東北地域災害科学研究41

第57巻（2021）

Prediction of sediment production in the Abukuma River basin due torainfall sensitivity
Edea Loa Graduate School of Symbiotic Systems Science and Technology, Fukushima University
Seiki Kawagoe Faculty of Symbiotic Systems Science, Fukushima University
1.

Introduction

Japan's economic activities and population growth since the mid 19th century have contributed to significant
developments that have resulted in land cover and land-use changes. The country is also prone to several
natural disasters, which also significantly impact land cover and land-use changes. Two of the recent disasters
are the Great East Japanese Earth Quake on March 11, 2011 (GEJE2011) and the Typhoon-Hagibis on October
2019 (Typhoon 201919). These ongoing land-use changes due to natural disasters and other human-madeactivities have led to land degradation and massive soil erosion, which may have significant environmental
concerns especially in vulnerable areas such as hilly terrain areas and the flood plain areas. Evaluating the soil
erosion within the basin environment is an important task that would assist decision-makers in the land andwater resource management and planning areas for predicting future disasters, proposing countermeasures andmonitoring of basin outlets. The average annual soil loss of the basin, together with a large impact event of theyear 2019, was analysed using the USLE equation. The USLE is an erosion model designed to predict theaverage rate of soil erosion for each feasible alternative combination of crop system and management practicein association with a specified soil type, rainfall pattern, and topography (Wischmeier and Smith 1978) [1].
The main objective of this paper is to analyse the Abukuma Basin average yearly soil loss for the year 2019,
together with a large impact rainfall event and map out an impact map with based on sub-basins and evaluate
the soil production factors and make projections for future soil losses within the impacted sub-basins.
2.

Study area

The study area is approximately 5390 km2 of watershed area and a total river length of 234km whichruns from Fukushima prefecture to Miyagi prefecture (Fig.1). Abukuma River Basin is the second-longest
river in the Tohoku region and sixth in the whole of Japan which consists of a mixture of steep and flat
conditions with irregular changes in surface water runoffs and soil erosion. It collects its water from theaffluent in the high mountains and discharges into the Pacific Ocean. The basin has some small to
medium-sized metropolitan areas which are scattered across the study basin.
JapanAbukuma Basin

Miyagi Pref.

Fukushima Pref.

Fig.1: Study area

Keyword㸸USLE, vegetation, landcover, rainfall sensitivity, soil production.
Kanayagawa1, Fukushima city, Fukushima. Fukushima University
Tel and Fax 024-548-5261

423.

Methodology

The widely used model for estimating soil loss referred to as the Universal Soil Loss Equation (USLE)
was used to analyse the mean annual soil loss in the study area. The equation uses the product of five (5)different factors as follows;‫ ܣ‬ൌ ܴ‫ܲܥܵܮܭ‬(1)

Where, A is the mean annual soil loss per unit area, R is the rainfall erosovity factor, K is the soil
erodibility factor, LS is slope length and steepness factors respectively, C is the land cover management
factor and the support practice factor denoted by P. The rainfall erosivity factor (R)is the rainfall erosiveforce specifically for all the rainfall events in a year. The R-factor derived from 60 minutes rainfall
intensity developed for Japan conditions by Hosoyamada & Fujiwara, (1984 a) [3] was adopted to (Eq.
(2)).
ܴ ൌ ‫଺ܫܧܭ‬଴‫ ܧܭ‬ൌ ሺͻͳ͸ ൅ ͵͵ͳሻ݈‫݃݋‬ଵ଴ ‫ܫ‬ሻͲǤ͹ͷ͵

(2)
(3)

The soil erodibility factor (K) is the measure of the susceptibility of soil particles to detach andtransport due to the impact of the raindrop and surface runoff. The K-factor for this study is the averagevalue from the standard experimental results of sediment model user guide. From Clay to very fine sandy
loam with the average K value of 0.78. The LS-factor (LS) or topographic factor is the combined outcomeof the slope length and slope steepness represented by L and S, respectively. The LS-factor for each land
cell may be evaluated using the equation derived from Moore and Burch (1986) [4] was adopted (Eq.
(4)):‫ ܵܮ‬ൌ  ቀி௟௢௪஺௖௖Ǥା஼௘௟௟௦௜௭௘ ଴Ǥସௌ௜௡ௌ௟௢௣௘ ଵǤଷቁ  ቀͲǤͲͺͻ͸ቁ ͳǤͶ ଶଶǤଵଷ଴Ǥ଴଼ଽ଺(4)The C-factor (C) is the crop or vegetation management factor. It represents the ratio comparing thesoil loss from the land under a specific crop and vegetation to the corresponding loss from the standard
soil plot. The C-factor was determined from remote sensing data. The Normalised Difference Vegetation
Index (NDVI) (Eq.(5)) was used to produce the C -factor map:ܰ‫ ܫܸܦ‬ൌ ሺேூோିோ௘ௗሻ
ሺேூோାோ௘ௗሻ

(5)

The method proposed by Durigon et al. (2014) [5] was used to estimate the C-Factor map (Eq.(6)).
ିே஽௏ூାଵቁଶ‫ܥ‬ൌቀ

(6)

The support factor denoted by P is the effect and impact of support practices that reduce the amount oferosion. In the study basin case with huge natural forest catchments, urban centres where these practices
are not done; hence, P's value is kept as 1.0.
4.

Results and discussions

From the analysis of each of the USLE factors, the average value for the R-factor in the year 2019 was
3,639 ton/ha/hr/yr (Fig. 5). The R-factor value from the impact of typhoon192019 was obtained as 2354
ton/ha/hr/yr. The K-factor value was obtained as the average value from the standard experimental results ofsediment model user guide with the value of 0.78. The LS-factor in the study area ranged from 0 to 115, withthe average values of 0.26. The C-factor values for the study area ranged from 0.16 to 0.62.

43< 20002000 - 3000
3000 - 4000
4000 - 5000
5000 - 6000
6000 - 7000
7000 - 8000
8000 - 9000

9000 - 10000
10 000 >Fig.2: R-factor Map (2019)
From the soil loss analysis, the average soil loss volume for the year 2019 was estimated to be around5.6x107m3. The impact from Typhoon 201919 alone on October 12, 2019 is estimated to an average of
3.7x107m3. The average soil loss based on the annual soil loss and the impact of the Typhoon 201919
indicate that Shirashikawa (78,775 ha) towards the northern and downstream end of the basin produced
the highest soil followed by Yashirogawa (43,563 ha) and Abukumagawajōryū (30,954 ha) sub basin
towards the southern end or the upstream sub-basins (Fig.3-Map A and B). The main factor contributing
to the high volumes of soil losses in these three basins is due to the larger catchment areas compared tothe smaller catchment. The soil loss impact map Fig.3-Map C was produced from dividing the soil lossesof each of the sub basins from the Typhoon201919 impact and the potential average impact. The results
indicate that Uchigawa (10,703 ha), Nigorikawa (3,479 ha), Omorikawa (1,933 ha) and Hirosegawa(23,968 ha) were the highly impacted sub basins from the Typhoon 201919. These impacted sub-basins
are located towards the mid to downstream end of the Abukuma basin (Fig. 3-Map C). The average soil
loss projection shows that by year 2050 Uchikawa will have produced an average of 4.7x105m3 by year
2050 (Fig.4). One of the major causes of which has caused the more significant impacts are due to the low
NDVI and land use changes, and the geographical steepness of the sub-basins observed from these four subbasins.

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CFig.3: Abukuma – Sub basin soil loss distribution Maps. (A) Typical Potential Average Soil
Loss, (B) Large Impact Event (C) Impact Map

Fig.4: Impacted Sub-basin Avg Soil Loss estimated projection.
5.

Conclusion

The USLE model was carried out in the GIS environment to estimate the soil loss in the Abukuma
River basin, Fukushima Prefecture, Japan, for 2019. The results of the estimates of a potential rainfall
erosivity impact and the impact of the large impact event (typhoon 201919) erosivity impact wereanalysed to identify the impact of the typhoon on each of the sub-basins. The soil loss production isgenerally caused by the naturally occurring agents such as the climate, topographical and land use
characteristics in the impacted sub-basins were studied. Apart from the naturally occurring force behindthe soil loss processes, human activities also contribute extensively to accelerating the process. The

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outputs of this study were based on historical and with limited data inputs. Further studies should becarried out to verify the model in terms of site survey and confirmation of the land surface changes.

Acknowledgment: This research was supported by the Environment Research and Technology
Development Fund (2-1907) of the Environmental Restoration and Conservation Agency of Japan, andPacific Leads Program, JICA.
References[1] Wischmeier, W.H., Smith, D.D.: Predicting rainfall erosion losses – a guide to conservation planning.
U.S. Department of Agriculture, Agriculture handbook No. 537 (1978)[2] Dhakal, A. TSUCHIYA, S. OHSAKA, O. (2006): Application of the USLE and sediment delivery
models in a mountainous catchment, p 44
[3] Hosoyamada, K., and Fujiwara, T. (1984 b): Application of the USLE for predicting the amount ofsoil erosion (II): Soil erodibility factor, slope length factor and support practice factor of the LISLE,
Journal of the Japanese Society of Irrigation Drainage and Reclamation Engineering, Vol. 52, p. 497502. (in Japanese)[4] Moore, I.D., Burch, F.J., 1986. Physical basic of the length–slope factor in the Universal Soil LossEquation. Soil Sci. Soc. Am. J. 50, 1294–1298.
[5] Durigon, V. L., Carvalho, D. F., Antunes, M. a H., Oliveira, P. T. S., & Fernandes, M. M.(2014).
NDVI time series for monitoring RUSLE cover management factor in a tropical watershed.
International
JournalofRemoteSensing,35,
441e453.
https://doi.org/10.1080/01431161.2013.871081.