A part of the streamflow construction and simulation process is the verification that a stochastic streamflow model reproduces those statistics which by design it should reproduce; the use of unbiased statistics is shown to be advantageous in this exercise. In addition, if a model reproduces statistics not used in the model-parameter estimation process, its credibility is further enhanced. These concepts are illustrated, and the performance of a wide range of monthly streamflow models are compared using data for the upper Delaware River basin in New York State. INTRODUCTION Stochastic monthly streamflow models are often used in simulation studies to evaluate the likely future performance of water resource systems. The development and use of a stochastic streamflow model can involve all of the following basic steps: (1) obtain streamflow records and other information, (2) select models to describe the marginal probability distributions of flows in different seasons and estimate the models' parameters, (3) select an appropriate model of the spatial and temporal dependence of the streamflows, (4) verify that the computer implementation of the model performs as specified, (5) validate the model for water resource system simulation, and (6) use the model. First, one collects the data to be used for parameter estimation, model verification, and any model validation. Then an appropriate model of the temporal and spatial dependence of flows and the marginal distribution of flows at each site in each period is selected, and its parameters are estimated. The fourth and fifth steps involve model verification and validation. An important distinction between these two activities has been drawn in the simulation literature [Fishman and Kiviat, 1968; Mihram, 1972; Schlesinger et al., 1979]. Schlesinger et al. [1974] describe verification asthe certification that the model is implemented on the computer in a manner that truly depicts the idealized model.

The parameters of stochastic models of monthly streamflows can be estimated with only limited precision given the finite and often short streamflow records available for planning. This paper illustrates the impact of the uncertainty in the parameters of the distribution of annual flows on estimates of monthly reservoir system reliability. Even with the 50-year flow record available for the upper Delaware River basin, the impact of the uncertainty in parameters describing the distribution of annual flows on estimated capacity-reliability relationships is shown to be rather large and as important as the choice between a relatively simple Thomas-Fiering monthly streamflow model and a Markov model of annual flows coupled with disaggregation to obtain monthly values.

No abstract

Since the mid‐1970's, a number of research projects at Cornell University have focused on the development and application of interactive models and computer programs for studying water resources and environmental management problems. These models and programs have been adapted for use with computer graphics display devices. This interactive computer‐aided planning system has been designed to facilitate data input, editing, and display; model building and solution; and analysis and synthesis of alternative resource management plans or policies. This paper discusses the approaches taken for managing and displaying data that are needed for, and derived from, this interactive modeling system. Several applications are presented and some conclusions on how such systems might be developed or expanded in the future are proposed.

No abstract