Original Article Evaluation of River Water Quality with Multivariate Analysis in Clear Stream Watersheds in Agricultural Area

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1 doi: /jwet Journal of Water and Environment Technology, Vol.15, No.3: 86 95, 2017 Original Article Evaluation of River Water Quality with Multivariate Analysis in Clear Stream Watersheds in Agricultural Area Yuri Yamazaki a, Toshimi Muneoka b, Hiromu Okazawa c, Masato Kimura b, Osamu Tsuji b a The United Graduate School of Agricultural Sciences, Iwate University, Morioka, Japan b Obihiro University of Agriculture and Veterinary Medicine, Obihiro, Japan c Faculty of Regional Environmental Science, Tokyo University of Agriculture, Tokyo, Japan ABSTRACT We analysed the river water quality of Rekifune River and Satsunai River watersheds, which are evaluated as a clear stream in Tokachi region, Japan with the principal component analysis (PCA) and the cluster analysis to interpret complex water quality data and to evaluate factors affecting river water quality on the basis of a 2008 investigation. The mean ph was neutral and stable, also the mean BOD, SS and EC were relatively low. However, T-N concentrations tended to be high in Satsunai River watershed. The PCA and cluster analysis integrated the trend of water quality to two main components and classified the sampling points into three clusters. From the results, the river water quality of Satsunai River watershed was deteriorated by agricultural impacts, whereas the river water quality was preserved in Rekifune River watershed. Furthermore, three sampling points affected by the point source were classified in both river watersheds. It is necessary to develop a framework of agricultural impacts on Satsunai River watershed to improve the river water quality. An equally important priority is to control the loads from agriculture in some parts of Rekifune River watershed to maintain good water quality. Keywords: river water quality, agricultural area, principal component analysis, cluster analysis INTRODUCTION Pollution of rivers due to agricultural activities is a worldwide problem. In particular, water pollution caused by the outflow of excess nitrogen from an agricultural land has been widely reported [1]. Use of chemical fertilizers and livestock manure has improved crop yields; however, their excessive use causes eutrophication of rivers and lakes [2,3]. Studies on several watersheds have shown that nitrogen concentrations in river water are strongly correlated with the proportion of cropland [4,5]. Large-scale agriculture, such as cropland and dairy farming, is practiced in Hokkaido, Japan, and increases in nitrogen concentrations of river water in this region have been reported [6 9]. In contrast, the agricultural area of Tokachi region has popular clear streams. Rekifune and Satsunai Rivers were ranked at a high level in a river water quality survey by the Ministry of Land, Infrastructure, Transport, and Tourism and the Ministry of the Environment. According to a riparian zone census, valuable species such as Ranunculus nipponicus var. submerses, Accipiter nisus, and Andrias japonicus occur in Satsunai River. The beautiful waterfront space of the watersheds of these two rivers has been a prime recreational and relaxation area for citizens. A significant challenge will be to maintain and preserve these clear stream watersheds and their diversity. In contrast, the rivers ranked by public institutions have been evaluated for organic matter, particularly biochemical oxygen demand (BOD); thus, it is necessary to conduct a water quality assessment that can be practiced as an index of nutrient salts in Rekifune and Satsunai Rivers located in an agricultural area. Besides, it is necessary to interpret the current conditions of river water quality using multiple evaluation parameters rather than individual water quality Corresponding author: Toshimi Muneoka, muneoka@obihiro.ac.jp Received: June 23, 2016, Accepted: January 23, 2017, Published online: June 10, 2017 Copyright 2017 Japan Society on Water Environment 86

2 Journal of Water and Environment Technology, Vol. 15, No. 3, Fig. 1 Land use and sampling points of Satsunai River watershed and Rekifune River watershed. parameters, such as nutrients and organic matter. Multivariate analyses such as cluster and principal component analyses can be used to interpret complex river water quality data and to identify factors affecting river water pollution [10 12]. In this study, we evaluated river water quality and all water quality factors using multivariate analysis in clear stream watersheds at a large agricultural area to develop guidelines for preserving river environments. MATERIALS AND METHODS Study sites Figure 1 and Table 1 show the outline of the study sites.

3 88 Journal of Water and Environment Technology, Vol. 15, No. 3, 2017 Table 1 River name, bridge name, watershed area and proportion of land use of Rekifune River and Satsunai River watersheds. No. River name Bridge name Catchment area Proportion of land use [%] [km 2 ] Agriculture Forests Urban Satsunai River Watershed 1 Satsunai River Nijiohashi Satsunai River Kamisatsunaibashi Satsunai River Nakasatsunaibashi Satsunai River Nakajimashinbashi (East) Satsunai River Nakajimashinbashi (West) Satsunai River Taisyobashi Satsunai River Dai2okawabashi Satsunai River Nantaibashi Satsunai River Aikokubashi Satsunai River Seiryuohashi Satsunai River Satsunaibashi Nuppukusyunai River Dai1gobashi Irishima River (upper) Irishimabashi Irishima River (down) no name no name no name Masu River Mototaisyobashi Okene River Kasugabashi Nuppuke River Aikokuohashi Urikari River Minamibashi Obihiro River no name Totsutabetsu River Nakajimabashi Rekifune River watershed A Rekifune River Hikatabashi B Rekifune River Aikawabashi C Rekifune River Kamuiohashi D Rekifune River Taikibashi E Rekifune River Furusatoohashi F Rekifune River Rekifunebashi G Pankehikata River Mikagebashi H Nakano River Nakanoohashi I Nubinai River Nubinaibashi J Toyosato River Toyosatobashi K Peneketaiki River Penkebashi L Panketaiki River Pankebashi M Furibetsu River Akatsukibshi N Memu River Memubashi The study sites included the watersheds of Rekifune and Satsunai Rivers in Tokachi region located in East Hokkaido in the northern part of Japan. Rekifune River watershed consists of the main stream and approximately eight tributaries, whereas Satsunai River watershed consists of the main stream and approximately nine tributaries. Rekifune River and Satsunai River watersheds have similarities and differences. Both the watersheds were evaluated as a clear stream watershed in Japan. Rekifune River and Satsunai River watersheds obtain water from Hidaka Mountains while Salix

4 Journal of Water and Environment Technology, Vol. 15, No. 3, Fig. 2 Location of the sampling points of Satsunai River watershed and Rekifune River watershed: (a) Diagram; (b) The sampling points 4 and 5 are located on the same bridge (Nakajimashinbashi), one on the east side (no.4) and one on the west side (no.5). arbutifolia that can only be found in a limited area in the eastern Asia grow wild at the waterfront. The watersheds have similar areas and the land is mainly used for agriculture and forestry. The main agricultural land use in Satsunai River watershed is general farming for crops such as wheat, potato, sugar beet, and beans, which occupies 30% of the total area. Both chemical fertilizers and livestock manure (organic fertilizer) are applied to agricultural land to provide the required nutrients for crop growth. Basal fertilizer is applied from mid- to late April after snow melting and topdressing are performed in June to July, but fertilization management varies with the crop. Pasture and forage crops are produced in Rekifune River watershed, which occupies 17% of the total area. Basically, livestock manure (organic fertilizer) is applied and chemical fertilizers are added to cover shortfall for maintenance of pasture. Fertilizing period is mid- to late April, after the first cutting and second cutting. Satsunai River has a multipurpose dam with the aims of flood control, crop irrigation, and hydroelectric power generation. The mean annual air temperature and precipitation from 1981 to 2010, measured at Kamisatsunai (Satsunai River watershed) and Taiki (Rekifune River watershed) were 5.3 C and 5.4 C, 1,254.7 mm and 1,150.1 mm, respectively. The mean annual air temperatures in 2008 when the investigation was conducted were 5.4 C and 5.5 C for Satsunai River and Rekifune River watersheds, respectively, which were comparable to the normal values. However, the annual precipitation (771.5 and mm, respectively) was less than the normal value in both watersheds. Water quality investigation Fourteen and 21 sampling points were selected in Rekifune River and Satsunai River watersheds, respectively; these points were monitored once per month in June, September, and November 2008 during normal water levels (Figs. 1, 2 and Table 1). The sampling points were located on the main stream (A F for Rekifune River and nos for Satsunai River) and downstream of each tributary (G N for Rekifune River and nos for Satsunai River). The sampling points nos. 4 and 5 of Satsunai River watershed were located on the same bridge (Nakajimashinbashi), one on the east side (no.4) and the other on the west side (no.5) (Fig. 2 (b)). The sampling points nos. 4 and 5 were set to investigate the impact of the tributary (Irishima River; nos. 14 and 13) which flow into the main stream at the upper east of Nakajimashinbashi (nos. 4 and 5). The sampling points nos. 13 and 14 were upper (no.13) and lower (no.14) parts of Irishima River. A total of 42 and 63 samples were collected from Rekifune River and Satsunai River watersheds, respectively. Electrical conductivity (EC) and water temperature were measured using a digital conductivity meter (DKK TOA Corporation; ; Japan). We analyzed the following chemical parameters: total nitrogen (T-N), nitrate (NO 3 - N), nitrite (NO 2 -N), ammonium (NH 4 -N), total phosphorus

5 90 Journal of Water and Environment Technology, Vol. 15, No. 3, 2017 Table 2 Mean values of ph, BOD, SS, EC, T-N, NO 3 -N, NO 2 -N, NH 4 -N, T-P and PO 4 -P of Rekifune River and Satsunai River watersheds. Sampling points ph BOD SS EC T-N NO 3 -N NO 2 -N NH 4 -N T-P PO 4 -P Satsunai River Rekifune River A B C D E F G H I J K L M N (T-P), phosphate (PO 4 -P), BOD, suspended solids (SS), and potential hydrogen (ph). Multivariate analysis We used the R package (R Foundation for Statistical Computing; Ver.3.0.3; Austria) for cluster and principal component analyses. The proportion of agricultural land, the

6 Journal of Water and Environment Technology, Vol. 15, No. 3, proportion of forest land (Table 1) and the average value of each water quality parameter (Table 2) was used as a variable. Cluster analysis and principal component analysis are a group of multivariate techniques. We have applied Ward s method to cluster analysis. Principal component analysis was used as the function princomp of the R package. Table 3 Loadings of the principal component 1 (PC1) and the principal component 2 (PC2). RESULTS AND DISCUSSION Evaluation of river water quality of Rekifune River and Satsunai River watersheds Table 2 shows the mean values of ph, BOD, SS, EC, T-N, NO 3 -N, NO 2 -N, NH 4 -N, T-P and PO 4 -P in Rekifune and Satsunai River watersheds. Mean ph values of each sampling point in Rekifune and Satsunai River watersheds were in the ranges of The river water qualities of both watersheds were neutral and stable during the observation periods. More than half of the sampling points of Rekifune River and Satsunai River watersheds showed low BOD concentration with 1.0 mg/l or lower. Mean SS values of all sampling points of both watersheds were 15 mg/l or lower. Mean EC values of more than half of sampling points of both watersheds were 10 ms/m or lower, however, the EC values of the tributaries in downstream of Rekifune River watershed and the tributaries in middle and downstream of Satsunai River watershed tended to increase. Also, two sampling points of Satsunai River watershed showed significant high values of BOD and EC compared to other sampling points. Mean BOD, SS and EC values of Rekifune River watershed showed lower than the values of Satsunai River watershed. The nitrogenous constituents of Rekifune and Satsunai River watersheds were inorganic nitrogen of 71% and 86%, respectively. NO 3 -N constituted the major portion of the T-N and the NO 2 -N and NH 4 -N were contained in small amounts. However, only two sampling points in Satsunai River watershed were confirmed with increasing trend of NO 2 -N and NH 4 -N concentrations. The mean T-N concentrations of Rekifune and Satsunai River watersheds were 1.3 mg/l and 4.2 mg/l, respectively. The mean T-N concentration of Satsunai River watershed showed a higher value than the value of Rekifune River watershed. In Rekifune River watershed, 11 of 14 sampling points showed the T-N concentrations of 1.0 mg/l or lower. Meanwhile, the T-N concentrations of Satsunai River watershed varied among the sampling points and showed a maximum value of 20 mg/l. The phosphorous constituents of Rekifune River and Satsunai River watersheds were 90% PO 4 -P or higher. T-P *proportion of agricultural land; **: proportion of forestland concentrations of both watersheds were low under base flow condition. Unlike other sampling points, only two sampling points of Satsunai River watershed showed high T-P concentration. Principal component analysis of the river water quality Principal component analysis (PCA) was conducted using the correlation matrix. We used the standardized data of the proportion of agricultural land, the proportion of forest land, mean NO 3 -N, NO 2 -N, NH 4 -N, PO 4 -P, BOD, SS, EC and ph values of each sampling points in the Rekifune and the Satsunai River watersheds as variables. T-N and T-P were excluded from the PCA analysis because T-N and T-P had a very strong correlation with NO 3 -N and PO 4 -P. Table 3 shows the factor loadings of principal components. The cumulative proportion was 85.9% for principal component 1 (PC1) to principal component 2 (PC2) to explain the characteristics of the river water quality in Rekifune River and Satsunai River watersheds by the 2 main components. From the factor loadings, PC1 had positive values for variables without the proportion of forestland and represents the extent of water pollution by all variables. Thus, when PC1

7 92 Journal of Water and Environment Technology, Vol. 15, No. 3, 2017 Fig. 3 Results of cluster analysis. We divided the data based on the Euclidean distance of ten: Blue numbers are Cluster 1, orange numbers are Cluster 2, and pink numbers are Cluster 3. was positive, concentrations of comprehensive water quality were high (river water quality was deteriorated), when PC1 was negative, concentrations of comprehensive water quality were low (river water quality was good). PC2 showed positive values of the proportion of agricultural land, NO 3 -N, SS and EC, but negative values of the proportion of forestland, NO 2 -N, NH 4 -N, PO 4 -P, BOD and ph. Therefore, PC2 has interpreted the type of external factor for water pollution. Since both the proportion of agricultural land and NO 3 -N showed positive PC2, this indicated the impact of agricultural activities especially fertilization. Classification of the characteristics of river water quality by cluster analysis Cluster analysis was conducted to detect similarities between the river water qualities of sampling points. We used the scores of PC1 and PC2 for the cluster analysis. Euclidean distance was used for calculating the distances of the data. Also, Ward s method was applied. The result of the cluster was divided into three clusters based on the Euclidean distance of ten (Fig. 3). Figure 4 shows the relationship between the score of PC1 and PC2 classified by three clusters. First, Cluster 1 contained eleven sampling points of Rekifune River watershed and twelve sampling points of Satsunai River watershed and showed negative PC1 and PC2 or approximately 0 of PC1 and PC2, respectively. Cluster 1 was estimated that the sampling points had good water quality owing to small external factor such as agricultural activities. Also, the sampling points of Cluster 1 have a high proportion of forestland (61 99%). Cluster 2 contained three sampling points of Rekifune River watershed and seven sampling points of Satsunai River watershed. PC1 showed approximately 0, and PC2 was positive. Only the sampling point M showed negative PC2. The river water quality deteriorated slightly when compared with Cluster 1, and also the effect of some agricultural activities was considered because Cluster 2 showed negative PC2 and has high proportion of agricultural land (47 91%). Finally, Cluster 3 showed a different trend from other clusters. Cluster 3 contained two sampling points of Satsunai River watershed. Comprehensive water quality deteriorated seriously because PC1 showed large positive values. However,

8 Journal of Water and Environment Technology, Vol. 15, No. 3, Fig. 4 Relationship between PC1 score and PC2 score of Cluster 1, Cluster 2 and Cluster 3 (a); relationship between PC1 and PC2 score of Satsunai River watershed and Rekifune River watershed (b). PC2 showed negative. It was highly possible that there were point sources such as industrial wastewater in Satsunai River watershed. As for the result of PCA by each watershed (Fig.4 (b)), twelve of fourteen sampling points of Rekifune River watershed were classified into Cluster 1 and evaluated that the river water quality was comprehensively good. It was considered that the river water quality is kept good because Rekifune River watershed has large forest area. However, the sampling points M, J and N of the tributaries in Rekifune River were classified into Cluster 2 and were suspected of deterioration of river water quality. High nitrogen concentration in the river water was a characteristic of the sampling points J and N. Also, the sampling points J and N have a high proportion of agricultural land (99% and 77%, respectively). Thus, the river water quality of the sampling points J and N were considered deteriorated by the agricultural load in the watershed. However, the sampling point M has negative PC2 and a low proportion of agricultural land. High PO 4 -P concentration and EC were characteristics of the sampling point M. The PC1 score was highest in Cluster 2 and PC2 score was 0.45 in the sampling point M. The river water quality of the sampling point M tended to deteriorate just like other sampling points of Cluster 2, but the source of pollution was different. It was considered that human sewage contributed to the water quality deterioration of the sampling point M. The river water qualities of the main stream of Satsunai River watershed were comprehensively good. However, the tributaries tended to deteriorate in comparison with Rekifune River watershed and the main stream of Satsunai River watershed since 7 of 21 sampling points were classified into Cluster 2. High nitrogen concentration was a characteristic of the sampling points nos Also, PC2 scores of seven sampling points showed positive values. These sampling points have a high proportion of agricultural land (47 91%). From these, the water quality deterioration of Satsunai River watershed was caused by agricultural activities. It was considered that runoff of fertilizer component into the agricultural land affects the water quality of Satsunai River strongly because there is a large agricultural land in the watershed. The sampling points nos. 4 and 14 had a high PC1 score and were classified into Cluster 3. It was inferred that the source of water pollution of the sampling points nos. 4 and 14 was different from other sampling points in Satsunai River watershed because the PC1 scores were markedly high. First, the trend of the river water quality of the sampling point no. 4 was different from no. 5, which was located on the west side of the same bridge as no. 4. Also, the water quality tended to be different from upper (no.3) and lower (no.6) in no.4. Thus, the river water quality of no.4 was affected by no.14. Sampling point no. 14 was a tributary of Satsunai River and flowed in just below no.4 in the mainstream. All water quality indices of nos.14 and 4 tended to increase; also the ph values were slightly high. Thus, contaminant input, such as industrial waste, was considered for no.14. In addition, the river water quality of no.13, which was located at the upper stream of the same tributary of no.14, showed different trend and was classified into Cluster 2. From this, it is regarded that there is a point source between nos. 13 and 14. Identify-

9 94 Journal of Water and Environment Technology, Vol. 15, No. 3, 2017 ing the point source and preventing the contaminant input in no.14 are the urgent tasks in Satsunai River watershed. CONCLUSIONS We evaluated the river water quality of Rekifune River and Satsunai River watersheds in Tokachi region, Japan with multivariate analysis. The river water qualities of Rekifune River and Satsunai River watersheds were maintained neutral with a mean ph of around 7.0, and showed comparatively low concentration of BOD, SS and EC. However, the T-N concentration of Satsunai River watershed tended to a high level, 71 86% of the T-N in the river water was composed of inorganic nitrogen. While the T-N concentrations of Rekifune River watershed showed a low concentration of 1.0 mg/l or lower, the T-N concentration of Satsunai River watershed varied between the sampling points, and showed a maximum concentration of 20 mg/l. From the results of PCA and cluster analysis with each water quality parameter, the river water qualities of Rekifune and Satsunai River watershed were classified into three clusters. While Rekifune River watershed was evaluated that the river water quality is kept well, only three sampling points of the tributaries of Rekifune River watershed confirmed that the river water qualities deteriorated under the influence of drainage water from the agricultural land and the urban area. Compared with Rekifune River watershed, the river water quality of Satsunai River watershed was comprehensively deteriorating. In particular, the tributaries of Satsunai River watershed suggested strong impacts from the agricultural loads. However, a different trend of the river water quality for the two sampling points of Satsunai River watershed was confirmed. The PCA score showed that there was a point source such as industrial waste in Satsunai River watershed. ACKNOWLEDGEMENTS This research was supported by JSPS KAKENHI, Grant Number 15J04743, The authors would like to express their gratitude to the students of Obihiro University of Agriculture and Veterinary Medicine for their assistance. REFERENCES [1] Carpenter S, Caraco NF, Correll DL, Howarth RW, Sharpley AN, Smith VH: Non-point pollution of surface waters with phosphorus and nitrogen. Ecol. Appl., 8(3), , doi: / (1998)008[0559:nposww]2.0.co;2 [2] Hantschel RE, Beese F: Site-oriented ecosystem management precondition to reducing the contamination of waters and the atmosphere. In: Rosen D, Tel-Or E, Hadar Y, and Chen Y (eds.): Modern Agriculture and the Environment. Springer Netherlands, Dordrecht, Netherlands, pp , [3] Van Drecht G, Bouwman AF, Knoop JM, Beusen AHW, Meinardi CR: Global modeling of the fate of nitrogen from point and nonpoint sources in soils, groundwater and surface water. Global Biogeochem. Cycles, 17(4), , doi: /2003gb [4] McFarland AMS, Hauck LM: Relating agricultural land uses to in-stream stormwater quality. J. Environ. Qual., 28, , doi: / jeq x [5] Tabuchi T, Yoshino K, Shimura M, Kuroda S, Ishikawa M, Yamaji E: Relation between land use and nitrate concentration of outflow water from watersheds of agricultural and forest areas. Trans. Jpn. Soc. Irrig. Drain. Reclam. Eng., 178, , [in Japanese with English abstract] [6] Nagumo T, Hatano R: Impact of nitrogen cycling associated with production and consumption of food on nitrogen pollution of stream water. Soil Sci. Plant Nutr., 46, , [7] Woli KP, Nagumo T, Hatano R: Magnitude of nitrogen pollution in stream water due to intensive livestock farming practices. Soil Sci. Plant Nutr., 48, , doi: / [8] Woli KP, Nagumo T, Kuramochi K, Hatano R: Evaluating river water quality through land use analysis and N budget approaches in livestock farming areas. Sci. Total Environ., 329(1-3), 61 74, PMID: , doi: /j.scitotenv [9] Yamazaki Y, Muneoka T, Wakou S, Shimura M, Yoshino K, Tsuji O, Tabuchi T: The difference of agricultural land use in watersheds and long term fluctuation on the river water quality. International Journal of Environmental and Rural Development, 4(1), , [10] Vega M, Pandro R, Barrado E, Deban L: Assessment of seasonal and polluting effects on the quality of river water by exploratory data analysis. Water Res., 32, , doi: /s (98) [11] Shimenov V, Shimenova P, Tsitouridou R: Chemometric quality assessment of surface waters: two case

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