Graduate Thesis Or Dissertation
 

A water balance model for reforestation sites : description and sensitivity

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https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/8910jx67q

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  • A model was developed for analysis of the soil water balance of individual reforestation sites in western Oregon. The numerical procedure for this model was programmed in compiled BASIC language and calculations for an entire season are made in about 180 seconds on an IBM AT microcomputer. The processes that define the water balance are represented in five model components: 1) An estimate of potential evapotranspiration using the energy-based Jensen-Haise method, 2) Partitioning of evapotranspiration from estimates of percentage cover by vegetation type and soil surface cover, 3) Actual evaporation at the soil surface, 4) Actual transpiration from calculations of soil water supply limit and the Nimah-Hanks uptake method, and 5) Soil water flow, including redistribution and drainage. The input data requirement consists of 20 parameters for characterizing site variation of climate, soil, and ground cover. Surface cover conditions (slash, mulch, and litter) and plant competition (grasses, forbs, and shrubs) are featured in the model because these ground cover variables are a major reforestation concern. The minimum input data requirement has been simplified in order to accomodate users with limited data for practical applications. Output of the model includes estimates of solar radiation, soil water storage, total water loss, and water allocation. To test the validity of model output, calculations of water loss were compared to measured values from a detailed field study of the environmental effects of site management practices. The results confirm that the model performs reasonably well and that theory and assumptions of the model are appropriate. Results of a sensitivity analysis are given in order to evaluate the importance of input parameters and to consider the effects of data error. The analysis demonstrates limitations and possible uses of the model. The predictive ability of the model was found to be most limited by the availability of precipitation data; this does not limit the model as a comparative tool. One important use of the model is the identification of harsh sites and potential water-limiting conditions. Model estimates will also facilitate the consideration of forest management options regarding type of harvest, modification of the seedling environment, species selection, and choice of stock characteristics.
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