Article Details


Oleh   Nguyen Thi Ngoc Anh [35315701]
Kontributor / Dosen Pembimbing : Dr.Eng.Ir. Priana Sudjono; Prof.Dr. Barti Setiani Muntalif; Dr. Agus Yodi Gunawan.
Jenis Koleksi : S3-Disertasi
Penerbit : FTSL - Teknik Lingkungan
Fakultas : Fakultas Teknik Sipil dan Lingkungan (FTSL)
Subjek :
Kata Kunci : steep slope, runoff, overland flow, subsurface flow, nutrient transport, physical model, Cellular Automata.
Sumber :
Staf Input/Edit : Irwan Sofiyan  
File : 1 file
Tanggal Input : 2019-09-02 10:57:44

The quantity and quality of river water are under the influence of surface runoff, pipe flow, return flow, and subsurface flow. The relations between rainfall and runoff and its quality deal with several hydrological processes. However, the limited understanding of the main runoff mechanism in a certain area, lack of the rainfall and runoff data and the concurrent nutrient substance data are some typical reasons that make difficulties to imitate the runoff and nutrient transport in nature. Most physically based models cannot reflect the true complexity and heterogeneity of the processes occurring in the fields. The research comprehensively explores the influence of rainfall on runoff generation and nutrient dispersion on the sloped catchment. The objective of this study is firstly to prove that the subsurface flow plays the dominant roles of runoff formation rather than a surface flow. Secondly, the main runoff quantity, the soil physical characteristics are the important factors that involve in the transport of nutrient under runoff processes. In order to achieve this aim, the study conducts the runoff process by different rainfall intensity, land cover plots in the field study; Obtaining the mineralization and nitrification to study the transport of nutrient in the form of ammonium, and nitrate in several soil layers and the discharge flow in the laboratory study; development of physical based model for specific conditions of steep-sloped of a tropical regions. The runoff generations in the field experiments can be observed in several plots under artificial rainfall. The soil moisture is the indicator to represent the water content in the soil layers. Besides that, some parameters related to the capacity of the soil to transmit water such as hydraulic conductivity, soil porosity, texture, density are measured. The results can be applied in the mathematical model. This stage helps to expand the understanding of soil moisture on the water content in the soil, and runoff generation. Under small rainfall, the surface flow and subsurface flow are not the dominant mechanism in a steep slopes, and clay soil layers. The moisture in land surface decides the main contribution to runoff flow in the downstream area in short period. In the laboratory experiments, a certain amount of fertilizer are applied in several soil columns to study the dispersion of nitrogen is the soil layers and the runoff flow. The soil samples from several layers and the water in the bottom of soil columns are collected to analyze the ammonium and the nitrate. These soil quality results are fitted by the curve of the ammonium and nitrate concentration by the Polynomial and the Fourier series. This stage found that the ammonium is the main form of nitrogen in the soil layers, and it increased quickly in the land surface; otherwise, the nitrate is very small and tends to stable in three layers. To support these empirical models based on the Polynomial and the Fourier function, a new model using Cellular Automata is explored to emulate the overland flow in flooded condition. The Cellular Automata model can successfully imitate the overland flow in a slope area, with acceptable results. Besides that, the dissertation also suggests a mathematical model to simulate the runoff flow and nutrient transport based on the soil moisture dynamic and the water balance equations in the various soil layers. The important keys of the method are using very thin soil layer, and small time steps to increase the accuracy of the simulation results. Both models have been simplified to be applicable for simulating the runoff and solute transport in limited data conditions. In conclusion, the results confirm the knowledge related to runoff generations. It is expected to contribute to a profound understanding of the behavior of river water quality and enhance development of a mathematical model for river water quality predictions. In the future, the further research is needed to overcome these limitations in order to study the runoff and nutrient transport deeper and correctly.