This paper begins with a critique of existing rainfall runoff models and proceeds to a largely new formulation in which the single store (representing, for example, interception of rainfall by vegetation, or retention of water in upper soil layers, or possibly both) is replaced by a statistical population of stores. The consequences of such an assumption are illustrated for the simplest, one‐parameter case in which the distribution of store depths is exponential. It is demonstrated that the use of a population of stores, even with but one parameter, can (1) afford a plausible description of the relation between actual evaporation and soil moisture deficit and (2) remove discontinuities of gradient in the objective function, optimization of which gives estimates of model parameters. The new formulation also permits observed runoff to be written down as a relatively simple function of past rainfall, potential evaporation, and the parameters in the statistical distribution of storages, with the consequence that gradient methods can be used to optimize the objective function in place of more time‐consuming direct search methods. An extension of the model to account for the translation of runoff to the basin outfall is accomplished by using a bivariate distribution of translation times and store depths. A simple recursive equation relating current flow to a proportion of the previous flow and an additive function of rainfall is obtained under the assumption that translation times and store depths are independent and exponentially distributed. More complex models are derived by relaxing the assumption of independence and by considering distributions other than exponential; expressions for two positively skewed density functions, the Weibull and gamma, are obtained. Series and parallel configurations of distribution function models are considered, and the relation of the models' elemental structure to different types of store commonly employed in conceptual modeling is discussed. The new formulation includes, as particular cases, all models based on linear systems theory. Application of the modeling approach to hourly values of flow, rainfall, and evapotranspiration from a number of the Institute of Hydrology's experimental basins results in very good model predictions of flows over the calibration period, with R2 values above 0.9. However, this level of performance as measured by the R2 statistic is not maintained over the test period, although quite reasonable predictions of the flood peaks are still obtained. The drop in performance is partly ascribed to the nature of the calibration period during which the basins were ‘wetting up’ after two years of relatively extreme drought. Model performance over the test period is improved by using a more realistic initial condition for the store contents but only at the expense of reduced R2 values in the calibration period. The need to assess the new model approach in a range of hydrological environments is recognised, especially where evapotranspiration forms an important com...
Abstract:In situ turbidity meters are being increasingly used to generate continuous records of suspended sediment concentration in rivers. However, the usefulness of the information obtained depends heavily on the existence of a close relationship between fluctuations in suspended sediment concentration and turbidity and the calibration procedure that relates suspended sediment concentration to the turbidity meter's signal. This study assesses the relationship between suspended sediment concentration and turbidity for a small (1Ð19 km 2 ) rural catchment in southern Brazil and evaluates two calibration methods by comparing the estimates of suspended sediment concentration obtained from the calibrated turbidity readings with direct measurements obtained using a USDH 48 suspended sediment sampler. With the first calibration method, the calibration relationship is derived by relating the turbidity readings to simultaneous measurements of concentration obtained from suspended sediment samples collected from the vicinity of the turbidity probe during flood events. With the second method, the calibration is based on the readings obtained from the turbidity meter when the probe immersed in samples of known concentration prepared using soils collected from the catchment. Overall, there was a close link between fluctuations in suspended sediment concentration and turbidity in the stream at the outlet of the catchment, and the estimates of sediment concentration obtained using the first calibration method corresponded closely with the conventionally measured sediment concentrations. However, use of the second calibration method introduced appreciable errors. When the estimated sediment concentrations were compared with the measured values, the mean errors were š122 mg l 1 and C601 mg l 1 for the first and second calibration procedures respectively.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.