**3. Infiltration capacity in Japanese cedar and Hiba arborvitae plantation forests**

#### **3.1. Site description and test plot design**

All sites were located in the environmental community forests developed through a conservation project in Ishikawa Prefecture, Japan. Plantations cover about 40% of the total forests in this Prefecture. In terms of species composition of the plantations, cedar forests tops with 71% followed by Hiba arborvitae with 12% and pine trees with 9%. Cedar forests are distributed equally throughout the entire areas in Ishikawa Prefecture, while Hiba arborvitae forests show unequal distribution with a large part of the forests located in the Noto Peninsula [31]. We selected 22 Japanese cedar and 16 Hiba arborvitae sites in all available forests before thinning or the forests with different years elapsed after thinning (**Figure 1**). The study sites are dominated by brown forest soils, and have a slope of 40°. Forest leaf litter accumulates at all the sites with dense and sparse understories. According to AMeDAS data [32], annual rainfall averages nearly 2302 mm (1976–2012) with an average temperature of 13°C (55°F) in Ishikawa Prefecture.

#### **3.2. Definition of infiltration rate**

Horton equation is based on the observation that infiltration capacity is gradually exponentially reduced with time when, although ground surface is always thin, fresh state is sufficiently supplied. Horton [33] proposed excess rainfall/infiltration processes and introduced that while the equation may not actually represent the law governing the physical processes

**Figure 1.** Location of the study site in Ishikawa Prefecture, Japan.

Relation between Infiltration Rate, Cover Materials and Hydraulic Conductivity of Forest Soils...

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169

**Figure 1.** Location of the study site in Ishikawa Prefecture, Japan.

In Ishikawa Prefecture, Japan, there are forests accounting for about 70% of the prefecture land, due to the restoration of the devastated forest land after the World War II, afforestation

of the forest degradation without thinning was concerned an urgent task in 2005. Ishikawa prefectural government stressed that it is necessary to focus on maintenance of degraded forests. The maintenance cannot be performed only by the people involved in forestry or forestry-related works as a living but have to involve professionals. The functions of forests have been maintained through forest management. However, forestry business has been concerned with declining public benefit with degradation, water recharge and conservation of mountain area has grown unprofitable due to the soaring prices of timber and depopulation of mountain area. As a result of this, Ishikawa Prefecture introduced 'Ishikawa Forest Environmental Tax' in fiscal 2007, intensive thinning of degraded plantations mainly in the water source area, and an attempt to save public function of forests. Therefore, since it is necessary to verify the effect of introducing the Ishikawa Forest Environmental Tax, we attended/ conducted a water soil conservation function survey in the same way as the verification of Yamaguchi Forest Management Prefectural Residence Tax [28]. The verification method is *in situ* permeability test using an artificial rainfall apparatus. As for the effect of introducing the Ishikawa Forest Environmental Tax was conducted along with the soil conservation function

**3. Infiltration capacity in Japanese cedar and Hiba arborvitae plantation** 

All sites were located in the environmental community forests developed through a conservation project in Ishikawa Prefecture, Japan. Plantations cover about 40% of the total forests in this Prefecture. In terms of species composition of the plantations, cedar forests tops with 71% followed by Hiba arborvitae with 12% and pine trees with 9%. Cedar forests are distributed equally throughout the entire areas in Ishikawa Prefecture, while Hiba arborvitae forests show unequal distribution with a large part of the forests located in the Noto Peninsula [31]. We selected 22 Japanese cedar and 16 Hiba arborvitae sites in all available forests before thinning or the forests with different years elapsed after thinning (**Figure 1**). The study sites are dominated by brown forest soils, and have a slope of 40°. Forest leaf litter accumulates at all the sites with dense and sparse understories. According to AMeDAS data [32], annual rainfall averages nearly 2302 mm (1976–2012) with an average temperature of 13°C (55°F) in Ishikawa

Horton equation is based on the observation that infiltration capacity is gradually exponentially reduced with time when, although ground surface is always thin, fresh state is sufficiently supplied. Horton [33] proposed excess rainfall/infiltration processes and introduced that while the equation may not actually represent the law governing the physical processes

of plantation. The maintenance area of 290 km<sup>2</sup>

has been rapidly carried out on about 990 km<sup>2</sup>

168 Hydrology of Artificial and Controlled Experiments

survey and function of biodiversity conservation.

**3.1. Site description and test plot design**

**forests**

Prefecture.

**3.2. Definition of infiltration rate**

involved, his equation is rationally formed, since it not only represents the observed data within the range of observation but also gives results in agreement with known facts for the limiting or boundary conditions.

Recent studies, however, have shown that infiltration rates can increase with increasing rainfall intensity until it reaches a constant value [5, 34]. Their 'apparent' infiltration rate at steady state (*f* s ) is defined as area-averaged infiltration rate of which a certain fraction contributes to rainfall excess production. Infiltration capacities can be assumed to have an exponential distribution [34], so *f* s can be given by:

$$f\_s = f\_{\max} \left( 1 - \exp\left(-i \left| f\_{\max} \right) \right) \right. \tag{1}$$

where *i* is rainfall intensity (mm/h), *f* max is average infiltration rate (mm/h), when the whole plot is contributing to rainfall excess production. With given *f* and *i*, the model has only one empirical parameter, *f* max, which makes it attractive for practical use. Yu et al. [35] and Stone et al. [36] applied the exponential model to their rainfall-runoff data, which yielded much better results than the application of a model with a constant *K*<sup>e</sup> . Langhans et al. [37] adapted his results, so fitting Eq. (1) to the logarithmic data gives a suitable description of the data in terms of fit, without allowing for any physical interpretation. Also, based on experiments in plots with different land-use patterns such as parks and pastures under artificial precipitation system, Tanaka and Tokioka [38] suggested the following hyperbolic function, which gives the relation between rainfall intensity and final infiltration rate:

$$f(i) = FIR\_{max} \cdot tanh(i)FIR\_{max} \tag{2}$$

rainfall intensity, we collected total sprinkled water using plastic sheet. Impact energy of rain-

**Figure 2.** Rainfall simulator and experimental guideline. (A) is machine body (B) is nozzle by under view, (C) is

Relation between Infiltration Rate, Cover Materials and Hydraulic Conductivity of Forest Soils...

energy obtained in the experiment in the *C. obtusa* forests [39]. Please also see the work by Kato et al. [8, 12]. The influence of moisture content cannot be ignored, but we sprinkled water with an intensity of 180 mm/h for 2 h to obtain an accurate final infiltration rate. The rainfall intensity of 180 mm/h is approximately equal to the maximum rainfall intensity that has ever been observed in Japan (187 mm/h: observed at Nagayo-cho municipal office during the 1982 flood disaster in Nagasaki Prefecture). The amount of water stored in a tray at the lower end of the plot was measured every hour to determine the discharge of overland flow. Rainfall was artificially produced until the discharge returned to original steady-state. The experiment could be usually completed within approximately 20–30 min, and the final infiltration rate was defined as the average value of the results taken over the last 5 min. Infiltration intensity may, in some cases, begin to slightly increase after the initial decreasing trend, followed by leveling off to the decreased values. If this is the case, the final infiltration rate was defined as the average value obtained from the values over 3 min before and after the infiltration inten-

Surface cover materials are composed of understories and leaf litter. In response to the research by Miura [15], small fractions (<2 mm) were excluded from the litter category because protection of the soil surface cannot be achieved. We collected understories (ground layer) and leaf litter after the experiment. These surface cover materials were air-dried for a week, then

/mm, which was similar to the average

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171

drop produced in this experiment was about 16.8 J/m<sup>2</sup>

sprinkling condition and (D) is experiment condition.

sity reaches minimum values.

**3.4. Measurement of surface cover materials**

where *i* is rainfall intensity (mm/h), *f* is final infiltration rate and *FIRmax* is the maximum infiltration rate.

#### **3.3. On-site infiltration test using rainfall simulator**

Sprinkling experiments corresponding to a certain degree of rainfall intensity were conducted in small size of plots established in each experimental site. We measured the amount of water applied to sprinkling and overland runoff from each plot on a regular basis. The difference between these two amounts means infiltration volume, and the final infiltration rate can be estimated using this infiltration volume. We established a plot in each study site with horizontal projected area of 1 m<sup>2</sup> (1 m × 1 m). Wave-board panels (about 25 cm height) were placed at the upper end and both sides of the plots. The panels were inserted vertically at a depth of 5 cm under soil surface to prevent the inflow from outside the plot and runoff from the plot. Trays are placed at the cover material-soil interface at the lower end of the plot. This system was adopted to catch and collect overland flow that will contain only the materials above the interface. An oscillating nozzle rainfall simulator was used for sprinkling water. The simulator was set, according to Hiraoka et al. [9] who used this device, with flow rate 12.5 L/min and nozzle height 2 m from the centre of sprinkled plot (**Figure 2**). The angle of nozzle was adjusted to obtain the targeted value for rainfall intensity (180 mm/h). To measure actual Relation between Infiltration Rate, Cover Materials and Hydraulic Conductivity of Forest Soils... http://dx.doi.org/10.5772/intechopen.70575 171

**Figure 2.** Rainfall simulator and experimental guideline. (A) is machine body (B) is nozzle by under view, (C) is sprinkling condition and (D) is experiment condition.

rainfall intensity, we collected total sprinkled water using plastic sheet. Impact energy of raindrop produced in this experiment was about 16.8 J/m<sup>2</sup> /mm, which was similar to the average energy obtained in the experiment in the *C. obtusa* forests [39]. Please also see the work by Kato et al. [8, 12]. The influence of moisture content cannot be ignored, but we sprinkled water with an intensity of 180 mm/h for 2 h to obtain an accurate final infiltration rate. The rainfall intensity of 180 mm/h is approximately equal to the maximum rainfall intensity that has ever been observed in Japan (187 mm/h: observed at Nagayo-cho municipal office during the 1982 flood disaster in Nagasaki Prefecture). The amount of water stored in a tray at the lower end of the plot was measured every hour to determine the discharge of overland flow. Rainfall was artificially produced until the discharge returned to original steady-state. The experiment could be usually completed within approximately 20–30 min, and the final infiltration rate was defined as the average value of the results taken over the last 5 min. Infiltration intensity may, in some cases, begin to slightly increase after the initial decreasing trend, followed by leveling off to the decreased values. If this is the case, the final infiltration rate was defined as the average value obtained from the values over 3 min before and after the infiltration intensity reaches minimum values.

#### **3.4. Measurement of surface cover materials**

involved, his equation is rationally formed, since it not only represents the observed data within the range of observation but also gives results in agreement with known facts for the

Recent studies, however, have shown that infiltration rates can increase with increasing rainfall intensity until it reaches a constant value [5, 34]. Their 'apparent' infiltration rate at steady

to rainfall excess production. Infiltration capacities can be assumed to have an exponential

*max*(1 − *exp*(−*i*

plot is contributing to rainfall excess production. With given *f* and *i*, the model has only one

et al. [36] applied the exponential model to their rainfall-runoff data, which yielded much

his results, so fitting Eq. (1) to the logarithmic data gives a suitable description of the data in terms of fit, without allowing for any physical interpretation. Also, based on experiments in plots with different land-use patterns such as parks and pastures under artificial precipitation system, Tanaka and Tokioka [38] suggested the following hyperbolic function, which gives

where *i* is rainfall intensity (mm/h), *f* is final infiltration rate and *FIRmax* is the maximum infil-

Sprinkling experiments corresponding to a certain degree of rainfall intensity were conducted in small size of plots established in each experimental site. We measured the amount of water applied to sprinkling and overland runoff from each plot on a regular basis. The difference between these two amounts means infiltration volume, and the final infiltration rate can be estimated using this infiltration volume. We established a plot in each study site with horizon-

at the upper end and both sides of the plots. The panels were inserted vertically at a depth of 5 cm under soil surface to prevent the inflow from outside the plot and runoff from the plot. Trays are placed at the cover material-soil interface at the lower end of the plot. This system was adopted to catch and collect overland flow that will contain only the materials above the interface. An oscillating nozzle rainfall simulator was used for sprinkling water. The simulator was set, according to Hiraoka et al. [9] who used this device, with flow rate 12.5 L/min and nozzle height 2 m from the centre of sprinkled plot (**Figure 2**). The angle of nozzle was adjusted to obtain the targeted value for rainfall intensity (180 mm/h). To measure actual

) is defined as area-averaged infiltration rate of which a certain fraction contributes

/ *f*

max, which makes it attractive for practical use. Yu et al. [35] and Stone

(1 m × 1 m). Wave-board panels (about 25 cm height) were placed

*max*)) (1)

/*FIRmax*) (2)

. Langhans et al. [37] adapted

max is average infiltration rate (mm/h), when the whole

limiting or boundary conditions.

170 Hydrology of Artificial and Controlled Experiments

s

*f*

where *i* is rainfall intensity (mm/h), *f*

can be given by:

better results than the application of a model with a constant *K*<sup>e</sup>

the relation between rainfall intensity and final infiltration rate:

*f*(*i*) = *FIRmax* · *tanh*(*i*

**3.3. On-site infiltration test using rainfall simulator**

*<sup>s</sup>* = *f*

state (*f* s

distribution [34], so *f*

empirical parameter, *f*

tration rate.

tal projected area of 1 m<sup>2</sup>

Surface cover materials are composed of understories and leaf litter. In response to the research by Miura [15], small fractions (<2 mm) were excluded from the litter category because protection of the soil surface cannot be achieved. We collected understories (ground layer) and leaf litter after the experiment. These surface cover materials were air-dried for a week, then re-dried in an oven at 70°C for 48 h to determine the dry weight. Photos were taken directly above the plot, and the floor cover percentage was estimated by calculating the percentage of forest floor that is covered with either litter or understories based on image analysis.

#### **3.5. Measurement of soil properties**

Generally, soil properties not only change for each type of soil, vary depending on the location in the same type of soil. It is desirable to make laboratory test (e.g. pF test, permeability test) using a small sample of soil *in situ* to obtain the characteristic value.

We collected soil samples after the experiments to estimate soil properties. To investigate soil properties affecting final infiltration rate, particle size, hydraulic conductivity and bulk density were estimated. Sampling and test were conducted by the following methods. After collecting surface cover materials, collection of undistributed sample soils was made using 400 cc core sampler (cross section area of 100 cm<sup>2</sup> and 4 cm in height) to measure particle size. The reason for examining the physical properties of the surface layer (up to 10 cm from the surface) was because the surface layer was found to be a major influencing factor on infiltration rate. Undistributed soil samples were taken to a depth of 0–5 and 5–10 cm using 100 cc core sampler (cross section area of 19.6 cm<sup>2</sup> and 5.1 cm in height). Three samples were collected at each layer to overcome the difficulties caused by inhomogeneity of soil properties. The average size of these three samples was taken to be the representative value.

Saturated hydraulic conductivity was measured by a permeability test after capillary rise for over 48 h. Determination of permeability was carried out using a constant head permeability test, but a falling head permeability test was used for the lower permeability materials. Then, to find the dry bulk density, the soil was oven dried at 105°C for 24 h and the weight of ovendried soil was measured.

Particle size distribution was determined by means of the sieving method and by using a particle size analyzer (SALD-3100; Shimadzu Corp., Kyoto, Japan) for fine fractions. We observed the content of particles finer than 0.063 mm, especially clay and silt fractions, in this experiment.
