Water Retention Curves
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- ebrew Μαρκόπουλος
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1 Soil Physics October 28, 2008 Homework 5 Due November 9 Water Retention Curves 1. Use the model proposed by Arya and Paris (1981) to predict the soil-water characteristic curves of B22tg (21-31 cm) horizon in soil S57NJ-12-1 (Matapeake taxadjunct, Middlesex County, NJ), and IIB 22t (22-27cm) horizon in soil S58NJ-8-3 (Aura sandy loam, Gloucester County, NJ). These two soil horizons were used by Arya and Paris (1981). Information required by the model can be obtained directly from the attached sheets taken from the Soil Survey Investigation Report Nο 26 (1974). (Soil Survey Laboratory Data and Description for Some Soils of New Jersey. SCS-NJAES.) For the calculations note the following (see example): A. Use 8 mass fractions: 5 sand fractions + 2 silt fractions + 1 clay fraction. B. Particle radii are selected as the mid-point of the particle size intervals. C. In the publication, water content is expressed as gravimetric water content: you need to convert it to volumetric water content. 2. Use the nonlinear optimization technique implemented in Excel to fit the van Genuchten (1980) model to the measured soil-water characteristic curves of the B22tg (21-31 cm) horizon and the IIB 22t (22-27cm) horizon. Optimize parameters α, θr, θs, and n; and define m as m = 1-1/n. Use textural class in Table 3.4 (attached) to find estimates of the parameter values for each horizon. Use those estimates as initial values in the optimization technique. 3. Use the pedotransfer functions (PTF) by Rawls et al. (1982) 1 (attached) to generate volumetric water content (m 3 m -3 ) at matric potentials of -4, -7, -10, -33, -100, -200, -700, and kpa. 4. For each soil create a graph containing the following four plots: A) the measured soilwater retention characteristic curve (express matric potential in kpa and soil-water as volumetric water content); B) soil-water retention predicted with the model of Arya and Paris (1981); C) soil-water retention fitting with the van Genuchten (1980) model with optimized parameters, and D) soil-water retention predicted with the Rawls et al. (1982) PTFs. Compare and discuss the results together with the advantages and disadvantages of the three method used. 1 Rawls, WJ, DL Brakensiek, and KE Saxton Estimation of soil water properties. Trans. ASAE 25: &1328.
2 pedqn CLASSIFICATION: Typic Hapludult; coarse-loamy, mixed, mesic SOIL Ma-tapeake taxad,junct SOIL Nos. S57NJ-12-1 LOCATION Middlesex County, New Jersey U. s. DEPARTMENT O AGRICULTURE SOIL CONSERVATION SERVICE SOIL SURVEY LABORATORY Beltsville, Maryland LAB. N b TGtal Sile cla Sand and particle diameler (mml 3At Sill Oepth jln.) HGr;ron Sand ) Silt Clay 1 V'Y,I CGI1H 10.0S- (e 0.002) I 0-5 All..,Al A P: 21 B21t t!f ' 0'< B22tg lic laa, I Md;um:5)1 Fin. V'Y fin,o Int. m 1 Inl. n ) ( (0.I-O.05f ( ( Pct. 01 -< Z mil , ' '4.61' J , (2..{).ll G Anll.lyses by Nev Jersey Aer. Eltp. Stn. Rutr:ers University a... 6B2a 6C1a liaur reaied llt suctions of Ayll1l- Depth a'ianic Nitr<l1ltn Gf' Ext. iron Field BClc BCIa Bul. able Cll.p&_ (In.) CllOOn 1$ Fe enslty ,[ 0. I I vater city bar bar bar bru- 1 (l:ll (1:1) bu bar 2.1 bar 6 I bar PCI. Pct. Pet. a/cc in/in Pct. ', I ,:; ;: :; I.;; 1 ;.. 1. ' >., , 1<.4 I Edrlclabl8 bau, 58\a 5HZI CEe 5Gld RatiGs tg cliv Blsi salur.tion Depth 6N2d 6Q1b 6P2a 602. Ed. '03 SC, (In.) J. ut. CEG Ell. 15 blr Ca/MI G,,.. acidity,..,.. iron.181,.. NH caligns caligns meq/loo I Pcl. Pcl tr. tr :' 21 tr. tr. tr. 0.2 n.? 11.:' tr. tr. tr tr. 0.8 tr Ac Depth M. ChI. (In.1 Clay Fraclion Analysis 7Alb d - ]A2 X ray 'm.j Mi. Inl. 'U. K> JG,b XXX XX = X XX XX XX xx XX Anal ses bv Ne Jers<.y II r. Ex. Stll.. Rut cr f)} :; o. ' <,,., Mt.;Oo MGnlmlllilklnite. ChI... cbl6rile. Vm... Vermkulit8. mi _ mica. Inl. _ Inl8ls1r.lifl8d liver, QU... quirt!:. KI... KaGIinit8 h'lhve Imounts: bllnk;oo nol d8t8rmined. dish _ licit detectld. It :8, l small. XI.. mgdellle. lu _ i1bund8nt. Ull _ dgminanl.
3 PEDON CSIFICATION: Typic Hapludult; fine-loamy, mixed, mesic SOIL Aura aandt loea SOIL Nos. 858&1-8-3 LOCATION O1oucu-ter County ev Jer., U. S. OEPARTMENT OF AGRICULTURE SOIL CONSERVATION SERViCE SOil SURVEY LABORATORY -,80,1,vII,,lo-,M,a,,,la,,,n,,d LAB. Nos. ---5,,9=16J.=-_-5,,9:::1=65< 181b Size class and putiele dilmeler (mm) 31 Tolll Sand Silt >, coarse (2-o.1J Cm Oeplh Horilon Sind Silt CII, (In ) (O.OS- (e 0.002) (2-1) 0-0,5) (0.$-0.25) ( (0,I-o.05) ( ) 0.002) Pel.of<2mm ).0 Coarse Irillmenh 391 C'., 1..mJ: V, J..J,. m 10' n 2.19_ < 14.0 o A'2 I: I t :g : B'l ;: 1' Q ')-= I i;2t 15JJ 33.' ll o '0,. -:;-,AI. 6_ 6Cla Water retained...t uetions of' Avnil_ Field M.' cap.a- Deplh Or.anie Nilrollen Ci' Ext. i,on.,. BCle 9Ch fin.) ea,bon b:r I ene1t,. 1..ter city 0'''1 0,[ 0>0 I (I:l) F bar hi' bar bar (1:1; 'or bar 6 I bill' KCI Pel. Pet. Pd. sloe pt in/in Pet. Mnlyee5 by II JCUL'Y,1er. Up. Stn. RutllO.,., Uniyer1ty 0-1.<0 0.08< , : in no,,, 1.'0 22.' 1,<.< 3.9. ;., I? it,, 0,, U ',0 bll.elable basn 58\1 6H2a efc 6Gld Ratios to dl' 8D all Ulration 0.,. 6N2d 60 6P2a 6Q2a 'd C1 lin.) J.,. CEC Ell. IS b., Ca/M8 C'., K S.m acidity Som.. S.m iron wale, S.m NH 4.-.e e.tiol\s cations meq/loo Pel. Pel. 0-. tr. tr. tr tr. tr < 0.1 tr. tr. 0.1 '. ' tr. tr tr Porosi t!j Iij ClllY Frldion Analys;s llb o M.. lyl1 by Ne J,rs, Arz:r. El St... Rut er3 I}} Methods refer- Oeplh MI. ChI. Mi. lnt. Q. KI. Gibbsite Hydrll.u llon_ Aggre- enced on (In.l 11, capll ClI.pll- Total Plut1e 'm.j &...t methods code eonduc '7 lory index utnbll_ sheet. la2 tiyity U, X Y 7AJ In/hr ',. ',. ',. ',. ', tl ?r 7'O 25 0.?
4 EXAMPLE3.4 Textural averages of hydraulic parameters based on UNSODA unsaturilted soil hydraulic properties database and NRCS soil survey database (Leij et al., 1998). Saturated Hydraulic Soil Water Retention Conductivity Textural (1Iem) (em/d) Class N 8, 8, et n N' K, UNSODA Sand Loamy sand Q Sandy loam Loam Silt ' Silt loam Sandy clay loam Clay loam Silty clay loam Silty clay Clay Saturated Hydraulic Soil Water Retention Conductivity Textural (1Iem) (em/d) Class N' 8, 8, et n N' K, Soil Survey Sand Loamy sand Sandy loam Loam Silt Silt loam Sandy clay loam Clay loam Silty clay loam Sandy clay Silty clay Clay Approximate sample size for Soil Survey database.
5 TABLE 3. COEFFICIENT FOR LINEAR REGRESSION EQUATIONS FOR PREDUCTION OF SOIL WATER CONTENT AS SPEClFIC METRIC POTENT(ALS. r.letric Organic Bulk 0.33 bar 15 bax Couelation potential Sand. Silt, Clar. matter. density. water retention, water retention, coefficient. b. Intercept gje.m ' cm 1 fern' em.) fem) R % _ Re&ression coetiiden1.$ b < d d f h L DAUB B O.OOU O.OOOB Sand (%) + silt ('0)... clay (%) = 100 Sand = mm Sill mm Cia}' < Ox = a + b x: sand (%) + e x silt ('io) d d x cla}' (%) + c x organic matter (%) + f x bulk density (g/cm) ) + g x: 0.33 bar moistu.re (cm] fcm J )... h x 15 bar moisture (cm ' lem 3 ) Ox = predicted water reli!ntion (em] Icm 3 ) for a given metric (x) potential a-n = reji:ression coefficients
Table 2 Suggested prediction methods to use for a given set of available input parameters per each examined soil hydraulic property) a.
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