The Estimation of Mean Monthly River Flows Using Limited Meteorological Data and Catchment Characteristics

Abstract

This project aims to estimate mean monthly flows at any given point on a river in a region of sparce hydrometric data. A conceptual model of the rainfall/run-off process has been developed which utilises available mean monthly meteorological data and catchment characteristics, The essential characteristics of the hydrological stores and processes and their relationship with catchment morphology are identified. The physical characteristics are defined in quantitative terms,and the meteorological characteristics and hydrological stores and processes are examined. The development and calibration of a rainfall/run-off model, based upon a monthly time step and incorporating the hydrological components and catchment characteristics is described. Two principal modifications were made to the model, firstly to the overland flow/interflow algorithm and secondly to the natural recharge/interflow algorithm. The validity of the model and its modified versions were’ tested using data from areas of the U.K. lying outside the original study area, The predicted mean monthly flows compared very favourably with the historic flows and thereby demonstrated the value of catchment characteristics for model calibration in areas of limited hydrometric data. Comparisons are made with the results obtained using a method based upon linear regression equations derived in a previous project using data from the same study area. The results show that the new models are far superior to the regression method when applied to areas outside the area used for calibration. The development and testing of the models and their calibration procedures form the bulk of the project, and the use of catchment characteristics for the calibration of the model is a novel feature of the study.