Changes In Lake Water Quality Research Articles

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems

Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water quality parameters in which their accurately in-situ measurements are impossible and face difficulties. Using a rich water quality dataset spanned from 1980 to 2023, we employed four machine learning-based models to estimate the British Colombia WQI (BCWQI) in the Lake Päijänne, Finland, without parameters like chemical oxygen demand (COD) and total phosphorus (TP). Measurement of both COD and TP is time-consuming, needs laboratory equipment and labor costs, and faces sampling-related difficulties. Our results suggest the machine learning-based models successfully estimate the BCWQI in Lake Päijänne when TP and COD are omitted from the dataset. The long-short term memory model is the least sensitive model to exclusion of COD and TP from inputs. This model with the coefficient of determination and root-mean squared error of 0.91 and 0.11, respectively, outperforms the support vector regression, random forest, and neural network models in real-time estimation of the BCWQI in Lake Päijänne. Incorporation of BCWQI with the machine learning-based models could enhance assessment of overall quality of inland-waters with a limited database in a more economical and time-saving way. Our proposed method is an effort to replace the traditional offline water quality assessment tools with a real-time model and improve understanding of decision-makers on the effectiveness of management practices on the changes in lake water quality.

Seasonal and interannual changes (2005-2021) of lake water quality and the implications for sustainable management in a rapidly growing metropolitan region, central China.

A series of restoration measures such as municipal wastewater treatment and aquaculture closures have been implemented in Wuhan City during recent years. In order to explore the impact of restoration measures and climate change on lake water quality, long-term (2005-2021) water quality data of 47 lakes were explored to reveal spatiotemporal changes in lake water quality. Percentages of polluted lakes were calculated according to six water-quality parameters, including total phosphorus (TP), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biological oxygen demand (BOD), chemical oxygen demand using potassium permanganate as oxidant (CODMn) and petroleum contamination (PET), at interannual and monthly timescales. At the interannual timescale, percentages of COD, BOD, CODMn and PET pollution decreased significantly, suggestive of water quality improvement during recent years. At the monthly timescale, low percentages of NH3-N and BOD pollution in March 2020 probably resulted from the sharp reduction in human activities during the COVID-19 lockdown. At the monthly timescale, temperature was positively correlated with percentage of CODMn pollution, but negatively correlated with percentage of NH3-N pollution; precipitation was negatively correlated with percentage of BOD pollution. The similarity of water-quality parameters generally decreased with an increase in geographical distance between each pair of lakes. However, the regression coefficients between the similarity of lake water quality and the geographical distance decreased with time, probably resulting from enhanced similarity of water quality parameters among all lakes with rapid urbanization. Our results highlight the importance of active restoration measures for sustainable management of lakes in Wuhan City, as well as in similar developing regions.

Restore polder and aquaculture enclosure to the lake: Balancing environmental protection and economic growth for sustainable development

The restoration of lakes and their buffer zones is crucial for understanding the intricate interplay between human activities and natural ecosystems resulting from the implementation of environmental policies. In this study, we investigated the ecological restoration of shallow lakes and buffer zones in the Yangtze-Huaihe River Basin, specifically focusing on the removal of polder and aquaculture enclosure areas within the lakes. By examining data from eight shallow lakes and their corresponding buffer zones, encompassing lake morphology, water quality parameters, and land use/land cover (LULC) data spanning from 2008 to 2022, which shed light on the complex relationships involved. During the process of restoring polder and aquaculture enclosure areas, we observed a general decrease in the extent of polders and aquaculture enclosures within the lakes. Notably, the removal of aquaculture enclosures had a more pronounced effect (reduction rate of 83.37 %) compared to the withdrawal of polders (reduction rate of 48.76 %). Linear regression analysis revealed a significant decrease in the concentrations of seven water quality parameters, including COD, CODMn, TN, TP, NH3-N, Chl-a, and F, while pH and DO factors exhibit a distinct increasing trend. The results of redundancy analysis and Pearson correlation analysis demonstrated significant correlations between the area of polders and aquaculture enclosures and the changes in lake water quality. Encouragingly, the withdrawal of polders and the removal of aquaculture enclosures had a positive impact on the lake water quality improvement. In contrast, the LULC in the buffer zones of the lakes experienced a gradual decline owing to land degradation, resulting in a reduction in ecosystem service value (ESV). These results offer valuable support for policymakers in their endeavors to restore lake water quality, mitigate the degradation of buffer zones land, and promote the sustainable development of land and water resources.

Ecosystem changes in eight Danish lakes after zebra mussel invasion

AbstractInvasion of zebra mussels (Dreissena polymorpha) can have profound effects on lake ecosystems. We investigated the overall ecological effects after invasion and fast expansion of zebra mussels in eight lakes in Denmark belonging to the same watercourse systems but with different morphological and eutrophication characteristics. A few years after the invasion, most of the lakes had experienced profound changes in lake water quality, e.g. chlorophyll a had been reduced by 18–62% and Secchi depth had increased by 38–171%. Nutrient concentrations also decreased, total phosphorus to 37–64% and total nitrogen to 49–77% of pre-invasion concentrations. Seasonally, differences between both summer and winter phosphorus and nitrogen concentrations diminished, suggesting a change in internal nutrient cycling after the invasion. In most lakes, the abundance of submerged macrophytes rose substantially, and often coverage increased by a factor 10 or more, and the maximum colonisation depth increased by up to 5.4 m. Plant species numbers increased markedly in four of the six lakes with macrophyte data. The fish community changed towards higher dominance of potential piscivorous perch and an increase in their body size. The profound effects of zebra mussel invasion may affect lake management and how ecological quality should be interpreted.

Investigating the Impact of Wildfires on Lake Water Quality Using Earth Observation Satellites

A study was carried out to investigate the effects of wildfires on lake water quality using a source dataset of 2024 lakes worldwide, covering different lake types and ecological settings. Satellite-derived datasets (Lakes_cci and Fire_cci) were used and a Source Pathway Receptor approach applied which was conceptually represented by fires (burned area) as a source, precipitation/drought representing transport dynamics, and lakes as the ultimate receptor. This identified 106 lakes worldwide that are likely prone to be impacted by wildfires via a terrestrial pathway. Satellite-derived chlorophyll-a (Chl-a) and turbidity variables were used as indicators to detect changes in lake water quality potentially induced by wildfires over a four-year period. The lakes with the largest catchment areas burned and characterized by regular annual fires were located in Africa. Evidence for a strong influence of wildfires was not found across the dataset examined, although clearer responses were seen for some individual lakes. However, among the hydro-morphological characteristics examined, lake depth was found to be significant in determining Chl-a concentration peaks which were higher in shallow and lower in deep lakes. Lake turbidity responses indicated a dependence on lake catchment and weather conditions. While wildfires are likely to contribute to the nutrient load of lakes as found in previous studies, it is possible that in many cases it is not a dominant pressure and that its manifestation as a signal in lake Chl-a or turbidity values depends to a large part on lake typology and catchment characteristics. Assessment of lake water quality changes six months after a fire showed that Chl-a concentrations either increased, decreased, or showed no changes in a similar number of lakes, indicating that a lake specific ecological and hydro-morphological context is important for understanding lake responses to wildfires.

Anthropogenic stressor impacts on hypolimnetic dissolved oxygen in Lake Erie: A chironomid-based paleolimnological assessment

The central basin of Lake Erie is annually subject to hypolimnetic hypoxia, which affects biochemical processes and aquatic biota. Since European settlement, water quality in Lake Erie has degraded due to land-use changes within its catchment, cultural eutrophication, climate change, and the effects of invasive species. As limnological monitoring data for Lake Erie are largely unavailable prior to the 1970s, paleolimnological methods were used to infer long-term trends in hypolimnetic dissolved oxygen. Changes in lake water quality affect benthic community composition, and those communities can be used as indicators of long-term environmental changes, particularly those that affect hypolimnetic oxygen concentrations. Chironomid subfossil remains preserved in dated sediment cores indicated that the hypolimnion of the central basin was exhibiting low oxygen conditions prior to major Euro-American settlement impacts, and it has been mesotrophic to eutrophic since ∼1850. The disappearance of oxic-type taxa and a transition towards anoxic-tolerant chironomid communities by the 1950s suggest that the severity and duration of hypolimnetic anoxia has increased in recent decades. Variance partitioning analysis (VPA) indicated that both land use and climate variables were significant drivers of these changes in chironomid assemblages in the central basin.

Research Progress on Remote Sensing Monitoring of Lake Water Quality Parameters

Lakes are an important component of the hydrosphere and are important freshwater resources. The water environment of lakes has become increasingly polluted, and monitoring the dynamic changes in lake water quality is of great significance for ecological environment protection. Remote sensing can provide technical support for lake water quality monitoring, overcoming the low-cost and poor timeliness characteristics of manual sampling; thus, it has been widely used in lake water quality monitoring. Remote sensing can be used to monitor many indicators, including suspended solids, chlorophyll a, soluble organic matter, dissolved oxygen, transparency, etc. Although remote sensing provides a new method for lake water quality monitoring, there are still some problems in practical application. ① It is difficult to accurately retrieve the component changes in different substances in lake water from the signals received by remote sensing, resulting in the limitation of remote sensing accuracy. Atmospheric correction can eliminate the images reflected by factors such as atmosphere and light. In order to improve the accuracy of water quality monitoring, higher-accuracy atmospheric correction algorithms are needed. However, at present the atmospheric correction algorithm is not mature enough and lacks the portability between sensors. Therefore, atmospheric correction is still a difficult problem of remote sensing retrieval in lake water quality. ② Due to seasonal and spatial constraints, there are differences in surface optical properties of different lakes and biological optical properties, resulting in changes in remote sensing reflectance. There is also a lack of portability of the model established by using limited measured data. ③ The interference of aquatic plants and external forces (wind, fish, etc.) causes the error between the measured data and the model estimation, and the synchronization of the data is difficult to guarantee, which will introduce large errors to the lake water quality model, resulting in a decrease in the reliability of the model. ④ The spatio-temporal scale of measured data and remote sensing data do not match, and it is difficult to capture dynamic and fine changes in water quality. More precise observation of water quality is needed that can capture rapid changes in lakes. However, it is still challenging to obtain real-time measured data that meet the requirements. Therefore, it is necessary to further understand the spectral characteristics of water quality parameters, combining multi-source data and other hydrological models. In the future, a retrieval algorithm with low dependence will be developed, and migrated models will be constructed to break the regional limitations of the model. Additionally, remote sensing promotes the operational development and early warning for the water quality of lakes.

Long‐Term Changes and Influencing Factors of Water Quality in Aquaculture Dominated Lakes Unveiled by Sediment Records and Time Series Remote Sensing Images

AbstractHydraulic connectivity has great effects on water quality. Enclosure aquaculture can largely alter lake flow regime and thus deteriorate water quality. Understanding the dynamics and influencing factors of water quality in enclosure aquaculture lakes is of great significance to ecosystem restoration of degraded lakes. However, it remains challenging due to the lack of long time series data. In this study, the dynamics of water quality in aquaculture dominated lakes were captured through 210Pb and 137Cs dating based on sediment records. Meanwhile, the effects of landscape pattern within aquaculture lakes on water quality were revealed by long time series of remote sensing images. Results showed the 210Pb and 137Cs sediment dating could provide an effective way to obtain long‐term series of lake water quality data in the unmonitored area. The contents of lake sediment nutrients showed an upward trend from 1960 to 2018. The transformation of lakes from agriculture dominated to aquaculture dominated had increased sediment nutrients level. The long‐term changes of lake sediment nutrients could be well explained by the landscape pattern metrics within aquaculture lakes, with an average explain power of 87.6%. The configuration metrics at class level had the most contribution (73.6%) to the changes of lake sediment nutrients, followed by the composition metrics (48.8%) and the configuration metrics at landscape level (33.4%). This study can provide a promising method to understand water quality changes in lakes with no historical monitoring data available and is of great benefit to water quality management in aquaculture dominated lakes.

Worldwide moderate-resolution mapping of lake surface chl-a reveals variable responses to global change (1997–2020)

Anthropogenic activity is leading to widespread changes in lake water quality—a key contributor to socio-ecological health. But, the anthropogenic forces affecting lake water quality (climate change, land use change, and invasive species) are unevenly distributed across lakes, across the seasonal cycle, and across space within lakes, potentially leading to highly variable water quality responses that are poorly documented at the global scale. Here, we used 742 million chlorophyll-a (chl-a) estimates merged over 6 satellite sensors (daily, 1 to 4 km resolution) to quantify water quality changes from 1997 to 2020 in 344 globally-distributed large lakes. Chl-a decreased across 56% of the cumulative total lake area, challenging the putative widespread increase in chl-a that is expected due to human activity. 19% of lakes exhibited both positive and negative chl-a trends (p-value < 0.1) across different locations or times of the year. This spatiotemporal complexity demonstrates the value of moderate resolution mapping of lake chl-a to inform water management decision-making and to determine the local ecological consequences of human activity.

Long-Term Changes in Relationship between Water Level and Precipitation in Lake Yamanaka

Lake water levels fluctuate due to both natural and anthropogenic influences. Climate change can alter precipitation, driving fluctuations in lake water levels. Extreme fluctuations can cause flooding, water shortages, and changes in lake water quality and ecosystems, as well as affecting fisheries and tourism. Despite the need to predict future water-level rises, especially in the context of climate change, long-term hydrological studies are scarce. Here, we analyzed 93 years of data from 1928 to 2020 to identify changes in the relationship between water level and precipitation in Lake Yamanaka, Japan. We found that the six-day maximum rise in water level for the same six-day maximum precipitation was significantly greater in the later period than in the earlier period; the difference increased with increasing precipitation. Particularly large increases in precipitation were sometimes caused by a single event or by multiple events occurring in succession.

Zooplankton communities in Precambrian Shield lakes (Quebec, Canada): responses to spatial and temporal gradients in water chemistry and climate

Zooplankton are relevant indicators of changes in lake water quality, used for monitoring the response of aquatic ecosystems to the combined effects of declining acidic deposition and rising air temperatures. First, the current landscape was defined from the recent (2017) spatial patterns of zooplankton communities in 73 Quebec lakes distributed over an 800-km SW–NE gradient, spanning a wide range of water quality, climate, and morphometric characteristics. On a large scale, we identified among-lake clustering of three types of zooplankton assemblages and variation in species composition at fine scale between lake pairs. Dissimilarity in zooplankton assemblages among lake pairs were best correlated (r > 0.400, p < 0.001) with their difference in air temperature, pH, and calcium, reflecting spatial gradients in climate and lake acid–base status. Second, to examine long-term response in the zooplankton community, we compared acidification indicators and abundance of taxa for a subset of 19 lakes sampled in 1982 and 2017. Despite an average threefold drop in sulfate concentration, changes in calcium and pH were relatively small, and consequently, no major changes in zooplankton assemblages were detected since 1982.

Water quality assessment of natural lakes and its importance: An overview

The proportion of freshwater on earth’s surface is only 2.5% of which only 1% is accessible for use. In this context, lakes are one of the most important water resources and have been used as a source of water supply for human consumption and in general accounts for about 0.3% of the total surface water body sources. As such, the conditions of lakes have been in constant deterioration due to increased anthropogenic activities surrounding them. In principle, the quality of lake water (or other surface sources) is evaluated using various physico-chemical and biological parameters selected on the Designated Best Use (DBU) of the water body (lake) for various purposes. Consequently, the use of Water Quality Index (WQI) is an important tool used for designating the quality of lake water. In general, natural lakes are confined bodies of water lacking a strong flow for self-cleansing of its water and therefore leading to accumulation of various impurities. In such cases, the quality of these impurities are determined using different indices like Heavy Metal Index (for heavy metals), eutrophication potential (due to nutrients) and other associated indices system. The determination of existing properties helps in determination of future trends of such pollutants and thereby the quality of the lake water in future scenario. Different modelling techniques are used for prediction of futuristic changes in lake water quality including watershed models, ground water models and lake models. The present study gives an overview and critically evaluates the literature on all aspects of water quality to give an insight of the various tools and techniques used for complete water quality monitoring and management.

Potential anthropogenic regime shifts in three freshwater lakes in Tropical East Asia

Abstract Regime shifts in ecology are characterised by major, often abrupt changes in ecosystem structure and functioning in response to one or more driving variables, or pressures. Changes in the provision of ecosystem services are a potential outcome. Despite the current combination of rapidly increasing pressures on what are often highly important socio‐ecological systems, the resilience of lakes in the warm tropics to human perturbation is far less well understood than those at higher latitudes. This paper focuses on evidence of aquatic ecosystem change from a cluster of three deep, freshwater, volcanic crater lakes (Yambo, Mohicap, and Sampaloc) at low altitude on the island of Luzon, Philippines. The lakes support different intensities of aquaculture, an important livelihood but also a driver of poor water quality throughout tropical Asia. Measured and monitored climate and water quality data, in addition to sedimentary evidence from sediment cores collected from the three study lakes, were used to determine the magnitude and trajectory of changes in lake water quality. Sediment cores were radiometrically dated and analysed for organic matter, spheroidal carbonaceous particles, and diatom remains. Diatom data were zoned numerically using cluster analysis. Diatom remains were also used to infer past variations in pH and possible relationships between potential driving climatic variables (temperature and rainfall). Diatom data sets were explored using detrended component analysis and principle component analysis. Despite differences in intensity of aquaculture, a common trajectory and timing of a potential regime shift, characterised by a replacement of benthic with planktonic diatoms and an increase in diatom accumulation rates from the early to mid‐1980s, is evident, and attests a low threshold for disturbance effects. A predominantly planktonic diatom flora has persisted even after recent improvements in environmental quality. The potential new regime may be less resilient and more susceptible to harmful algal blooms, abrupt expansions of anoxic conditions, and periodic mass fish kills when compared with its former state. The research further highlights the sensitivity of freshwater ecosystems in the warm tropics to disturbance pressures, and the risks to livelihoods, ecosystem services, and sustainable development.

Integrating multisensor satellite data merging and image reconstruction in support of machine learning for better water quality management

Monitoring water quality changes in lakes, reservoirs, estuaries, and coastal waters is critical in response to the needs for sustainable development. This study develops a remote sensing-based multiscale modeling system by integrating multi-sensor satellite data merging and image reconstruction algorithms in support of feature extraction with machine learning leading to automate continuous water quality monitoring in environmentally sensitive regions. This new Earth observation platform, termed “cross-mission data merging and image reconstruction with machine learning” (CDMIM), is capable of merging multiple satellite imageries to provide daily water quality monitoring through a series of image processing, enhancement, reconstruction, and data mining/machine learning techniques. Two existing key algorithms, including Spectral Information Adaptation and Synthesis Scheme (SIASS) and SMart Information Reconstruction (SMIR), are highlighted to support feature extraction and content-based mapping. Whereas SIASS can support various data merging efforts to merge images collected from cross-mission satellite sensors, SMIR can overcome data gaps by reconstructing the information of value-missing pixels due to impacts such as cloud obstruction. Practical implementation of CDMIM was assessed by predicting the water quality over seasons in terms of the concentrations of nutrients and chlorophyll-a, as well as water clarity in Lake Nicaragua, providing synergistic efforts to better monitor the aquatic environment and offer insightful lake watershed management strategies.

Combining expert elicitation and stated preference methods to value ecosystem services from improved lake water quality

With increasing attention on the contribution of ecosystems to human well-being, there is a need for tools that integrate ecological and economic models for valuing ecosystem services. To address this, we develop a protocol for linking ecological processes and outcomes to human preferences, which combines environmental modeling, expert elicitation, and nonmarket valuation methods. Our application values reductions in nutrient loads to lakes in the southeastern US. The innovation centers on how biochemical measures of water quality (e.g., chlorophyll a) are translated into terms that are meaningful to individuals who derive ecosystem services from them. Using expert elicitation data, we estimate a model linking changes in biochemical measures to an index of eutrophication in lakes. We then develop a stated preference survey including (a) detailed descriptions of the perceptible outcomes – e.g., water color, clarity – associated each eutrophication index level; and (b) policy scenarios involving state-level changes in lake eutrophication conditions. We estimate a function that predicts households' willingness to pay for changes in lake water quality. We demonstrate the protocol through a case study examining the benefits of lake quality improvement in Virginia as a result of recent policies to reduce nutrient loads in the Chesapeake Bay watershed.

Unexpected Response of High Alpine Lake Waters to Climate Warming

Over the past two decades, we have observed a substantial rise in solute concentration at two remote high mountain lakes in catchments of metamorphic rocks in the European Alps. At Rasass See, the electrical conductivity increased 18-fold. Unexpectedly high nickel concentrations at Rasass See, which exceeded the limit in drinking water by more than 1 order of magnitude, cannot be related to catchment geology. We attribute these changes in lake water quality to solute release from the ice of an active rock glacier in the catchment as a response to climate warming. Similar processes occurred at the higher elevation lake Schwarzsee ob Sölden, where electrical conductivity has risen 3-fold during the past two decades.

Combined effects of best management practices on water quality in oxbow lakes from agricultural watersheds

Water quality conditions in three oxbow lakes were examined before and after best management practices (BMPs) implementation within the Mississippi Delta. Experimental design called for the development of structural and cultural treatments to reduce sediment and associated pollutants entering watershed oxbow lakes. Three watersheds were selected and developed with different levels of BMPs. Changes in lake water quality were used as measures of management success. Analyses of water quality data prior to the implementation of BMPs suggested the lakes were stressed and ecologically damaged due to excessive sediment inflow. Significant improvements in water quality were observed with the use of cultural and structural BMPs. Sediments decreased 34–59%, while Secchi visibility and chlorophyll generally increased. The most dramatic improvements in water quality occurred in the two watersheds that featured cultural practices and combinations of cultural and structural practices. Reducing suspended sediment concentrations in these oxbow lakes favored phytoplankton production resulting in increased chlorophyll concentrations and higher concentrations of dissolved oxygen. Cultural BMPs, more so than structural BMPs, play a vital role in improving lake water quality, and are needed in addition to structural measures to ensure improved water quality in oxbow lakes receiving agricultural runoff.

Classification of the ecological status of volcanic lakes in Central Italy

A synthesis is made of biological data collected in the last three decades on five volcanic lakes in Central Italy with the aim of evaluating their environmental status by means of biological parameters related to zooplankton, littoral and profundal zoobenthos frequently used to detect water quality changes in lakes. A number of bioindicators and bioindices were selected for this purpose, as far as possible following an integrated approach using information drawn from physical and chemical variables. Our results allowed the lakes to be classified according to their biological quality level, which proved to be in good agreement with physical and chemical diagnoses. Lake Bracciano exhibited the best environmental quality, due to the presence of a ring waste water collecting system, to its large size and depth, and to its strong hydrodynamism. Lake Martignano followed, with some symptoms of stress in the hypolimnion due to a marked summer deoxygenation. Oxygen depletion in the profundal characterized also Lake Vico, which showed a mesotrophic condition in the sixties, and 20 years later now shows clear signs of increased trophy (meso-eutrophy). Lake Albano seemed meso-eutrophic with total absence of fauna below a depth of 120 m due to a meromictic status. Finally Lake Nemi, exposed to domestic wastes in the 70s, suffered a heavy eutrophication with dramatic algal blooms and fish kills. Following the diversion of discharges that occurred in the early 90s, today this lake is characterized by the partial improvement of many ecological features. The need for integration between physical and chemical analyses and biological data in order to obtain a reliable evaluation of lake environmental quality is stressed, especially as far as routine implementation in managing and recovery procedures is concerned.

近年の諏訪湖における生物群集の動態研究の意義

Studies of the organic community in Lake Suwa have been performed since 1907. During the long history of such studies, lake eutrophication reached serious levels in 1960s and 1970s, and eutrophication problems occurred. These studies have, therefore, reflected the changes in the community associated with lake eutrophication. In order to solve the resultant problems, a sewerage system was built in the lake catchment area in 1979, and the residential area covered by the system has increased since that time. Nevertheless, the lake water quality had not been markedly restored for about the last 20 years. Around 1997, however, the seasonal patterns in various parameters of the organic community started to change. This may indicate that ecosystem of Lake Suwa is changing associated with changes in lake water quality, which is being markedly restored. Therefore, since current studies are starting to show how the ecosystem responds to the water quality improvement, such studies should be intensified. To effectively conduct such studies in future, it is very important to review the results of recent studies on the organic community of the lake. For this purpose, five review papers were produced and are presented in this special issue. They concern chironomid populations, zooplankton, bloom-forming cyanobacteria and its toxins, and the fish community; all of which are characteristic of the Lake Suwa ecosystem. Three of them (papers on chironomids and zooplankton) are published in the present issue, while the remaining two will appear in the next issue.

Forecasting the changes in lake water quality in response to climate changes, using past relationships between meteorological conditions and water quality

In order to forecast the effects of global warming on the water environment, the relationship between meteorological conditions and lake water quality was investigated statistically using 17 years of monitoring data obtained from a shallow eutrophic lake, Lake Kasumigaura. The usefulness of the DPY (difference from the previous year) method was confirmed for removing the watershed change (e.g. land cover, population, etc.). From the analysis of the relationships between air temperature and water temperature on a monthly basis, the delay of time was seen to be negligible, but the gain was reduced due to the high frequency of change. As the amount of precipitation affected their relationship on a yearly basis, the slopes of 1·0–1·2 °C water temperature/ °C air temperature were determined with the DPY method by excluding the combinations of the years having large difference in annual precipitation. The deterioration of lake water quality, such as increases in COD (chemical oxygen demand) and decreases in transparency, was quantitatively assessed as corresponding to an increase in air temperature. In addition, we found that higher precipitation led to high nitrogen concentrations on a monthly basis, as well as on a yearly basis, probably induced by both the runoff of soilwater having high concentrations and the lowering of residence times of lake water. Copyright © 2000 John Wiley & Sons, Ltd.