Watershed hydrologic modeling

Refsgaard, J. C. and B. Storm. 1995. MIKE SHE. In V. P. Singh (ed.) Computer Models of Watershed Hydrology. Water Resources Publishers, Highlands Ranch, CO. pp. 809-846. 

Direct measurement of transpiration is difficult for all but relatively small plants that can be grown in weighing lysimeters or enclosed in chambers in which the flux of water can be ealculated from the humidity increase in the enclosure. Common approaches used to quantify transpiration in the field include precipitation minus runoff on gauged watersheds, energy balance equations (Allen et al., 1998), eddy covariance (water vapor gradients above and below canopy) (Baldocchi, 2003), hydrologic models, and sap flow measurements (Vose et al., 2003). 

Assists in modeling a watershed and creating the inputs to HEC-1 for hydrologic simulations. 

HSPF. The Hydrologic Simulation Program (FORTRAN) ( 1, 42) is based on the Stanford Watershed Model. Version 7 of HSPF incorporates the process models of SERATRA in its aquatic section, with several (user-selectable) options for sediment transport computations. HSPF includes the generation of transformation products, each of which is in turn subject to volatilization, phototransformation, biolysis, etc. 

Soil compartment chemical fate modeling has been traditionally performed for three distinct subcompartments the land surface (or watershed) the unsaturated soil (or soil) zone and the saturated (or groundwater) zone of a region. In general, the mathematical simulation is structured around two major cycles the hydrologic cycle and the pollutant cycle, each cycle being associated with a number of physicochemical processes. Watershed models account for a third cycle sedimentation. 

The Stanford Watershed Model (SWM) developed at Stanford University (10- It can simulate the hydrologic behavior of an entire watershed. 

Hydrology Stanford Watershed Model IV. Dept, of Civ. Eng., Stanford Univ., Stanford, Calif. Tech- Rep.39. 1966. 210... 

Parameters for which measured values are not clearly defined or readily available are often determined through calibration with observed data. In watershed chemical fate modeling, calibration has traditionally been associated with hydrologic parameters (e.g., erodibility coefficients, scour and deposition rates) because the required flow and sediment data are often available. Although initial parameter values can always be estimated, calibration is usually recommended to account for local and spatial variations. 

Borah DK, Bera M (2004) Watershed scale hydrologic and nonpoint source pollution models review of applications. Trans ASAE 47(3) 789-803... 

Perhaps most easy to overlook are spatial and temporal dependencies. For example, the hydrologic component of the pesticide root zone model-exposnre analysis modeling system (PRZM-EX AMS) treats mnltiple field plots over whole watersheds as independent, nnconpled, simple, 1-dimensional flow systems. In reality, the field plots are coupled systems that exhibit complex 3-dimensional water flow and pesticide transport (US SAP 1999). These higher order processes introduce spatial dependencies that may need to be considered in the assessment. Temporal autocorrelations are also likely when assessing exposure. 

Tschantz, B. A. Moran, B. M. Modeling of the Hydrologic Transport of Mercury in the Upper East Fork Poplar Creek (UEFPC) Watershed Technical Report for Lockheed Martin Energy Systems Bethesda, MD, September 2004. 

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