No abstract available.DOI: http://dx.doi.org/10.3329/jbayr.v2i1.20539 Journal of the Bangladesh Association of Young Researchers (JBAYR): Vol.2(1), 2012 & 2013: 33-37

Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model's performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model's initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.

Soil profiles are generally heterogeneous and consist of various horizontal layers due to geological processes, the formation of crusts, or other artificial or man-made activities. To quantify infiltration into these heterogeneous soil profiles, the Modified Green-Ampt Model (MGAM) is a physically-based hydrologic model that can efficiently perform under both steady and unsteady rainfall events. Based on the secondary data, this study sought to determine the effect of changing soil layers (soil textures) on infiltration rates and cumulative infiltrations in in both laboratory and field settings. Different scenarios were analyzed by rearranging soil layers and evaluating their impacts on corresponding infiltration rates and cumulative infiltrations. Simulations were run with HYDROL-INF software environment using MGAM. Three scenarios were considered for a laboratory experiment with two different types of soil texture coupled with five different soil profiles. Similarly, four scenarios were considered for the field experiments with five different types of soil texture couple with eight different soil profiles. The simulated infiltration rates and cumulative infiltrations were found to vary with soil layer change scenarios. The simulated cumulative infiltrations, ponding times, infiltrating rates at ponding, and total depth of wetting front at ponding of a five-layered laboratory soil column were identical for the three scenarios. Simulated cumulative infiltrations were 33.16, 23.65, 21.29, and 42.77 cm, respectively, for scenarios (combinations) 1, 2, 3, and 4 in the eight-layered soil profile in the field scenarios. Infiltration rates among scenarios at ponding were identical (0.46 to 0.53 cm/h) with field scenario data.

Hydrologic modeling is a popular tool for estimating the hydrological response of a watershed. However, modeling processes are becoming more complex due to land-use changes such as urbanization, industrialization, and the expansion of agricultural activities. The primary goal of the research was to use the HEC-HMS model to evaluate the impact of impervious soil layers and the increase in rainfall-runoff processes on hydrologic processes. For these purposes, the Watershed Modelling System (WMS) and Hydrologic Engineering Center's-Hydrologic Modeling System (HEC-HMS) models were used in this study to simulate the rainfall-runoff process. To compute runoff rate, runoff volume, base flow, and flow routing methods SCS curve number, SCS unit hydrograph, recession, and loss routing methods were selected for the research, respectively. To reduce the processing time and computational complexity, a small section of the Pipestem Creek Watershed was selected to understand the methods and concepts associated with the hydrologic simulation model building. A DEM along with other required data such as land use land cover data, soil type data, and meteorological data was utilized to delineate the watershed in WMS. The output of WMS was utilized to run the HEC-HMS model for five different scenario analyses. All the relevant data were plugged in to the model to get the desired map. Subsequently, outlets at appropriate locations were selected for the sub-basin delineation for further analysis. Finally, the model was parametrized to get successful simulation results. Overall, peak discharges and runoff volumes were increased with increasing storm depths and impervious areas. Peak discharges were increased to 36% and 51% when rainfall depths were increased by 10% and 20% from the initial rainfall depth, respectively. Runoff volumes were also increased to 35% and 49% for the same scenarios, respectively.