Research Article

Performance Evaluation of Four-Parameter Models of the Soil-Water Characteristic Curve

Table 4

Statistical measures of the models for various soil textural classes.

Soil typeModelSoil sample 1ā€‰Soil sample 2ā€‰
RMSEWt.* RMSEWt.*

SandBC0.98780.0147(4)0.97650.0216(4)
VG0.99580.0086(3)0.98900.0147(3)
LN0.99640.0080(2)0.99090.0134(2)
MG0.99720.0071(1)0.99230.0124(1)

Loamy sandBC0.99610.0074(4)0.97840.0125(4)
VG0.99730.0061(1)0.98980.0092(3)
LN0.99620.0073(3)0.99110.0086(2)
MG0.99710.0064(2)0.99230.0080(1)

Sandy loamBC0.97640.0113(4)0.98380.0192(4)
VG0.99310.0066(3)0.99350.0122(3)
LN0.99800.0035(2)0.99660.0088(2)
MG0.99820.0034(1)0.99740.0078(1)

Silty loamBC0.97790.0120(4)0.98130.0220(4)
VG0.99010.0080(3)0.99390.0126(3)
LN0.99380.0064(2)0.99650.0096(2)
MG0.99400.0062(1)0.99730.0083(1)

SiltBC0.95910.0294(4)0.95290.0288(4)
VG0.97970.0207(3)0.96240.0257(1)
LN0.98400.0188(2)0.95750.0273(3)
MG0.98570.0178(1)0.96080.0263(2)

LoamBC0.99090.0063(4)0.92870.0191(4)
VG0.99900.0021(3)0.97050.0131(3)
LN0.99930.0018(2)0.98260.0094(2)
MG0.99950.0015(1)0.98640.0083(1)

Sandy clay loamBC0.97930.0120(4)0.99060.0049(4)
VG0.98100.0109(3)0.99910.0015(3)
LN0.99540.0057(2)0.99960.0010(2)
MG0.99560.0053(1)0.99990.0005(1)

Silty clay loamBC0.96130.0105(4)0.99590.0104(4)
VG0.97950.0077(3)0.99940.0038(3)
LN0.99800.0027(2)0.99970.0028(2)
MG0.99860.0022(1)0.99980.0024(1)

Clay loamBC0.96310.0064(4)0.98370.0039(4)
VG0.98690.0038(3)0.99320.0025(3)
LN0.99420.0025(2)0.99340.0025(2)
MG0.99530.0023(1)0.99420.0024(1)

Sandy clayBC0.97120.0096(4)0.97940.0049(4)
VG0.99280.0048(3)0.99390.0027(3)
LN0.99310.0047(2)0.99530.0023(2)
MG0.99420.0043(1)0.99650.0020(1)

Silty clayBC0.89200.0129(4)0.98500.0094(4)
VG0.93820.0105(3)0.99240.0067(3)
LN0.95640.0088(2)0.99320.0063(2)
MG0.95850.0086(1)0.99360.0061(1)

ClayBC0.98060.0077(4)0.98590.0096(4)
VG0.99680.0031(2)0.99820.0035 (3)
LN0.99660.0032(3)0.99890.0028(2)
MG0.99710.0030 (1)0.99890.0027(1)

Values in parentheses are the weightage (Wt.) where a value of one indicates least RMSE value and a value of four indicates largest RMSE value for the data set.