4.7 Article

Spatial analysis of infiltration in agricultural lands in arid areas of Iran

Journal

CATENA
Volume 170, Issue -, Pages 25-35

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.catena.2018.05.039

Keywords

Agricultural lands; Infiltration models; Scaling factors; Scaled infiltration

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Infiltration plays an important role in the hydrologic cycle, runoff generation, soil erosion, as well as irrigation. In the current study, we evaluated a variety of infiltration models, in order to determine the model that is best suited to predict infiltration on agricultural lands in arid areas of the Semnan province in Iran. Additionally, we analyzed spatial variability of the infiltration process using scaling parameters. A number of 60 points were determined for the measurement of water infiltration using the conditioned Latin hypercube sampling (cLHS) method. Each infiltration measurement was carried out with a tension infiltrometer apparatus. Several infiltration models, including Philip, Horton, Kostiakov (KO), Modified Kostiakov (MKO) and Revised Modified Kostiakov (RMKO) models, were fitted to the measured infiltration data. Among the mean coefficient of determination (R-2) values, the highest R-2 values were associated with the RMKO, MKO and Horton models, respectively. While base on the Akaike criterion (ACI), the MKO model was slightly better than the RMKO model for prediction of cumulative infiltration. Cumulative infiltration was scaled using Sorptivity (alpha(S)) and transmissivity (alpha(A)) scaling factors. By minimizing the differences of the sum of squares between the scaled and the average infiltration, the optimum scaling factors (alpha(opt)) were estimated. Arithmetic, geometric and harmonic means (i.e. alpha(m), alpha(G), alpha(H); respectively) of alpha(S )and alpha(A) scaling factors were calculated and the infiltration data were scaled utilizing the mentioned scaling factors. Our findings indicated that the best result was yielded by alpha(H). Strong correlations were found for alpha(G) (r = 0.86) and alpha(H) (r = 0.86) with alpha(opt). For defining the relationship between alpha(opt) and alpha(A), alpha(S), alpha(m), alpha(G) and alpha(H) data, a regression analysis was performed. According to our results, curves reflecting the relationship between alpha(opt) and alpha(A), alpha(S), alpha(m), alpha(G) and alpha(H) were sigmoid. Based on the results of this study, infiltration in agricultural lands in the arid area displays a great spatial variability.

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