Applied Hydrology Infiltration

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Presentation transcript:

Applied Hydrology Infiltration Prof. Ke-Sheng Cheng Department of Bioenvironmental Systems Engineering National Taiwan University

Water Distribution in the Soil (Unsaturated zone) 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

The capillary zone lies above the lower saturated layers. The soil water zone begins at the ground surface and extends downward, encompassing the root layers. During periods of rainfall (or other water application such as irrigation), this area may become saturated. It is otherwise in an unsaturated state, part of the soil pores are filled with air. The intermediate zone extends down to the capillary fringe. It is unsaturated except during periods of extreme precipitation. The capillary zone lies above the lower saturated layers. The saturated zone has all pores filled with water (surficial aquifer). 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Subsurface water appears as hydroscopic, capillary, or gravitational water. Hydroscopic and capillary water are held by molecular forces in thin films around soil particles. Hydroscopic water is essentially unavailable. Capillary water results when more water is available filling gaps between soil particles but in a discontinuous fashion. Capillary water can be in direct connection with groundwater or in isolated pockets. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Soil moisture at some depth in the intermediate layer may not change with time. In humid or well-irrigated areas, field capacity (FC), the maximum amount of water the soil can hold against gravity, is a good moisture assumption for this layer. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Definition of soil moisture content max =s (Saturated soil moisture content) 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Soil Moisture Profile 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Infiltration rate and infiltration capacity Infiltration rate: the actual rate of movement of water through soil surface (e.g. cm/hr, inch/hr) Infiltration capacity: the maximum rate of infiltration when there is an excess supply of water at the surface. Infiltration capacity is influenced by soil type and initial soil moisture content primarily. Factors affecting infiltration rate: SMC landcover soil type (hydraulic connectivity) 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Typical soil moisture distribution profile during the downward movement of water. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Relation of soil suction and soil moisture content T: surface tension of water w: density of water P: Pressure of water at the top of capillary water column. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

(Hysteresis effect) Suction (negative pressure) means that the pressure at the point of consideration is less than the atmospheric pressure. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

The hysteresis effect 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Modeling the Infiltration Process Horton's model for infiltration capacity The Horton's equation assumes the soil surface is saturated at all time, i.e. excess water at surface. The value of fc is equivalent to the saturated hydraulic conductivity. The Horton’s infiltration model is used for modeling point-scale infiltration capacity. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Horton’s infiltration model Actual infiltration rate vs infiltration capacity What is the real infiltration rate at time t1? 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Ponding time Case A. Excess water at surface (ponded infiltration) (fi*=infiltration capacity, fi=actual infiltration rate) Case B. Non-ponding infiltration until ponding at surface occurs. 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Assume a constant rainfall intensity i (fc < i < fo) 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

SCS Curve Number (CN) method The SCS CN method is proposed for infiltration rate estimation in watershed-scale. P=Pe+Ia+Fa 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

P: total rainfall depth of a storm Pe: total depth of direct runoff, or excess rainfall (inch) Fa: depth of water retained in the watershed after runoff begins (i.e. the amount of infiltration after runoff begins) (inch) Ia: initial abstraction before ponding (no runoff occurs) S: potential maximum retention after runoff begins (inch) 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

Initial abstraction (Ia) is all losses before runoff begins Initial abstraction (Ia) is all losses before runoff begins. It includes water retained in surface depressions, water intercepted by vegetation, evaporation, and infiltration. Ia is highly variable but generally is correlated with soil and cover parameters. Through studies of many small agricultural watersheds, Ia was found to be approximated by the following empirical equation: Ia =0.2S 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

CN=100  S=0, Ia=0 CN<100  S>0, Ia>0 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

SCS CN method Initial abstraction 11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU

11/20/2018 Lab for Remote Sensing Hydrology and Spatial Modeling, Dept. of Bioenvironmental Systems Eng., NTU