IJERD – International Journal of Environmental and Rural Development (2023) 14-1

Research article
erd

Habitat Evaluation of Agricultural Waterways where
Environmental Improvement Was Practiced for Recreation
MASAYUKI NITTA*
Sado Island Center for Ecological Sustainability, Niigata University, Sado, Japan
Email: nitta@cc.niigata-u.ac.jp

MITSURU OHIRA
Field Science Center for Northern Biosphere, Hokkaido University, Hokkaido, Japan

MUNEYUKI AOKI
Department of Civil and Environmental Engineering, Toyo University, Kawagoe, Japan

MASAHIRO NAKAJIMA
Institute of Agriculture, Tokyo University of Agriculture and Technology, Fuchu, Japan
Received 28 May 2022

Accepted 10 June 2023(*Corresponding Author)

Abstract In rural areas, agricultural irrigation and drainage systems developed for paddy fields
have a high potential to become components of green infrastructure by providing ecosystemservices. In order to manage and operate agricultural waterways as green infrastructure, thehabitat evaluation of aquatic organisms is important. In this context, we conducted a habitat
evaluation of aquatic organisms in the waterway network where environmental improvement
was practiced to promote recreational use by residents. Based on evaluation results, thephysical characteristics of canals with high biodiversity were investigated. The Evaluation
Program for Fish Habitats in Agricultural Canals, which was developed for non-professional
users such as residents, was applied to biological (fishes and crustaceans) and physical datacollected in the waterway network in the town of Koura, Shiga Prefecture, Japan. The model
generated by the program showed high fitness (0.80 for fishes, 0.76 for crustaceans), whichsuggests the program applies to waterway networks including various types of watercourses.
The characteristics of the canals which were assigned a high habitat score by the program
included 1) deeper water depth, 2) higher velocity for fish, 3) lower velocity, 4) higher
vegetation coverage, and 5) gravel canal bed for crustaceans, relative to the low-scoring canals.
The canals in diversion parks developed as part of environmental improvement efforts tended
to have these characteristics and higher scores. Therefore, our findings suggest that conserving
irrigation canals and developing diversion parks in waterway networks, which were conducted
as part of environmental improvement efforts in the target area, contributes not only topromoting recreational use by residents but also to habitat conservation.
Keywords habitat evaluation, agricultural waterways, environmental improvement,
green infrastructure

INTRODUCTION
Green infrastructure is defined as a strategically planned network of natural and semi-natural areas
with other environmental features designed and managed to deliver a wide range of ecosystemservices in both rural and urban settings (European Commission, 2013). Agricultural waterways for
irrigation and drainage have been historically developed in rice-farming regions. Such waterways
were traditionally used not only for irrigation but also for fisheries, recreation, and domestic use.
Therefore, agricultural waterways have a high potential to become components of green
infrastructure by providing ecosystem services.

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However, recent modernization of agricultural landscapes and infrastructures modified only for
efficient agricultural production and accelerated to use as grey infrastructure (Lee et al., 2015). Thus,
improving irrigation infrastructures as green infrastructure based on sustainable ecosystem service
use, such as recreational use, is a recent fundamental challenge (Matsuno et al., 2006; Katayama etal., 2015; Nishida, 2018). In this context, the habitat evaluation of aquatic organisms is important tomanage and operate agricultural waterways as the green infrastructure.
Currently, agricultural waterways in rice-farming landscapes have been modified for themodernization of irrigation systems. Particularly, irrigation canals have been converted into pipelines
to distribute water efficiently. Further, even in open canals, concrete lying degrades habitat
conditions. Such negative impacts of modification for aquatic organisms have been reported (e.g.,
Nishida et al. 2018) and could be a significant concern for the availability of ecosystem services.
However, consideration of the availability of such waterways for people is limited in planning andmanaging agricultural landscapes as green infrastructure in addition to habitat conservation andrestoration.
In a waterway network in Koura town, Shiga Prefecture, Japan, environmental improvement
was practiced promoting the recreational use of residents. Recreation constitutes cultural ecosystemservices of agricultural waterways and is important from a well-being perspective for the formationof rural living environments. However, it is not known that such modification for recreational use
benefits to restoration of ecosystem services (Lin et al., 2020). In restoration practice, considering
the habitability of aquatic organisms with such environmental improvement is key for the availabilityof wider ecosystem services (Matsuno et al., 2006).
OBJECTIVE
The study aims to assess the habitability of aquatic species in agricultural waterways adapted forrecreational purposes.
METHODOLOGY
Study Area
The study was conducted in a waterway network in the town of Koura (35.2 N, 136.26 E), Shiga
Prefecture, Japan. Koura town is a rural area located on the alluvial fan formed by the Inukami River(Fig. 1). In this area, it was planned to convert all irrigation systems to pipelines for water shortagein 1981.
N

Lake Biwa

Inukami River

Shiga Prefecture
Koura Town
0 1

2km

Fig. 1 Location of the study area, Koura Town, Japan
An aerial photograph is quoted by the Geospatial Information Authority of Japan and modified partially.

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However, implemented the water environment improvement project in 1989, the irrigation anddrainage canals were drastically altered to improve for recreational use by the residents: (1) the
irrigation plan was modified to maintain open canals; (2) diversion parks were developed utilizing
the pipeline discharge and diversion points; (3) the open irrigation canals were environmentallyprotected by masonry revetments; (4) sands and gravels were added to the irrigation canal beds; and(5) landscape facilities such as flower beds were installed
Data Collection
Based on the characteristics of the waterway network in this area, a total of 26 canal sections
containing a variety of environmental conditions were selected as survey sites (Fig. 2). Each of thesurvey sites was 20 m in length and the width was the canal width. We conducted a biological andenvironmental survey on 10-18 August 2018.
As the physical environment varies depending on the type of canal, the survey sites werecategorized into four canal types: diversion park (No. 1 to No. 6, Fig. 3a); drainage canal (No. 7 toNo. 11, Fig. 3b); irrigation canal A (No. 12 The
to Inukami
No. 20,Fig. 3c); and irrigation canal B (No. 21 to No.
River
The Inukami River26, Fig. 3d).
: Diversion park
: Drainage canal

The Inukami River

The Inukami River
The
InukamiRiver
River
The
InukamiThe Inukami River: Irrigation canal A(wider)The Inukami River: Irrigation canal B(smaller): Open canal: Pipeline
Weir

0m

500m

Fig. 2 Location of survey sites with canal typeFig. 3 Example of four canal types in the study areaa) diversion park; b) drainage canal; c) irrigation canal A; andd) irrigation canal BⒸ ISERD155

The Inukami River

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In this waterway network, irrigation water is introduced from the Inukami River, after that, water
is distributed into diversion works of each village through pipelines. The diversion park as the waterpark was developed in diversion points and the associated canals. The survey sites of diversion parks
were located in one of the associated canals to compare other canal sites. The Irrigation Canal A is
the main canal and has a wider canal width for carrying water to areas of paddy fields. Irrigation
Canal B is a small canal that branches off from Canal A and supplies water directly to each paddy
field. In diversion parks the environmental improvement commonly modified the canal structure forrecreational use: the canal width was widened; gravel was laid on the streambed; the slope of therevetment was made gentler; and emergent plants were planted. In this waterway network, vertical
drops were constructed between irrigation canals and drainage canals. However, fish migration was
thought to mainly come from the Inukami River through pipelines. Thus, we did not consider theeffects of barriers to fish migration.
To measure physical characteristics, cross sections were placed at 5 m intervals in each site. We
conducted a field survey including both physical characteristics and biological sampling. To examine
the hydraulic conditions of survey sites, water depth, water velocity, canal width, and wetted width
were measured. The difference between canal width and wetted width was used as land width acrossthe canal. Water depth and water velocity were measured across cross sections, and the points weredivided into quarters. A uniaxial electromagnetic anemometer (Kenek, LP40) was used to measurewater velocity. The percentage of streambed material (concrete, large gravel (cobble, > 64 mm),small gravel (pebble and granule, 2-64 mm), sand and silt (< 2 mm)) and vegetation cover were
measured visually. We also measured water temperature, electric conductivity, and pH at the sametime as those samples. However, the remarkable differences among sites were not shown.
We conducted biological sampling for fish and crustaceans. Two fyke-nets (mesh size: 5 mm)
were set at both ends of the sampling section and hand nets (2 mm) were used to collect fish andcrustaceans inside the survey site. The sampling effort of each site was fundamentally ten minutesby three persons. However, areas of the survey site (i.e., canal width) differed among sites. Thus, thesampling effort was adjusted to the area of the survey site to ensure an equivalent sampling effort
among survey sites. After collecting fish and crustaceans, we identified species and counted
individuals of each species. After that, we released sampled fish and crustaceans to the sampling site.
Analysis
To evaluate aquatic habitat, the "Evaluation Program for Fish Habitats in Agricultural Canals"(Watabe et al., 2018; 2020) (hereafter referred to as the "EPFH"), which was developed as a simple
evaluation method by non-specialists, was applied. EPFH was developed and published free ofcharge by the National Agriculture and Food Research Organization (NARO, 2018). In ecosystemfriendly measures, it is important to conduct continuous monitoring surveys and adaptive
management, such as updating and modifying facilities, to prevent habitat degradation. However,there are issues such as the significant cost of continuing monitoring surveys and the difficulty ofinterpreting the results of environmental assessments without specialists. EPFH was developed as asimple evaluation tool to address these issues. In this study, the EPFH was selected based on theassumption that it would be operated by non-specialists (local residents) who are the maintenancemanagers of the agricultural waterways.
In this program, the evaluation score is calculated using Eq. (1). This is a regression equation,
which is positively correlated with both the number of species and the number of individuals
identified and is explained by the physical environmental conditions such as water depth and watervelocity (Watabe et al., 2018).
y=a0 +a1x1 +a2x2 +a3x3 +a4x4 +a5x5(1)

Where y is the evaluation score, a0 is the constant term, a1 to a5 are the coefficients of eachvariable, and x1 to x5 are environmental indices. The values of a0 and a1 to a5 are determined so thatboth the correlation coefficient r1 between the evaluation score y and the number of species and theⒸ ISERD

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correlation coefficient r2 between the evaluation score y and the number of individuals are high. The
goodness of fit of the model F is defined by the following Eq. (2);
𝑟 +𝑟2
2

𝐹= 1

(2)

where r1 represents the correlation coefficient between the evaluation score and the number of species,and r2 represents the correlation coefficient between the evaluation score and the number ofindividuals. The goodness of fit ranges from values of -1 to 1. In this study, to confirm the reliabilityof the accuracy of this program, a correlation test of the correlation between the evaluation score andShannon-Wiener's diversity index H' (Whittaker, 1972) was also conducted.
The Kruskal-Wallis’s test was conducted to analyze differences in scores of habitat evaluation
among canal types. If the test showed significant differences, multiple comparisons were made using
the Steel-Dwass method to determine a pair of canal types with significant differences among thefour canal types. All of the statistical analyses were performed using R version 4.0.5 (R Core Team,2021). The results of this analysis were shown for biological data but not for physical environments.
Because the variations were very large depending on the site characteristics. Thus, we focused on the
numerical difference of the physical environments.
RESULTS AND DISCUSSION
Status of Physical Environments of Waterways and Aquatic Organisms
The physical environmental conditions of canal type are shown in Fig. 4. Average canal width ofsurvey sites ranged from 50.0 to 446.5 cm, and the land width ranged from 0 to 146.0 cm. Water
depth ranged from 3.2 to 43.7 cm, and water velocity ranged from 1.7 to 38.7 cm/s. Vegetation coverranged from 0 to 51%. Streambed materials were largely varied.
Diversion parks tended to have relatively wider canal widths and deeper water depths. Only thediversion park contained canals with a water depth of more than 30 cm. This is because the diversion
park includes the canals through which pipeline water flows before it is diverted, and thus hasabundant water flow. As for water velocity, the drainage canals tended to be slower. Vegetation covertended to be higher in diversion parks and drainage canals. This is because aquatic plants wereplanted in the diversion park at the time of environmental improvement for landscaping, and also
because sediments were deposited in the drainage canals due to the slow water velocity andvegetation growth. Comparing canal bed materials, there was no concrete in the diversion park. The
percentage of small gravel tended to be lower in the drainage canal than in the diversion park.
Irrigation canals A and B showed similar trends.
The results of the aquatic organism survey are shown in Table 1. In total, 657 individuals of 13
fish species and 4,039 individuals of 4 crustacean species were observed. Among the fish species,
dark chub Nipponocypris sieboldii was most abundant (351 individuals at 12 sites), followed byAmur goby Rhinogobius sp. (153 individuals at 10 sites). Among crustaceans, the number offreshwater shrimps Paratya compressa was largely abundant (3,630 individuals at 21 sites). Japanese
freshwater crab Geothelphusa dehaani, which is an indicator species for good water quality (Ministryof the Environment, 2017), was found at 15 sites (57.7%) with 211 individuals so water quality inthe study area was suggested to be relatively good. Among fish species, Japanese medaka Oryzias
sp. (59 individuals at 3 sites) and weather loach Misgurnus anguillicaudatus (14 individuals at 4
sites), which were listed as endangered species on the Red List 2020 (Ministry of the Environment,2020), were included.
Aquatic Habitat Evaluation
1) Fitness of the modelⒸ ISERD

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Based on the data of physical conditions and aquatic organisms, the EPFH was performed to evaluate
the habitat quality of the survey sites. As a result, the goodness-of-fit of the model F was 0.80 forfish and 0.74 for crustaceans (Table 2). The correlation between the model score and ShannonWiener's diversity index H' showed a strong correlation for fish (r = 0.63, p < 0.01). On the other
hand, no significant correlation was detected for crustaceans (r = 0.37, p = 0.90). This is thought tobe that the extremely large number of freshwater shrimps compared to other crustacean species
skewed the results of the analysis, resulting in a low correlation with Shannon-Wiener's diversity
index H', which takes into account the evenness of the number of individuals of each species.

Fig. 4 Boxplots of physical environmental conditions of survey sites by canal typea) canal width; b) water depth; c) water velocity; d) vegetation cover; and percentage of streambed
materials: e) concrete, f) sand and silt, g) small gravel and large gravel. Crosses in each figure indicate
the average value.

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The goodness-of-fit of the model in this study was higher than that of the previous study (0.71,
Watabe et al., 2018), which supports that the EPFH applies to waterway networks containing
different canal types such as size, structure, and role for irrigation. On the other hand, though thegoodness-of-fit of the model for crustaceans was not low, the correlation with Shannon-Wiener's
diversity index was weak. Thus, the model score as an indicator of habitat quality might be usefulfor habitat evaluation for this taxon.
Table 1 Results of biological survey (fish and crustaceans)
Taxon

Number ofindividuals

SpeciesFish

Nipponocypris sieboldii
Rhynchocypris lagowskii
steindachneri
Oryzias sp.
Rhinogobius sp.
Cobitis sp. BIWAE type B
Odontobutis obscura
Opsariichthys platypus
Plecoglossus altivelis
Misgurnus anguillicaudatus
Nipponocypris temminckii
Rhynchocypris oxycephalus jouyi
Pseudogobio esocinus
Tribolodon hakonensis
Crustaceans Geothelphusa dehaani
Procambarus clarkii
Paratya compressa
Palaemon paucidens

Observed sites

Standard length

Number Ratio (%)

Mean ± S.D. (cm)

351

12

46.2

5.8 ± 2.7

22

5

19.2

4.7 ± 1.8

59
153
1
3
22
24
14
3
1
3
1
211
163
3,630
35

3
10
1
3
3
7
4
2
1
1
1
15
10
21
7

11.5
38.5
3.8
11.5
11.5
26.9
15.4
7.7
3.8
3.8
3.8
57.7
38.5
80.8
26.9

2.5 ± 0.6
3.5 ± 0.7
7.0 ± 0.0
3.1 ± 1.1
5.9 ± 2.1
11.8 ± 1.3
8.0 ± 0.7
7.8 ± 2.3
4.7 ± 0.0
9.3 ± 1.5
9.7 ± 0.0
1.5 ± 0.6
5.8 ± 2.2
2.0 ± 0.4
4.3 ± 0.4

Table 2 Fitness of the EPFH model (fish and crustaceans)
Goodness of fit of the model F
calculated by EPFH

Correlation coefficient of the model andShannon-Wiener's diversity index H’

Fish

0.80

0.63**

Crustaceans

0.74

0.37

Significant difference is indicated by *p < 0.05, **p < 0.01, and ***p < 0.001, if detected

2) Environmental factors identified by the EPFH model
Based on the EPFH model for fish, five factors were identified as effective factors on fish habitat:water depth, water velocity, land width, vegetation cover, and percentage of sand in the streambed
material (Table 3). Four of the factors, except land width, had a positive effect on habitat. Thus, theresults indicated that good fish habitat had the following characteristics: (1) deeper water depth; (2)higher water velocity; (3) narrower land width; (4) higher vegetation cover; and (5) a greater
proportion of small gravel in the streambed material.
As effective environmental factors on crustacean habitat identified by the EPFH model, fivefactors were identified: water depth, water velocity, land width, vegetation cover, and percentage ofconcrete in the streambed material. Among these factors, only vegetation cover had a positive effecton crustacean habitat, while the other four factors had negative effects. Thus, the results indicatedthat good crustacean habitat had the following characteristics: (1) shallower water depth; (2) lower
water velocity; (3) narrower land width; (4) higher vegetation cover, and (5) a smaller proportion of
concrete in the streambed material.

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Table 3 Environmental factors and coefficients comprising the fish habitat model

Coefficients

Water depth

Watervelocity

Land width

Vegetation
cover

Streambed material(small gravel)

0.034

0.021

-0.018

0.014

0.02

Table 4 Environmental factors and coefficients comprising the crustacean habitat model

Coefficients

Water depth

Watervelocity

Land width

Vegetation
cover

Streambed material(concrete)-0.046-0.049-0.0050.022-0.015

3) Habitat score estimated by the model and its comparison by canal typeFigure 5 shows the habitat score for fish and crustaceans of each survey site, which was calculatedby the model. The score ranges from 1 to 5, with higher scores indicating better habitat at that site.
The site with a score of 5 for fish habitat was only No. 2 (Diversion Park), and the sites that scored
5 for crustacean habitat were No. 1 (Diversion Park) and No. 13 (Irrigation Canal A).
To examine differences in habitat quality among channel types, the mean habitat scores and themean Shannon-Wiener’s diversity index H’ are compared. Comparing the habitat scores, thediversion park was the highest (3.3 score), followed by the drainage canal (3.0 score), irrigation canal
A (1.9 score), and irrigation canal B (1.7 score) in order of highest to lowest (Table 5). As a result of
the Kruskal-Wallis’s test, significant differences were detected for the fish score (p < 0.01), while nosignificant differences were detected for crustaceans (p = 0.075). Multiple comparisons for fishmodel scores suggested the scores significantly differ between the diversion park and irrigation canal
A (p = 0.029, < 0.05, Table 6) and between the diversion park and irrigation canal B (p = 0.012, <0.05, Table 6). The drainage canal was not significantly different from irrigation canals A and B,
although the mean habitat score was high.

D.P.

I.C. A

D.C.

I.C. B

Fig. 5 Habitat score for fish and crustaceans at each survey site
D.P. indicates Diversion Park, D.C. indicates Drainage Canal,
I.C.A indicates Irrigation Canal A, and I.C.B indicates Irrigation Canal B.

Table 5 Habitat score and Shannon Weiner's diversity index H’ by canal type
Canal type
Diversion park

Fish
Habitat score(Mean ± S.D.)
3.3 ± 0.8

H
(Mean ± S.D.)'
1.2 ± 0.9

Crustaceans
Habitat score
H'(Mean ± S.D.)(Mean ± S.D.)
3.5 ± 1.4
0.8 ± 0.5

Drainage canal

3.0 ± 1.2

1.0 ± 0.6

3.8 ± 0.4

0.4 ± 0.4

Irrigation canal A

1.9 ± 0.8

0.3 ± 0.5

3.2 ± 1.0

0.3 ± 0.3

Irrigation canal B

1.7 ± 0.5

0.3 ± 0.6

2.7 ± 1.0

0.2 ± 0.5

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Table 6 Results of multiple comparisons using the Steel-Dwass method tofish habitat score
Combination of comparison
Drainage canalvsDiversion park
Drainage canalvsIrrigation canal A
Drainage canalvsIrrigation canal B
Diversion parkvsIrrigation canal A
Diversion parkvsIrrigation canal B
Irrigation canal AvsIrrigation canal B

t-value
0
1.796
1.896
2.772
3.052
0.523

p-value
1
0.275
0.230
0.029
0.012
0.954

The canals in the diversion park have the highest discharge among canal types. These canals arelocated upstream of the irrigation system and thus carry water before being diverted to canals A and
B. Thus, the conservation practice would benefit from ensuring such habitat property. In addition,
the environmental improvements in the canals of the diversion parks created habitat structure as
follows: the canal width was widened; gravel was laid on the canal ed; the slope of the revetment
was made gentler; and emergent plants were planted. Such habitat modification might support toconservation of functional habitat characteristics for fish such as higher vegetation cover (Nishida etal., 2011) and coverage of natural material on canal beds (Katano et al., 2003) among factors of fish
habitat characteristics. The average habitat score (and Shannon-Wiener index) of the diversion park
was higher than drainage canal, although the difference was not significant. Those environmental
modifications for recreation, such as gravel beds against concrete lying, may positively affect suchhigher habitat value. However, the higher scores in drainage canals might not be negligible becauseof their greater canal width, water depth, and vegetation cover.
On the other hand, high scores of crustaceans were found in shallow canals, though we did notconduct a detailed analysis per canal type because of the unconfident model score. Further, theirdistribution was tended to different from fish. Thus, branched irrigation canals might have habitat
value for crustaceans, and considering the effects of preservation of those canals as open canal andtheir availability for recreational use has remained a future challenge of this study.
CONCLUSION
The canals in diversion parks developed by environmental improvement had higher habitat value forfish. This habitat is characterized by the following conditions: (1) deeper water depth, (2) higher
water velocity, (3) greater vegetation cover, and (4) a higher proportion of gravel in the canal bed
material. Among these variables, canal bed materials in diversion parks were different from drainage
canals, though both canals have higher discharge in an agricultural waterway network (i.e. higher
availability for fish). Irrigation canals are generally modified into pipelines with the current
modernization of irrigation systems. Our result suggested that conserving and improving theenvironment of irrigation canals for recreation, particularly in water diversion canals, benefits
ensuring higher value of fish habitat. Therefore, our findings demonstrated a way to evaluate themulti-functionality of agricultural waterways from the aspect of recreational use and habitat
conservation as green infrastructure.
ACKNOWLEDGEMENTS
We would like to thank Yuta Shimizu and Sho Takayama for their generous cooperation in
conducting the analysis. Also, we would like to thank Takuto Fujimori, Seiya Aihara, and Masato
Kondo for their generous cooperation in conducting the survey. This study is supported by the Toyo
University Faculty of Science and Technology Policy Research 2020 and JSPS KAKENHI Grant
Number 18K05876.

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