Abstract
ABSTRACTThe study was conducted on cultivated land at College of Agricultural Engineering and Post Harvest Technology (CAEPHT campus), Ranipool, Gangtok, Sikkim, India. Twenty five points were identified at 10 m grid interval and field measurements were performed using double ring infiltrometer method. Result of soil analysis suggests sandy loam and loamy sand texture and the bulk density and particle density have varied from 1.412–1.716 g/cm3 and 2–3.03 g/cm3, respectively. The basic infiltration rate has varied from 0.3 cm/h to 6.8 cm/h. Result show that sand, particle density and organic carbon content have a positive correlation with infiltration rate by 0.75, 0.18 and 0.22, respectively, whereas silt, clay, bulk density and moisture content, have a negative correlation with infiltration rate by −0.41, −0.73, −0.33 and −0.22, respectively. The analysis performed for five classes considering the combination of soil properties and subjected to regression analysis. Result shows that in order to predict soil infiltration rate based on few properties of soil with seven independent variables, multi-linear regression model EIR = -30,578.81–305.56(sand%)-306.16(silt%)-0.306.33(clay%)-5.18(BD%)+.34(MC%)+4.18(PD)+16.85(OC%) with R2(0.80), mean RMSE (1.52) and standard error (2.39) is the best model for the estimation of infiltration rate and recommended for the study area.
Highlights
Soil and water are the vital natural resources used in the crop production system
These were considered as the independent variables which were used in the multiple linear regression (MLR) for the prediction of infiltration rate and considered as the main key for analysis and development of the prediction model
Infiltration models can be developed through pedo-transfer functions (PTFs) using different soil properties and will be useful for the prediction of infiltration rate in the hilly region of Sikkim where the direct/field measurement of soil infiltration rate is very difficult due to one or more reasons
Summary
Efficient management of water will be required a greater control of infiltration in the soil. Soil infiltration rate is the most essential process that affects the surface irrigation uniformity and efficiency because of its mechanism of transfer and distributes water from surface to soil profile (Rashidi et al, 2014). The measurement of infiltration of water into the soil is an important indication concerning the efficiency of irrigation and drainage, optimizing the availability of water for plants growth and metabolism, improving the yield of crops and minimizing erosion (Adeniji, Umara, Dibal, & Amali, 2013). Adequate knowledge of infiltration rate of a soil data is essential for reliable prediction and control of soil and water related environmental hazards. Soils have been amended using three loadings such as poultry manure, sewage sludge, barley straw (Hordeum vulgare L.), and alfalfa (Medicago sativa L.) to an Arlington soil (coarse loamy, mixed, thermic Haplic Durixeralf) for 2 years and found that water infiltration rates in the organicamended soils have initially increased by stimulation of microbial activity, which has increased the stability of soil aggregates. Cerda (1996) studied the infiltration rates for contrasting slope in south Spain using simulated rainfall and ponding method and suggested that the aspect, slope and vegetation cover governs the steady state infiltration rates, whereas, seasonal change plays an important role in varying infiltration rates. Fox, Bryan, and Price (1997) studied influence of slope
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