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GIS-理論と応用Theory and Applications of GIS, 2009, Vol. 17, No.1, pp.53-62
【研究・技術ノート】
Using GIS for assessing stream water chemistryin a forested watershed
Akiyuki KAWASAKI, Reiji FUJIMAKI, Nobuhiro KANEKO and Satoru SADOHARA
Abstract: Systematic survey preparation and data analysis are required for conducting efficient
research on forested mountains because investigating many streams in such an environment
is difficult. A methodology of GIS utilization for surveying and analyzing nitrogen leaching in
headwaters was demonstrated in this paper. Firstly, support maps for the Tanzawa Mountains,
Southern Kanto District, Japan, were created for effective data collection by field surveys.
Then, contributions of catchment properties to N-leaching were investigated by spatial analysis
using fine-scale terrain data. Finally, N-leaching prediction maps were created for decision-
support.
Keywords: forest ecosystem, catchment, water sampling point, nitrogen
1 . Introduction1 -1 Background
Nitrogen (N) plays a key role in regulating
primary production in ecosystems, especially in land-
based systems. Increased human socioeconomic
activity has changed nitrogen circulation drastically
on a global level. Increased reactive nitrogen from
humans through synthetic fer tilizers, industrial
use, and fossil fuel consumption has been exerting
strong influences on the ecosystem. High levels
of anthropogenic nitrogen, coming primarily from
atmospheric deposition, are recognized as a crucial
environmental issue in natural ecosystems on a
par with global warming and acid rain (Aber et al.,
1998; Galloway et al., 2003). Problems associated
with high nitrogen levels were also featured in the
United Nations’ Millennium Ecosystem Assessment
(Millennium Ecosystem Assessment, 2005). A
major symptom caused by increased nitrogen input
to forested catchments is increased nitrate (NO3-)
concentrations in stream waters, which can cause
eutrophication and acidification in freshwater and
coastal waters, which deteriorates water quality while
threatening human health (Vitousek et al., 1997).
There is an increasing need to understand stream
water quality.
In general, researching streams in an entire
watershed is difficult due to its large area. Therefore,
systematic monitoring location planning and
analysis are crucial for effective research. Recent
developments in information technology such as
Geographic Information Systems (GIS) allow the
rapid arrangement of a spatial data infrastructure and
comprehensive analyses of various kinds of spatial
data. Consequently, GIS of fer promising tools for
planning and analyzing the study of stream water
quality in large-scale forested watersheds. This paper
provides a case study on applying GIS to streamwater
research in the Tanzawa Mountains of northwestern
Kanagawa Prefecture, central Japan. The Tanzawa
Mountains are an impor tant area because most
川崎:〒150 -8925 東京都渋谷区神宮前5丁目53 -70 国際連合大学サステイナビリティと平和研究所 United Nations University, Institute of Sustainability and Peace 5 -53 -70 , Jingumae, Shibuya-ku, Tokyo 150 -8925 , Japan E-mail:[email protected]
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Kanagawa Prefecture residents depend on the area
as a source of water. For that reason, deterioration
of water quality in this area is a critical issue for
Kanagawa water resources. This area, located
in Japan’s southern Kanto district, is most likely
affected by anthropogenic disturbances. Okochi and
Igawa (2001) reported high nitrate concentrations in
a stream in the Tanzawa Mountains, but their study
was limited to only one stream; so water chemistry
patterns on a broader scale within the Tanzawa
Mountains remains unclear. Additionally, nitrogen
leaching from forest ecosystems varies significantly
because of many factors like differences in geology
(Willard et al., 2005), hydrology (Shibata et al., 2001),
watershed topography (Creed and Band, 1998), and
tree species composition (Lovett et al., 2000).
1 -2 ObjectiveThe research team for this study consists of
geologists, pedologists, and vegetation scientists.
The team has been tr ying to explain nitrogen
leaching mechanisms from forest ecosystems and
proposed a future strategy of forest management
(Kaneko and Fujimaki, 2006; Sakai et al., 2007). The
research project involved conducting a general field
survey to assess the current nitrogen leaching from
forest ecosystems in the Tanzawa Mountains. The
study described in this paper specifically examines
the utilization of GIS for survey and analysis. This
paper proposes and describes implementation of
spatial information utilization for promoting efficient
nitrogen leaching assessments in forested mountain
headwaters.
G I S h a v e b e e n u s e d t o i n v e s t i g a t e t h e
characteristics of watersheds for many purposes;
for example, Luzio et al. (2004) developed a model
to assess agricultural non-point and point pollution
loading at the watershed scale; Downs and Priestnall
(1999) studied river channel adjustments; and
Kaur et al. (2004) analyzed the impact of land-
use planning on soil conser vation by using a
watershed-scale hydrologic model. Specifically as a
preceding study, Jarvie et al. (2002) investigated the
relationship between river chemistry and watershed
characteristics, including landuse, topography and
geology, using GIS and statistical analysis for the
Humber catchment in England. In addition, nitrogen
leaching factors at the catchment scale in forested
mountains in Japan were analyzed using a 50 meter
mesh digital elevation model (DEM) (Ito et al., 2004;
Ogawa et al., 2006). However the priority and process
of selecting water sampling points remain unclear,
and spatial patterns of nitrogen loss in streams and
the cause of the pattern were analyzed within the
watershed delineated from these sampling points.
A methodology for designing sampling points are
necessary to consider forest management in the
Tanzawa Mountains, which consists of precipitous
terrain combined with a variety of geology and
vegetation over a broad area.
In this study, sur vey suppor ting maps were
prepared for effective data collection in the field by
considering some working hypotheses. Then, factors
contributing to water chemistry were analyzed using
fine-scale spatial data in an individual catchment.
Finally a “nitrogen leaching prediction map” was
created for decision support concerning the type and
location of actions to properly manage future forest
ecosystems in the Tanzawa Mountains.
Fig. 1 Research site
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2 . Developing working hypotheses and allocating sampling points
2 -1 Study areaThe Tanzawa Mountains are located in the
northwestern part of Kanagawa Prefecture, in an
area extending 50 km east and west and 30 km north
and south. The mountain range is located where the
Philippine, Eurasian and North American continental
plates collide, and it was formed by the collision of
the Honshu Arc and the Izu Arc. Japan’s highest
rates of orogenic uplift and denudation by the Izu-Arc
are still observed here (Arima and Kaneko, 2006)
and the topography is composed of steep slopes.
The impact of atmospheric pollution is apparent
in the Tanzawa Mountains. The distance from the
center of the Tokyo metropolitan area, where Japan’s
socio-economical activities are concentrated, is
approximately 50 km. In the mountains, 11.3 kg-N/
ha/year of nitrogen deposition was measured in
Ooyama and 13.3 kg-N/ha/year was measured in
Fudagake (Asou et al., 2001).
Six river systems in the mountains were studied
(Fig. 1): the Hayato River and Shimizu River flowing
to Miyagase Lake in the eastern par t; and the
Kurokura River, Nakagawa River, Oomatazawa River,
and Yozuku River flowing to Tanzawa Lake in the
western part. The Tanzawa region straddles both
Kanagawa and Yamanashi Prefectures, but only
the Kanagawa side was chosen due to personnel
limitations. The total research area was 21,000 ha:
95.7% of the area was covered by forest, 2.5% by waste
land, and 1.6% by water (National-Land Information
Office, 1997). The elevation of the area ranges from
290 to 1,673 m with an average of 851 m.
2 -2 Preparing datasets and characterizing catchments
To assess the influences of topography, geology
and vegetation on water quality, headwater outlets
discharged from various small catchments were
targeted as sampling points. The tentative size of
the catchments was limited to less than 80 ha so
that the results could be applied to a selection of
future experimental sites for long term monitoring.
For example, the Hubbard Brook Ecosystem Study
for a US site of the Long Term Ecological Research
(LTER), on ecosystem patterns and processes
in a watershed, selected nine watersheds of less
than 80 ha for observation (Hubbard Brook LTER,
2008). Fur ther consideration of the catchment
size is required if this unit is suitable for complex
topography in Japan, or for considering topography,
geology, vegetation and soil as a unit, and how
heterogeneous characteristics inside the catchment
is changed as the catchment size increases.
Several GIS datasets were collected and analyzed
to find appropriate sampling points (Table 1). First,
as an interpolation-conversion from elevation point
to raster dataset, catchments were delineated using
a DEM with a 12 m cell size using ESRI ArcGIS
Desktop 9.1 and Spatial Analysis. The DEM was
generated from vector elevation data called GISMAP
Terrain. Although the nominal resolution of the
data is 10 m, we produced the 12 m DEM due to the
Table 1 GIS data sources
Dataset name Format Scale Product name Data provider Category used in this study
Elevation Point 1:25,000 GISMAP Terrain(10 m mesh)
Hokkaido-chizu Co.Ltd. Elevation: 800 m> or 800 m<;Slope gradient: <30°, 30-35° or >35°
Bedrock geology Polygon 1:50,000National land
classification surveys
Ministry of Land,Infrastructure and Transpor t;
Ishikawa et al . (2005)
Tuff bedrock, Plutonic bedrock,Pyroclastic rock, Mudstone,
Pudding stone, or Loam
Vegetation Polygon 1:50,000 Vegetation inventory Kanagawa Pref. Natural forest, Plantation forestor Mixed vegetation
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parameter setting of the interpolation-conversion
module of the software. The Tanzawa Natural
Environment Information Station by Kanagawa
Prefecture also adopted a 12 m cell size for deriving
a DEM from the same data (Kanagawa Prefecture
Natural Environment Conservation Center, 2006).
With a flow accumulation grid delineated from
the DEM, streams were defined through a flow
accumulation value of 1,500 cells. A threshold flow
accumulation of 1,500 cells with a 12 m cell size
correspond to a drainage area of 216,000 m2 or
21.6 ha. The reasons for defining a threshold value
and verification of water flow status are described
in section 3-2. Next, stream junctions were treated
as catchment outlets. As a result, 139 headwater-
catchment sampling points were selected from the
study area.
The watershed characteristics of the selected
sampling points were classified according to the
following properties (Fig. 2).
Elevation: Catchments were categorized into two
elevation groups: one with mean elevation greater
than 800 m, the other less than 800 m. At this latitude
(35°24' – 35°37'N), native vegetation growing at
elevations higher than 800 m is different from that
growing in lower areas. Cool-temperate natural mixed
forests with deciduous broadleaf trees (beech) and
conifers (fir and hemlock) prevail in upper elevations,
whereas temperate evergreen broadleaf forests
prevail in the lower areas (oak). Nowadays, the
latter areas are dominated by secondary vegetation
and conifer plantations such as cedar and Japanese
cypress (Sakai, 2006). These changes in vegetation
type, along with elevation, might alter the nitrogen
retention in catchment areas.
Slope: Slope gradient was assumed to influence
water transfer speeds on the sur face and inside
the soil, as well as to affect soil depth. Mean slope
gradient was used to categorize catchments into
three types: <30°, 30–35°, and >35°, since thick loamy
volcanic soils tend to cover moderate slopes less than
30°, and granitic tonalite soils cover a broad range of
slopes but the soil depth tends to decline inversely
with the gradient in the Tanzawa Mountains (Kaneko
et al., 2007; Sakai et al., 2007). Granitic tonalite soils
have higher productive capacity of nitrates per
organic substance than volcanic ash soils, because
organic matter in granitic tonalite soils tends to have
higher mineral content. Slopes around 30°and higher
were considered to have high nitrate production rates
because such slopes are mainly covered by granitic
tonalite soils.
Geology: The eastern part of the research site is
covered by tuff bedrock developed in the Miocene
Fig. 2 GIS datasets for categorizing the watershed characteristics of selected sampling points
Elevation Slope
Geology Vegetation Candidate points
Candidate point
Watershed
Elevation Slope
Geology Vegetation Candidate points
Candidate point
Watershed
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(Ter tiar y) period, and the western par t on the
other side is mainly covered by plutonic bedrock
(granitic tonalite). This geological distribution was
assumed to have a significant influence on stream
water chemistry and ecosystem material flow by
affecting vegetation and chemical weathering of the
soil. Furthermore, such mechanisms might influence
the buffering capacity against nitrogen deposition in
forest water systems.
Vegetation: The catchments are dominated by
degraded trees due to a lack of forest management,
and this may strongly influence nitrate leaching.
Consequently, the catchments were categorized as
“natural forest, plantation forest or mixed vegetation”
by calculating the dominant vegetation (>70% of
the area) of each catchment. Catchments were
categorized as having mixed vegetation when either
natural or plantation forest covered less than 70%
of the total area. The value of 70% was a tentative
threshold.
3 . Implementation of water sampling3 -1 Survey outline
A general survey by six teams with 25 members
was conducted to assess nitrogen leaching in the
Tanzawa Mountains headwaters on July 13th and
14th, 2006. Each team was supplied with two types of
the river system map highlighting sampling points
and catchment properties (Figures 3 and 4), 1:25,000
Geographical Survey Institute (GSI) topographical
maps, longitude and latitude of sampling points, and
GPS units. Some members were familiar with the
study site, while some were not. Team members
were assigned to collect samples from watersheds
that have various characteristics of elevation, slope,
geology and vegetation in a balanced manner using
survey support maps.
Despite initially aiming to acquire 100 samples
out of 139 candidate points in Fig. 2, the survey
ultimately yielded 51 samples of water, soil and
leaves (bamboo grass and Polygonum cuspidatum),
inc lud ing severa l unp lanned po ints due to
topographic difficulty in accessing several planned
points, time restrictions, and heavy rainfall on July
14th (Figures 5 and 6). The points not surveyed were
either too far from main road, too dangerous for
data collection (rough landscape and swollenness of
stream), or unsuitable in terms of the balance of the
watershed characteristics. For supporting a more
systematic sur vey, focusing on priority areas by
preliminarily considering catchment properties and
displaying optimal routes might be useful. Achieving
over half of the intended water samples in this short
period under imperfect conditions was considered
successful.
Additionally, the GPS units including Trimble
Fig. 4 Survey support map – example 2Fig. 3 Survey support map – example 1
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Pathfinder Pro XR and ProXH provided accurate
location information (accuracy of less than 1 m using
real time differential correction), which allowed the
effective surveying and collection of sample points.
However, GPS signals were often insufficient due
to the forested mountainous terrain, so the GSI
topographical maps were used to supplement the
searching tasks.
3 -2 Verifying the status of headwater flow extracted from the DEM
No standard processes exist regarding what
methodologies and parameters to use for extracting
streams using a DEM, and it is possible to delineate
a wide range of stream features using GIS depending
on the data used, analysis resolution, extraction
parameters and methodologies, etc (Kawasaki, 2006;
Maidment, 2002). In this study, sampling points
were designed from catchments and stream data
delineated from the DEM, as described in section
2-2. In general, water chemistry analysis gets more
complicated with larger catchment areas, and it is
ideal to collect samples from the upper reaches of
a catchment to assess the effects of topographical
features, geology, and vegetation on water chemistry.
Therefore, it was necessar y to capture accurate
locations of headwaters not described even in the GSI
topographical map. For that reason, headwaters that
regularly maintain at least a minimum level of flow
despite seasonal and conditional variability had to be
extracted using GIS.
Accordingly, a flow accumulation value of 1,500
cells was defined as the stream delineation threshold
based on the knowledge of experts familiar with a
part of the study area (Nishizawa catchment, 306
ha). The experts compared various kinds of stream
data extracted using a range of thresholds, and
determined the most suitable threshold to describe
actual water flow including small streams.
During the survey, stream flow at the planned
points was verified including locations at which actual
water samplings were not implemented. Inventory
forms were distributed to each team and the status of
water flow was identified as one of the four categories
in Table 2 by visual observation. The table shows
that actual water flow in various statuses was verified
at most locations checked during the survey. Total
rainfall was recorded as 2 mm for one week prior to
the survey (July 7th - 13th), and 94 mm for the past
two weeks (June 30th - July 13th) at the neighboring
Tanzawa Lake observation site (Japan Meteorological
Agency, 2006). The results shown in Table 2 might
be biased since the results were limited to only those
locations accessed, and some field survey members
might have selected easier locations for obtaining
water.
4 . Analysis and modeling of nitrogen leaching
4 -1 Chemical analysis and mapping the resultStream water, soil, and leaf samples were used to
assess water chemistry such as pH balance, water
temperature, nitrate (NO3-), NH4
+, total nitrogen (TN),
and dissolved organic carbon (DOC). The result
was outlined in this paper and utilized to create the
nitrogen leaching prediction map in section 4-2.
The mean concentration of TN of all stream water
was 0.74 mg-N/L, ranging 0.18 mg/L to 1.30 mg/
L with over 95% containing nitrate (Figures 5 and
6). The factors shown in Fig. 2 were almost equally
distributed because of the use of the survey support
maps (Figures 3 and 4). Nitrate concentrations in
headwaters of the eastern Tanzawa Mountains tend
to be higher than those of western areas (Fig. 6),
which corresponds to dif ferences in geology: the
eastern part consists of tuff bedrock, whereas the
western part consists of plutonic bedrock (Fig. 2).
Chemical analysis methods and equipments, as well
as the results and mechanisms of Nitrogen leaching
in the Tanzawa Mountains are described in Fujimaki
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et al. (2008)
4 -2 Predicting model of nitrogen leachingA general linear model was used to predict the
nitrogen concentrations in streams using topographic
characteristics in the catchment areas. The following
parameters were assessed.
a ) Distance from the Yokohama city center (km)
b ) Distance from the Sagami Bay coast line (km)
c ) Total catchment area (ha)
d ) Mean catchment elevation (m)
e ) Catchment elevation standard deviation (m)
f ) Catchment elevation range (maximum −
minimum, m)
g ) Catchment mean slope (deg.)
h ) Catchment slope gradient standard deviation
(deg.)
i ) Proportion of steep slopes (>30°) area to total
catchment area (%)
j ) Most frequently observed slope aspect category
k ) Mean of the cosine-transformed value of the
slope aspect azimuth: The cosine of the slope
aspect azimuth represents the degree of north
facing, ranging from -1 to 1.
l ) Mean catchment Laplacian value
m) Standard deviation of catchment Laplacian
value
From the geological map and the vegetation
inventor y, each catchment was categorized as
follows:
n ) Most frequently observed bedrock geology in
three categories (plutonic, tuff, and volcanic
tuff)
o ) Dominant vegetation (>70% of area) in three
categories (natural forest, conifer plantation,
and mixed vegetation);
Model selection was per formed according to
Akaike’s information criterion (AIC), a statistical
reference for determining the suitability of statistical
models among several options (Venables and Ripley,
1999). Lower AIC values indicate a better model
based on the lowest squares of residual sum but
with a penalty for the greater number of parameters.
The software program R 2.6.0 (R Development Core
Team, 2007) was used for the statistical analysis. The
selected model was;
TN = 2.5913 - 0.2389 k - 0.1541 h - 0.0071 a ,
where TN is total nitrogen concentration (mg-N/L)
in stream waters, k is mean of the cosine-transformed
value of the slope aspect azimuth, h is catchment
slope gradient standard deviation (deg.), and a is
distance from Yokohama city center (km) (R2 = 0.343,
AIC = -5.19, F = 8.17, p < 0.001).
TN was negatively related to k, showing that
stream TN tends to be high when the proportion of
south-facing slopes increases. This is because soils
Fig. 5 Total nitrogen [mg-N/L]
Fig. 6 Nitrate (NO3--N [mg-N/L])
Table 2 Stream flow status (n=61)Stream flow status Number of points (ratio)
)%58( 25wolf retaw tnadnubA)%2( 1wolf ot eganaM)%8( 5retaw pmuS)%5( 3wolf retaw oN
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in south-facing slopes tend to be warmer, probably
promoting nitrogen mineralization and nitrification.
TN was also negatively correlated to h, indicating that
nitrogen is less likely to leach with more complex
terrain, but this exact mechanism requires further
investigation. Additionally, the Tanzawa Mountains,
directly facing the Kanto Plane where Yokohama
is located and where industry and agriculture are
highly developed, receive reduced nitrogen loads
that are inversely propor tional to a. Additional
interpretation of individual parameters is described
in Fujimaki et al. (2008). AIC analysis also yielded the
following model:
TN = 2.1577 - 0.1954 k - 0.1473 h(R2 = 0.313, AIC = -4.91, F = 10.91, p < 0.001).
This second model had fewer parameters than
the first model with little dif ference in AIC value,
although the coefficient of determination was less.
Fig. 7 shows the results of the first model fitted
to a topographical map. Continuing sur veys and
analyses with additional consideration are required
for improving the scientific credibility of this study
because this map was extrapolated from spatial
nitrogen leaching patterns observed on July 13th
to 14th, 2006. This map, however, can contribute
to effective and advanced surveys in the future by
illustrating where to collect water in an ef ficient
manner.
5 . ConclusionsThis study used GIS for supporting sampling point
selection to analyze nitrogen leaching in headwaters
and explained the available methodologies. The
following results were obtained:
1. Sur vey suppor t maps were created to locate
sampling points and field data collection.
Headwaters in small catchments with dif ferent
properties were successfully extracted.
2. Spatial analysis based on fine-scale terrain data
was used to investigate the effects of catchment
topography like slope gradient and slope aspect
on nitrogen leaching.
3. A nitrogen leaching prediction map was created
for the entire Tanzawa Mountains based on data
from 51 sampling points. Estimation of the status
of the broad range of mountains and considering
further desirable countermeasures are possible,
by expanding the analysis results in small
catchments to the broad range of all mountains
using GIS, where capturing aerial ecosystem data
was difficult.
Further debate is required on how to use GIS for
creating a material flow model to predict nitrogen
status in mountain headwaters and estimating
effective countermeasures using scenario analysis.
AcknowledgmentsWe are especially grateful to the valuable support
and suggestions from the referees and editorial
committee of GISA, and also Prof. Arima, Prof.
Nakamura, Prof. Ohno, Prof. Ito, Prof. Ishikawa,
Dr. Kaneko and Dr. Sakai at Yokohama National
University. This study was financially supported by
the 21st Century COE Program of the Japan Society
for the Promotion of Sciences, the scientific research
fund of the Ministry of Education, Culture, Sports,
Science and Technology (No. 18710035), and the
fund for Enhancement of Education and Research in
Yokohama National University.
Fig. 7 N-leaching prediction map (TN)
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(2008年4月15日原稿受理,2009年3月13日採用決定,2009年4月27日デジタルライブラリ掲載)