Hydrodynamic Simulations Of Vacuum-Driven Storage Tanks

As a result of urbanization, stormwater runoff flow rates and volumes are significantly increased due to increasing impervious land cover and the decreased availability of depression storage. Storage tanks are the basic devices to efficiently control the flow rate in drainage systems during wet weather. Presented in the paper conception of vacuum-driven detention tanks allows to increase the storage capacity by usage of space above the free surface water elevation at the inlet channel. Partial vacuum storage makes possible to gain cost savings by reduction of both the horizontal area of the detention tank and necessary depth of foundations. Simulation model of vacuum-driven storage tank has been developed to estimate potential profits of its application in urban drainage system. Although SWMM5 has no direct options for vacuum tanks an existing functions (i.e. control rules) have been used to reflect its operation phases. Rainfall data used in simulations were recorded at raingage in Czestochowa during years 2010÷2012 with time interval of 10minutes. Simulation results gives overview to practical operation and maintenance cost (energy demand) of vacuum driven storage tanks depending of the ratio: vacuum-driven volume to total storage capacity. The following conclusion can be drawn from this investigations: vacuum-driven storage tanks are characterized by uncomplicated construction and control systems, thus can be applied in newly developed as well as in the existing urban drainage systems. the application of vacuum in underground detention facilities makes possible to increase of the storage capacity of existing reservoirs by usage the space above the maximum depth. Possible increase of storage capacity can achieve even a few dozen percent at relatively low investment costs. vacuum driven storage tanks can be included in existing simulation software (i.e. SWMM) using options intended for pumping stations (including control and action rules ).

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.