臺灣博碩士論文加值系統

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.

中文摘要 i
英文摘要 iii
目次 v
圖目次 vii
表目次 x
符號說明 xii

第一章　前言 1
第一節 緣起 1
第二節 研究動機與目的 2
第二章　前人研究 4
第一節 土壤水分特性曲線 4
第二節 量測方法及模式的起源 6
第三節 模式的發展 6
第四節 模式的演進 9
第五節 土壤資料庫之應用 10
第三章　理論基礎 13
第一節 土壤保水機制 13
第二節 模式理論及假設 13
第四章　研究材料與方法 17
第一節 研究流程 17
第二節 研究材料 18
第三節 模式之運算 29
第四節 資料分析 30
第五章　結果與討論 34
第一節 推估所得各質地土壤水分特性 34
第二節 參數值對於模式推估之影響 44
第三節 資料來源對推估結果之影響 56
第四節 模式推估能力之評估 58
第六章　結論與建議 61
第一節 結論 61
第二節 建議 62
參考文獻 64
附錄 70
一、樣本粒徑分佈資料 70
二、實測之土壤水分特性資料 80

一、圖書
1.林俐玲、董小萍（1996），「土壤物理學實習手冊」，國立中興大學水土保持學系。
2.萬鑫森 譯（1987），「基礎土壤物理學」，國立編譯館主編，茂昌圖書有限公司發行。
二、期刊論文
1.謝銘（2002），「中部地區坡地土壤水分流動之研究」，國立中興大學水土保持學系研究所碩士論文。
2.Arya, L. M., and J. F. Paris (1981) A physico-empirical model to predict soil moisture characteristic from particle-size distribution and bulk density data. Soil Sci. Soc. Am. J. 45:1023–1030.
3.Arya, L. M., J. C. Richter, and S. A. Davidson (1982), A comparison of soil moisture characteristic predicted by the Arya-Paris model with laboratory-measured data. AgRISTARS Tech. Rep. SM-L1-04247, JSC-17820. NASA-Johnson Space Center, Houston, TX.
4.Arya, L. M. and T. S. Dierolf (1992), Predicting soil moisture characteristics from particle-size distribution: An improved method to calculate pore radii from particle radii. p115-125. In: van Genuchten et al.(ed.) Proc. Int. Workshop on Indirect Methods for Estimating the Hydraulic Properties of Unsaturated Soils. U.S. Salinity Laboratory, Riverside, CA.
5.Arya, L. M., F. J. Leij, M. Th. van Genuchten, and P. J. Shouse (1999a), Scaling parameter to predict the soil water characteristic from particle-size distribution data. Soil Sci. Soc. Am. J. 63:510–519.
6.Arya, L. M., F. J. Leij, P. J. Shouse, and M. Th. van Genuchten (1999b), Relationship between the hydraulic conductivity function and the particle-size distribution. Soil Sci. Soc. Am. J. 63:1063–1070.
7.Basile, A., and G. D’Urso (1997), Experimental corrections of simplified methods for predicting water retention curves in clay-loamy soils from particle-size determination. Soil Technology 10:261-272.
8.Brooks, R. H., and A. T. Corey (1964), Hydraulic properties of porous media. Hydrology Paper 3. Colorado State Univ., Fort Collins, CO.
9.Bouma, J. (1989), Using soil survey data for quantitative land evaluation. Adv. Soil Sci. 9:177–213.
10.Buczko, U., and H. H. Gerke (2005), Evaluation of the Arya and Paris Model for estimating water retention characteristics of lignitic mine soils. Soil Sci. 142:483–494.
11.Campbel, G. (1974), A simple method for determining unsaturated conductivity from moisture retention data. Soil Sci. 142:311–314.
12.Comegna, V., P. Damiani , and A. Sommella (1998), Use of a fractal model for determining soil water retention curves. Geoderma 85:307-323.
13.Cornelis, W. M., J. Ronsyn, M. Van Meirvenne, and R. Hartmann (2001), Evaluation of pedotransfer functions for predicting the soil moisture retention curve. Soil Sci. Soc. Am. J. 65:638–648.
14.Gee, G. W., and J. W. Bauder (1986) Particle size analysis. In: Methods of Soil Analysis: Part 1, second ed. American Society of Agronomy (Agronomy 9), Madison, p383–411.
15.Gupta, S. C., and R. P. Ewing (1992), Modeling water retetion characteristics and surface roughness of tilled soils. p379-388. In: van Genuchten et al.(ed.) Proc. Int. Workshop on Indirect Methods for Estimating the Hydraulic Properties of Unsaturated Soils. U.S. Salinity Laboratory, Riverside, CA.
16.Hwang, S. I, K. P. Lee, D. S. Lee, and S. E. Powers (2002), Models for estimating soil particle-size distributions. Soil Sci. Soc. Am. J. 66:1143–1150.
17.Hwang, S. I. and S. E. Powers (2003), Using Particle-Size Distribution Models to Estimate Soil Hydraulic Properties. Soil Sci. Soc. Am. J. 67:1103–1112.
18.Haverkamp, R., M. Vauclin, J. Touma,; P. J. Wierenga, and, G. Vachaud (1977), A Comparison of Numerical Simulation Models for One-Dimensional Infiltration. Soil Sci. Soc. Am. J. 41:285 - 294.
19.Jones, S. B., and D. Or. (1998), Design of porous media for optimal gas and liquid fluxes to plant roots. Soil Sci. Soc. Am. J. 62:563 - 573.
20.Lascano, R. J. and L. Stroosnijder (1993), A simple method for predicting the spatial distribution of soil hydraulic properties. Soil Sci. Soc. Am. J. 57:1479 - 1484.
21.Leij, F. J., W. J. Alves, M. Th. van Genuchten, and J.R.Williams (1996), Unsaturated Soil Hydraulic Database. UNSODA 1.0 User’s Manual Report EPA/600/R96/095. US Environmental Protection Agency, Ada. OK 103p.
22.McBratney, A. B., B. Minasny, S. R. Cattle, and R. W. Vervoort (2002), From pedotransfer functions to soil inference systems. Geoderma 109:41-73.
23.Meadows, D. G., M. H. Young, and E.V. McDonald (2005), A laboratory method for determining the unsaturated hydraulic properties of soil peds. Soil Sci. Soc. Am. J. 69:807-815.
24.Naime, J. M., C. M. P. Vaz, and A. Macedo (2001), Automated soil particle size analyzer based on gamma-ray attenuation. Computers and Electronics in Agriculture 31:295–304.
25.Nemes, A., J. H. M. Wösten, A. Lilly, and J. H. Oude Voshaar (1999), Evaluation of different procedures to interpolate particle-size distributions to achieve compatibility within soil databases. Geoderma 90:187-202.
26.Nemes, A., M. G. Schaap, F. J. Leij, and J. H. M. Wosten. (2001), Description of the unsaturated soil hydraulic database UNSODA version 2.0. Journal of Hydrology 251:151–162.
27.Skaggs, T. H., L. M. Arya, P. J. Shouse, and B. P. Mohanty (2001), Estimating particle-size distribution from limited soil texture data. Soil Sci. Soc. Am. J. 65:1038 - 1044.
28.Tomasella, J., Ya. Pachepsky, S. Crestana, and W. J. Rawls (2003), Comparison of Two Techniques to Develop Pedotransfer Functions for Water Retention. Soil Sci. Soc. Am. J., July 1, 2003; 67(4):1085 - 1092.
29.van Genuchten, M. Th. (1980), A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44:892-898.
30.van Genuchten, M. Th., and D. R. Nielsen (1985), On describing and predicting the hydraulic properties of unsaturated soils. Ann. Geophys. 3:615–628.
31.Vaz, C. M. P. , M. D. F. Iossi, J. D. M. Naime, Á. Macedo, J. M. Reichert, D.J. Reinert, and M. Cooper (2005), Validation of the Arya and Paris water retention model for Brazilian soils. Soil Sci. Soc. Am. J. 69:577-583.
32.Wildenschild, D., J. W. Hopmans, and J. Simunek (2001), Flow rate dependence of soil hydraulic characteristics. Soil Sci. Soc. Am. J. 65:35-48.
33.Wösten, J. H. M., A. Lilly, A. Nemes, and C. L. Bas (1999), Development and use of a database of hydraulic properties of European soils. Geoderma 90:169-185.
34.Wösten, J. H. M., Y. A. Pachepsky, and W. J. Rawls (2001), Pedotransfer functions: bridging the gap between available basic soil data and missing soil hydraulic characteristics. Journal of Hydrology 251:123-150.
三、網路及電子資源
（一）土壤資料庫
1.台灣坡地土壤圖（1995），水土保持局。
（http://www.swcb.gov.tw/newpage/swcb10/B/08.htm）
2.台灣省山坡地土壤資料查詢系統（2000），國立中興大學水土保持學系、國立嘉義大學土木與水資源工程學系。
3.國內地圖及遙測影像資源
（http://www.ascc.sinica.edu.tw/gis/index1/cat.htm）
4.Australian Soil Resource Information System（http://www.asris.csiro.au/index_ie.html）
5.Agricultural Soil Information System, Korea （http://asis.rda.go.kr/）
6.Food and Agriculture Organization, FAO （http://www.fao.org/）
7.Hydraulic Properties of European Soils
（http://www.macaulay.ac.uk/hypres/index.html）
8.National Soil Information System, USA（http://nasis.nrcs.usda.gov/index.html）
9.The National Soil Database, Canada（http://sis.agr.gc.ca/cansis/nsdb/intro.html）
10.Unsaturated Soil hydraulic Database, UNSODA
（http://www.ars.usda.gov/services/software/download.htm?softwareid=106）
（二）工具軟體
1.CurveExpert 1.3
（http://curveexpert.webhop.biz/）
2.GOSA Scientific Software（http://www.bio-log.biz/index.php）
3.Curve Fitting Toolbox 1.1.5
（http://www.mathworks.com/products/curvefitting/）