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標題: 以Arya and Paris Model推估土壤水分特性之研究
Estimation of Soil Water Characteristics with Arya and Paris Model
作者: 陳信宏
Chen, Hsin-Hung
關鍵字: particle size distribution
bulk density
particle density
pedotransfer functions
出版社: 水土保持學系所
摘要: 以傳統及常用之實驗方法來量測土壤水分特性,往往需要相當長的時間及繁瑣的實驗程序,影響可研究之樣本數目,儘管近年來有新的實驗儀器與現地監測技術,來量測並記錄即時的土壤水分特性,已能有效地提昇精確度、減少誤差,但仍具有耗費時間及實驗過程繁複之缺點。因而有學者提出以其他間接的方法或模式,來模擬並推估土壤的水分特性,這些方法一般統稱為「土壤轉換函數(PTFs)」。 本研究所使用的Arya and Paris Model(APM)即是PTFs的其中一種模式。它是以土壤的粒徑分佈、總體密度和顆粒密度,三者來推估土壤水分特性。由於APM需要相當詳盡的粒徑分佈資料,作為推估之依據,礙於資料不易取得,因此本研究將簡化並利用未飽和土壤水力資料庫(UNSODA)的資料,直接從現有的粒徑分佈資料來推估土壤的水分特性,並配合資料庫中試驗量測之結果,作對照並驗證其信賴度。 以五種土壤來做研究,其質地大致上由粗至細,包括:砂土、砂質壤土、壤土、坋質壤土與黏土。從資料庫中篩選出滿足模式要求的土壤性質之樣本,作為本研究之材料。另外,按照所使用的模式參數值,區分成三種處理來進行模式之推估。其中,第一及第二種處理之參數值就所有樣本而言,分別為1.38與0.938。而第三種處理,則依照這五種土壤的質地,分別以1.285、1.459、1.375、1.15和1.16來推估。將模式所需之土壤資料依序輸入模式的計算公式,得到模式估算的土壤含水量及張力勢能。並使模式運算之結果進行曲線擬合,以資料庫中實測之張力勢能為相同條件,對應於水分特性曲線上的推估含水量,以及試驗之實測含水量進行分析,探討模式在各質地的推估能力與表現。 結果顯示,以砂質壤土、壤土和黏土之推估效果較為良好。另外,砂土和坋質壤土兩者推估之情況則是不盡理想。分析各項結果發現,模式適用在中等質地及粒徑分佈較均勻的土壤,而其他質地的土壤,模式則表現不佳。此外,於本研究中當參數值為0.938時,不適合用來推估土壤水分特性。而第一及第三種處理之參數值,依土壤質地之差異,展現出不同的推估效果。
The traditional and frequently used research methods of measuring soil water characteristics, usually take much time and have complicated experimental procedures; this may restrict the number of samples for study. In recent years, in the field new monitoring technologies have been developed and new experimental instruments have been used now to measure and record soil water characteristics effectively. There is less range of error than in the past. Nevertheless they are still time consuming as the research procedures are complex. Therefore, some scholars suggested simulating and estimating the soil water characteristics by indirect methods and models. These are generally called “pedotransfer functions (PTFs).” In this study, the Arya and Paris Model (which is a PTF) was used to estimate soil water characteristics from soil particle size distribution, bulk density, and particle density. This model needs detailed particle size distribution data as the basis for estimating soil water characteristics. Such particle size distribution data is not easy to obtain. For this reason, this research has simplified and made use of particle size distribution data available directly from the unsaturated soil hydraulic databases (UNSODA) to estimate soil water characteristics, and to compare the results with measured data from databases, in order to compare and evaluate their reliability. Soils with five kinds of textures from coarse to fine were selected as study materials. These were sand, sandy loam, loam, silt loam, and clay. The chosen criteria for the soil samples from the database had to correspond to soil properties needed in the model. For all samples, in the first and the second treatment, the parameter values in the model are 1.38 and 0.938. However, in the third treatment, the parameter values were set at 1.285, 1.459, 1.375, 1.15, and 1.16 respectively, according to the textures of the five kinds of soils. The essential soil data were put sequentially into the equations of the model, in order to compute the soil water content and the matric potential, then curve fitting technique was applied to establish the soil water characteristic curve equation. Assuming measured matric potential from database as the same conditions, estimated water content was compared with measured water content; then the estimating performance, and capability of model for different soil textures was discussed. The results indicated that the model performed comparatively well for sandy loam, loam, and clay. But for sand and silt loam the results were less good. Consequently, this model is suitable for the soils with medium texture and uniform particle size distribution, but not so suitable for other kinds of soil. This study also demonstrated that it is also inappropriate to use this method when the parameter value is 0.938. With regard to the first and the second treatment, different soil textures produced different soil water estimates.
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