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Karen Torres Analog, empirical, process, hybrid techniques I. Introduction. Application of model techniques in River Restoration a. Gross representation of real system processes b. Use known information of watershed processes to make predictions of watershed response to changes in input parameters. Examples would be changes in precipitation, land cover, evapo-transpiration and topography. c. Benefits-saves time and costs and can be modified based on additional’ improved parameter data. II. Model Overview Used Fleming classification, which will be used in this article, subdivides deterministic hydrology into empirical methods and conceptual models, and statistical hydrology into probabilistic methods and stochastic models. <Model Flow Chart> a. Types of Models- Deterministic - Statistical i. Deterministic treat the hydrological processes in a physical way and make use of historical stream flow data as well as data on rainfall and other phenomena (infiltration, evapo-transpiration etc.) which affect the properties of runoff, once the parameters are determined, deterministic methods always produce the same output from a given input. Categorized into empirical and conceptual ii. Statistical methods utilize information from the analysis of historical stream flow data only. Because these methods deal directly with stream flow its characteristics can only be described by the theory of statistics. 1. Stochastic Models use the statistical characteristics or to predict possible outcomes. Uses a random element to generate different outcomes with each model simulation. The probability of the various model results are calculated and used to predict the frequency of a particular scenario. Will not be discussed in this paper. III. Empirical models a. Regression model that uses statistics/ probability to relate measureable processes to a particular discrete response. (example needed i. Rational Method- Estimated by formula ππ πΆπππ΄ πΎπ Qp – Peak Discharge (L3/T) C = runoff constant Pg = rainfall intensity (L/T) A = area Km = constant 360 for metric. 1. Assumes rainfall intensity is uniform: used when little data exists like sizing a road culvert. ii. Unit Hydrograph Complexities of basin defined by a single empirical curve (Boonstra MM each drainage basin has a unique hydrograph Physical Characteristics of drainage basin (shape, size slope) are constant. 1. Volume of storm flow from an isolated event by rainfall, sufficient to flow into the stream, of short duration is plotted against time. Storm flow is separated from base flow and divided by the drainage area to equate flow to depth of precipitation. Divide area under the discharge curve into ordinates (equal sections) Divide the value of each section by the depth of precipitation to develop a normalized graph of rainfall intensity vs. time. The difference between total precipitation and storm flow are attributed to losses (interception, storage, deep seepage) (books et al) Observed flow separated into Base flow and runoff. Runoff is the stream flow caused. Is measured as the increase in flow above the base flow, or constant flow not attributed to storm events. b. Conceptual Models- integration of empirical methods but on a continuous time basis versus a single event. Assigns a mathematical operation to for each major component of the hydrological cycle. . There is an assumption that the system functions are well understood and can be mathematically simulated. Basin characteristics are fed into the model; corresponding runoff data is calculated and compared to observed data. Input parameters are adjusted to fit the historic data. i. GIS Models ii. HEC RAS iii. Modflow iv. Hybrid Models