Temporal Changes In Water Quality Research Articles

Spatio-Temporal Dynamics Coupling between Land Use/Cover Change and Water Quality in Dongjiang Lake Watershed Using Satellite Remote Sensing

With rapid social and economic development, land use/land cover change (LUCC) has intensified with serious impacts on water quality in the watershed. In this study, we took Dongjiang Lake watershed as the study area and obtained measured data on water quality parameters from the watershed’s water quality monitoring stations. Based on Landsat-5, Landsat-8, or Sentinel-2 remote sensing data for multiple periods per year between 1992 and 2022, the sensitive satellite bands or band combinations of each water quality parameter were determined. The Random Forest method was used to classify the land use types in the watershed into six categories, and the area proportion of each type was calculated. We established machine learning regression models and polynomial regression models with WQI as the dependent variable and the area proportion of each land use type as the independent variable. Accuracy test results showed that, among them, the quadratic cubic polynomial regression model with grassland, forest land, construction land, and unused land as its independent variables was the best model for coupling watershed water quality with LUCC. This study’s results provide a scientific basis for monitoring spatial and temporal changes in water quality caused by LUCC in the Dongjiang Lake watershed.

Temporal Changes in Water Quality with Increasing Ambient Temperatures Affect the Distribution and Relative Abundance of 10 Species of Balitorid Fishes in Small Streams of Eastern Thailand

Stream degradation increases with high anthropogenic activity and climate variability, while declines occur in biodiversity. However, few studies have been undertaken on tropical waterways, a major impediment to biodiversity conservation. The present study was conducted on 95 relatively pristine small streams in Eastern Thailand with 10 reasonably uncommon species of balitorid fishes. Measurements were made of 21 physical and chemical factors and the substrate particle size. Stepwise regression identified the direct importance of substrate particle size and nitrate on the species’ richness of balitorids, whereas its abundance was negatively related with iron concentrations. A Canonical Correspondence Analysis identified three fish groups: the 1st group was negatively correlated with ammonia and positively correlated with dissolved silica, the 2nd group was positively correlated with substrate particle size and negatively correlated with stream ambient temperature and ammonia concentration, and the 3rd group was negatively correlated with low dissolved silica, respectively. The results of this study may indicate the vulnerability of balitorids under climate warming and anthropogenic pressure that alter the water physicochemical factors and river degradation including the substrate type. Thus, a conservation framework should be provided regarding the limits for water temperature, ammonia, and iron in Thailand’s Water Quality Criteria to better protect its freshwater ecosystem. Balitorid is a potential bioindicator for evaluating the river temperature effect in combination with ammonia nutrient stressors as long as the way-of-life habits of the species are taken into account.

Estimation of Global Water Quality in Four Municipal Wastewater Treatment Plants over Time Based on Statistical Methods

Wastewater from urban and industrial sources can be treated and reused for crop irrigation, which can certainly help to protect aquifers from overexploitation and potential environmental risks of groundwater pollution. In fact, water reuse can also have negative effects on the environment, such as increased salinity, pollution phenomena or soil degradation, among others. Consequently, reuse of wastewater requires rigorous treatment and a very detailed analysis of different parameters, in compliance with established quality limitation standards. Therefore, this study was carried out to develop a prediction of temporal changes in water quality by introducing a wastewater quality index (WWQI) for four regional wastewater treatment plants (WWTPs) in Murcia, Southeast Spain, where a significant number of physicochemical and biological parameters are obtained in time series over the period 2019–2021. For this purpose, multivariate statistical analyses have been adopted to predict the performance of WWQI. By robust PCA of the sixteen physicochemical variables of the raw and treated wastewater, five main principal components (PCs) were extracted, which explain between 21.39% and 36.79% of the data variability. From the loadings of the PCs, the relationships between the original parameters are analyzed. The accuracy of the developed models in terms of fit to the training dataset ranged from 74.3% to 97.9%, with p-values < 0.05. The techniques incorporated in this study provided a comprehensive evaluation framework for monitoring wastewater treatment.

Multiple Evaluations of the Spatial and Temporal Characteristics of Surface Water Quality in the Typical Area of the Yangtze River Delta of China Using the Water Quality Index and Multivariate Statistical Analysis: A Case Study in Shengzhou City.

Surface water assessments are of critical importance for balancing economic development with the ecological environment in rapidly developing regions. In this research, Shengzhou City, a typical town in the Yangtze River Delta region of China, was chosen to conduct a surface water quality study. As a region with a well-developed water system, monthly water quality monitoring data from eight sampling sites on the major tributaries and the mainstream were selected for six consecutive years from 2013 to 2018, containing seven important water quality indicators (pH, DO, CODMn, CODCr, BOD, NH4+-N, and TP). The comprehensive evaluation method based on the water quality index (WQI) and multivariate statistical analysis methods of cluster analysis (CA) and principal component analysis (PCA) were applied to explore the spatial and temporal changes of water quality in Shengzhou City. The main findings are as follows: (1) spatially, for three main tributaries, Xinchang River had the worst water quality, followed by Changle River, while Huangze River had the best. The water quality of the tributaries had higher volatility than the mainstream. (2) The sampling sites with similar locations had similar water quality characteristics. (3) Seasonally, for the four indicators of DO, CODMn, CODCr, and BOD, the water quality was better in the dry season while, for NH4+-N and TP, water quality was better in the wet season. The low WQI points were more likely to appear in the wet season. (4) The results of WQI assessment showed an improving trend in water quality. (5) Nitrogenous substances and organic matter were the key pollutants in this area. The research results prove that water quality evaluation methods and multivariate statistical methods are effective for the study of regional surface water quality.

Groundwater monitoring near oil sands development: Insights from regional water quality datasets in the Alberta Oil Sands Region (AOSR)

Study regionThis study is carried out across a 142,000 km2 area within the Alberta Oil Sands Region (AOSR), Alberta, Canada. Study focusGroundwater quality data for the AOSR are compiled and interpreted to provide information on regional water quality to inform groundwater monitoring and land use planning. A database of 546 water quality parameters measured between 1958 and 2015 from 5118 water wells is compiled, cleaned, and analyzed by hydrostratigraphic unit (HSU). New hydrologic insights for the regionBaseline water quality conditions were found to vary in the 12 main HSU’s, with wide ranges in total dissolved solids and geochemical facies, reflecting variable lithology and geochemical processes. Median concentrations for multiple parameters exceeded “interim trigger values” under consideration by government regulators. Statistically significant temporal changes in water quality were detected in the 2000’s in isolated areas of Surficial Sands aquifer, the Cretaceous and Devonian formations in the North Athabasca Oil Sands, and in Quaternary aquifers in the South Athabasca Oil Sands and Cold Lake Beaver River. Temporal anomalies occur in areas with enhanced vertical connectivity due to the presence of buried channels, incised rivers, or where the Colorado Group is thin or completely absent. The compiled dataset highlights the role of geochemical data in identifying aquifer connectivity and monitoring priority. Lack of publicly available data for key aquifers near some mining areas are noted.

Assessment of Spatial and Temporal Changes in Water Quality of a Tropical River in Southern Western Ghats, Kerala, India, Using Physicochemical Quality Indices and Multivariate Analysis

Assessment of Spatial and Temporal Changes in Water Quality of a Tropical River in Southern Western Ghats, Kerala, India, Using Physicochemical Quality Indices and Multivariate Analysis

Assessing the factors influencing water quality using environment water quality index and partial least squares structural equation model in the Ebinur Lake Watershed, Xinjiang, China.

Surface water quality deterioration is commonly associated with environmental changes and human activities. Although some research has been carried out to evaluate the relationship between various influencing factors and water quality, there is still very little scientific understanding on how to accurately define the key factors of water quality deterioration. This study aims to quantify the impact of environmental factors and land use land cover (LULC) changes on water quality in the Ebinur Lake Watershed, Xinjiang, China. A total of 20 water parameters were used to calculate the Environment Water Quality Index (CWQI). Meanwhile, the partial least squares-structural equation model (PLS-SEM) was used to quantify the impact of eleven factors influencing water quality in the watershed. About 33.3% of the monitoring points that located mostly in the downstream region with dominant anthropogenic activities were detected as poor quality. There were no obvious temporal changes in water quality from 2016 to 2019. The PLS-SEM simulation shows that the latent variable "land use/cover types" (path coefficient = - 0.600) and "Environmental factor" (path coefficient = - 0.313) are two major factors affected water quality in the Ebinur Lake Watershed, with a strong explanatory power to water quality change (R2 = 0.727). In the latent variable "Environmental factors", the "NDVI" and "night light brightness value" have a great influence on water quality, with the weights of 0.451 and 0.427, respectively. Correspondingly, the "farmland" and "forest land" within the latent variable of "Land use/cover type" have a considerable impact water quality, with the weights of 0.361 and - 0.340, respectively. In conclusion, the influence of anthropogenic activities on surface water quality of the Ebinur Lake Watershed is greater than that of environmental factors. Compared with the traditional multivariate statistical method, PLS-SEM provides a new insight for quantifying the complex relationship between different influencing factors and water quality.

A Bayesian approach to understanding the key factors influencing temporal variability in stream water quality – a case study in the Great Barrier Reef catchments

Abstract. Stream water quality is highly variable both across space and time. Water quality monitoring programmes have collected a large amount of data that provide a good basis for investigating the key drivers of spatial and temporal variability. Event-based water quality monitoring data in the Great Barrier Reef catchments in northern Australia provide an opportunity to further our understanding of water quality dynamics in subtropical and tropical regions. This study investigated nine water quality constituents, including sediments, nutrients and salinity, with the aim of (1) identifying the influential environmental drivers of temporal variation in flow event concentrations and (2) developing a modelling framework to predict the temporal variation in water quality at multiple sites simultaneously. This study used a hierarchical Bayesian model averaging framework to explore the relationship between event concentration and catchment-scale environmental variables (e.g. runoff, rainfall and groundcover conditions). Key factors affecting the temporal changes in water quality varied among constituent concentrations and between catchments. Catchment rainfall and runoff affected in-stream particulate constituents, while catchment wetness and vegetation cover had more impact on dissolved nutrient concentration and salinity. In addition, in large dry catchments, antecedent catchment soil moisture and vegetation had a large influence on dissolved nutrients, which highlights the important effect of catchment hydrological connectivity on pollutant mobilisation and delivery.

Diatom responses to river water quality in the Kruger National Park, South Africa

Background: Although the Kruger National Park (KNP) is a protected area, it is not exempted from anthropogenically induced impacts, which often compromise river water flow and quality. Measures of river water quality in South Africa have conventionally been based on water chemistry as well as different ecological indicator groups such as fish and macroinvertebrates. Diatoms have been shown to be useful indicators of changes in water quality resulting from pollution and land-use impacts.Objectives: To determine the applicability of diatoms for hind-casting water quality in the KNP and to compare recent diatom community composition with those from the 1980s.Methods: In this study, pH and electrical conductivity (EC) were used to evaluate temporal changes in water quality of three rivers within the KNP. Additionally, we made use of historic diatom samples from three of the five perennial rivers to evaluate if diatom communities reflected changes in water conditions between 1983 and 2015.Results: Diatom community structure was significantly different between 1983 and 2015. Diatom-based index scores (SPI) indicated an improvement in water quality for the Letaba and Olifants rivers.Conclusion: Diatoms were shown to be useful indicators of current water quality and are also useful for determining temporal changes.

Dynamic Hydraulics in a Drinking Water Distribution System Influence Suspended Particles and Turbidity, But Not Microbiology

Spatial and short-term temporal changes in water quality as a result of water age and fluctuating hydraulic conditions were investigated in a drinking water distribution system. Online measurements of total and intracellular adenosine tri-phosphate (ATP), total and intact cell concentrations measured with flow cytometry (FCM), turbidity, and particle counts were performed over five weeks at five subsequent locations of the distribution system. The high number of parallel FCM and ATP measurements revealed the combined effect of water age and final disinfection on spatial changes in microbiology in the system. The results underlined that regular daily dynamics in flow velocities are normal and inevitable in drinking water distribution systems, and significantly impact particle counts and turbidity. However, hydraulic conditions had no detectable impact on the concentration of suspended microbial cells. A weak correlation between flow velocity and ATP concentrations suggests incidental resuspension of particle-bound bacteria, presumably caused by either biofilm detachment or resuspension from sediment when flow velocities increase. The highly dynamic hydraulic conditions highlight the value of online monitoring tools for the meaningful description of short-term dynamics (day-scale) in drinking water distribution systems.

The performance of diatom indices in assessing temporal changes in water quality in a large lowland river ecosystem

AbstractBenthic diatoms are often included in bioassessment programs of river health as sensitive indicators of nutrient status and pollution. Many diatom‐based indices have been developed and are frequently used to infer conditions in water quality. However, concerns have been raised regarding the robustness of these indices in riverine systems that have natural variability in environmental conditions, including seasonal change of water quality parameters, especially in terms of physical and chemical characteristics of water, which also influence diatom community composition. Here, we used three diatom‐based indices (Diatom‐based eutrophication/pollution index, EPI‐D; Biological Diatom Index, IBD; Watanabe's Index, WAT), which have previously been validated as robust for water quality assessment in China, to explore their response to temporal changes in water quality and diatom community structure in a riverine network over time. Concentrations of total nitrogen (TN), nitrate nitrogen (NO3‐N), total phosphorus (TP), temperature (t), and turbidity in April 2010 were significantly higher than in November 2007. The 141 diatom taxa we found in April 2010 were fewer than the 194 taxa we found in November 2007. On both occasions, the three diatom indices responded to same water quality variables (phosphorus and chloride or nitrogen) as reported in previous studies. Of the three diatom indices tested, EPI‐D provided the most robust measure of natural seasonal changes in water quality and indicated the phosphorus and chloride. Our study confirms that these three diatom indices are effective for evaluating long‐term water quality in large rivers.

Daily changes in household water access and quality in urban slums undermine global safe water monitoring programmes.

Global drinking water monitoring programmes and studies on water quality in urban slums often overlook short-term temporal changes in water quality and health risks. The aim of this study was to quantify daily changes in household water access and quality in an urban slum in Malawi using a mixed-method approach. Household drinking water samples (n=371) were collected and monitored for E. coli in tandem with a water access questionnaire (n=481). E. coli concentrations in household drinking water changed daily, and no household had drinking water that was completely safe to drink every day. Seasonal changes in drinking water availability, intermittent supply, limited opening hours, and frequent breakdown of public water points contributed to poor access. Households relied on multiple water sources and regularly switched between sources to meet daily water needs. There were generally similar E. coli levels in water samples considered safe and unsafe by residents. This study provides the first empirical evidence that water quality, water access, and related health risks in urban slums change at much finer (daily) temporal scales than is conventionally monitored and reported globally. Our findings underscore that to advance progress towards Sustainable Development Goal (SDG) Target 6.1, it is necessary for global water monitoring initiatives to consider short-term changes in access and quality.

Predicting attenuation of salinized surface- and groundwater-resources from legacy energy development in the Prairie Pothole Region

Oil and gas (energy) development in the Williston Basin, which partly underlies the Prairie Pothole Region in central North America, has helped meet U.S. energy demand for decades. Historical handling and disposal practices of saline wastewater co-produced during energy development resulted in salinization of surface and groundwater at numerous legacy energy sites. Thirty years of monitoring (1988–2018) at Goose Lake, which has been producing since the 1960s, documents long-term spatial and temporal changes in water quality from legacy energy development. Surface water quality was highly variable and decoupled from changes in groundwater quality, likely due to annual and regional climatic fluctuations. Therefore, changes in surface water-quality were not considered a reliable indicator of subsurface chloride migration. However, chloride concentrations in monitoring wells near wastewater sources exhibited systematic temporal reductions allowing for estimates of the time required for natural attenuation of groundwater to U.S. Environmental Protection Agency acute and chronic chloride toxicity benchmarks and a local background level. Point attenuation rates differed based on sediment type (outwash vs till) and yielded a range of predicted years when water-quality targets will be reached: acute – 2045 to 2113; chronic – 2069 to 2160; background – 2126 to 2275. Bulk attenuation rates from four separate years of data were used to calculate the distances chloride could migrate downgradient from the largest wastewater source. Potential distances of downgradient migration before dilution to water-quality targets decreased from 1989 to 2018: acute – 949 to 673 m; chronic – 1220 to 922 m; background – 1878 to 1525 m. Several downgradient wetlands are within these distances and will continue to receive saline contaminated groundwater for years. While these results demonstrate chloride attenuation at a legacy energy site, they also highlight the persistence of saline wastewater contamination and the need to mitigate future spills to prevent long-term salinization from energy development.

A baseline analysis of coastal water quality of the port Honduras marine reserve, Belize: a critical habitat for sport fisheries

This analysis examines temporal changes in water quality of the Port Honduras Marine Reserve (PHMR), Belize from 1998 to 2015. Trends in dissolved oxygen (DO), salinity, temperature and pH were analyzed from ten sites throughout PHMR for statistically significant relationships. Maintaining satisfactory water quality is critical for sustaining healthy fisheries. PHMR represents a unique link between upland watersheds and coastal wetlands, mangroves, coral reefs, and seagrass beds. These ecosystems comprise important habitat for many fisheries including the economically valuable sport fish species of Megalops atlanticus (Atlantic tarpon), Albula vulpes (bonefish) and Trachinotus falcatus (permit). Sport fishing in the PHMR area has become increasingly popular in recent decades and is responsible for generating direct and indirect income opportunities for local communities, including Punta Gorda, the largest town in southern Belize. As a result, degradation of water quality of PHMR through land-based human activities could have ecological and economic consequences for southern Belize. The results of the analyses revealed significant seasonal variations and slight increasing trends in DO and salinity at several sampling sites. These relatively stable results are likely related to several factors including limited coastal development and low population density of southern Belize. This study provides baseline information for future research and outlines recommendations for management strategies of PHMR to mitigate impacts from current and future threats to water quality.

Assessment of water samples with complex compositions using microalgal bioassay based on the community level physiological profiling (CLPP)

The ability to effectively characterize the response of microalgal communities to changes in water quality is limited. Earlier, a microalgal bioassay was developed based on community level physiological profiling (CLPP). The efficacy of this assay was evaluated using three wetland water samples, a surface water sample, and two wastewater samples (i.e. primary and secondary), all collected from southwestern Ontario, Canada. In addition, the assay was applied to untreated and activated carbon treated oil sand process water (OSPW). YT (Yeast Identification Test Panel) and Biolog plates were successfully utilized for defined microalgal community under both heterotrophic and mixotrophic growth conditions to characterize the changes in the defined microalgal community due to the changes in water type. It was found that, although the degrees of changes in the algal community varied, all tested water samples were distinguished under both growth regimes using principal component analysis (PCA). The variations in the algal community were caused by the differences of the water samples. The response of the assay due to changes in the algal community caused by different waters was found to be very sensitive and could be used to differentiate different water bodies. It further can be used to monitor temporal changes of water quality of the same water body.

The assessment and prediction of temporal variations in surface water quality-a case study.

In order to optimize the processes of sampling, monitoring, and management, the initial aim of this paper was to develop a model for the definition and prediction of temporal changes of water quality. In the case of the Morava River Basin (Serbia), the patterns of temporal changes have been recognized by applying different multivariate statistical techniques. The results of the conducted cluster analysis are the indicators of the existence of the three monitoring periods: the low-water, transitional, and high-water periods, which is in accordance with changes in the water flow in the analyzed river basin. A possibility of reducing the initial data set and recognizing the main pollution sources was examined by carrying out the principal component/factor analysis. The results indicate that the natural factor has a dominant influence in temporal groups. In order to recognize the discriminatory water quality parameters, a discriminant analysis (DA) was carried out. Conducting the DA enabled a significant reduction in the data set by the extraction of two parameters (the water temperature and electrical conductivity). Furthermore, the artificial neural network technique was used for testing the possibility of predicting changes in the values of the discriminant factors in the monitoring periods. The reliability of this method for the prediction of temporal variations of both extracted parameters within all temporal clusters has been proven.

Discriminant analysis as a decision-making tool for geochemically fingerprinting sources of groundwater salinity

Concern over contamination of groundwater resources in areas impacted by anthropogenic activities has led to an increasing number of baseline groundwater quality surveys intended to provide context for interpreting water quality data. Flexible screening tools that can parse through these large, regional datasets to identify spatial or temporal changes in water quality are becoming more important to groundwater scientists. One such tool, developed from previous work by the authors, makes use of linear discriminant analysis (LDA) to identify the most probable source of chloride salinity in groundwater samples based on their geochemical fingerprints. Here, we applied the model to a dataset of shallow groundwater with known sources of contamination compiled from two studies of groundwater quality in Illinois: Panno et al. (2005) and Hwang et al. (2015). By predicting the source of salinity in groundwater samples for which the sources of contamination are known, we validated model prediction-accuracy. Results show high classification accuracy for groundwater samples impacted by basin brines (e.g. deep saline groundwater) and road salt (>80%), with diminishing success for those impacted by organic sources of chloride, such as septic effluent and animal waste. Posterior probabilities, a statistic inherent to LDA, provide a proxy for prediction confidence that enables the model to be used for assessment and accountability measures, such as identifying parties responsible for contamination. LDA is complementary to fingerprinting using halogen ratios (e.g. Cl/Br) because it implicitly relies on halogen ratios for classification decisions while providing a clearer, more quantitative classification of contamination sources. Our model is ideal for regional assessment or initial screening of salinity sources in groundwater because it makes use of commonly measured solute concentrations in publicly available water quality databases.

Water Quality Index, a Useful Tool for Evaluation of Danube River Raw Water

The Danube River is the major source of drinking water supply for the cities in the southern part of Romania. The study was a descriptive-analytical one and lasted for 9 month. Samples were taken monthly between March 2016 and November 2016. Six sampling sites were selected to evaluate the spatial and temporal changes of water quality along the river. The samples were analyzed based on the standard methods for the following parameters: pH, conductivity (EC), NH4+, NO3-, Cl -, suspended solids, PO43-, SO42-, metals (Fe, Cd, Cr, Pb, Ni, Hg, As, Zn, Cu, Mn). The obtained values were compared with those imposed by the Romanian environmental legislation. An efficient and simplified method to express the quality of water used for consumption is provided by the Water Quality Index (WQI). WQI reflects the quality of water in a single value by comparing data obtained from the investigation of a number of physico-chemical parameters to the existing limits. The evaluation of water quality was performed using the Water Quality Index of the Canadian Council of Ministries of the Environment (CCME WQI). Water quality indices were classified as: excellent, good, medium, bad and very bad. The results indicated the water quality classification as �good� in all six sampling selected sites.

Designing and Implementing a Network for Sensing Water Quality and Hydrology across Mountain to Urban Transitions

AbstractWater resources are increasingly impacted by growing human populations, land use, and climate changes, and complex interactions among biophysical processes. In an effort to better understand these factors in semiarid northern Utah, United States, we created a real‐time observatory consisting of sensors deployed at aquatic and terrestrial stations to monitor water quality, water inputs, and outputs along mountain to urban gradients. The Gradients Along Mountain to Urban Transitions (GAMUT) monitoring network spans three watersheds with similar climates and streams fed by mountain winter‐derived precipitation, but that differ in urbanization level, land use, and biophysical characteristics. The aquatic monitoring stations in the GAMUT network include sensors to measure chemical (dissolved oxygen, specific conductance, pH, nitrate, and dissolved organic matter), physical (stage, temperature, and turbidity), and biological components (chlorophyll‐a and phycocyanin). We present the logistics of designing, implementing, and maintaining the network; quality assurance and control of numerous, large datasets; and data acquisition, dissemination, and visualization. Data from GAMUT reveal spatial differences in water quality due to urbanization and built infrastructure; capture rapid temporal changes in water quality due to anthropogenic activity; and identify changes in biological structure, each of which are demonstrated via case study datasets.

The impacts of environmental variables on water reflectance measured using a lightweight unmanned aerial vehicle (UAV)-based spectrometer system

Remote sensing methods to study spatial and temporal changes in water quality using satellite or aerial imagery are limited by the inherently low reflectance signal of water across the visible and near infrared spectrum, as well as environmental variables such as surface scattering effects (sun glint), substrate and aquatic vegetation reflectance, and atmospheric effects. This study exploits the low altitude, high-resolution remote sensing capabilities of unmanned aerial vehicle (UAV) platforms to examine the major environmental variables that affect water reflectance acquisition, without the confounding influence of atmospheric effects typical of higher-altitude platforms. After observation and analysis, we found: (1) multiple water spectra measured at the same location had a standard deviation of 10.4%; (2) water spectra changes associated with increasing altitude from 20m to 100m were negligible; (3) the difference between mean reflectance at three off-shore locations in an urban water body reached 29.9%; (4) water bottom visibility increased water reflectance by 20.1% in near shore areas compared to deep water spectra in a clear water lake; (5) emergent plants caused the water spectra to shift towards a shape that is characteristic of vegetation, whereas submerged vegetation showed limited effect on water spectra in the studied lake; (6) cloud and sun glint had major effects and caused water spectra to change abruptly; while glint and shadow effects on spectra may balance each other under certain conditions, the water reflectance can also be unpredictable at times due to wave effects and their effects on lines-of-site to calm water; (7) water spectra collected under a variety of different conditions (e.g. multiple locations, waves) resulted in weaker regression models compared to spectra collected under ideal conditions (e.g. single location, no wave), although the resulting model coefficients were relatively stable. The methods and results from this study contribute to better understanding of water reflectance acquisition using remote sensing, and can be applied in UAV-based water quality assessment or to aid in validation of higher altitude imagery.