Lake Color Research Articles

Earth observation reveals the shifting patterns of China's lake colour driven by climate change and land cover

Water colour has been recognized as one of the most important Essential Climate Variables of the lake ecosystem, as it is directly related to changes in water constituents and almost all of the lake's ecological changes could alter water colour. Given the high retrieval accuracy from existing Earth observation satellite data, water colour, in terms of Forel Ule Index (FUI), can be a realistic indicator to track the long-term changes in the lake ecosystem and further explore the lake response to environmental changes. This paper aims to comprehensively investigate the spatiotemporal variation patterns of FUI in 159 large lakes (≥25 km2) across China during 2000–2022 based on the MODIS data and detect the climatic and anthropogenic driving forces of these changes. The 23 years of MODIS records revealed an overall downward trend of lake FUI across China, indicating the lakes in China shifted to bluer colour during the past two decades. Through driving factor analyses, the complicated interplay among lake colour, lake morphology, regional climate shifts and human interference dynamics was uncovered. In the long term, it was found the pronounced change in lake colour in the western lake zones was primarily attributed to climate warming and humidification, whereas that in the eastern lake zones was mainly related to the alterations in regional land cover during the past two decades. Seasonally, lake basin's air temperature was identified as the main factor impacting the seasonal patterns of lake colour, followed by wind speed and runoff. Spatially, there was high spatial variability in lake colour across China, which was mainly associated with lake elevation and lake basin's precipitation rate, although the factors exhibited considerable divergence across different zones. Based upon the above findings, the implications for lake environment protection and management in different regions of China were further discussed.

Investigating the Morphometry and Hydrometeorological Variability of a Fragile Tropical Karstic Lake of the Yucatán Peninsula: Bacalar Lagoon

Comprehensive morphometric and hydrometeorological studies on Bacalar Lagoon, Mexico’s largest tropical karstic lake and a significant aquatic system of the Yucatán Peninsula, are lacking. This study provides a detailed analysis of its bathymetry, morphometry, and hydrometeorological characteristics. The lake’s main basin stretches more than 52.7 km in length, with widths varying from 0.18 km to 2.28 km. It has a volume of 554.4 million cubic meters, with an average depth of 8.85 m, reaching depths of up to 26 m in the north and featuring sub-lacustrine dolines in the south, with depths of 38 m, 48.5 m, and 63.6 m. The study reveals seasonal variations in surface water temperature, closely linked to air temperature (r = 0.89), and immediate responses of water levels to hydrometeorological events. Water level fluctuations also exhibit seasonal patterns that are correlated with regional aquifer conditions, with a lag of 2 months after seasonal rainfall. Interannual variability in rainfall and water levels was observed. From 2010 to 2012, rainfall consistently remained below its mean climatic value, due to a prolonged La Niña event, while the exceptionally wet conditions in 2020 were also associated with La Niña. Extreme and anomalous hydrometeorological events, such as those following tropical storm Cristobal in 2020, revealed the fragility of Bacalar Lagoon, causing a notable transformation in lake color and transparency, shifting it from its typical oligotrophic state to eutrophic conditions that lasted longer than a year. These color changes raise questions about the factors impacting ecological health in tropical karstic regions. Additional factors affecting water quality in the BL in 2020, such as deforestation, coastline changes, and urban growth, warrant further investigation. Our study can serve as a starting landmark.

Analysis of taiga and tundra lake browning trends from 2002 to 2021 using MODIS data

Lakes in taiga and tundra regions may be silently undergoing changes due to global warming. One of those changes is browning in lake color. The browning interacts with the carbon cycle, ecosystem dynamics, and water quality in freshwater systems. However, spatiotemporal variabilities of browning in these regions have not been well documented. Using MODIS remote sensing reflectance at near ultraviolet wavelengths from 2002 to 2021 on the Google Earth Engine platform, we quantified long-term browning trends across 7616 lakes (larger than 10 km2) in taiga and tundra biomes. These lakes showed an overall decreased trend in browning (Theil-Sen Slope = 0.00015), with ∼36% of these lakes showing browning trends, and ∼1% of these lakes showing statistically significant (p-value <0.05) browning trends. The browning trends more likely occurred in small lakes in high latitude, low ground ice content regions, where air temperature increased and precipitation decreased. While temperature is projected to increase in response to climate change, our results provide one means to understand how biogeochemical cycles and ecological dynamics respond to climate change.

The Long-Term Detection of Suspended Particulate Matter Concentration and Water Colour in Gravel and Sand Pit Lakes through Landsat and Sentinel-2 Imagery

Over the past half century, the demand for sand and gravel has led to extensive quarrying activities, creating many pit lakes (PLs) which now dot floodplains and urbanized regions globally. Despite the potential importance of these environments, systematic data on their location, morphology and water quality remain limited. In this study, we present an extensive assessment of the physical and optical properties in a large sample of PLs located in the Po River basin (Italy) from 1990 to 2021, utilizing a combined approach of remote sensing (Landsat constellation and Sentinel-2) and traditional limnological techniques. Specifically, we focused on the concentration of Suspended Particulate Matter (SPM) and the dominant wavelength (λdom, i.e., water colour). This study aims to contribute to the analysis of PLs at a basin scale as an opportunity for environmental rehabilitation and river floodplain management. ACOLITE v.2022, a neural network particularly suitable for the analysis of turbid waters and small inland water bodies, was used to atmospherically correct satellite images and to obtain SPM concentration maps and the λdom. The results show a very strong correlation between SPM concentrations obtained in situ and those obtained from satellite images, both for data derived from Landsat (R2 = 0.85) and Sentinel-2 images (R2 = 0.82). A strong correlation also emerged from the comparison of spectral signatures obtained in situ via WISP-3 and those derived from ACOLITE, especially in the visible spectrum (443–705 nm, SA = 10.8°). In general, it appeared that PLs with the highest mean SPM concentrations and the highest mean λdom are located along the main Po River, and more generally near rivers. The results also show that active PLs exhibit a poor water quality status, especially those of small sizes (&lt;5 ha) and directly connected to a river. Seasonal comparison shows the same trend for both SPM concentration and λdom: higher values in winter gradually decreasing until spring–summer, then increasing again. Finally, it emerged that the end of quarrying activity led to a reduction in SPM concentration from a minimum of 43% to a maximum of 72%. In this context, the combined use of Landsat and Sentinel-2 imagery allowed for the evaluation of the temporal evolution of the physical and optical properties of the PLs in a vast area such as the Po River basin (74,000 km2). In particular, the Sentinel-2 images consistently proved to be a reliable resource for capturing episodic and recurring quarrying events and portraying the ever-changing dynamics of these ecosystems.

Shifts, Trends, and Drivers of Lake Color Across China Since the 1980s

AbstractLakes are sentinels of global changes and integrators of processes in watersheds. Changes of lake water quality can be observed in shifts in lake color, however, the prevalence of shifts and trends in color and relevant factors remain elusive. Here, a comprehensive examination of color in 2,550 Chinese lakes from 1984 to 2021 revealed that color in 68% of the lakes shifted toward shorter visual wavelengths. Lakes in the Tibetan Plateau had larger declines in wavelength than lakes in other areas. The factors associated with reduced visual wavelengths varied in different ecoregions. A warmer and wetter climate in deep lakes in western China is associated with shifts toward blue. Increased vegetation in watershed and decreased wind are associated with green‐yellow shifting to green‐cyan color in shallow lakes of eastern China. Our study highlights the heterogeneous controls of climate and humans on changing patterns of lake colors.

Limnology and diatom ecology of shallow lakes in a rapidly thawing discontinuous permafrost peatland

ABSTRACT Lakes in discontinuous permafrost peatlands are on the front lines of climate change, sensitive to even modest increases in air temperature. The aim of this study was to provide the first limnological characterization of shallow (∼1–2 m depth) lakes in the Scotty Creek basin (Northwest Territories, Canada), a field site of circumpolar significance due to the existence of long-term ecohydrological monitoring going back decades. We use this previous work as a foundation to advance our process-based understanding of the potential drivers of lake ecosystem change. Our results showed that dissolved organic carbon (DOC) and lake color were not correlated, a pattern that seems to be an important driver of diatom (siliceous single-celled algae) assemblages in these lakes. Diatoms in the study lakes tended to fall into 1 of 2 assemblage clusters. One cluster, composed of small benthic Fragilariaceae and small Navicula species (sensu lato), was found associated with higher lake color; the second cluster, composed of Encyonopsis and large Navicula species, was found associated with high DOC, lower color, and the presence of a benthic moss mat. From this finding, we suggest that DOC quality is a primary control on lake ecology in this region for its role in controlling light penetration to the lake bottom. Our hypothesis that the prevalence of nearshore fens and collapse scar wetlands would be important drivers of DOC was not supported in the 9 study lakes with available data to map shoreline features.

Heterogenous controls on lake color and trends across the high-elevation U.S. Rocky Mountain region

Global change may contribute to ecological changes in high-elevation lakes and reservoirs, but a lack of data makes it difficult to evaluate spatiotemporal patterns. Remote sensing imagery can provide more complete records to evaluate whether consistent changes across a broad geographic region are occurring. We used Landsat surface reflectance data to evaluate spatial patterns of contemporary lake color (2010–2020) in 940 lakes in the U.S. Rocky Mountains, a historically understudied area for lake water quality. Intuitively, we found that most of the lakes in the region are blue (66%) and were found in steep-sided watersheds (>22.5°) or alternatively were relatively deep (>4.5 m) with mean annual air temperature (MAAT) <4.5°C. Most green/brown lakes were found in relatively shallow sloped watersheds with MAAT ⩾4.5°C. We extended the analysis of contemporary lake color to evaluate changes in color from 1984 to 2020 for a subset of lakes with the most complete time series (n = 527). We found limited evidence of lakes shifting from blue to green states, but rather, 55% of the lakes had no trend in lake color. Surprisingly, where lake color was changing, 32% of lakes were trending toward bluer wavelengths, and only 13% shifted toward greener wavelengths. Lakes and reservoirs with the most substantial shifts toward blue wavelengths tended to be in urbanized, human population centers at relatively lower elevations. In contrast, lakes that shifted to greener wavelengths did not relate clearly to any lake or landscape features that we evaluated, though declining winter precipitation and warming summer and fall temperatures may play a role in some systems. Collectively, these results suggest that the interactions between local landscape factors and broader climatic changes can result in heterogeneous, context-dependent changes in lake color.

The Color of Earth’s Lakes

AbstractAlthough water color is a fundamental property of freshwater ecosystems, the global distribution of lake color remains unknown. Here, we used 5.14 million color records derived from satellite images during 2013–2020 to determine the modal water color of 85,360 representative lakes worldwide. We find that globally, lake modal colors span the visible spectrum with a bimodal distribution of blue versus non‐blue (green‐brown), with 31% of lakes being blue and 69% being non‐blue. Both climate and lake morphology influence lake modal color. Blue lakes are associated with cooler summer air temperature, winter ice cover, and higher precipitation. Under a 3°C increase in summer air temperature, 14% of blue lakes could shift to a non‐blue regime, representing a substantial change to their underlying ecology. As lake ecosystems continue to face a range of stressors, this study provides a critical baseline for understanding lake responses to global environmental change.

Monitoring and classification of high Arctic lakes in the Svalbard Islands using remote sensing

Arctic lakes are an essential element of the environment. This study inventoried and classified lakes on three of the Svalbard Islands (Spitsbergen, Barentsøya, and Edgeøya) using Sentinel-2 images. The Forel-Ule color index (FUI) was employed to measure the lake's color, and a new equation to calculate the concentration of suspended sediment using satellite images was developed and tested using measurements from coastal waters. These two measures, plus the normalized difference vegetation index for vegetation on the lakeshore, and the lakes' location were used for clustering and classification. More than 1000 natural lakes were found on the three Svalbard islands. Nearly 80 % of these were smaller than 0.01 km2 (1 ha), with the largest a few km2 in area. Lake distribution analysis identified six zones of increased lake density, five of which were located along the western coast of Spitsbergen. The FUI was thus demonstrated to be useful for the monitoring of Arctic lakes. The K-means clustering results and analysis of the spectral signatures divided the lakes into seven classes: clear water, moderately clear water, tundra, coastal tundra, meltwater, extreme meltwater, and supraglacial lakes. Meltwater and clear water lakes were the two most common types, accounting for about 80 % of the total lake area.

Seasonal forecasting of lake water quality and algal bloom risk using a continuous Gaussian Bayesian network

Abstract. Freshwater management is challenging, and advance warning that poor water quality was likely, a season ahead, could allow for preventative measures to be put in place. To this end, we developed a Bayesian network (BN) for seasonal lake water quality prediction. BNs have become popular in recent years, but the vast majority are discrete. Here, we developed a Gaussian Bayesian network (GBN), a simple class of continuous BN. The aim was to forecast, in spring, mean total phosphorus (TP) and chlorophyll a (chl a) concentration, mean water colour, and maximum cyanobacteria biovolume for the upcoming growing season (May–October) in Vansjø, a shallow nutrient-rich lake in southeastern Norway. To develop the model, we first identified controls on interannual variability in seasonally aggregated water quality. These variables were then included in a GBN, and conditional probability densities were fit using observations (≤39 years). GBN predictions had R2 values of 0.37 (chl a) to 0.75 (colour) and classification errors of 32 % (TP) to 17 % (cyanobacteria). For all but lake colour, including weather variables did not improve the predictive performance (assessed through cross-validation). Overall, we found the GBN approach to be well suited to seasonal water quality forecasting. It was straightforward to produce probabilistic predictions, including the probability of exceeding management-relevant thresholds. The GBN could be sensibly parameterised using only the observed data, despite the small dataset. Developing a comparable discrete BN was much more subjective and time-consuming. Although low interannual variability and high temporal autocorrelation in the study lake meant the GBN performed only slightly better than a seasonal naïve forecast (where the forecasted value is simply the value observed the previous growing season), we believe that the forecasting approach presented here could be particularly useful in areas with higher sensitivity to catchment nutrient delivery and seasonal climate and for forecasting at shorter (daily or monthly) timescales. Despite the parametric constraints of GBNs, their simplicity, together with the relative accessibility of BN software with GBN handling, means they are a good first choice for BN development with continuous variables.

Shifting Patterns of Summer Lake Color Phenology in Over 26,000 US Lakes.

Lakes are often defined by seasonal cycles. The seasonal timing, or phenology, of many lake processes are changing in response to human activities. However, long‐term records exist for few lakes, and extrapolating patterns observed in these lakes to entire landscapes is exceedingly difficult using the limited number of available in situ observations. Limited landscape‐level observations mean we do not know how common shifts in lake phenology are at macroscales. Here, we use a new remote sensing data set, LimnoSat‐US, to analyze U.S. summer lake color phenology between 1984 and 2020 across more than 26,000 lakes. Our results show that summer lake color seasonality can be generalized into five distinct phenology groups that follow well‐known patterns of phytoplankton succession. The frequency with which lakes transition from one phenology group to another is tied to lake and landscape level characteristics. Lakes with high inflows and low variation in their seasonal surface area are generally more stable, while lakes in areas with high interannual variations in climate and catchment population density show less stability. Our results reveal previously unexamined spatiotemporal patterns in lake seasonality and demonstrate the utility of LimnoSat‐US, which, with over 22 million remote sensing observations of lakes, creates novel opportunities to examine changing lake ecosystems at a national scale.

Declining greenness in Arctic-boreal lakes

The highest concentration of the world's lakes are found in Arctic-boreal regions [C. Verpoorter, T. Kutser, D. A. Seekell, L. J. Tranvik, Geophys. Res. Lett. 41, 6396-6402 (2014)], and consequently are undergoing the most rapid warming [J. E. Overland et al., Arctic Report Card (2018)]. However, the ecological response of Arctic-boreal lakes to warming remains highly uncertain. Historical trends in lake color from remote sensing observations can provide insights into changing lake ecology, yet have not been examined at the pan-Arctic scale. Here, we analyze time series of 30-m Landsat growing season composites to quantify trends in lake greenness for >4 × 105 waterbodies in boreal and Arctic western North America. We find lake greenness declined overall by 15% from the first to the last decade of analysis within the 6.3 × 106-km2 study region but with significant spatial variability. Greening declines were more likely to be found in areas also undergoing increases in air temperature and precipitation. These findings support the hypothesis that warming has increased connectivity between lakes and the land surface [A. Bring et al., J. Geophys. Res. Biogeosciences 121, 621-649 (2016)], with implications for lake carbon cycling and energy budgets. Our study provides spatially explicit information linking climate to pan-Arctic lake color changes, a finding that will help target future ecological monitoring in remote yet rapidly changing regions.

A dataset of remote-sensed Forel-Ule Index for global inland waters during 2000\u20132018

Water colour is the result of its constituents and their interactions with solar irradiance; this forms the basis for water quality monitoring using optical remote sensing data. The Forel-Ule Index (FUI) is a useful comprehensive indicator to show the water colour variability and water quality change in both inland waters and oceans. In recent decades, lakes around the world have experienced dramatic changes in water quality under pressure from both climate change and anthropogenic activities. However, acquiring consistent water colour products for global lakes has been a challenge. In this paper we present the first time series FUI dataset for large global lakes from 2000–2018 based on MODIS observations. This dataset provides significant information on spatial and temporal changes of water colour for global large lakes during the past 19 years. It will be valuable to studies in search of the drivers of global and regional lake colour change, and the interaction mechanisms between water colour, hydrological factors, climate change, and anthropogenic activities.

Coupling between increased lake color and iron in boreal lakes

Increasing evidence show that lake color has increased more than DOC in several boreal lakes, promoted by enhanced levels of light absorbing iron (Fe). Fe levels show great spatial and temporal variations in northern freshwaters, and processes regulating long-term Fe trends as well as differences among lakes are not fully understood. In a boreal lake district of SE-Norway, the coupling between lake color and Fe were investigated in 24 non-productive lakes during 1983–2017. The lakes showed significant increases in color, total organic carbon (TOC), specific UV absorption and Fe with time. Based on regression models, TOC and Fe together explained 89% of lake color. Fe averagely contributed to 12% of the lake color. The color contribution from Fe was better predicted by the Fe-to-TOC ratio than the absolute Fe concentration. The variability in Fe contribution to color was large - ranging from 0 to 65% based on 429 lake water samples. Variability in Fe levels and color contribution were related to differences in water retention time (WRT), pH and to the terrestrial input of Fe-organic matter complexes. Size fractionation analyses showed that Fe and colored TOC were mainly in a colloidal form (>10 kDa). Along with reduced acid rain, there has been a significant reduction in ionic strength in several boreal lakes since 1980s, which promote the stability of colloids. Negative correlation between the Fe-to-TOC ratio and WRT, might be due to a size selective removal of colloidal Fe complexes related to water flow, which is supported by a higher Fe-to-TOC ratio in wet years compared to dry years. Responses of Fe complexes to increased runoff are relatively higher in lakes with short compared to long WRT. In addition, increases in hydrological extremes, due to climate change, may enhance the Fe variability among lakes even further in a future climate.

Shifting Patterns of Summer Lake Color Phenology in Over 26,000 US Lakes

Shifting Patterns of Summer Lake Color Phenology in Over 26,000 US Lakes

Effects of different food ingredients on the color and absorption spectrum of carminic acid and carminic aluminum lake.

In this study, three foodstuffs (surimi, minced meat, and milk) were dyed with carminic acid and carminic aluminum lake. The effects of protein, metal ions, and food additives on the color of carminic acid and carminic aluminum lake were investigated. After being dyed by carminic acid, the colors of surimi, minced meat, and milk were light purple, red, and gray‐green, respectively. When using carminic aluminum lake, surimi and milk were magenta, and minced meat was red. Regarding the carminic acid solution, the presence of myofibrillar protein (MFP), whey protein isolate (WPI), and soy protein isolate (SPI) turned it red by changing the pH, while the presence of casein made it orange. The carminic aluminum lake solution turned magenta in all four cases, which were not affected by protein. The color of carminic acid and carminic aluminum lake was significantly affected by 0.001–0.1 mol/L Fe3+, 0.001–0.1 mol/L Fe2+, 0.001–0.1 mol/L Cu2+, and 0.1 mol/L Ca2+, limiting their application in iron‐, copper‐, and high‐calcium foods. The color of carminic acid was changed to yellow by 0.01%‐1% sodium nitrite, but 0.01%–1% ascorbic acid and 0.01%–0.1% monascus color did not significantly affect the color of either carminic acid or carminic aluminum lake. This paper provides a reference for the application of carminic acid and carminic aluminum lake in food science.

Satellite and airborne remote sensing of gross primary productivity in boreal Alaskan lakes

In terrestrial and marine ecosystems, remote sensing has been used to estimate gross primary productivity (GPP) for decades, but few applications exist for shallow freshwater ecosystems.Here we show field-based GPP correlates with satellite and airborne lake color across a range of optically and limnologically diverse lakes in interior Alaska. A strong relationship between in situ GPP derived from stable oxygen isotopes (δ18O) and space-based lake color from satellites (e.g. Landsat-8, Sentinel-2 and CubeSats) and airborne imagery (AVIRIS-NG) demonstrates the potential power of this technique for improving spatial and temporal monitoring of lake GPP when coupled with additional field validation measurements across different systems. In shallow waters clear enough for sunlight to reach lake bottoms, both submerged vegetation (macrophytes and algae) and phytoplankton likely contribute to GPP. The stable isotopes and remotely sensed shallow lake color used here integrate both components. These results demonstrate the utility of lake color as a feasible means for mapping lake GPP from remote sensing. This novel methodology estimates GPP from remote sensing in shallow lakes by combining field measurements of oxygen isotopes with airborne, satellite and CubeSat imagery. This use of lake color for providing insight into ecological processes of shallow lakes is recommended, especially for remote arctic and boreal landscapes.

The success of Gonyostomum semen (Raphidophyceae) in a boreal lake is due to environmental changes rather than a recent invasion

The freshwater microalgal species, Gonyostomum semen, has increased in abundance and distribution in boreal lakes during the past few decades, concerning ecologists and water managers. Due to its rapid spread, G. semen has often been referred to as an invasive species, although it was first described in the 1800s. We hypothesized that G. semen is not an invasive species in Norwegian lakes, and that the increasing success is due to beneficial changes in environmental conditions for this species during the past century. We tested these hypotheses by performing a paleolimnological study of a Norwegian Lake, Skjeklesjøen, with known mass occurrence of G. semen. A specific G. semen pigment biomarker, heteroxanthin, was used to detect this species in layers of a sediment core with known age determinations. Environmental factors in both lake and catchment were further investigated and the relationships with the amounts of G. semen was tested. Our results suggested that G. semen was in fact not an invasive species in this lake the past decades. Several factors were identified as plausible drivers for G. semen in this boreal lake. Between 1874–2016, the increasing levels of G. semen in Lake Skjeklesjøen was most closely correlated with Carbon (C), lake color (measured as absorbance of sediment extracts), Nitrogen (N) and spring temperature. Our results suggest that the rapid increase in G. semen population in this boreal lake over the past 70 years was probably due to a combination of climate change and local anthropogenic activities in the catchment, causing increased browning and increased inputs of organic matter and nutrients.

The Color Formation Mechanism of the Blue Karst Lakes in Jiuzhaigou Nature Reserve, Sichuan, China

The karst lakes in Jiuzhaigou Nature Reserve are an integral part of the karst lake landscape, yet research on the formation mechanism for the color of the blue-green lakes in Jiuzhaigou is insufficient. With the help of hyperspectral instruments, coupled with hydro-chemical analysis, this paper elaborates on the unique color characteristics of the Jiuzhaigou karst lakes, delves into the color formation mechanism of the lakes, establishes a regression equation for the color of the lakes as well as the water quality parameters, and sheds light upon the causes for the color distinction between the karst lakes in Jiuzhaigou and the plateau freshwater lakes. The experiment shows that the Jiuzhaigou karst lakes are primarily blue and green, while the proportion of short-wavelength light in the normalized water-leaving radiance and the total incident irradiance of lake water is higher. Based on the redundancy analysis and the correlation analysis, travertine deposition is the core link in the color formation of the blue karst lakes in Jiuzhaigou, while the selective reflection and scattering of the suspended calcium carbonate particulate matters towards visible light represents the optical foundation for the formation. In addition, physical factors such as depth and transparency, changes to the water quality parameters that affect the travertine deposition rate, and the eutrophication process will all exert significant influence over the formation. By building on water-leaving radiance, this paper quantifies the lake color with the tristimulus values (R, G, B) via colorimetrical methods, which features solid goodness of fit with the linear regression equation established based on the water quality parameters. The principal component analysis and colorimetrical analysis show that the color of the karst lakes in Jiuzhaigou varies substantially from that of the plateau freshwater lakes, which mainly results from the difference in the water quality. Research conducted in this paper on the color formation mechanism of the distinct blue karst lakes in Jiuzhaigou illuminates the formation and maintenance mechanism of the plateau karst lakes, which is conducive to better understanding towards the relationship between the water quality and colors of the karst lakes, and provides scientific proof for the establishment of the water quality assessment indicator system based on the colors of the karst lakes.

Traditional Ecological Knowledge for Climate Change Assessment and Rainfall Prediction: A Case of Adami Tulu Jido Kombolcha District, Oromia Region, Ethiopia

Data on environmental problems of the area, local manifestations of climate change, climate change coping strategies, rainfall prediction mechanisms and their threats were collected in three systematically selected administrative units of the study area using focus group discussion, key informant interview and household (HH) survey from May to June, 2017. Focus group (FG) discussion that participate youth, elders, women, religion and tradition leaders and experts with average members of 15 was organized at each administrative units. Sample key informants (KI) were selected by the focus group members by setting criteria to get deep information. HH survey was conducted from randomly selected 92 HHs samples determined by Kothari (2004). Qualitative data analysis method was used to summarize the information. Results showed that environmental problems in the area are directly or indirectly related to climate. And the communities rely on their indigenous rainfall prediction using meteorological, astronomic and animal behavioral indicators. The main indicators are: wind direction, appearance and shape of cloud, star pattern, moon’s appearance, cattle behavior, chirping of bird, bee’s migration, and color of lake and appearance of rainbow. The study also depicted that most (85%) of the communities heavily rely on the indigenous knowledge for planning agricultural activities or early warnings for preparedness. However, it has been threatened due to critics by religious people, lack of trust of young generation, degradation of the indicators and lack of documentation. There is need for careful evaluation and enhancement for social-ecological resilience of the vulnerable communities.