Lake Surface Water Research Articles

Динамика площади зеркала горных озер бассейна реки Гунт (Памир, Таджикистан

The article discusses mountain lakes posing threat to downstream settlements and infrastructure based on the example of Lakes Rivakkul and Nimatskul in the Gunt River Basin. In recent decades, the number and area of lakes have been growing at an accelerated rate due to the shrinking of glaciers in the target basin home to over 600 such reservoirs. The elaboration of recommendations for the installation of early warning equipment to inform population about high-mountain lake outbursts is critical for the sustainable development of the Central Asian Region. The study aimed to investigate the surface area dynamics of 2 (two) mountain lakes in the Gunt River Basin during 2000-2019. Using remote sensing data, summary data were collected on their water supply, location and surface area. The paper presents the findings obtained based on Landsat 7-8 imagery (August and September 2000-2019). The harvested data showed that 2006 witnessed the maximum increase in the area of Lake Nimatskul, whereas the same was observed for Lake Rivakkul in 2010. During the study period (from 2000 to 2019), Lake Nimatskul demonstrated a gradual surface area decrease from 0.513 to 0.462 km2, while Lake Rivakkul remained more stable. It was established that the surface area dynamics of mountain lakes are closely related to meteorological parameters, and that surface and underground runoff stabilized lake surface area and water level.

Review on the Change Trend, Attribution Analysis, Retrieval, Simulation, and Prediction of Lake Surface Water Temperature

Lake surface water temperature (LSWT) is indicative of changes in climate and geomorphology. It has been found that LSWT has shown faster warming than air temperature in recent decades, which has greatly affected the aquatic ecosystem of lakes and even led to ecological collapse. It was mainly caused by climate warming and geomorphological changes caused by human activities. However, lakes with different properties respond differently to these changes, resulting in temporal and spatial heterogeneity in the changes of LSWT. After an extensive literature review, it was found that the research on LSWT is mainly focused on the following aspects: (1) qualitative or quantitative analysis of natural and anthropogenic factors affecting LSWT changes; (2) impacts of LSWT changes on lake ecology; (3) acquisition of LSWT data, such as retrieval based on remote sensing (RS) imagery, model-based simulation prediction; (4) study of temporal and spatial variation characteristics of LSWT long time series. Dynamically monitoring LSWT changes, predicting and quantifying the response of lakes with different properties to abrupt or gradual climate changes and changes in human activity intensity, can inform modeling of ecosystem response processes and long-term management planning of large freshwater ecosystems. Therefore, this paper provides a systematic review of LSWT from the above four aspects to provide empirical insight and methodological reference for conducting LSWT research.

IMPACT OF WASTEWATER ON SURFACE WATER QUALITY IN KENYIR LAKE BASIN, HULU TERENGGANU

Lake water ia an essential resource for livelihood things and the necessary for environment. Human activities affect of water quality, water quantity and alteration the ecosystem system.The sustainable use of lake water resource need more give attention and monitoring programs based on the systematic decision making and management tools. The purpose of this study was to assess the improper wastewater and its effluents discharged into surface lake water resources in Kenyir Lake Basin in order to determine the existing physical environment. A total 21 monitoring stations covering the study area (along the Kenyir Lake Basin) were selected for sampling fieldwork of three season from 2018 until 2019 (Wet Season (Augut 2018), Dry Season (March 2019) and Normal Season (July 2019). There are a few parameters for water quality characteristics were analyzed based on in-situ and ex-situ analysis. As a result, the mean values of mostly water quality paremeters more degrade during wet season compared dry season and normal season. This study proved the water quality status effects on the owing to lack of wastewater management along the lake basin but still in control situation. The policy, environmental knowledge and enforcement triggered for slowing the rate of ecosystem degradation. There are need for a precautionary approach in developing and implementing lake management interventions to protect them to sustain.

Relationship between Atmospheric Deposition of Nutrient (N and P) Concentration and Wind Direction in Lake Kivu Watershed, DR Congo Side

Recent researches have suggested that atmospheric depositions are a major source of nutrients to aquatic ecosystems. It is important to identify and quantify nutrients deposited into surface water and the relationship with wind direction and wind speed to understand the contributing sources of nutrient deposition to Lake Kivu. This study analyzed the relationship of the contribution of TP and TN from the atmospheric deposition with wind direction and wind speed during the period 2017-2019 using regression analysis. Atmospheric deposition of nutrients (TP and TN) and lake water were analyzed in the laboratory for TP and TN using standard analytical methods. Wind speed (m/s) and wind direction (o) were collected at Lwiro station using automatic sensor and gaps were filled by data downloaded from NASA/POWER SRB/FLASHFlux/MERRA2/GEOS website. Temporal variation of TN and TP atmospheric deposition rates is significantly different over time (p<0.000) at Lwiro station. Natural and anthropogenic activities in the watershed such as volcanic activities, biomass burning, and soil erosion introduce particles in the atmosphere following meteorological conditions and surface lake water becomes nutrients rich due to increasing nutrients input. It was observed that the average high rates of nutrients were coming more from the north part of the Lake (Goma) than other points. Volcanic and traffic activities were identified as being the main sources of nutrients in the north part of the watershed and appear to play an important role in the Lake eutrophication. The results can serve as a baseline as far as atmospheric nutrient loading sources in Lake Kivu watershed are concerned and suggest strategies for future assessment.

Enhanced Warming in Global Dryland Lakes and Its Drivers

Lake surface water temperature (LSWT) is sensitive to climate change. Previous studies have found that LSWT warming is occurring on a global scale and is expected to continue in the future. Recently, new global LSWT data products have been generated using satellite remote sensing, which provides an inimitable opportunity to study the LSWT response to global warming. Based on the satellite observations, we found that the warming rate of global lakes is uneven, with apparent regional differences. Indeed, comparing the LSWT warming in different climate zones (from arid to humid), the lakes in drylands experienced more significant warming (0.28 °C decade−1) than those in semi-humid and humid regions (0.19 °C decade−1) during previous decades (1995–2016). By further quantifying the impact factors, it showed that the LSWT warming is attributed to air temperature (74.4%), evaporation (4.1%), wind (9.9%), cloudiness (4.3%), net shortwave (3.1%), and net longwave (4.0%) over the lake surface. Air temperature is the main driving force for the warming of most global lakes, so the first estimate quantification of future LSWT trends can be determined from air temperature projections. By the end of the 21st century, the summer air temperature would warm up to 1.0 °C (SSP1-2.6) and 6.3 °C (SSP5-8.5) over lakes, with a more significant warming trend over the dryland lakes. Combined with their higher warming sensitivity, the excess summer LSWT warming in drylands is expected to continue, which is of great significance because of their high relevance in these water-limited regions.

The Effect of Climate Changes on The Fluctuation of The Water Level of Al- Razzaza Lake, Iraq

One of the serious environmental challenges that Iraq faces is climate changes and impacts of changing weather patterns and extreme global weather events. This paper addresses changes in the temporal and spatial characteristics of water levels of Razzaza Lake and response to climatic changes using archived series of Multispectral satellite images Landsat. TM, ETM+ and OLI images acquired on 1990, 2000 and of 2016. In order to extract, mapping the water surface area of the Razzaza Lake, Multispectral spectral band rationing the Normalized Difference Water Index (NDWI) technique was adopted, and the climatic elements data for the period (1990-2016) were analyzed which provide significant information of surface water. The results show that Razzaza Lake has a particularly sharp change rate in the water level and there are significant fluctuations on lake level and water surface area over the time.

SELF v1.0: a minimal physical model for predicting time of freeze-up in lakes

Abstract. Predicting the freezing time in lakes is achieved by means of complex mechanistic models or by simplified statistical regressions considering integral quantities. Here, we propose a minimal model (SELF) built on sound physical grounds that focuses on the pre-freezing period that goes from mixed conditions (lake temperature at 4 ∘C) to the formation of ice (0 ∘C at the surface) in dimictic lakes. The model is based on the energy balance involving the two main processes governing the inverse stratification dynamics: cooling of water due to heat loss and wind-driven mixing of the surface layer. They play opposite roles in determining the time required for ice formation and contribute to the large interannual variability observed in ice phenology. More intense cooling does indeed accelerate the rate of decrease of lake surface water temperature (LSWT), while stronger wind deepens the surface layer, increasing the heat capacity and thus reducing the rate of decrease of LSWT. A statistical characterization of the process is obtained with a Monte Carlo simulation considering random sequences of the energy fluxes. The results, interpreted through an approximate analytical solution of the minimal model, elucidate the general tendency of the system, suggesting a power law dependence of the pre-freezing duration on the energy fluxes. This simple yet physically based model is characterized by a single calibration parameter, the efficiency of the wind energy transfer to the change of potential energy in the lake. Thus, SELF can be used as a prognostic tool for the phenology of lake freezing.

Groundwater recharge pathway according to the environmental isotope: the case of Changwu area, Yangtze River Delta Region of China

Abstract Groundwater recharge is an important factor affecting water circulation. As groundwater has slow seepage, directly observing the seepage velocity and recharge path of groundwater in the aquifer is difficult. Environmental isotope technology has become an important means to clarify the mechanism of groundwater movement and the mechanism by which groundwater recharges from the micro and macro perspectives. The Changwu area of Jiangsu Province was taken as an example to identify the recharge sources of groundwater and the recharge paths of groundwater and surface water by using the measured data of isotopes D, 18O, 34S, and T. The results indicated that the shallow aquifer and the I confined aquifer in the Changwu area are mainly recharged by precipitation and surface lake water. The II confined aquifer along the Yangtze River is recharged by modern precipitation. Moreover, the II confined aquifer in the Henglin area was recharged by the ancient Yangtze River before 4,000 years ago, and no recharge relationship exists now. the recharge condition of the II confined aquifer around the northwest of Gehu Lake is in the climate environment of 8,000 years ago and was caused by the surface depression lake water at that time. Additionally, the concealed limestone aquifer is primarily supplied by the II confined aquifer, while the concealed sandstone aquifer supplies the II confined aquifer. Hence, to find out the recharge conditions of groundwater aquifers based on the environmental isotope is conducive to scientific and reasonable evaluation of groundwater resources and to ensure the sustainable development and utilization of groundwater resources.

Forecasting Development of Mine Pit Lake Water Surface Levels Based on Time Series Analysis and Neural Networks

Forecasting Development of Mine Pit Lake Water Surface Levels Based on Time Series Analysis and Neural Networks

Smoothing spatio-temporal data with complex missing data patterns

We consider spatio-temporal data and functional data with spatial dependence, characterized by complicated missing data patterns. We propose a new method capable to efficiently handle these data structures, including the case where data are missing over large portions of the spatio-temporal domain. The method is based on regression with partial differential equation regularization. The proposed model can accurately deal with data scattered over domains with irregular shapes and can accurately estimate fields exhibiting complicated local features. We demonstrate the consistency and asymptotic normality of the estimators. Moreover, we illustrate the good performances of the method in simulations studies, considering different missing data scenarios, from sparse data to more challenging scenarios where the data are missing over large portions of the spatial and temporal domains and the missing data are clustered in space and/or in time. The proposed method is compared to competing techniques, considering predictive accuracy and uncertainty quantification measures. Finally, we show an application to the analysis of lake surface water temperature data, that further illustrates the ability of the method to handle data featuring complicated patterns of missingness and highlights its potentiality for environmental studies.

A Slight Temperature Warming Trend Occurred over Lake Ontario from 2001 to 2018

Satellite-derived lake surface water temperature (LSWT) measurements can be used for monitoring purposes. However, analyses based on the LSWT of Lake Ontario and the surrounding land surface temperature (LST) are scarce in the current literature. First, we provide an evaluation of the commonly used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived LSWT/LST (MOD11A1 and MYD11A1) using in situ measurements near the area of where Lake Ontario, the St. Lawrence River and the Rideau Canal meet. The MODIS datasets agreed well with ground sites measurements from 2015–2017, with an R2 consistently over 0.90. Among the different ground measurement sites, the best results were achieved for Hill Island, with a correlation of 0.99 and centered root mean square difference (RMSD) of 0.73 K for Aqua/MYD nighttime. The validated MODIS datasets were used to analyze the temperature trend over the study area from 2001 to 2018, through a linear regression method with a Mann–Kendall test. A slight warming trend was found, with 95% confidence over the ground sites from 2003 to 2012 for the MYD11A1-Night datasets. The warming trend for the whole region, including both the lake and the land, was about 0.17 K year−1 for the MYD11A1 datasets during 2003–2012, whereas it was about 0.06 K year−1 during 2003–2018. There was also a spatial pattern of warming, but the trend for the lake region was not obviously different from that of the land region. For the monthly trends, the warming trends for September and October from 2013 to 2018 are much more apparent than those of other months.

Effects of Meteorological Parameters on Surface Water Loss in Burdur Lake, Turkey over 34 Years Landsat Google Earth Engine Time-Series

The current work aims to examine the effect of meteorological parameters as well as the temporal variation on the Burdur Lake surface water body areas in Turkey. The data for the surface area of Burdur Lake was collected over 34 years between 1984 and 2019 by Google Earth Engine. The seasonal variation in the water bodies area was collected using our proposed extraction method and 570 Landsat images. The reduction in the total area of the lake was observed between 206.6 km2 in 1984 to 125.5 km2 in 2019. The vegetation cover and meteorological parameters collected that affect the observed variation of surface water bodies for the same area include precipitation, evapotranspiration, albedo, radiation, and temperature. The selected meteorological variables influence the reduction in lake area directly during various seasons. Correlations showed a strong positive or negative significant relationship between the reduction and the selected meteorological variables. A factor analysis provided three components that explain 82.15% of the total variation in the data. The data provide valuable references for decision makers to develop sustainable agriculture and industrial water use policies to preserve water resources as well as cope with potential climate changes.

Temporal and spatial heterogeneity of recent lake surface water temperature trends in the Qinghai-Tibet Plateau

Lake surface water temperature (LSWT) monitoring is significant as it provides valuable information on climate changes and resultant changes in lakes. Here, monthly moderate resolution imaging spectroradiometer LSWT data of 364 lakes during 2001–2015 were analysed to determine spatiotemporal patterns of daytime (LSWTd), nighttime (LSWTn), daily LSWT (LSWTm) and their drivers in the Qinghai-Tibet Plateau at monthly, seasonal and annual timescales. We focused on spatiotemporal heterogeneity of LSWT trends. Results showed climatological LSWT presented a saddle-shaped distribution along the northeast-southwest direction except for LSWTd in March, while highly heterogeneous LSWT trends without spatial dependence were observed at all timescales. Diurnal asymmetry of LSWT trends was evident with 56.04–88.19% lakes showing smaller LSWTd trends than LSWTn trends except for August and September. Further, we found lake surface albedo trend could effectively explain spatial patterns of LSWT trends at different timescales, and its interactions with other variable trends generally were the largest or second-largest.

Optimization of Landsat Chl-a Retrieval Algorithms in Freshwater Lakes through Classification of Optical Water Types

The application of remote sensing data to empirical models of inland surface water chlorophyll-a concentrations (chl-a) has been in development since the launch of the Landsat 4 satellite series in 1982. However, establishing an empirical model using a chl-a retrieval algorithm is difficult due to the spatial heterogeneity of inland lake water properties. Classification of optical water types (OWTs; i.e., differentially observed water spectra due to differences in water properties) has grown in favour in recent years over traditional non-turbid vs. turbid classifications. This study examined whether top-of-atmosphere reflectance observations in visible to near-infrared bands from Landsat 4, 5, 7, and 8 sensors can be used to identify unique OWTs using a guided unsupervised classification approach in which OWTs are defined through both remotely sensed reflectance and surface water chemistry data taken from samples in North American and Swedish lakes. Linear regressions of algorithms (Landsat reflectance bands, band ratios, products, or combinations) to lake surface water chl-a were built for each OWT. The performances of chl-a retrieval algorithms within each OWT were compared to those of global chl-a algorithms to test the effectiveness of OWT classification. Seven unique OWTs were identified and then fit into four categories with varying degrees of brightness as follows: turbid lakes with a low chl-a:turbidity ratio; turbid lakes with a mixture of high chl-a and turbidity measurements; oligotrophic or mesotrophic lakes with a mixture of low chl-a and turbidity measurements; and eutrophic lakes with a high chl-a:turbidity ratio. With one exception (r2 = 0.26, p = 0.08), the best performing algorithm in each OWT showed improvement (r2 = 0.69–0.91, p < 0.05), compared with the best performing algorithm for all lakes combined (r2 = 0.52, p < 0.05). Landsat reflectance can be used to extract OWTs in inland lakes to provide improved prediction of chl-a over large extents and long time series, giving researchers an opportunity to study the trophic states of unmonitored lakes.

A Google Earth Engine Application to Retrieve Long-Term Surface Temperature for Small Lakes. Case: San Pedro Lagoons, Chile

Lake surface water temperature (LSWT) is a crucial water quality parameter that modulates many lake and reservoir processes. Therefore, it is necessary to monitor it from a long-term perspective. Over the last decades, many methods to retrieve LSWT fields from satellite imagery have been developed. This work aims to test, implement and automate six methods. These are performed in the Google Earth Engine (GEE) platform, using 30 m spatial resolution images from Landsat 7 and 8 satellites for 2000–2020. Automated methods deliver long-term time series. Series are then calibrated with in situ data. Two-dimensional (2D) × time data fields are built on the lakes with the calibration, and a subsequent LSWT climatology is derived. Our study area is two urban lagoons with areas smaller than two (2) km2 of the city of San Pedro de la Paz, South-Central Chile. The six methods describe the seasonal variation of LSWT (Willmott’s index of agreement > 0.91, R2 > 0.67). The main difference between series is their bias. Thus, after a simple calibration, all series adequately describe the LSWT. We utilized the Pedro de la Paz lagoons to demonstrate the method’s utility. Our research demonstrates that these adjacent lagoons exhibit comparable LSWT spatial (15.5–17 ∘C) and temporal (7–25 ∘C) trends throughout the year. Differences in geographical pattern might result from the northern island’s heat impact and the existence of the Biobío river to the east. Our work represents an efficient alternative for obtaining LSWT in particular lakes and reservoirs, especially useful in medium and small-sized ones.

Highly Stable and Nontoxic Lanthanum-Treated Activated Palygorskite for the Removal of Lake Water Phosphorus

Nutrient pollution of surface water, such as excess phosphate loading on lake surface water, is a significant issue that causes ecological and financial damage. Despite many technologies that can remove available phosphate, such as material-based adsorption of those available phosphate ions, the development of a material that can trap them from the surface water is worth doing, considering other aspects. These aspects are: (i) efficient adsorption by the material while it settles down to the water column, and (ii) the material itself is not toxic to the lake natural microorganism. Considering these aspects, we developed a trace lanthanum-grafted surface-modified palygorskite, a fibrous clay mineral. It adsorbed a realistic amount of phosphate from the lake water (typically 0.13–0.22 mg/L). The raw and modified palygorskite (Pal) includes unmodified Australian Pal, heated (at ~400 °C) Pal, and acid (with 3 M HCl)-treated Pal. Among them, while acid-treated Pal grafted a lower amount of La, it had a higher adsorption capacity (1.243 mg/g) and a quicker adsorption capacity in the time it took to travel to the bottom of the lake (97.6% in 2 h travel time), indicating the adsorption role of both La and clay mineral. The toxicity of these materials was recorded null, and in some period of the incubation of the lake microorganism with the material mixture, La-grafted modified clays increased microbial growth. As a total package, while a high amount of La on the already available material could adsorb a greater amount of phosphate, in this study a trace amount of La on modified clays showed adsorption effectiveness for the realistic amount of phosphate in lake water without posing added toxicity.

Surface Heat Budget estimation for Laurance Lake, US

Estimating heat budget factors are important to understand the many physical processes of large lakes and their reaction to the atmosphere. Some of these components are affected by water temperature, while the other depends on atmospheric conditions. This paper estimates the total heat flux for Lawrence lake via a code developed in MATLAB environment. The code can deal with different time resolutions if the lake water surface temperature data were at different time resolutions from the meteorological data. Results showed that solar energy peaks at 842 Watt/m2 at 540 Julian day, which is very normal for a sunny summer day, while the longwave radiation has 204 Watt/m2 as a min value. The back radiation did not make any reaction for the variation, but it revealed a small gradient. Furthermore, evaporation recorded - 67 Watt/m2 as a minimum value at 659 Julian day and 360 Watt/m2 as a maximum value at 578.43 Julian day close to the maximum water surface temperature event.

Water Quality Monitoring in Inle Lake, Myanmar from the Floating Garden Activity

Inle Lake is the second largest inland lake in Myanmar. Floating gardens, mostly for tomato cultivation, are a unique and profitable method of agriculture used by people living on and around the lake. This study investigated the water quality of Inle Lake and how it has been affected by the different agricultural practices used in tomato cultivation on floating garden beds, by measuring pollution levels. Water samples were collected from the sites representing two types of agricultural practice from four villages. The first was designated as being grown under good agricultural practices (GAP), and the other as under non-good agricultural practices (non-GAP), with this study undertaken during wet season, 2019 and dry season, 2020. Two additional sets of water samples were collected as references. One of these sets was from the center of the lake and the other from an inlet stream to the lake. All water samples were analyzed for physical and chemical properties. The results found that Ca2+, Mg2+ and HCO3- were dominant in the lake surface water. The results showed significant differences in the mean values for some water quality parameters between the GAP and non-GAP of each study sites in both seasons. In particular, nutrient pollution from chemicals such as nitrogen and phosphorus from the non-GAP were significantly higher than those from GAP. Water quality index was calculated to describe the overall quality of lake surface water. It was observed that the water quality was almost threatened in the floating garden areas. In comparison between two practices, the non-GAP gave the higher water quality index value than the GAP. This investigated that poor management of fertilizers usage has had a negative effect on the water quality of the lake. The differences seen in water quality from the GAP and non-GAP areas, point to ways to successfully manage sources of water pollution in order to better conserve the lake by sustainable agricultural production.

Occurrence and risk assessment of antibiotics in the surface water of Chaohu Lake and its tributaries in China

The extensive use of antibiotics for treating humans, animals, and plants has resulted in the contamination of aquatic environments, posing a potential threat to public health and aquatic life; hence, this topic is of great concern worldwide. Lakes are considered to be antibiotic-rich reservoirs because many of the antibiotics discharged from rivers enter lakes. Chaohu Lake is one of the top five freshwater lakes in China. This study aims to provide a current evaluation of the antibiotics present in the surface water of the Chaohu Lake basin. To this end, the occurrences of 18 antibiotics categorized into 5 different groups were investigated in the study area, and the impact of inflowing rivers on their distribution was assessed. The results showed that the concentrations of 14 antibiotics in water samples ranged from 0 to 892 ng/L, and that antibiotics were detected at most sampling sites. Among them, the Nanfeihe and Shiwulihe rivers, which are close to the city, contributed the most to antibiotic pollution, indicating the widespread occurrence of antibiotics in the study area. A risk assessment based on the risk quotient method indicated that ofloxacin, ciprofloxacin, sulfamethoxazole, erythromycin, and norfloxacin in the lake water posed a high ecological risk to algae, while sulfamethazine posed a high risk to plants (RQ >1).

Urban Land Surface Temperature Monitoring and Surface Thermal Runoff Pollution Evaluation Using UAV Thermal Remote Sensing Technology

With the continuous advancement of urbanization, the impervious surface expands. Urbanization has changed the structure of the natural land surface and led to the intensification of the urban heat island (UHI) effect. This will affect the surface runoff temperature, which, in turn, will affect the surface water temperature of urban lakes. This study will use UAS TIR (un-manned aerial system thermal infrared radiance) remote sensing and in situ observation technology to monitor the urban space surface temperature and thermal runoff in Kunming, Yunnan, in summer; explore the feasibility of UAS TIR remote sensing to continuously observe urban surface temperature during day and night; and analyze thermal runoff pollution. The results of the study show that the difference between UAS TIR LSTs and in situ LSTs (in situ air temperature 10 cm above the ground.) varies with the type of land covers. Urban surface thermal runoff has varying degrees of impact on water bodies. Based on the influence of physical factors such as vegetation and buildings and meteorological factors such as solar radiation, the RMSE between UAS LSTs and in situ LSTs varies from 1 to 5 °C. Land cover types such as pervious bricks, asphalt, and cement usually show higher RMSE values. Before and after rainfall, the in situ data of the lake surface water temperature (LSWT) showed a phenomenon of first falling and then rising. The linear regression analysis results show that the R2 of the daytime model is 0.92, which has high consistency; the average R2 at night is 0.38; the averages R2 before and after rainfall are 0.50 and 0.83, respectively; and the average RMSE is 1.94 °C. Observational data shows that thermal runoff quickly reaches thermal equilibrium with the land surface temperature about 30 min after rainfall. The thermal runoff around the lake has a certain warming effect on LSWT.