habitat‐biota relationships.6. The derived models may be used to help guide environmental flow allocations, for example by predicting the slope of response of LIFE score to flow for comparable new locations which lack biological data.

Does quantifying antecedent flow conditions improve stream phosphorus export estimation?

Summary A reliable and economical method for the estimation of nutrient export (e.g. phosphorus) in stream flow from catchments is necessary to quantify the impact of land use or land use change upon aquatic systems. The transport of phosphorus (P) from soil to water is known to impact negatively on water quality. A key observation from studies is that most P export occurs during high stream flow. However, it is not yet clear how flood-antecedent conditions affect the P export during flood events. In this study, the P loss from soil to water as represented by soluble reactive phosphorus (SRP) in stream waters from three different catchments, varying in land use, scale and location in Ireland was monitored over 1 year. This study examined the role of antecedent stream flow conditions on SRP export and identifies a catchment-specific relationship between SRP flood event load (EL) and a flow ratio (FR). The FR is defined as the ratio of the flood event volume (EV) to the pre-event volume (PEV). The latter is the cumulative flow volume for a number of days preceding the event. This PEV period was found to be longer (average 81 days) in the grassland catchments which were known to be saturated with soil P than in the forested catchments (average 21 days) with minimal soil P. This FR ratio is a measure of the antecedent hydrological state (wet or dry) of the catchment. For SRP for each catchment, a specific relationship between SRP EL and FR was identified. The annual SRP export was estimated, using this ratio and compared with the concentration/discharge ( C / Q ) method. The new flow ratio method was used with data from 12 flood events during the year to estimate an annual export of SRP. For the two grassland catchments in the study, using the FR method, we estimated an SRP export of 1.77 and 0.41 kg ha −1 yr −1 . Using the C / Q method, for the same sites, our estimate of SRP export was 1.70 and 0.50 kg ha −1 yr −1 respectively. The C / Q method used SRP concentrations covering 40% of the year while the FR method used only 12 flood events covering less than 2% of the year. This new method which takes account of the antecedent flow state of the river is an alternative to and may be more promising than the traditional C / Q method, particularly when short duration or flood sampling of water quality is carried out.

Temporal changes in fish abundance in response to hydrological variability in a dryland floodplain river

Riverine fish living in unpredictable flow environments tend to be ecological generalists with traits that allow them to persist under highly variable and often harsh conditions associated with hydrological variation. Cooper Creek, an Australian dryland river, is characterised by extreme flow variability, especially in the magnitude, timing and duration of channel flows and floods, which, if they occur, do so mainly in summer. The present study examined the influence of hydrological variability on fish assemblages and abundance in four waterholes in the Windorah reach of Cooper Creek over eight occasions between 2001 and 2004. Antecedent flows had marked influences on fish species richness and assemblage structure. Following high summer flows, all waterholes supported a rich and abundant fish fauna, whereas fewer species and lower numbers were recorded following periods of zero channel flow. Recruitment of three of the four most common and abundant species was enhanced when intermittent flows inundated backwater and floodplain habitats that provide a food-rich environment. Opportunistic responses to rising channel flows and occasional large floods in Cooper Creek help to explain the prominent ‘boom’ patterns of fish production in this arid-zone river, whereas low-level recruitment during periods of low or no flow maintains populations of some species through the ‘bust’.

Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed

AbstractThis paper reports on an evaluation of the use of artificial neural network (ANN) models to forecast daily flows at multiple gauging stations in Eucha Watershed, an agricultural watershed located in north‐west Arkansas and north‐east Oklahoma. Two different neural network models, the multilayer perceptron (MLP) and the radial basis neural network (RBFNN), were developed and their abilities to predict stream flow at four gauging stations were compared. Different scenarios using various combinations of data sets such as rainfall and stream flow at various lags were developed and compared for their ability to make flow predictions at four gauging stations. The input vector selection for both models involved quantification of the statistical properties such as cross‐, auto‐ and partial autocorrelation of the data series that best represented the hydrologic response of the watershed. Measured data with 739 patterns of input–output vector were divided into two sets: 492 patterns for training, and the remaining 247 patterns for testing. The best performance based on the RMSE, R2 and CE was achieved by the MLP model with current and antecedent precipitation and antecedent flow as model inputs. The MLP model testing resulted in R2 values of 0·86, 0·86, 0·81, and 0·79 at the four gauging stations. Similarly, the testing R2 values for the RBFNN model were 0·60, 0·57, 0·58, and 0·56 for the four gauging stations. Both models performed satisfactorily for flow predictions at multiple gauging stations, however, the MLP model outperformed the RBFNN model. The training time was in the range 1–2 min for MLP, and 5–10 s for RBFNN on a Pentium IV processor running at 2·8 GHz with 1 MB of RAM. The difference in model training time occurred because of the clustering methods used in the RBFNN model. The RBFNN uses a fuzzy min‐max network to perform the clustering to construct the neural network which takes considerably less time than the MLP model. Results show that ANN models are useful tools for forecasting the hydrologic response at multiple points of interest in agricultural watersheds. Copyright © 2008 John Wiley & Sons, Ltd.

Development of blooms of Cyclotella meneghiniana and Nitzschia spp. (Bacillariophyceae) in a shallow river and estimation of effective suppression flows

Diatom blooms in the middle reaches of the shallow, freshwater, Hunter River, Australia, are a frequent nuisance to river users. During a 4-year study, blooms of Cyclotella meneghiniana and Nitzschia spp. coincided with water temperatures above 23°C and flows below 400 Ml d−1 that lasted for more than 12 days. Redundancy analysis showed that water temperature was positively related, and antecedent flow was negatively related, to the abundance of both taxa. Addition experiments indicated that nutrients are seldom limiting to growth. It is suggested that a combination of faster growth rates at higher temperatures and longer retention times at low flows allows bloom populations to develop. Simulation modelling showed that flow regulation and water extraction have decreased flows in the river during summer, and consequently have probably increased the number of diatom blooms. Environmental flows have been provided to the river, but are not sufficient to prevent blooms. Discharges required for bloom suppression are described.

Future climate scenarios and rainfall–runoff modelling in the Upper Gallego catchment (Spain)

Global climate change may have large impacts on water supplies, drought or flood frequencies and magnitudes in local and regional hydrologic systems. Water authorities therefore rely on computer models for quantitative impact prediction. In this study we present kernel-based learning machine river flow models for the Upper Gallego catchment of the Ebro basin. Different learning machines were calibrated using daily gauge data. The models posed two major challenges: (1) estimation of the rainfall–runoff transfer function from the available time series is complicated by anthropogenic regulation and mountainous terrain and (2) the river flow model is weak when only climate data are used, but additional antecedent flow data seemed to lead to delayed peak flow estimation. These types of models, together with the presented downscaled climate scenarios, can be used for climate change impact assessment in the Gallego, which is important for the future management of the system.

Stress History Effects on Graded Bed Stability

This paper presents the first detailed examination of the dependence of graded bed stability on antecedent flow conditions stress history. Thirty-three experiments, including repetitions, were undertaken where a bimodal sediment bed D50=4.8 mm, g=2.1 was conditioned for between 30 and 5,760 min. The antecedent shear stress ranged from 53 to 91% of the critical shear stress for the D50 of the sediment bed. Data indicate that higher antecedent shear stresses reduce bed stability due to selective entrainment of the fine matrix; conversely, extending the duration of the antecedent conditioning phase increases bed stability due to local particle rearrangement. Analysis of the competitive effects indicates that particle rearrangement may be of greater relative importance than compositional change. Overall, the paper demonstrates the significance of antecedent flow conditions for hydraulic engineering and research, including the modeling of bed-load transport during flood events and the need for standardizing the flume-based experimental procedure.

Prediction of flood abnormalities for improved public safety using a modified adaptive neuro-fuzzy inference system

It is widely accepted that an efficient flood alarm system may significantly improve public safety and mitigate economical damages caused by inundations. In this paper, a modified adaptive neuro-fuzzy system is proposed to modify the traditional neuro-fuzzy model. This new method employs a rule-correction based algorithm to replace the error back propagation algorithm that is employed by the traditional neuro-fuzzy method in backward pass calculation. The final value obtained during the backward pass calculation using the rule-correction algorithm is then considered as a mapping function of the learning mechanism of the modified neuro-fuzzy system. Effectiveness of the proposed identification technique is demonstrated through a simulation study on the flood series of the Citarum River in Indonesia. The first four-year data (1987 to 1990) was used for model training/calibration, while the other remaining data (1991 to 2002) was used for testing the model. The number of antecedent flows that should be included in the input variables was determined by two statistical methods, i.e. autocorrelation and partial autocorrelation between the variables. Performance accuracy of the model was evaluated in terms of two statistical indices, i.e. mean average percentage error and root mean square error. The algorithm was developed in a decision support system environment in order to enable users to process the data. The decision support system is found to be useful due to its interactive nature, flexibility in approach, and evolving graphical features, and can be adopted for any similar situation to predict the streamflow. The main data processing includes gauging station selection, input generation, lead-time selection/generation, and length of prediction. This program enables users to process the flood data, to train/test the model using various input options, and to visualize results. The program code consists of a set of files, which can be modified as well to match other purposes. This program may also serve as a tool for real-time flood monitoring and process control. The results indicate that the modified neuro-fuzzy model applied to the flood prediction seems to have reached encouraging results for the river basin under examination. The comparison of the modified neuro-fuzzy predictions with the observed data was satisfactory, where the error resulted from the testing period was varied between 2.632% and 5.560%. Thus, this program may also serve as a tool for real-time flood monitoring and process control.

Evaluating fine sediment mobilization and storage in a gravel‐bed river using controlled reservoir releases

AbstractTwo controlled flow events were generated by releasing water from a reservoir into the Olewiger Bach, located near Trier, Germany. This controlled release of near bank‐full flows allowed an investigation of the fine sediment (<63 µm) mobilized from channel storage. Both a winter (November) and a summer (June) release event were generated, each having very different antecedent flow conditions. The characteristics of the release hydrographs and the associated sediment transport indicated a reverse hysteresis with more mass, but smaller grain sizes, moving on the falling limb. Fine sediment stored to a depth of 10 cm in the gravels decreased following the release events, indicating the dynamic nature and importance of channel‐stored sediments as source materials during high flow events. Sediment traps, filled with clean natural gravel, were buried in riffles before the release of the reservoir water and the total mass of fine sediment collected by the traps was measured following the events. Twice the mass of fine sediment was retained by the gravel traps compared with the natural gravels, which may be due to their altered porosity. Although the amount of fine sediment collected by the traps was not significantly related to measures of gravel structure, it was found to be significantly correlated to measures of local flow velocity and Froude number. A portion of the traps were fitted with lids to restrict surface exchange of water and sediment. These collected the highest amounts of event‐mobilized sediments, indicating that inter‐gravel lateral flows, not just surface infiltration of sediments, are important in replenishing and redistributing the channel‐stored fines. These findings regarding the magnitude and direction of fine sediment movement in gravel beds are significant in both a geomorphic and a biological context. Copyright © 2006 John Wiley & Sons, Ltd.

Combined Sewer Overflow forecasting with Feed-forward Back-propagation Artificial Neural Network

A feed-forward, back-propagation Artificial Neural Network (ANN) model has been used to forecast the occurrences of wastewater overflows in a combined sewerage reticulation system. This approach was tested to evaluate its applicability as a method alternative to the common practice of developing a complete conceptual, mathematical hydrological-hydraulic model for the sewerage system to enable such forecasts. The ANN approach obviates the need for a-priori understanding and representation of the underlying hydrological hydraulic phenomena in mathematical terms but enables learning the characteristics of a sewer overflow from the historical data. The performance of the standard feed-forward, back-propagation of error algorithm was enhanced by a modified data normalizing technique that enabled the ANN model to extrapolate into the territory that was unseen by the training data. The algorithm and the data normalizing method are presented along with the ANN model output results that indicate a good accuracy in the forecasted sewer overflow rates. However, it was revealed that the accurate forecasting of the overflow rates are heavily dependent on the availability of a real-time flow monitoring at the overflow structure to provide antecedent flow rate data. The ability of the ANN to forecast the overflow rates without the antecedent flow rates (as is the case with traditional conceptual reticulation models) was found to be quite poor.

Prediction of macrophyte communities in drought-affected groundwater-fed headwater streams

The results of a 10 year study of groundwater-dominated streams in the chalklands of southern England show that macrophyte communities occupying the headwaters of such streams have a measurable variability in terms of species composition and spatial cover, especially in relation to river flow. This occurs as a result of species adaptation to typically ephemeral flow regimes. Associations have also been established between variations in the vegetation and hydroclimatic parameters at the catchment scale, such as rainfall, percolation and soil moisture conditions. This has led to the derivation of a system whereby the nature of headwater macrophyte communities can be forecast/hindcast, on the basis of parameterized, antecedent flow records, to a current accuracy level of 72% for any of 13 community types and 90% for any of four community groups. It is anticipated that this accuracy rate will improve with (i) an updated community classification, (ii) refinement of the parameterization procedures for flow records, and (iii) the extension of the method from the six study streams currently under scrutiny to a further 18 streams. Greater accuracy of prediction will be constrained by natural variation within the vegetation and the interaction of an array of geomorphological and land-use variables operating at diverse spatial scales. The process used here to establish vegetation–flow relationships could be used in other locations with groundwater-fed streams, providing a useful tool for assessing some of the impacts of bioclimatic changes driven by global warming. Copyright © 2005 John Wiley & Sons, Ltd.

An experimental test of the effects of food resources and hydraulic refuge on patch colonization by stream macroinvertebrates during spates

1. The passive or active movement of organisms between habitat patches plays important roles in achieving ecosystem resilience to disturbance and long-term control of population levels. However, causal mechanisms of disturbance-induced movements of mobile biota across heterogeneous habitat patches at a relatively short time-scale are little understood. 2. We experimentally tested the effects of food resource values on macroinvertebrate colonization of hydraulic refugia from spates in a second-order creek. Experimental cages were colonized by macroinvertebrates with combinations of resource types (natural or polyester leaves), and extent of exposure to stream flow (exposed to or sheltered from current); one half of each set was collected before and after a spate. This experiment was repeated over three spates of varying magnitude and seasonal contexts. 3. Pre-spate colonization was consistently greater for the cages with natural leaves relative to artificial leaves regardless of the extent of flow exposure. Two autumn spates with relatively low and stable antecedent flow conditions caused large movements of organic matter and macroinvertebrates across the stream, showing community-level accumulations into hydraulically sheltered patches independent of food treatment. The smallest spate with high and variable antecedent flows during winter resulted in negligible responses, which we interpret to be a result of depletion of easily transportable organic matter and organisms. 4. Two detritivorous taxa, the mayfly Paraleptophlebia spp. and stonefly Despaxia augusta (Banks) were the most responsive to autumn spates, and had disproportionately higher colonization rates of cages when provided with natural leaves during the largest autumn spate. Preferential settlement in food-enriched hydraulic refugia was attributable to taxon-specific mobility related to efficient acquisition of detritus resource, whose availability varies spatially and temporally. 5. Our findings suggest (1) detritivorous macroinvertebrate colonization of hydraulic refugia can be influenced by hydraulic controls as well as food resource value, and (2) pre-spate environmental conditions in terms of resource distribution and availability may pre-condition organisms' susceptibility to spates and also affect refugium usage, at least in food-limited, detritus-based stream systems.

Flume investigations into the influence of shear stress history on a graded sediment bed

A series of flume‐based experiments was undertaken to investigate the effect of below‐threshold antecedent flow conditions on the stability of a graded sediment bed (D16 = 1.8 mm, D50 = 4.8 mm, D84 = 7.8 mm, and σg = 2.08). The experiments revealed that stability is dependent not only on the applied shear stress of the antecedent flow (1.46, 2.08, 2.19, 2.41, and 2.63 N m−2) but also on its duration (0, 15, 30, 60, 1440 and 5760 min). A new stability diagram has been developed to illustrate stress history effects for the graded substrates and hydraulic conditions used in the investigation. The diagram has implications for flume‐based experimental practice, the prediction of sediment transport rates, and sediment management in river restoration.

A Daily Time Series Analysis of StreamWater Phosphorus Concentrations Along an Urban to Forest Gradient

During a 1-year period, we sampled stream water total phosphorus (TP) concentrations daily and soluble reactive phosphorus (SRP) concentrations weekly in four Seattle area streams spanning a gradient of forested to urban-dominated land cover. The objective of this study was to develop time series models describing stream water phosphorus concentration dependence on seasonal variation in stream base flows, short-term flow fluctuations, antecedent flow conditions, and rainfall. Stream water SRP concentrations varied on average by +/- 18% or +/- 5.7 microg/L from one week to another, whereas TP varied +/- 48% or +/- 32.5 microg/L from one week to another. On average, SRP constituted about 47% of TP. Stream water SRP concentrations followed a simple sine-wave annual cycle with high concentrations during the low-flow summer period and low concentrations during the high-flow winter period in three of the four study sites. These trends are probably due to seasonal variation in the relative contributions of groundwater and subsurface flows to stream flow. In forested Issaquah Creek, SRP concentrations were relatively constant throughout the year except during the fall, when a major salmon spawning run occurred in the stream and SRP concentrations increased markedly. Stream water SRP concentrations were statistically unrelated to short-term flow fluctuations, antecedent flow conditions, or rainfall in each of the study streams. Stream water TP concentrations are highly variable and strongly influenced by short-term flow fluctuations. Each of the processes assessed had statistically significant correlations with TP concentrations, with seasonal base flow being the strongest, followed by antecedent flow conditions, short-term flow fluctuations, and rainfall. Times series models for each individual stream were able to predict approximately 70% of the variability in the SRP annual cycle in three of the four streams (r2 = 0.57-0.81), whereas individual TP models explained approximately 50% of the annual cycle in all streams (r2 = 0.39-0.59). Overall, time series models for SRP and TP dynamics explained 82% and 76% of the variability for these variables, respectively. Our results indicate that SRP, the most biologically available and therefore most important phosphorus fraction, has simpler and easier-to-predict seasonal and weekly dynamics.

Runoff Characteristics in a Tropical Rain Forest Catchment

Knowledge of runoff characteristics plays an important role in managing the function of water conservation in the forests. Hydrological observation was conducted at Bukit Tarek Experimental Watershed (BTEW) of a tropicalrain forest in Peninsular Malaysia. Stormflow, groundwater recession and stream regimen characteristics were analyzed based on 3-y (1992-1994) of record. Small storm events (< 30 mm) produced less than 10% of rainfall as stormflow, which may have been determined in the stream channel and riparian areas. The stormflow depended strongly on the antecedent wetness as represented by the antecedent flow rate during large storm events (≥ 30 mm). The depth and physical properties of soils could be important factors to determine production of stormflow. The discharge-duration curves were different among 1992, 1993 and 1994 because of the differences of variation in rainfall (e.g. monthly distribution) and annual rainfall. The relationship between ratio of plentiful runoff to scanty runoff and recession coefficient at BTEW was similar to the results from watershed underlain by the same geology in Japan. These results imply that soil, variation in rainfall, as well as annual rainfall and geology are important factors to understand runoff characteristics.

Climate-Induced Episodic Acidification of Streams in Central Ontario

In this study we have analyzed the hydrochemical effect of drought conditions during 311 hydrological episodes in nine headwater streams in central Ontario over the past 20 years. Acid Neutralization Capacity (ANC) was logarithmically correlated (p<0.05) to antecedent discharge in eight of the nine streams, with the largest decline in ANC occurring after low antecedent flow. In eight of the nine streams SO4(2-) was the most important driving mechanism of ANC decline, but dilution as well as organic acidity was important in several streams. No decrease in the SO4(2-) driven ANC decline was observed over the 20 year study period despite a approximately 40% reduction in SO4(2-) deposition. The strong correlation between ANC decline and low antecedent discharge demonstrates that episodic acidification during rain events is strongly associated with preceding drought conditions, especially in wetland-dominated catchments. The results have important implications for recoveryfrom acidification, especially in northern ecosystems where climate scenarios forecast that warmer and drier conditions will be more common.

Recession flow analysis of the Blue Nile River

AbstractEstimates of the amount of recession flow can be derived from streamflow records. Such estimates are critical in the assessment of low flow characteristics for the Blue Nile River, from which about two‐thirds of the irrigation requirements in Sudan are satisfied. The recession flow hydrograph can be estimated by fitting the conceptual non‐linear storage outflow model using an iterative algorithm. An analytical model to forecast the Blue Nile recession flow is developed and the performance of the model is compared to the previous Blue Nile recession flow model. In the proposed model, a simple linear regression equation is introduced to illustrate the effect of antecedent flow on the recession parameter. Results indicate that the model can provide a simple and reliable method to predict the recession flow of the Blue Nile River. Copyright © 2003 John Wiley &amp; Sons, Ltd.

Dunes and associated sand transport in a tidally influenced sand-bed channel: Fraser River, British Columbia

Dunes form annually on the sand bed of the tidally influenced South Arm of Fraser River, British Columbia. Bathymetric surveys along the center of the main channel throughout a snow-melt freshet provided measurements of dune geometry and migration. Dune length, height, and steepness all increase with river discharge. However, lag between the highest flow conditions and development of the largest, steepest dunes reflects the influence of antecedent flow conditions on dune geometry. Population averages of dune height and steepness ratio change more rapidly than dune length, whilst coefficients of variation of dune height, length, and steepness ratio indicate high variability in dune geometry within the estuarine reach during periods of dune growth and decay. Unlike dune geometry, dune migration rates display little lag with flow conditions. The largest coefficients of variation for dune migration occur during periods of rapid change in discharge and tidal fall, corresponding to the onset of rapid change in dune geometry on both rising and falling limbs. Migration rate estimates and geometry measurements are used to estimate associated sand transport. In the absence of hydraulic measurements in the estuary, Mission and Hope discharges are adopted to drive simple statistical models of sand transport as a function of discharge and tidal fall. The models cover 65–70% of the transport, and tidal fall is only marginally significant. Comparison with historical direct measurements indicates that the dune-associated transport coincides with bed-load transport in the estuary, and arguments are made that it constitutes the preponderance of all bed-material transport.

INSTANTANEOUS RESPONSE FUNCTIONS OF OVERLAND FLOW AND SUBSURFACE STORMFLOW FOR CATCHMENT MODELS

The storm response of a catchment can be considered to consist of two components; the hillslope response and the stream network response. The first of these is examined here. Simple analytical models of overland flow and subsurface stormflow are presented which are applicable for use in catchment-scale models of the rainfall-runoff response. The hillslope models are meant to describe the collective responses of the hillslopes in a catchment in a simple way that is also physically meaningful. The overland flow model is based on a generalization of classic work by Horton and of more recent work by Rose et al. known as Rose's approximation. The subsurface flow model consists of two components. The piston displacement model is used to describe flow in the unsaturated zone between the soil surface and the perched water-table. The kinematic assumption combined with Rose's approximation is used to describe flow in the saturated zone. These hillslope models are then used to derive instantaneous response functions for both overland flow and subsurface stormflow, under different rainfall intensities and antecedent flow conditions.