Interactions of multiple abiotic stresses exacerbate mollusk diversity loss in a high-discharge coastal mangrove wetland.

SummaryTo quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.

Nutrient input estimation and reduction strategies related to land use and landscape pattern (LULP) in a near-eutrophic coastal bay with a small watershed in the South China sea

It is crucial to understand the spatial-temporal variation of water quality for the water safety and eutrophication migration in plateau lakes. To identify the variation property and the main causes of eutrophication and continuous water quality deterioration, the water quality, including the water temperature (WT), dissolved oxygen (DO), pH, Chl-a, turbidity, total nitrogen (TN) and total phosphorus (TP), of Lake Xingyun was monitored from 2016 to 2021, and their spatial and temporal distribution characteristics were analyzed. The results show that there is no obvious thermal stratification in the vertical direction; pH and DO decrease with depth, which is caused by both physical and biochemical processes, especially at the bottom of Lake Xingyun, which has an anaerobic environment. The chlorophyll content was higher during the high-flow periods and varied significantly in the vertical direction; the spatial variation of water quality in Lake Xingyun was more obvious in the low-flow period and alkaline throughout the year. The average content of total phosphorus (TP) ranged between 0.33 and 0.53 mg/L during the high-flow periods and between 0.22 and 0.51 mg/L during the low-flow periods, while the average content of total nitrogen (TN) ranged between 1.92 and 2.62 mg/L and 1.36 and 2.53 mg/L during the high- and low-flow periods, respectively. The analysis of the inflow samples shows that exogenous nitrogen and phosphorus is the main pollution source affecting the nitrogen and phosphorus content of Lake Xingyun. The trophic level index (TLI) shows that Lake Xingyun is in eutrophication all year round, and even in areas less affected by the exogenous nutrient, there are still conditions for cyanobacterial blooms. This study shed new light on the water quality, eutrophication status and changes in Lake Xingyun, providing suggestions for controlling lake pollution and eutrophication mitigation.

The seasonal and spatial variation in the phytoplankton community structure and the environmental variables were investigated in December (the dry season) 2016 and July (the rainy season) 2017 in the Jinjiang River Estuary, China. We identified a total of 138 species of phytoplankton, which were mainly Chlorophyta, Bacillariophyta, and Cryptophyta in the dry season; however, in the rainy season, only Bacillariophyta were found. In the Jinjiang River Estuary, the species evenness and the biodiversity index were higher in the rainy season and that the species diversity was higher in the dry season. Redundancy analysis (RDA) revealed that the dominant species were statistically related to many of the environmental variables, including the water temperature (WT), pH, salinity (Sal), dissolved oxygen (DO), total phosphorus (TP), and total nitrogen (TN). Among the variables, the Sal, DO, TP, and TN had a significant influence on the dominant species distribution, and the WT and pH also affected the dominant species distribution to some extent.

The application of machine learning (ML) approaches to predict estuarine dissolved oxygen (DO) from a set of environmental covariates including nutrients remains unexplored due to nutrient data unavailability. Employing data from 12 southwest coastal Florida water quality stations, the applicability of four ML models – support vector machine (SVM), random forest (RF), decision tree, and Wang–Mendel – was examined in predicting DO under a limited nutrient data environment. Monthly water temperature, pH, salinity, total nitrogen (TN), and total phosphorus (TP) data were used for model development. The multiple linear regression model was trained as benchmarks to compare the ML model performances. The site-specific RF and SVM showed superior model efficiency (Nash–Sutcliffe Efficiency > 0.80) when all the predictor variables were used for model development. However, models trained without nutrients demonstrated reduced prediction accuracy. Modeling by synthesizing all site data under TN-limited, TP-limited, and TN- & TP-co-limited regimes illustrated a preferable performance of RF. Overall, the study rendered two crucial conclusions that could complement the existing approaches to estimate total daily loads for environmental management: (1) nutrients serve as a necessary predictor of estuarine DO dynamics and (2) RF performs better among the ML methods under a limited data environment.

Saemangeum Reservoir in South Korea is an estuarine system enclosed by a dyke construction, where seawater inflow and retained water outflow are managed by the opening/closing of sluice gates installed in the southern part of the dyke. An exchange of the reservoir water can cause spatiotemporal fluctuations in the salinity and trophic state, which are major drivers determining variation in the composition of biological communities in estuarine systems. Here, we investigated the seasonal and spatial variability in the copepod community and environmental conditions (water temperature, salinity, transparency, chlorophyll a concentration, total nitrogen, total phosphorus and Carlson’s trophic state index) based on seasonally conducted field monitoring in the Saemangeum Reservoir from July 2013 to January 2018. In addition to the role of temperature, salinity and chlorophyll a concentration in structuring the copepod community and diversity, the biological indices of copepods with respect to salinity range and trophic state, were evaluated. The spatiotemporal variability in the salinity and trophic state variables showed contrasting patterns, and chlorophyll a concentration was negatively affected by salinity, indicating that the reservoir water was being highly exchanged with opening of the sluice gates. The mean trophic state index values, however, were constant in the eutrophic state (50―70). Dominant copepods were Acartia (A. hudsonica, A. sinjiensis, Acartia spp.) and Oithona (O. davisae and Oithona spp.), which are common species in eutrophic neritic water. Variation in the copepod community was mainly associated with the seasonal succession of the dominant species rather than a spatial gradient (from around the estuary to the sluice gates); however, site-specific differences in frequencies of several non-dominant species could be detected around the estuary (Sinocalanus tenellus) and the sluice gates (Centropages spp., Tigriopus spp. and Labidocera rotunda). The copepod diversity increased with species-richness from around the estuary to the sluice gates, which could result from variation in the site-specific location of non-dominant species. The frequency of particular species was also able to discriminate in terms of the salinity range (oligohaline: A. pacifica, S. tenellus and A. sinjiensis; mesohaline: Pseudodiaptomus inopinus; and polyhaline: C. abdominalis and Centropages spp.) and the trophic state (mesotrophic: C. abdominalis, Calanus sinicus and Centropages spp.; and hypereutrophic: S. tenellus, P. inopinus and Sinocalanus spp.). The findings from this study not only identify the factors determining spatiotemporal variation in the copepod community in the Saemangeum Reservoir, but also expand the applicability of copepods as biological indicators of conditions associated with salinity range and trophic state in other enclosed estuarine systems.

The accumulation of nutrients in rivers is a major cause of eutrophication, and the change in nutrient content is affected by a variety of factors. Taking the River Yi as an example, this study used wavelet analysis tools to examine the periodic changes in nutrients and environmental factors, as well as the relationship between nutrients and environmental factors. The results revealed that total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH4+-N) exhibit multiscale oscillation features, with the dominating periods of 16-17, 26, and 57-60 months. The continuous wavelet transform revealed periodic fluctuation laws on multiple scales between nutrients and several environmental factors. Wavelet transform coherence (WTC) was performed on nutrients and environmental factors, and the results showed that temperature and dissolved oxygen (DO) have a strong influence on nutrient concentration fluctuation. The WTC revealed a weak correlation between pH and TP. On a longer period, however, pH was positively correlated with TN. The flow was found to be positively correct with N and P, while N and P were found to be negatively correct with DO and electrical conductance (EC) at different scales. In most cases, TP was negatively correlated with 5-day biochemical oxygen demand (BOD5) and permanganate index (CODMn). The correlation between TN and CODMn and BOD5 was limited, and no clear dominant phase emerged. In a nutshell, wavelet analysis revealed that water temperature, pH, DO, flow, EC, CODMn, and BOD5 had a pronounced influence on nutrient concentration in the River Yi at different time scales. In the case of the combination of environmental factors, pH and DO play the largest role in determining nutrient concentration.

To determine the variation of water quality in rice-crayfish (Procambarus clarkii) integrated systems (RCIS) in China, eleven water quality parameters were measured monthly in a typical RCIS located in Qianjiang City (Hubei Province) from July 2014 to June 2015, the parameters were analyzed with principal component analysis (PCA) and compared between the trenches and rice areas during the rice fallow period (Nov-May). The trench and rice area comprehensive results showed that pH (7.48-8.68), NH4+-N (0.2-1.09 mg/L), NO2--N (<0.052 mg/L) and conductivity (435-951 μS/cm) were within the suitable ranges for P. clarkii and that turbidity (TU) was high during the crayfish harvesting and rice planting season. Annual averages of total nitrogen (TN), total phosphorus (TP), permanganate index (CODMn), and chlorophyll a (Chl.a) content were <2 (except in Nov-Dec), 0.25, 10 mg/L, and 50 mg/m3 (especially in Nov-May, <10 mg/m3), respectively. Dissolved oxygen (DO) was below 4 mg/L in Mar-Sep, with a minimum of ~ 1 mg/L, and much higher in Oct-Feb. The maximum and minimum monthly average water temperature (WT) were 31.4°C in July and 5.7°C in December, while the maximum and minimum instantaneous WT were 39.7°C and 2.5°C, respectively . PCA analysis showed that the first three axes, which were mainly correlated with DO, WT and nutrient level, described most information of the parameters, and parameters showed seasonal changes. Some differences were observed in water parameters between the trenches and rice areas, i.e., trenches generally had higher TU, WT and DO, and lower TN, TP and CODMn, although no significant differences were found in some months and some parameters. The study revealed relatively low water nutrient level, probable extreme WT and DO level in some seasons, and certain differences between the trenches and rice areas in typical CRIS in China. Accordingly, some measures should be taken to improve the negative parameters: 1) enhance the water fertility; 2) increase DO, especially in Mar-Sep; 3) increase the trench and water depth to avoid extreme WT. And water quality management should be addressed in both trenches and rice areas. Keywords: rice-crayfish integrated system, co-culture, water quality parameters, trench, rice production area, PCA DOI: 10.25165/j.ijabe.20181103.3761 Citation: Yu J X, Ren Y, Xu T, Li W, Xiong M T, Zhang T L, et al. Physicochemical water quality parameters in typical rice-crayfish integrated systems (RCIS) in China. Int J Agric & Biol Eng, 2018; 11(3): 54–60.

Land cover change plays an essential role in the alternation of soils properties. By field investigation and applying satellite images, land cover information in the Shelihu wetland was carried out in an area of 2,819 hm2 in 1985, 1995, 2000, 2005, 2010 and 2011, respectively, in Horqin Sandy Land. A total of 57 soil sampling sites across Shelihu were chosen in wet meadow (CL0), cropland (CL) and sandy land (SL) according to the spatial characteristics of water body change. Soil texture, organic carbon (SOC), total nitrogen (TN) and total phosphorus (TP) contents, electrical conductivity (EC) and pH were measured at the soil depths of 0–10, 10–20 and 20–40 cm to examine the influence of agricultural conversion and continuous cultivation on soil properties. The results showed that the study area was covered by water body in 1985, which gradually declined afterwards and then reclaimed rapidly at a mean annual rate of 132.1 hm2/a from wet meadow to cropland since 1995. In 2011, water body was drained and the area was occupied by 10.8% of CL0, 76.9% of CL and 12.3% of SL. Large amounts of SOC, TN and TP were accumulated in the above depths in CL0. Soil in CL0 also had higher EC and silt and clay fractions, lower pH than in SL and CL. Soil in SL was seriously degraded with lower contents of SOC, TN and TP than in CL and CL0. SOC, TN content and EC in CL decreased with the increase of cultivation age, while pH showed a reverse trend with significance at plough horizon. The agricultural conversion in Shelihu was driven by the comprehensive factors of precipitation reduction, economic development and intense competitions for irrigation water. Continuous cultivation in this process is not sustainable because of SOC degradation and nutrient content reduction. The key point is that conventional tillage and removal of residuals induced further land degradation. Wetland reclamation for immediate economic interests led to greater costs in the long-term environmental restoration in Horqin Sandy Land.

Nitrogen and phosphorus entering waterways from diffuse agricultural sources is a major problem in New Zealand and internationally. This problem is well documented for lowland areas but little is known about nutrient enrichment from farming in high country areas. The Lake Clearwater catchment, in the Canterbury high country of New Zealand, has a native ecosystem that has adapted to low-nutrient conditions. The Department of Conservation's Arawai Kakariki Wetland Restoration Programme identifies wetlands in the catchment as one of three key endemic wetland types. Uncertainty regarding diffuse nutrient load from agriculture into the lake and wetland is limiting effective management of this unique catchment. This study investigated the hydrological regimes and nitrogen and phosphorus concentrations and loads in five key surface waterways at ten surface water sites and three groundwater seeps for two years. It aims to improve knowledge of nutrient sources, characteristics and loads from agricultural land use in this 46 km2 high country catchment. Additionally, nutrient load predictions from the Catchment Land Use for Environmental Sustainability (CLUES) model were compared to measured nutrient loads to assess the applicability of the model in high country catchments. The CLUES model was developed, primarily for lowland areas, to predict changes in water quality and nutrient loads from land-use change. The total nitrogen concentrations downstream of farmland were typically above the Australia and New Zealand Environment and Conservation Council (ANZECC) water quality guideline and the median concentration for upland Canterbury waterways. Specifically, the nitrate concentration (0.19-0.29 g m-3) in farmland subsurface runoff was elevated, compared to streams in the Lake Clearwater catchment with unfarmed catchments, and was estimated to contribute 52% of total nitrogen yield from farmland. The total nitrogen yield (1.96-2.94 kg ha-1 year-1) for farmed land was comparable to minimum values for New Zealand pastoral land use reported in the literature. The total estimated nitrogen export from Lake Clearwater (2518 kg year-1) was 83% greater than the estimated diffuse input from all land in the catchment (1375 kg year-1). This indicated an additional source of nitrogen into the lake and seasonal nitrogen saturation. Total phosphorus yields (0.093-0.123 kg ha-1 year-1) downstream of farmland were well below yields for New Zealand pastoral land use reported in the literature. Total estimated phosphorus export from the lake (58 kg year-1) was 24% less than total estimated diffuse loads into the lake (76 kg year-1). The ratio of total nitrogen to total phosphorus in Lake Clearwater (49:1) indicated that phosphorus is the limiting nutrient and that nitrogen loads into the lake are above natural levels. Total nitrogen loads predicted by the CLUES model in the Lake Clearwater catchment were reasonable, providing land-use area inputs are accurate and nutrient loads exit catchments in surface water. However, CLUES greatly overestimated phosphorus loads from farmed and unfarmed land.

Temporal and spatial distribution of macrobenthos communities and their responses to environmental factors in Lake Taihu

Water quality parameters-based prediction of dissolved oxygen in estuaries using advanced explainable ensemble machine learning.

It is important to explore the relationship between land use types and water quality to improve the surface water environment. Based on monthly water quality monitoring data from 16 nationally controlled surface water quality monitoring stations in Tianjin and land use data in 2021, GIS spatial analysis and mathematical and statistical methods were used to study the influence of land use types on surface water quality in buffer zones at different scales. The results showed that:① the land use types in the study area were mainly construction land, farmland, and water areas, which had significant effects on river water quality. Except for water temperature (WT) and pH, the farmland, construction land, and water areas were negatively correlated with each water quality indicator; forest land and grassland were positively correlated with dissolved oxygen (DO) and total nitrogen (TN) and negatively correlated with other water quality indicators. ② The water quality indicators showed obvious spatial differences in different seasons. The pH, DO and TN concentrations were higher in the dry season, whereas the permanganate index, ammonia nitrogen (NH4+-N), and total phosphorus (TP) concentrations were higher in the rainy season. ③ The results of the RDA analysis showed that the 800 m buffer zone land use had the greatest explanatory power for water quality changes in the dry season (50.4%), whereas the 3 000 m buffer zone land use could explain the water quality changes in the rainy season to the greatest extent (49.6%); from the average explanation rate of the dry and rainy seasons, the 3 000 m buffer zone was the best impact scale (50.0%) on water quality indicators in Tianjin. ④ The partial least squares regression (PLSR) analysis showed that the most important variables affecting surface water quality changes were construction land, farmland, and water areas. The predictive ability of the PLSR model of most water quality indicators was stronger in the dry season than that in the rainy season. In the dry season, all water quality indicators, except WT and pH, were most influenced by farmland. In the rainy season, construction land had the greatest influence on WT and NH4+-N concentrations, and the most important influencing factor for the remaining water quality indicators was still farmland. This study showed that the rational planning of land use types within 3 000 m of rivers or lakes was beneficial to improving the water quality of surface water.

First posted November 17, 2016 For additional information, contact: Director, Virginia Water Science CenterU.S. Geological Survey1730 East Parham RoadRichmond, VA 23228http://va.water.usgs.gov/ Despite widespread and ongoing implementation of conservation practices throughout the Chesapeake Bay watershed, water quality continues to be degraded by excess sediment and nutrient inputs. While the Chesapeake Bay Program has developed and maintains a large-scale and long-term monitoring network to detect improvements in water quality throughout the watershed, fewer resources have been allocated for monitoring smaller watersheds, even though water-quality improvements that may result from the implementation of conservation practices are likely to be first detected at smaller watershed scales.In 2010, the U.S. Geological Survey partnered with the U.S. Environmental Protection Agency and the U.S. Department of Agriculture to initiate water-quality monitoring in four selected small watersheds that were targeted for increased implementation of conservation practices. Smith Creek watershed is an agricultural watershed in the Shenandoah Valley of Virginia that is dominated by cattle and poultry production, and the Upper Chester River watershed is an agricultural watershed on the Eastern Shore of Maryland that is dominated by row-cropping activities. The Conewago Creek watershed is an agricultural watershed in southeastern Pennsylvania that is characterized by mixed agricultural activities. The fourth watershed, Difficult Run, is a suburban watershed in northern Virginia that is dominated by medium density residential development. The objective of this study was to investigate spatial and temporal variations in water chemistry and suspended sediment in these four relatively small watersheds that represent a range of land-use patterns and underlying geology to (1) characterize current water-quality conditions in these watersheds, and (2) identify the dominant sources, sinks, and transport processes in each watershed.The general study design involved two components. The first included intensive routine water-quality monitoring at an existing streamgage within each study area (including continuous water-quality monitoring as well as discrete water-quality sampling) to develop a detailed understanding of the temporal and hydrologic variability in stream chemistry and sediment transport in each watershed. The second component involved extensive water-quality monitoring at various sites throughout each watershed to develop a detailed understanding of spatial patterns. Both components were used to improve understanding of sources and transport processes affecting stream chemistry, including nutrients and suspended sediments, and their implications for detecting long-term trends related to best management practices. This report summarizes the results of monitoring that was performed from April 2010 through September 2013.Individual Small Watershed SummariesSummaries for each of the four small watersheds are presented below. Each watershed has a more descriptive and detailed section in the report, but these summaries may be particularly useful for some watershed managers and stakeholders desiring slightly less technical detail.Smith CreekSmith Creek is a 105.39-mi2 watershed within the Shenandoah Valley that drains to the North Fork Shenandoah River. The long-term Smith Creek base-flow index is 72.3 percent, indicating that on average, approximately 72 percent of Smith Creek flow was base flow, which suggests that Smith Creek streamflow is dominated by groundwater discharge rather than stormwater runoff. A series of cluster and principal components analyses demonstrated that the majority of the variability in Smith Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed for turbidity, suspended sediments, total nitrogen, ammonium, orthophosphate, iron, total phosphorus, and the ratio of calcium to magnesium. Statistically significant inverse correlations with flow were observed for specific conductance, magnesium, δ15N of nitrate, pH, bicarbonate, calcium, and δ18O of nitrate. Of particular note, flow and nitrate were not statistically significantly correlated, likely because of the relatively complex concentration-discharge relationship observed in continuous and discrete datasets. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, turbidity, orthophosphate, total phosphorus, suspended-sediment concentration, and silica were higher during the warm season, but pH, dissolved oxygen, and sulfate were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loads in Smith Creek using the continuous water-quality monitors. The mean Smith Creek in-stream sediment load was approximately 6,900 tons per year, with nearly 90 percent of the sediment load over the 3-year study period contributed during the eight largest storm events during that period. The Smith Creek total phosphorus load was approximately 21,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods, although a substantial phosphorus load still occurs during base-flow conditions. The Smith Creek total nitrogen load was approximately 400,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions (as was the case for sediment and total phosphorus) and strongly affected by base-flow export of nitrogen from the basin.Extensive water-quality monitoring throughout the Smith Creek watershed revealed how the complex geology and hydrology interacted to result in variable water chemistry. During relatively dry and low base-flow periods, much of the discharge in Smith Creek was contributed by a single dominant spring—Lacey Spring. During wetter base-flow periods, the flows in Smith Creek were largely generated by a mixture of headwater springs and forested mountain tributaries with very different geochemical composition. The headwater springs generally issued from limestone bedrock and were characterized as having relatively high nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The undeveloped, high-gradient, forested mountain sites were generally characterized by low ionic strength waters with low nutrient concentrations. Nitrate isotope data from the limestone springs generally were consistent with manure-derived nitrogen sources (such as cattle and poultry), although the possibility of other mixed sources cannot be excluded. Nitrate isotope data from the undeveloped, high-gradient forested mountain sites were more consistent with nitrogen from undisturbed soils, atmospheric deposition, or nitrogen fixation. Regardless of the nitrogen source, oxygen isotope data indicate that the nitrate was largely a result of nitrification. Land-use data indicate that manure sources of nitrogen dominated watershed nitrogen inputs. Phosphorus sources were less well studied. The presence of a single point-source discharge near the town of New Market contributed the majority of the phosphorus to Smith Creek under base-flow conditions, but nonpoint sources of phosphorus dominated the loading to Smith Creek during stormflow periods.Implementation of conservation practices increased in the Smith Creek watershed during the study period, and even though a broad range of practice types was implemented, the most common practices included stream fencing (for cattle exclusion), the development of nutrient management plans, conservation crop rotation, and the planting of cover crops. While the implementation of these conservation practices is encouraging, results indicate small increases in nitrate concentrations at the streamgage over the last 29 years, concurrent with small decreases in nitrate fluxes. It will likely be years before the cumulative effect of these practices can be detected in the Smith Creek water quality, and the magnitude of the effect of these conservation practices detected in Smith Creek will depend largely on whether nutrient loading (of manure and commercial fertilizer) is reduced over time.Upper Chester RiverThe Upper Chester River watershed includes the 36-square-mile (mi2) watershed area around several nontidal tributaries that drain into the tidal Chester River. The streamgage is on Chesterville Branch, the largest nontidal tributary (approximately 6.12 mi2) and is the site for continuous water-quality monitoring for this project. The base-flow index at Chesterville Branch is about 72 percent and indicates that, as in most of the Coastal Plain, groundwater is the greatest contributor to streamflow. As such, more than 90 percent of the nitrogen in the stream is in the form of nitrate from groundwater. Continuous and discrete data collected at Chesterville Branch show the effects of streamflow and season on water quality. Significantly positive correlations with flow were observed for ammonium, dissolved and total phosphorus, sediment, and turbidity as runoff carried these constituents from the land surface into Chesterville Branch. Other constituents that increased significantly with flow include potassium, sulfate, iron, and manganese, which are likely contributed from near-stream areas and ponds with high organic-matter content. Total nitrogen, pH, and specific conductance, along with chemical constituents associated with groundwater inputs including nitrate, calcium, ratio of calcium to magnesium, silica, bicarbonate, and sodium, were negatively correlated with flow because concentrations of these constituents were diluted by runoff.Seasonal differences in water chemistry, which are most likely related to increased biologic effects on the uptake and release of chemicals in the stream and near-stream areas, also were observed. Water temperature, orthophosphate, δ15N of nitrate, bicarbonate, sodium, and the ratio of sodium to chloride were higher during the warm season, and dissolved oxygen, total nitrogen, nitrate, magnesium, sulfate, and manganese were higher during the cool season.Surrogate-regression models developed by using continuous water-quality data showed that the annual sediment load for the 2013 water year was about 2,600 tons, with more than 90 percent of this sediment contributed during two storms. The total phosphorus load in 2013 was about 13,000 pounds with more than 90 percent contributed during the same two storms as sediment. The load of total nitrogen, 140,000 pounds, accumulated steadily throughout the 2013 water year as nitrate in groundwater continuously discharged into the stream. The same two large storms that contributed 90 percent of the suspended-sediment and total phosphorus load only contributed about 20 percent of the annual total nitrogen load.Extensive water-quality monitoring of stream base flow throughout the Upper Chester River watershed identified how differences in land use and hydrogeology affected water chemistry. In parts of the watershed with well-drained soil and thick sandy aquifer sediments, concentrations of nitrate and other chemicals associated with fertilizer and lime application increased in streams as agricultural land use increased. More than 90 percent of the nitrogen in streams from these areas was in the form of nitrate, and concentrations ranged from about 5 milligrams per liter (mg/L) to 8 mg/L as nitrogen in the two largest tributaries. Stream nitrate concentrations were about 1 mg/L as nitrogen where soils were more poorly drained, the surficial aquifer sediments were thinner, and forests and wetlands were more widespread than agriculture. Nitrate isotope data were consistent with inorganic fertilizers ± atmospheric deposition and N2 fixation as sources of nitrogen, and with nitrification as the dominant nitrate-forming process. Nitrate reduction was indicated by elevated δ15N and δ18O values in some samples from streams draining watersheds with poorly drained soils. An analysis of land-use data and SPARROW modeling input data attributed almost 90 percent of the nitrogen sources in the Upper Chester River watershed to inorganic fertilizer and fixation of atmospheric nitrogen by legumes, which is in agreement with the isotopic characteristics of nitrate in this watershed. Local sources of manure are limited in this area. Total phosphorus concentrations during base flow ranged from below detection to about 0.2 mg/L. Stream phosphorus concentrations during base flow were generally lower than those measured during storms because most phosphorus transport likely occurs as phosphorus attached to sediment particles during runoff. Because manure is not widely used in this area, the major source of phosphorus is likely fertilizer.The implementation of conservation practices in the Upper Chester River watershed increased substantially during the study period, with a total implementation of 1,194 U.S. Department of Agriculture-compliant practices. The most frequently used practices were oriented towards nutrient and sediment control, including cover crops, nutrient management planning, conservation crop rotation, conservation tillage, and irrigation management. The current Chesapeake Bay model for this area predicts that implementation of best management practices should result in a 13-percent decrease in overall delivery of nitrogen to the Upper Chester River. Because most nitrogen travels through the groundwater system for years to decades before being discharged to streams, the time period of monitoring was not sufficient to see the effects of these practices on water quality. The magnitude of the effect that may eventually be detected will depend on the degree to which nitrate leaching into the groundwater system is reduced over time. Loadings of phosphorus and sediment are primarily transported during large runoff events and are difficult to control and analyze for trends because of their timing and episodic nature.Conewago CreekConewago Creek has two primary monitoring locations—one near the middle of the 47-mi2 watershed and the other near the outlet just upstream of the Susquehanna River. The base-flow index was 47.3 percent for 2012–2013, indicating that on average, approximately 53 percent of the streamflow in Conewago Creek exited the watershed as surface flow, which suggests that the stormwater runoff was somewhat greater than groundwater discharge (base flow). A series of cluster and principal components analyses demonstrated that the majority of the variability in the Conewago Creek water quality could be attributed to hydrologic and seasonal variability. Statistically significant positive correlations with flow were observed at both monitoring sites for ammonium, total phosphorus, orthophosphate, iron, and manganese; additionally, at the upstream monitoring station, total nitrogen demonstrated a statistically significant positive correlation with flow. Statistically significant inverse correlations with flow were observed at both sites for water temperature, specific conductance (at the downstream site only), sulfate, chloride, calcium, and magnesium. Statistically significant seasonal patterns were observed for several water-quality constituents. Water temperature, phosphorus (upstream site only), and orthophosphate were higher during the warm season, and nitrate and total nitrogen (upstream site only) were higher during the cool season.Surrogate regression models were developed to compute sediment and nutrient load in Conewago Creek by using the continuous water-quality monitors and water-quality samples. Conewago Creek sediment load was approximately 9,900 tons in 2012 and approximately 18,900 tons in 2013, with nearly 80 percent of the sediment load in 2013 contributed by the three largest storm events. Annual total nitrogen loads could not be estimated due to poor model performance. The addition of continued monitoring or a continuously recording nitrate sensor could improve estimates of total nitrogen loads. During 2012 and 2013, phosphorus loads in Conewago Creek were approximately 50,000 pounds in each year.Combining data from one high-flow synoptic sampling with the data from routine sampling revealed how the geology and hydrology interact to result in variable water chemistry throughout the Conewago Creek watershed. The areas above the upstream gage in the headwaters are generally underlain by forested non-carbonate bedrock and are characterized by relatively low nitrate, specific conductance, calcium, and magnesium, as well as relatively low concentrations of phosphorus, ammonium, iron, and manganese. The more developed, agricultural areas below the upstream site were generally characterized by higher ionic strength waters with higher nutrient and metal concentrations. An analysis of land-use data and SPAtially Referenced Regressions On Watershed (SPARROW) modeling data indicates that manure sources of nitrogen dominate the input of nitrogen to the watershed.Implementation of conservation practices increased in the Conewago Creek watershed during the study period, and while a broad range of practice types were implemented, the most common practices included residue and tillage management, cover crops, nutrient management, terracing, and stream fencing (for animal exclusion or bank restoration). While the implementation of these conservation practices is encouraging, the cumulative effects of these practices probably will not be detected in Conewago Creek water quality for several years. The magnitude of the effects of these conservation practices on water quality in Conewago Creek will depend largely on the extent to which nutrient loading (septic, manure, and commercial fertilizer) and sediment-producing activities are reduced over time.Difficult RunThe Difficult Run watershed is a 57.82-mi2 watershed that drains to the Potomac River. The long-term Difficult Run base-flow index (from 1936 to 2010) was 57.9, indicating that approximately 58 percent of streamflow exited the watershed as base flow and 42 percent as stormflow; however, with continued development and urbanization of the watershed, the base-flow index has decreased to 50 percent during the last 20 years. This base-flow index was less than those of the other watersheds evaluated in this study, likely because the Difficult Run watershed largely is underlain by crystalline piedmont metamorphic rocks and has a greater proportion of impervious urban land cover. A series of cluster and principal components analyses indicated that most of the variability in Difficult Run water quality could be attributed to hydrologic variability and seasonality. Statistically significant positive correlations with flow were observed for turbidity, dissolved oxygen, suspended sediments, ammonium, orthophosphate, iron, and total phosphorus. Statistically significant inverse correlations with flow were observed for water temperature, pH, specific conductance, bicarbonate, calcium, magnesium, nitrate, δ15N of nitrate, and silica. Statistically significant seasonal patterns were observed for numerous water-quality constituents: water temperature, ammonium, orthophosphate, and δ15N of nitrate were higher during the warm season, and dissolved oxygen, nitrate, and manganese were higher during the cool season. Surrogate regression models were developed to compute sediment and nutrient loading rates. The Difficult Run sediment load was approximately 8,000 tons per year, with greater than 95 percent of the sediment load in the 2013 water year contributed by the seven largest storm events. The total phosphorus load in Difficult Run was approximately 14,000 pounds of phosphorus per year, with the majority of the load contributed during stormflow periods. The total nitrogen load in Difficult Run is estimated to have been approximately 140,000 pounds per year, with total nitrogen accumulation less dominated by stormflow contributions than that of phosphorus and strongly affected by base-flow export of nitrogen from the basin.Extensive water-quality monitoring throughout the Difficult Run watershed revealed relatively uniform generation of flow per unit of watershed area, as well as spatial variation in water quality that is strongly related to land-use activities. Elevated nitrate concentrations were observed in a subset of monitoring sites that are inversely correlated with population density and positively correlated to the septic system density within each subwatershed. The majority of the elevated nitrate concentrations for these sites are hypothesized to be caused by nitrate leaching from septic systems, more so than homeowner fertilizer usage among these subwatersheds that have lower population densities than other parts of the watershed. Nitrate isotope data, temporal patterns in the water-quality data, mass-balance computations, and a separate land-use analysis all generally indicate that leachate from septic systems was the likely source of the elevated nitrate. Another group of water-quality sites have relatively low nitrogen concentrations, are located in areas that are served by city sewer lines, and have experienced stream restoration activities. A final group of sites drained the areas with the highest imperviousness and had strongly elevated specific conductance, chloride, and sodium, which were likely caused by a combination of road salting and other anthropogenic sources draining these urbanized areas in the watershed. A fourth group of sites represents a mixture of water sources and had water quality similar to that at the Difficult Run streamgage. Analysis of the nitrate isotope data generally indicates a broad range of composition indicative of mixed natural and anthropogenic nitrogen sources. Implementation of conservation practices increased in the Difficult Run watershed during the study period, and while a broad range of practice types was implemented, the most common practices included stream restoration. While the implementation of these conservation practices is encouraging, the cumulative effect of these practices probably will not be detected in Difficult Run water quality for several years.

Spatiotemporal dynamics of physicochemical and sediment parameters in Gulf of Mannar waters, Southeast coast of India