IJERD – International Journal of Environmental and Rural Development (2017) 8-1

Research article
erd

Impact of the Land Use Diversity on the River Water Quality
in the Agricultural Area
YURI YAMAZAKI*The United Graduate School of Agricultural Sciences, Iwate University, Iwate, JapanTOSHIMI MUNEOKA
Obihiro University of Agriculture and Veterinary Medicine, Hokkaido, Japan
Email: muneoka@obihiro.ac.jp

MASATO KIMURA
Obihiro University of Agriculture and Veterinary Medicine, Hokkaido, JapanOSAMU TSUJI
Obihiro University of Agriculture and Veterinary Medicine, Hokkaido, Japan
Received 15 December 2016

Accepted 5 May 2017(*Corresponding Author)Abstract Water pollution due to agriculture has become a serious global problem. Also,
agricultural development has had major impacts on biodiversity. Impacts on the ecology of awatershed should be considered when proposing changes to land use and management for water
quality conservation. Habitat diversity is one of the most important factors for conserving
biodiversity in an agricultural landscape. In recent years, several fields of research have showna positive correlation between a mosaic of land types and species richness. Herein, weevaluated the land use diversity of the Tokachi River basin and examined an appropriate spatial
unit to calculate a land cover heterogeneity index for river water quality. The Tokachi Riverbasin is located in the northern part of Japan and plays an important role in a food production
area. The main land use types are forest, cropland, pasture, and dairy farming. Here we applied
the Satoyama Index (SI) as a land cover heterogeneity index to examine land use diversity. SI
evaluates a diverse mosaic of agricultural and non-agricultural land as an index from 0.0 to 1.0based on Simpson’s diversity index. High SI values are an indicator of high habitat diversity.
The mean SI value of the Tokachi River basin (No.17) was 0.6, and SI tended to be high in thecentral basin and low in the headwater of mainstream and tributaries. SI values had negative
correlations with total nitrogen, nitrate, and electrical conductivity (EC) of river water. Unified
land uses for extensive agricultural land results in increasing nitrogen and EC of the river waterand leads to monotonic habitat conditions in the Tokachi River basin.
Keywords Satoyama Index (SI), land use diversity, river water quality, biodiversity,spatial unit size

INTRODUCTION
Ecologically sustainable agriculture is regarded as a strategy to respond to global population growthand food issues, environmental degradation, climate change, and degrading natural resources (Kassamand Friedrich, 2012; Robertson et al., 2014; Bedoussac et al., 2015). The concept of an “ecologicalfarm” is an approach adopted to implementing ecologically sustainable agriculture that is in harmony
with nature; it involves the use of cultivation techniques and breeding programs that do not rely onsoluble chemical fertilizers, pesticides, herbicides, or artificial genetic modifications. The Food andHealth Organisation (FAO) established the Globally Important Agricultural Heritage System (GIAHS)Ⓒ ISERD117

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in 2002 to promote traditional agricultural systems and landscapes; these have been created, shaped,
and maintained based on diverse natural resources, using locally adapted management practices.
However, the agricultural production of eco-friendly agriculture still requires improvement.
In the Tokachi area, which is an important food production area in Japan, nitrogen pollution
caused by agriculture has been reported (Yamazaki et al., 2013, 2014, 2015, 2016(a)). Yamazaki et al.,2016(b) showed that it is necessary to control the restructuring of land use to alleviate nitrogen
pollution of the Tokachi River basin. Local ecosystems have to be considered when designing aneffective layout of land use in an agricultural land to facilitate water quality conservation.
In recent years, several studies have demonstrated a positive correlation between land use
diversity and species richness (biodiversity) in an agricultural area (Robinson and Sutherland, 2002;
Firbank et al., 2008). Kadoya and Washitani (2011) proposed the Satoyama Index (SI), a biodiversity
indicator which is a simple composite index of agricultural landscape heterogeneity and thecontribution of nonagricultural land use. They showed that a high SI value is an indicator of highhabitat diversity, whereas a low SI indicates a monotonic habitat condition, which is typical ofextensive monoculture landscapes.
In this study, we analyzed land use diversity of the Tokachi River basin by SI and examined therelationship between the SI score and the river water quality to design an eco-friendly measure of water
quality conservation in the Tokachi region, a large-scale agricultural landscape in Japan.
METHODOLOGYThe Tokachi River basin
This study was conducted in the Tokachi River basin located in the eastern part of Hokkaido, Japan(142.68–144.02 N, 42.55–43.65 E, 0–2,077 m altitude) (Fig. 1 and Table 1). The basin has a total areaof 9,010 km2 and a total stream length of 156 km. According to the Köppen–Geiger climateclassification, the Tokachi River basin is characterized as a warm summer continental climate type(Dfb) with an annual mean air temperature of 6.8 °C and an annual precipitation of 887.8 mm/y; thesemeasurements are the means of the recorded values at Obihiro City from 1981 to 2010. The soil types
in the Tokachi River basin are volcanic soil, lowland soil, upland soil, and peat soil. In particular,volcanic soil (andosols) is widely distributed in this basin. The main land uses in this river basin are foragriculture and forestry, with 60% of the agricultural land used as cropland and 40% used as pasture.
Both chemical fertilizers and livestock manure are applied to the agricultural land.
Water Quality Investigation and Analyses
The river water quality was monitored at 21 sampling points located on the main stream (No.17) and ateach tributary (A–T) of the Tokachi River basin in June, in either August or September, and in Octoberfrom 2007 to 2011 under base flow conditions. Water samples were analyzed for total nitrogen (T-N),
nitrate (NO3-N), total phosphorus (T-P), pH, biological oxygen demand (BOD), suspended solids (SS),and electrical conductivity (EC).
Satoyama Index (SI; Kadoya and Washitani, 2011)
We calculated the SIs of 21 watersheds in the Tokachi River basin. Calculation for SI is shown in Eq. 1
based on the agricultural landscape heterogeneity index (ALHI) using Simpson’s diversity index(Lande, 1996; Eq. 2) by ArcGIS Desktop (ver.10, ESRI).

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SI = ALHI ×

𝑝𝑜𝑡ℎ𝑒𝑟𝑘×
𝑘𝑘 −1(1)

ALHI = 1 − ∑𝑠𝑖 =1 𝑝𝑖2(2)pother is the number of grid squares of the other land uses, and k is the total number of the gridsquares in a spatial unit in Eq. 1. S is the number of different land cover items in a spatial unit, and pi isthe proportion of agricultural land to the total number of grid squares in Eq. 2.

Fig.1 Locations of the 21 sampling points in the Tokachi River basin
In this study, the following were the values
used: “land use raster data” (100 m grid size;
publication in 2009) published by the National
Digital Information and “JAXA High Resolution
Land-Use and Land-Cover Map (Ver. 16.02)”(10 m grid size; publication in 2016) publishedby ©JAXA. The proportion of agricultural land
and forest land in Table 1 was calculated by“land use raster data”. Also, Kadoya andWashitani (2011) set a spatial unit size of 6 km;
however, we set four different spatial unit sizes(500×500 m2, 1×1 km2, 5×5 km2, and 10×10km2) to calculate SI of the Tokachi River basin.

Table 1 Watershed and land use informationfor each sampling point
Samplingpoint

RESULTS AND DISCUSSION
Figure 2a, b shows the spatial distribution of SI
calculated by a combination of 500 × 500 m2
spatial unit size and 10 m or 100 m resolution(500 m unit size and 10 m resolution or 500 munit size and 100 m resolution) in sampling
point No.17. SI tended to be low in the center(lowland) of the watershed and high in theheadwater of mainstream and tributaries of thewatershed. In the Tokachi River basin, theⒸ ISERD

119

Watershed
area

River
lengthProportion (%)

km

2km

Agricultural
land

ForestlandA
BC
DEFGHIJKL
MNO
PQRST

234872337
210
263518016433667693
197
704
316
127
449
2850
173
66

47
2729422516183836226794
80
43
41
3152
150
25
13022254073
79
1673
52
47
1871
3065
79
70
19234498
96
97
68
53
111874
1744
44
6170
1228
12257673
51

178982146

3158

IJERD – International Journal of Environmental and Rural Development (2017) 8-1

center area is dominated by extensive agricultural land, resulting in monotonic habitat conditions;however, the headwater tributary areas were covered by forests and had rich habitat diversities. The
spatial distribution of SI of combinations with other spatial unit sizes (1 × 1 km2, 5 × 5 km2, and10 × 10 km2) showed the same trend. SI of the 10 m resolution varied between the center area (low SI)
and the headwater of mainstream and tributaries (high SI).

Fig.2a, b Spatial distribution of the Satoyama Index in the sampling point No.17
Fig. 3a, b shows the percentage of each SI value (0.0–1.0) calculated by a combination of four
spatial unit sizes (500 × 500 m2, 1 × 1 km2, 5 × 5 km2, and 10 × 10 km2) and two resolutions (10 m,Fig. 3a; 100 m, Fig. 3b) in the sampling point No.17. SI‒1.0 and SI‒0.1 were high percentages of 10 mresolution, whereas SI‒1.0 and SI‒0.0 were high percentages of 100 m resolution. Also, SI‒0.2 to SI‒
0.9 increased with increasing unit size of both resolution types. From this, the land use of the TokachiRiver basin is polarized between either agricultural land area or forest area.
We calculated the mean SI of the each watershed of the 21 sampling point of No.17 and A–T.
Fig. 4 shows the mean SIs of 500 m unit size‒10 m resolution and 500 m unit size‒100 m resolution in
the sampling point No.17 and A–T as one example. Where the sampling points have less than 0.5 of SIvalue, Mean SI of the 500m unit size-10 m resolution and 500m unit size -100m resolution showednearly the same value. However, the mean SI of the 500 m unit size-100m resolution was found to behigher than that of the 500 m unit size-10 resolution at the sampling points has more than 0.5 of SIvalue. It was considered that minor land use type recognized at 50 m resolution was excluded at 100 mresolution. Habitat diversity of the watershed at the sampling points A–D, H, L, R, and S werecomparatively rich since mean SI of these sampling points was higher than SI‒0.6. Conversely, thepoints on the watershed located at F, G, I, M, O, P, and Q were dominated by extensive agriculturalland since mean SI of these sampling points was lower than SI‒0.2. The same trend was confirmed of a
combination with another spatial unit size (1 × 1 km2, 5 × 5 km2, and 10 × 10 km2). However, SI
tended to decrease with increasing unit size.
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IJERD – International Journal of Environmental and Rural Development (2017) 8-1(a) Percentage of SI of 10 m grid size
0.980
Percentage of SI (%)

100

1.0

0.8
0.7

60

0.6
0.5

40

0.4

0.3

200.2(b) Percentage of SI of 100 m grid size
1.00.980
Percentage of SI (%)

100

0.8
0.760

0.6
0.5

40

0.4

0.3

20

0.2

0.1
0

500_101000_105000_10

10000_10

0.00.1
0500_100

Unit size_grid size (m)1000_100

5000_100 10000_100

0.0

Unit size_grid size (m)Fig.3 Percentage of Satoyama Index (SI)‒0.0 to SI‒1.01.00.6SI500_10

SI0.8

500_100

0.40.20.0
A B C D E F G H I

J K L M N O P Q R S T

17Sampling point (No.17; A-T of tributaries)

Fig.4 Mean Satoyama Index (SI) of the watershedin the 21 sampling point of No.17 and A–TTable 2 shows the correlation coefficients of the relationships between seven river water quality
variables (T-N, NO3-N, T-P, pH, BOD, SS, and EC) and mean SI. The mean SI of 21 sampling points
had a negative correlation with T-N, NO3-N, and EC. This implies that nitrogen concentration anddissolved matter tended to increase with low SI (unified to agricultural land). When we compared thecorrelation coefficients of T-N, NO3-N, and EC with each combination of unit size and resolution, thecorrelation coefficients tended to be higher in 10 m resolution than in 100 m resolution, and alsotended to be higher in the small unit size.

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Table 2 Correlation coefficients of the relationships between water quality
and mean Satoyama Index (SI). ** shows significance level (p < 0.01).
Water quality
index

500 m

SI_ 10 m grid size
Unit size
1 km
5 km

10 km

500 m

SI_ 100 m grid size
Unit size
1 km
5 km

-0.81**-0.79**-0.78**-0.76**-0.69 **
-0.68 **

-0.82**-0.80**-0.80**-0.79**-0.75 **
-0.73 **

-0.69**-0.68**

10 km

T-N

(mg/L)

NO3-N
T-P(mg/L)-0.82 **
-0.81 **

(mg/L)

-0.32

-0.37

-0.34

-0.36

-0.36

-0.34

-0.33

-0.34

0.12
-0.42

0.10
-0.42

0.01
-0.42

0.14
-0.41

0.15
-0.43

0.13
-0.38

0.03
-0.35
-0.03
-0.69**pHBOD(mg/L)

0.18
-0.41

SS

(mg/L)

-0.06

-0.09

-0.07

-0.06

-0.05

-0.08

-0.06

EC(mS/m)-0.83 **

-0.84**-0.79**-0.73 **

-0.82**-0.81**-0.75 **

CONCLUSION
Herein, we analyzed the habitat diversity of 21 sites in the Tokachi River basin using the Satoyama
Index (SI) and examined the relationships between the river water quality and SI. In the Tokachi Riverbasin, the center (lowland) area had low SI and was dominated by extensive agricultural land, whereas
the headwater of mainstream and tributaries had high SI and had rich habitat diversity. Mean SI of the
21 sampling points showed a negative correlation with T-N, NO3-N, and EC. The nitrogenconcentration and dissolved matter of the river water tended to increase in the sampling points
dominated by extensive agricultural land. Also, it was suggested that the combination of 500 m unit
size and 10 m resolution was optimal for explaining the relationships between SI and the river waterquality.
ACKNOWLEDGEMENTS
This research was supported by JSPS KAKENHI, Grant Number 15J04743, 2015. We would like toexpress our gratitude to the research assistance provided by the students and the Obihiro University ofAgriculture and Veterinary Medicine.
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