WU Peiyao, QIN Fucang, DONG Xiaoyu, et al. Water Infiltration Characteristics and Simulation on Exposed Slope in Pisha Rock Area Under the Influence of Slope[J]. 2022, 36(2): 64-69.
DOI:
WU Peiyao, QIN Fucang, DONG Xiaoyu, et al. Water Infiltration Characteristics and Simulation on Exposed Slope in Pisha Rock Area Under the Influence of Slope[J]. 2022, 36(2): 64-69. DOI: 10.13870/j.cnki.stbcxb.2022.02.008.
Water Infiltration Characteristics and Simulation on Exposed Slope in Pisha Rock Area Under the Influence of Slope
In order to explore the water infiltration characteristics and optimal infiltration model of arsenic sandstone soil (gray white
mixed color
purplish red) with different textures under different slopes (5°
10°
20°
30°)
the characteristics of soil water infiltration and fitting results were compared and analyzed by indoor simulated soil column method. The results showed that:(1) The soil bulk density of different slopes in the study area is 1.513~1.737 g/cm3. The soil infiltration capacity of gray white arsenic sandstone under 30° slope was strong
and the soil infiltration capacity of purple red arsenic sandstone under 5° slope was weak. (2) In the process of one-dimensional vertical infiltration of arsenic sandstone soil
the initial infiltration rate was 2.000~8.600 cm/min
and the stable infiltration rate (0.160~1.800 cm/min) was reached after the infiltration time was 3.500~5.000 min. The infiltration rate and wetting front migration rate decreased with time in a power function. The smaller the slope and the darker the color was
the lower the infiltration rate and cumulative infiltration rate was
and the slower the migration of wetting front was. The values of initial infiltration rate
stable infiltration rate
initial wetting front migration rate
and stable wetting front rate all decreased with the decrease of slope gradient and the deepening of arsenic sandstone soil color. (3) Kostiakov model and Philip model fit well the results of soil water infiltration in arsenic sandstone area
and the determination coefficients were more than 0.900. The average value of the decision coefficient of Kostiakov model was 0.948
and the fitting effect was the best. The average value of Philip model determination coefficient was 0.937
and the fitting effect was the second. The average value of the determination coefficient of Horton model was 0.688
and the fitting effect was poor. Through the mean absolute error (MAE)
root mean square error (RMSE)
percentage of deviation (PBIAS)
and Nash efficiency coefficient (NSE)
it was verified that the simulated values of Kostiakov model and Philip model have little difference and high degree of coincidence with the measured values.