Citation
Al-shaheen, Husam Hasan Abdulaali
(2018)
Modelling the optimal size of silt pits for soil water conservation.
Doctoral thesis, Universiti Putra Malaysia.
Abstract
Malaysia experiences high total rainfall intensity, which increases soil erosion on steep
slopes and causes a reduction in soil fertility, pollution of fresh and groundwater, and
the degradation of adjacent lands. Although Malaysia has high rainfall, oil palm may
still experience water stress due to high rainfall intensity which results in fast
downslope water movement and little time for water to infiltrate into the soil. One of
the most effective measures of soil and water conservation in Malaysia is the use of
silt pits. The function of a silt pit is to control the runoff, trap and settle down the
sediments, increase soil moisture or recharge the groundwater, reduce the effect of
slope length and further reduce soil erosion and fertiliser losses. However, what is the
optimal size and dimensions of a silt pit to enable the water to reach the farthest roots
and empty slowly to release the water over the most extended period? What is the
effect of the slope, runoff (volume of water), the volume of the pit, and type of soil of
the spatial silt pit size? The study aimed to use the HYDRUS 2D/3D models and to
formulate the simulation results as equations to select the optimal size and dimensions
of a silt pit depending on the rainfall and soil properties. The treatments used in this
study included the following four factors: seven type of soils (sand, sandy loam, loam,
silt, sandy clay, silty clay, clay), six surface slopes (0˚, 5˚, 10˚, 15˚, 20˚, and 25˚), three
silt pits sizes (3, 4, and 5 m3), each size having three depth levels (50, 75, and 100 cm),
and several levels to cater for the volume of water available in the silt pit. Three stages
were adopted in this study. The first stage utilised the software HYDRUS 2D/3D
models to simulate the soil water content, wetting front, and time-to-empty from a silt
pit of various sizes on different soils and slopes. The second stage distinguished the
trend and determined the best fit by using statistical methods (Multiple linear
regression (MLR) and Artificial neural network (ANN)) to estimate the optimal silt
pit size. The last stage applied the fitted model to find the optimum silt pits in some
areas of Peninsula Malaysia. From the simulation results, all parameters (distance of
wetting front, water content, and time-to-empty) were affected by nearly all the factors (water head in the pits (H), pit width (W), amount of water applied (Vw), pit volume
(Vp), and surface slope (Slope)). For instance, increasing the slope will slightly
increase the wetting front distance (from 130.54 to 136.45 cm) and soil water content
(from 0.374 to 0.375 m3/ m3) with downslope, but decrease significantly the upslope
wetting front and soil water content (130.53 to 101.26 cm and 0.373 to 0.333 m3/m3,
respectively). However, there was no effect on the time-to-empty. The reduction of
unfavourable results of the increasing slope was compensated by manipulating the
values of H and Vp. The MLR models did not perform adequately especially for timeto-
empty (Mean Squared Error (MSE) = 85.83; R2 = 0.632) compared with the ANN
models (MSE = 10.33; R2 = 0.977), mostly due to the non-linear relations between the
factors. The results demonstrated that despite requiring the same input data, the ANN
models could favourably be used for all parameter predictions. However, processbased
numerical models are undoubtedly a better choice for predicting the results with
lower uncertainties when the required data are available. The fitted problem was then
used to select the optimum sizes of the silt pit in Peninsula Malaysia, based on the soil
texture and rainfall intensity. The results show that some types of the soils (sand, loam
sand, and sandy loam) which have high values of hydraulic conductivity make the
rainwater infiltrate into the soil. So, for these land, there is no need to construct the silt
pits. While in the case of soils (sandy clay loam, clay loam, silt clay loam, sandy clay,
silty clay, and clay) which have low values of hydraulic conductivity, a large volume
of runoff water will be caught in those land compared to the sizes of silt pit used in
the experiment. Therefore, length of the pit during construction must be extended to
avoid flooding of water.
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