Spatiotemporal Variations Of Water Quality Research Articles

Temporal and depth variation of water quality due to thermal stratification in Karkheh Reservoir, Iran

Study regionKarkheh Dam Reservoir (KDR) located in western Iran. Study focusTo date, there has been no research in the KDR that investigates the interconnections among thermal stratification (ThS), water quality, and nutrients, based on field measurements. This study explored the temporal trend of ThS in the KDR and its interrelationship with water quality parameters based on data measured from 2005–2006. New hydrological insights for the regionThe results showed that a noticeable ThS in the KDR starts in late April and continues until early December. The strongest ThS occurs during late summer when the water temperature difference between the surface and bottom layers in the reservoir exceeds 18 °C. As a result of external forces that generally intensify in December, vertical water circulation occurs, and by January and February there is a minimal temperature gradient between the surface and bottom layers. During ThS, dissolved oxygen (DO) is strongly confined by the metalimnion and does not penetrate into the hypolimnion. However, even during late December to February, there is a large difference between DO concentration in the surface and bottom layers, which indicates limited mixing. Ammonium increasing and nitrate decreasing with depth was observed, likely due to denitrification (in the bottom layers) and nitrification (in the surface layers), respectively. The results of the present study provide new information on the spatio-temporal variation of water quality in large reservoirs, which is important for stakeholders with concerns related to lake and reservoir eutrophication and water quality issues.

Spatio-temporal Variations of Diatom Community and Their Relationship with Water Environment in Fuxian Lake

Fuxian Lake is an important deep lake in China with trophic status generally categorized as class I. However, there exists a trend of degradation in its ecological and environmental health under the increasing impacts derived from catchment development and recent global warming. Therefore, it is important to evaluate the community composition, distribution patterns, and driving factors of lake biota. In order to uncover the spatio-temporal variations in water quality and diatom communities, a monthly survey of diatom community composition and limnological characteristics was carried out in the surface waters of three sampling sites from the south, middle, and north of the lake basin in Fuxian in 2015. A total of 166 diatom species belonging to 31 genera were identified, which was dominated by planktonic diatoms with the extirpation of Cyclotella rhomboideo-elliptica, an endemic species for Yunnan. Diatom community structure showed significant seasonal succession across the three sites, which were dominated by Fragilaria crotonensis in January and February, by Aulacoseira granulata in March, by Cyclotella ocellata and F. crotonensis in April, and by C. ocellata for other months (i.e., relative abundance of ~80%). Over the spatial scale, the distribution of the dominant diatoms displayed a high degree of similarity. Principal component analysis further showed that there existed significant difference in the diatom community structure and lake environment over the temporal scale, but no significant deviance was found across the three sites. The results of redundancy analysis and variation partitioning revealed that the key driver included meteorological and physical factors (i.e., water temperature, wind velocity, and Secchi depth), which accounted for 27.6% of the total variance in diatom community changes. In combination with the thermocline analysis, the change in lake hydrodynamics may have influenced the thickness and duration of the thermal stratification of lake water, resulting in the reorganization of the diatom community. At the same time, the lake-water nutrients and ions also exerted an important influence on community structuring, which explained the 21.2% and 9.4% of the diatom variation, respectively. Therefore, regional warming and catchment development have significantly structured the biological community and ecosystem health of Fuxian Lake. In all, measures should be taken not only to control the watershed input of pollutants but also to actively mitigate the long-term impact of climate change for the protection and ecological remediation of Fuxian Lake.

Spatio-temporal variation of water quality and bio indicators of the Badulu Oya in Sri Lanka due to catchment disturbances

Safe and ample supply of freshwater is fundamental to humans and for the sustainability of ecosystem function. Therefore, impacts of catchment disturbances on surface water quality have been given special attention currently. The Badulu Oya sub-catchment of the Upper Mahaweli catchment area in Sri Lanka is one of the landscapes affected by intensive agricultural activities and urban development. This study was aimed at evaluating the spatial and temporal variation of water quality, stream physical habitat quality and macroinvertebrate bioindicators in the Badulu Oya catchment area in relation to disturbances due to agricultural and urban practices. Physicochemical water quality parameters and macroinvertebrate indices were evaluated at ten sampling sites in the Badulu Oya catchment area within a one year period. The results revealed that water quality variables such as electrical conductivity (EC), total solids (TS), total dissolved solids (TDS), dissolved oxygen (DO), alkalinity, nitrate-N(NO3-N) and physical variables such as stream channel quality index (CQI) and riparian quality index (RQI) are significantly influenced by the degree of catchment disturbances. Among the macroinvertebrate indices tested, total abundance and family richness significantly varied with the degree of catchment disturbances. The findings of the present study revealed that the land use practices of Badulu Oya catchment result in significant impacts on stream ecological health. Similarly the study also revealed the prospect of using attributes such as water quality, physical habitat quality and macroinvertebrate bioindices for river health monitoring programmes.

Seasonal and spatial variation of reservoir water quality in the southwest of Ethiopia.

This research investigated the spatiotemporal variation of water quality in the Gilgel Gibe reservoir, Ethiopia, using physicochemical water quality parameters. Nonparametric tests and multivariate statistical techniques were used to evaluate data sets measured during dry and rainy seasons. Electrical conductivity (EC), pH, biochemical oxygen demand (BOD5), total phosphorus (TP), total nitrogen (TN), nitrate (NO3-), total dissolved solids (TDSs), and total suspended solids (TSSs) were all significantly different among seasons (Mann-Whitney U test, p < 0.01). In addition, principal component analysis distinguished dry season samples from wet season samples. The dry season was positively associated with EC, pH, TP, TN, NO3-, TDS, and TSS and negatively associated with BOD5. The wet season was in contrast associated with high values of turbidity, soluble reactive phosphorus (SRP), water temperature, and dissolved oxygen (DO). Within the reservoir, spatial variation was observed for some of the water quality parameters, with significant difference at p = < 0.05. Overall, high nutrient concentrations suggest eutrophic conditions, likely due to high nutrient loading from the watershed. Levels of TSS, attributed to inputs from tributaries, have been excessive enough to inhibit light penetration and thus have a considerable impact on the aquatic food web. Our findings indicate that the reservoir is at high risk of eutrophication and siltation, and hence, urgent action should target the planning and implementation of integrated watershed management for this and similar reservoirs in the region.

Spatio-temporal variations of water quality in Nova Ponte Reservoir, Araguari River Basin, Brazil

Multivariate techniques, like cluster analysis (CA) and principal component analysis (PCA), were used to evaluate the spatial and temporal variability of surface water quality in a large neotropical hydroelectric reservoir (Nova Ponte Reservoir). The dataset, obtained during the period of 1995–2011 from the Energy Company of Minas Gerais State (CEMIG), contains 14 parameters surveyed quarterly in 14 sites, at different depths. The CA grouped the 14 sites in three main groups: lotic sites, half of the photic zone sites and bottom sites. Statistical tests showed that only three parameters (total dissolved solids, nitrate and chemical oxygen demand) have no significant difference between cluster groups. The PCA results showed temporal changes of the water quality in all groups, illustrating modifications to the importance of the parameters over time. PCA also revealed the major causes of water deterioration from 1995 to 2005 were related to agricultural and livestock activities. Currently, the water quality parameters related to organic pollution are also highlighted. Generally, this study shows that possible optimization of the monitoring network should consider temporal variation of water quality parameters.

Assessment of Spatio-Temporal Variations in Water Quality of Shailmari River, Khulna (Bangladesh) Using Multivariate Statistical Techniques

Surface water has become one of the most vulnerable resources on the earth due to deterioration of its quality from diverse sources of pollution. Understanding of the spatiotemporal distribution of pollutants and identification of the sources in the river systems is a prerequisite for the protection and sustainable utilization of the water resources. Multivariate statistical techniques such as Principal Component Analysis (PCA) and Factor Analysis (FA) were applied in this study to investigate the temporal and spatial variations of water quality and appoint the major factors of pollution in the Shailmari River system. Water quality data for 14 physicochemical parameters from 11 monitoring sites over the year of 2014 in three sampling seasons were collected and analyzed for this study. Kruskal-Wallis test showed significant (p < 0.01) temporal and spatial variations in all of the water quality parameters of the river water. Principal component analysis (PCA) allowed extracting the contributing parameters affecting the seasonal water quality in the river system. Scatter plots of the PCs showed the tidal and spatial variation within river system and identified parameters controlling the behavior in each case. Factor analysis (FA) further reduced the data and extracted factors which are significantly responsible for water quality variation in the river. The results indicate that the parameters controlling the water quality in different seasons are related with salinity, anthropogenic pollution (sewage disposal, effluents) and agricultural runoff in pre-monsoon; precipitation induced surface runoff in monsoon; and erosion, oxidation or organic pollution (point and non-point sources) in post-monsoon. Therefore, the study reveals the applicability and usefulness of the multivariate statistical methods in assessing water quality of river by identifying the potential environmental factors controlling the water quality in different seasons which might help to better understand, monitor and manage the quality of the water resources.

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China

Water quality forecasting is an essential part of water resource management. Spatiotemporal variations of water quality and their inherent constraints make it very complex. This study explored a data-based method for short-term water quality forecasting. Prediction of water quality indicators including dissolved oxygen, chemical oxygen demand by KMnO4 and ammonia nitrogen using support vector machine was taken as inputs of the particle swarm algorithm based optimal wavelet neural network to forecast the whole status index of water quality. Gubeikou monitoring section of Miyun reservoir in Beijing, China was taken as the study case to examine effectiveness of this approach. The experiment results also revealed that the proposed model has advantages of stability and time reduction in comparison with other data-driven models including traditional BP neural network model, wavelet neural network model and Gradient Boosting Decision Tree model. It can be used as an effective approach to perform short-term comprehensive water quality prediction.

Characterizing and explaining spatio-temporal variation of water quality in a highly disturbed river by multi-statistical techniques.

Assessing the spatio-temporal variations of surface water quality is important for water environment management. In this study, surface water samples are collected from 2008 to 2015 at 17 stations in the Ying River basin in China. The two pollutants i.e. chemical oxygen demand (COD) and ammonia nitrogen (NH3-N) are analyzed to characterize the river water quality. Cluster analysis and the seasonal Kendall test are used to detect the seasonal and inter-annual variations in the dataset, while the Moran’s index is utilized to understand the spatial autocorrelation of the variables. The influence of natural factors such as hydrological regime, water temperature and etc., and anthropogenic activities with respect to land use and pollutant load are considered as driving factors to understand the water quality evolution. The results of cluster analysis present three groups according to the similarity in seasonal pattern of water quality. The trend analysis indicates an improvement in water quality during the dry seasons at most of the stations. Further, the spatial autocorrelation of water quality shows great difference between the dry and wet seasons due to sluices and dams regulation and local nonpoint source pollution. The seasonal variation in water quality is found associated with the climatic factors (hydrological and biochemical processes) and flow regulation. The analysis of land use indicates a good explanation for spatial distribution and seasonality of COD at the sub-catchment scale. Our results suggest that an integrated water quality measures including city sewage treatment, agricultural diffuse pollution control as well as joint scientific operations of river projects is needed for an effective water quality management in the Ying River basin.

Evaluation of the physicochemical and chlorophyll-a conditions of a subtropical aquaculture in Lake Nasser area, Egypt

Water quality, nutritional characteristics and phytoplankton biomass in aquaculture of Oreochromis niloticus (L.) simultaneously with its water source supply (Lake Nasser), were monthly investigated over a one-year period (July 2009–2010). Analysis of the results showed that application of fertilizers and environmental conditions appeared to be the principal factors influencing the spatio-temporal variations of water quality and productivity. The data obtained revealed differences between the fish pond and its water supply. Monthly fluctuations in the availability of the major nutrients reflected the occasional supply of the fish pond with different nutrients. Phytoplankton biomass in terms of chlorophyll-a concentrations were always of relatively higher values in the fish pond than those in Lake Nasser's water. Elevation of pH values and dissolved oxygen saturation levels appeared concomitantly with the increase of chlorophyll-a concentrations due to the phytoplankton photosynthetic assimilation activities. The observations of the present study highlighted the chlorophyll-a concentrations as an indicator of phytoplankton biomass reflecting water quality in the Nile tilapia aquaculture ecosystem.

Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China

Fuzzy comprehensive assessment and multivariate statistical techniques including cluster analysis, discriminant analysis, principal component analysis, and factor analysis were applied to analyze the water quality status of Yuqiao Reservoir Basin, North China, for assessing its spatio-temporal variations and identifying potential pollution sources. In this paper, we considered data for 14 water quality parameters collected during 1990–2004 at 7 water quality monitoring sites. The results of fuzzy comprehensive assessment revealed that water quality in Yuqiao Reservoir Basin showed a downtrend from 1990 to 2001 with fluctuation, and a slowly upward trend after 2001. The major water quality belonged to Class III and IV. Besides, hierarchical cluster analysis divided 7 monitoring sites into two groups (Group A and B), and 12 months into three periods (low-flow (LF), normal-flow (NF), and high-flow (HF) period). Temp, pH, SS, T-har, DO, NO3-N and TP were identified as significant variables affecting spatial variations, and Temp, pH and NO2-N were identified as significant variables affecting temporal variations by discriminant analysis. Factor analysis identified four latent pollution sources for water quality variations: nutrient pollution, organic pollution, inorganic pollution, and natural pollution. Moreover, for Group A regions, pollution inputs mainly came from domestic wastewater and industrial sewage. For Group B regions, it is more likely that water pollution resulted from the combined effects of domestic wastewater, hospital wastewater, agriculture runoff, and fishpond discharge, as well as the incoming water from upstream.

Characterization and evaluation of hydrological processes responsible for spatiotemporal variation of surface water quality at Narmada estuarine region in Gujarat, India

This study is an effort to trace the spatiotemporal variation in water at Narmada estuarine region through solute concentration. A total of 72 water samples were collected and analyzed from three sampling points along with in situ measurement of tidal height at monthly basis for 2 years. Result shows that spatiotemporal variation of water quality occurs because of the following main mechanisms, i.e., carbonate weathering, dilution and seawater–freshwater mixing. Firstly, points situated toward inland showing the simple dilution effect on receiving high amount of monsoonal precipitation. Secondly, tidal fluctuation pattern has a strong influence on the water quality taken from the point located in near proximity to the coast. Finally, it can be concluded that water quality shows a different response, in accordance with the different tidal phase and the distance from the sea.

Spatial and seasonal characteristics of river water chemistry in the Taizi River in Northeast China

Anthropogenic activities have led to water quality deterioration in many parts of the world, especially in Northeast China. The current work investigated the spatiotemporal variations of water quality in the Taizi River by multivariate statistical analysis of data from the 67 sampling sites in the mainstream and major tributaries of the river during dry and rainy seasons. One-way analysis of variance indicated that the 20 measured variables (except pH, 5-day biological oxygen demand, permanganate index, and chloride, orthophosphate, and total phosphorus concentrations) showed significant seasonal (p ≤ 0.05) and spatial (p < 0.05) variations among the mainstream and major tributaries of the river. Hierarchical cluster analysis of data from the different seasons classified the mainstream and tributaries of the river into three clusters, namely, less, moderately, and highly polluted clusters. Factor analysis extracted five factors from data in the different seasons, which accounted for the high percentage of the total variance and reflected the integrated characteristics of water chemistry, organic pollution, phosphorous pollution, denitrification effect, and nitrogen pollution. The results indicate that river pollution in Northeast China was mainly from natural and/or anthropogenic sources, e.g., rainfall, domestic wastewater, agricultural runoff, and industrial discharge.

Spatiotemporal variation of surface water quality for decades: a case study of Huai River System, China

Characterization of spatiotemporal variation of water quality is a basic environmental issue with implications for public health in China. Trends in the temporal and spatial distribution of water quality in the Huai River System (HRS) were analyzed using yearly surface water quality data collected from 1982 to 2009. Results showed that the water quality of the main stream deteriorated in the 1990s and early 2000s but has been ameliorated since 2005. The sections that were classified as severely polluted from the monitoring data were located largely in the middle reach. The water quality of HRS fluctuated during the period 1997-2009; it has improved and stabilized since 2005. In terms of spatialized frequency of serious pollution, heavily polluted regions were mostly concentrated in the area along several tributaries of the Ying, Guo and New Sui Rivers as well as the area north of Nansi Lake. These regions decreased from 1997 to 2009, especially after 2005. Our analysis indicated that water pollution in HRS had a close relation with population and primary industry during the period 1997-2009, and implied that spatiotemporal variation of surface water quality could provide a scientific foundation for human health risk assessment of the Huai River Basin.

Spatio-temporal Water Quality Variations at Various Streams of Han-River Watershed and Empirical Models of Serial Impoundment Reservoirs

Spatio-temporal Water Quality Variations at Various Streams of Han-River Watershed and Empirical Models of Serial Impoundment Reservoirs

Assessment of spatio-temporal variations in surface water quality of Ghaggar River (North-Western, India) utilized for drinking and agricultural purposes

In the present study, statistical analyses (descriptive and principal component analysis) were applied to Ghaggar River surface water data set monitored in the month of June 2006 and 2007 to check spatio-temporal variations in water quality. From these, two summer observations were taken into consideration because in summer season, high concentrations are observed for different water constituents. The various physico-chemical constituents like pH, total dissolved solids (TDS), electrical conductivity (EC), temperature, Cl - , HCO 3 - , CO 3 2- , Na + , K + , Ca 2+ , Mg 2+ , F - , SO 4 2- and PO 4 3- were analyzed. Statistical results revealed that water quality variables were totally different during the two summer observations. Keywords : Principal component analysis, spatio-temporal variations, water quality, summer season.

Evaluation of spatial and temporal variation in stream water quality by multivariate statistical techniques: A case study of the Xiangxi River basin, China

The analysis and interpretation the spatiotemporal patterns of river water quality are a critical element in the assessment, restoration, and protection of local and region water quality. In this case study, multivariate statistical techniques, including cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA), had been integrated to evaluate and interpret spatiotemporal variations of water quality in Xiangxi River, with a 5-years (2002-2006) continual monitoring data (14 parameters at 12 sites). Hierarchical cluster analysis revealed all sites could be grouped into three clusters representing different levels of pollution: relatively less polluted upper catchments sites (US), medium polluted Middle catchments sites (MS), and highly polluted lower catchments sites (LS). Factor analysis/principal component analysis was used to explore the most important factors determining the spatiotemporal dynamics of water quality in Xiangxi River. Varifactors obtained from the factor analysis indicated the parameters responsible for water quality variation were mainly related to soluble salts (natural), point source pollution of phosphorus and non-point pollution of nitrogen (anthropogenic). Discriminant analysis provided an important data reduction as it uses six parameters (TN. Si0(2), hardness, Ca2+, WT and pH), affording 70.5% correct assignations in temporal analysis, and two parameters (NO3-N and Alk), affording 55.9% correct assignations in spatial analysis, of three different regions in the basin. The low correct assignation in spatial analysis was related to the anthropogenic influence. This study suggested that multivariate statistical techniques are useful tools for identification of important water quality monitoring sites parameters and design of a monitoring network for the effective management of water resources. (C) 2012 Elsevier Ltd and INQUA. All rights reserved.

Spatio-Temporal Variations in Water Quality of the Chao Phraya River, Thailand, between 1991 and 2008

Spatio-temporal variations in the water quality of the Chao Phraya River, Thailand, were examined, on average-yearly basis, between 1999 and 2008, from 32 surface water stations from the river origin to the delta. Five water quality parameters viz., DO, BOD, TCB, FCB, NH3-N and water temperature were used in the analysis. Analysis was performed by using the Self Organizing Maps. Four distinct spatially approached clusters were classified, according to the similarity of water quality parameters, while temporal variations of most of the surface water stations were not obviously observed. The worst water quality condition was at the stations near the river delta and highly related to anthropogenic stresses. Result from the correspondence analysis showed that, except for the cluster of the worst water quality, the stations of the remaining three clusters were overlapped. There was no statistical difference in water temperature among clusters but the expected effects from climate change should be a precautionary focus since the will eventually affect the water quality.

Assessment and Spatiotemporal Variation Analysis of Water Quality in the Zhangweinan River Basin, China

Abstract Spatiotemporal variation analysis of water quality and identification of water pollution sources in river basins is very important for water resources protection and sustainable utilization. In this study, fuzzy comprehensive analysis and two statistical methods including cluster analysis and seasonal Kendall test method were used to evaluate the spatiotemporal variation of water quality in the Zhangweinan River basin. The results for spatial cluster analysis and assessment on water quality at 19 monitoring sites indicated that water quality in the Zhangweinan River basin could be classified into two regions according to pollution levels. One is the Zhang River basin located in northwest of the Zhangweinan River basin where water quality is good. Another one includes the Wei River and eastern plain of the Zhangweinan River basin, and the water pollution in this region is serious, where the pollutants from point sources flow into the river and the water quality changes greatly. The results of temporal cluster analysis and seasonal Kendall test indicated that the sampling periods may be classified into three periods during 2002-2009 according to water quality. Results of temporal cluster analysis and seasonal Kendall test indicated that the study periods may be classified into three periods and two different trends was detected during the period of 2002-2009. The first period was the year of 2002-2003, during which water quality had deteriorated and serious pollution was observed in the Wei River basin and eastern plain of the Zhangweinan River basin. The second period was the year of 2004-2006, during which water quality became better. The year of 2007-2009 is the third period, during which water quality had been improved greatly. Despite that water quality in the Zhangweinan River basin had been improved during the period of 2004-2009, water quality in the Wei River (southwestern part of the basin), the Wei Canal River and the Zhangweixin River (eastern plain of the basin) is still poor. These results provide may useful information for better pollution control strategies in the Zhangweinan River basin.

Sustainable microbial water quality monitoring programme design using phage-lysis and multivariate techniques

Contamination of surface waters is a pervasive threat to human health, hence, the need to better understand the sources and spatio-temporal variations of contaminants within river catchments. River catchment managers are required to sustainably monitor and manage the quality of surface waters. Catchment managers therefore need cost-effective low-cost long-term sustainable water quality monitoring and management designs to proactively protect public health and aquatic ecosystems. Multivariate and phage-lysis techniques were used to investigate spatio-temporal variations of water quality, main polluting chemophysical and microbial parameters, faecal micro-organisms sources, and to establish ‘sentry’ sampling sites in the Ouse River catchment, southeast England, UK. 350 river water samples were analysed for fourteen chemophysical and microbial water quality parameters in conjunction with the novel human-specific phages of Bacteroides GB-124 (Bacteroides GB-124). Annual, autumn, spring, summer, and winter principal components (PCs) explained approximately 54%, 75%, 62%, 48%, and 60%, respectively, of the total variance present in the datasets. Significant loadings of Escherichia coli, intestinal enterococci, turbidity, and human-specific Bacteroides GB-124 were observed in all datasets. Cluster analysis successfully grouped sampling sites into five clusters. Importantly, multivariate and phage-lysis techniques were useful in determining the sources and spatial extent of water contamination in the catchment. Though human faecal contamination was significant during dry periods, the main source of contamination was non-human. Bacteroides GB-124 could potentially be used for catchment routine microbial water quality monitoring. For a cost-effective low-cost long-term sustainable water quality monitoring design, E. coli or intestinal enterococci, turbidity, and Bacteroides GB-124 should be monitored all-year round in this river catchment.

토지이용이 다변화된 산림 유역의 수질에 미치는 몬순 강우의 영향

토지 이용이 다변화된 산지 유역에서 몬순 강우에 의한 환경 영향을 평가하는데 필수적인 기초 자료를 확보하기 위해 수질의 계절간 비교와 강우사상 집중샘플링의 방법을 활용하여 지표수 수질의 시공간적 변이 특성을 조사하였다. 유역 내 토지 이용을 반영하는 지표수 9개 지점을 대상으로 건 우기 수질의 계절적 차이를 비교하고, 2회의 강우사상에 대해 산림과 농경지 하천 2개 지점에서 집중 샘플링을 실시하였다. 대부분의 지점에서 건기보다 우기에 전기전도도와 <TEX>$Cl^-$</TEX> 농도는 더 낮았으나, 총 금속 농도는 우기에 훨씬 더 높았다. 이는 우기에 늘어난 유량에 의해 용존 이온은 희석되고, 토양 침식량은 증가됐기 때문인 것으로 보인다. 한편 18mm의 적은 강우 시에 산림 하천의 수질에서는 거의 변화가 보이지 않은 데 반해, 농경지 하천에서는 부유토사와 용존 물질 농도가 모두 가파른 변화를 보였으며, 452mm의 많은 강우에 대해서는 농경지 하천은 물론 산림 하천에서도 큰 수질 변화를 관찰할 수 있었다. 농경지 하천의 Pb 농도는 부유토사 농도와 높은 양의 상관관계를 보였다. 제한된 샘플링 횟수와 조사지점으로 인해 결과 해석에 신중을 기해야 하겠지만, 전체 결과는 가파른 산지 유역에 농경지가 무분별하게 확장되면 강우의 변동폭과 극단화가 심해질 경우 토양 침식과 그에 따른 환경 영향의 취약도가 증가할 것임을 시사한다. To provide baseline information essential for assessing environmental impacts of monsoon rainfalls in a mountainous watershed under mixed land use, we investigated spatiotemporal variations in water quality using a combined approach of seasonal water quality survey and intensive storm samplings. Biannual water sampling at nine locations encompassing major land use types showed generally lower electrical conductivity and Cl- concentrations during the typical wet period compared to the dry period, indicating rainfall-induced dilution of dissolved ions. Total metal concentrations, however, were significantly higher during the monsoon period, probably associated with rainfall-induced increases in suspended sediments. Intensive storm sampling during a small monsoon rainfall event (18 mm) and an extreme event (452 mm) showed rapid changes in both suspended sediments and dissolved solutes in an agricultural stream draining the Haean Basin where arable lands have expanded rapidly over the recent decades. By contrast, a nearby forest stream derived from North Korea showed little responses to the small event compared to larges changes during the extreme event. In the agricultural stream total Pb concentrations showed significant positive relationships with suspended sediments. Although limited sampling frequency and locations require a cautious interpretation, the overall results suggest that expansion of agricultural fields in steep mountainous watersheds can increase the susceptibility of soil erosion and its off-site environmental impacts under increasing rainfall variability and extremes.