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In recent years, the continued technological advances have led to the spread of low-cost sensors and devices supporting crowdsourcing as a way to obtain observations of hydrological variables in a more distributed way than the classic static physical sensors. The main advantage of using these type of sensors is that they can be used not only by technicians but also by regular citizens. However, due to their relatively low reliability and varying accuracy in time and space, crowdsourced observations have not been widely integrated in hydrological and/or hydraulic models for flood forecasting applications. Instead, they have generally been used to validate model results against observations, in post-event analyses. This research aims to investigate the benefits of assimilating the crowdsourced observations, coming from a distributed network of heterogeneous physical and social (static and dynamic) sensors, within hydrological and hydraulic models, in order to improve flood forecasting. The results of this study demonstrate that crowdsourced observations can significantly improve flood prediction if properly integrated in hydrological and hydraulic models. This study provides technological support to citizen observatories of water, in which citizens not only can play an active role in information capturing, evaluation and communication, leading to improved model forecasts and better flood management.
A comprehensive series of interconnected computer models are described which assist water control managers in operating reservoir systems during real-time flood emergencies. The need for and the desirable features of a transportable comprehensive software system are presented along with a description of the various computer models developed for this purpose by the Hydrologic Engineering Center of the U.S. Army Corps of Engineers. The functions, capabilities and inerties of the Data Management, Operation, Forecast and Display computer modules used in this software system are described and an example application of this system on one of the Corps' reservoir systems is presented. (Author).
Computer program HEC-1, a precipitation-runoff model widely used throughout the United States, includes the capability to estimate automatically any of twelve parameters necessary to model the precipitation-runoff process and the channel routing process. The parameter estimation scheme employs Newton's method to minimize a weighted sum of squares of differences between observed and computed hydrograph values. Applications of this parameter estimation procedure are presneted, and typical steps of the procedure for deterimining optimal parameter estimates are outlined. Recent efforts to improve the estimation algorithm and recent use of the calibration capability to update sequentially parameter estimates in a flood forecasting application are discussed. (Author).