Comparison of Satellite Reflectance Algorithms for Estimating Phycocyanin Values and Cyanobacterial Total Biovolume in a Temperate Reservoir Using Coincident Hyperspectral Aircraft Imagery and Dense Coincident Surface Observations

We analyzed 27 established and new simple and therefore perhaps portable satellite phycocyanin pigment reflectance algorithms for estimating cyanobacterial values in a temperate 8.9 km2 reservoir in southwest Ohio using coincident hyperspectral aircraft imagery and dense coincident water surface observations collected from 44 sites within 1 h of image acquisition. The algorithms were adapted to real Compact Airborne Spectrographic Imager (CASI), synthetic WorldView-2, Sentinel-2, Landsat-8, MODIS and Sentinel-3/MERIS/OLCI imagery resulting in 184 variants and corresponding image products. Image products were compared to the cyanobacterial coincident surface observation measurements to identify groups of promising algorithms for operational algal bloom monitoring. Several of the algorithms were found useful for estimating phycocyanin values with each sensor type except MODIS in this small lake. In situ phycocyanin measurements correlated strongly (r2 = 0.757) with cyanobacterial sum of total biovolume (CSTB) allowing us to estimate both phycocyanin values and CSTB for all of the satellites considered except MODIS in this situation

Assessing the Use of Smartphones in Agriculture

Smartphones are an as yet untapped resource available to agriculture. They are ubiquitous across the globe yet have not previously been tested as a resource available to farmers. Imaging methods such as unmanned aerial vehicles (UAV) and satellite imaging have been well-explored and employed in various aspects of agriculture; however, such methods can be cost-prohibitive and at the mercy of another company or agency. If smartphones could be shown to capture color in such a way that relates in a quantifiable way to data measured by laboratory-grade equipment they could prove to be extremely valuable to farmers. Cutting out expensive and specialized technology for a device already sitting in people’s pockets would benefit farmers around the world. Given this idea, three experiments were designed to assess the color capabilities of smartphone cameras in relation to agricultural applications. The first experiment assessed the capability of smartphone cameras to identify the presence of cyanobacteria in a given water sample based on measurements of color and transmission spectra. These data were then related to color captured by four smartphones. Additionally, the measurements were used to create a preliminary customized Color Checker(TM)-inspired chart for use in identification of cyanobacteria. Current techniques employed by the state of New York for identifying cyanobacteria in water are cumbersome, involving week-long testing in government labs. This project is an attempt to simplify the process by using image capture with smartphones. The second assessment was similar to the first, with tomatoes in place of cyanobacteria. Five smartphone devices were used to image tomatoes at different stages of ripeness. A relationship was found to exist between the hue angles taken from the smartphone images and as measured by a spectroradiometer. A tomato Color Checker(TM) was created using the spectroradiometer measurements. The chart is intended for use in camera calibration for future imaging of tomatoes. The final assessment was an online experiment, wherein participants were asked to choose a color from an array generated from images of tomatoes that best represent the color of the tomato. This was a first step toward understanding which characteristics people use to categorize a crop as ripe and how those characteristics are rendered by smartphone imaging

Lake dynamics in Central Asia in the past 30 years

Water is a key resource in arid Central Asia (CA) and is heavily affected by climate change and human activities. Temperature across the region has increased drastically especially in the mountain region while precipitation change is less homogeneous. The increased temperature has caused increased melting of glacier and snow which has a large contribution to the runoff in rivers. Human activities such as agriculture irrigation and reservoir management also affect water availability. In the Soviet era, agriculture in CA expanded continuously and large amount of water was extracted from rivers for irrigation. This has caused the catastrophic decline of the Aral Sea. In the post-Soviet era, countries in CA have reorganized their agriculture structure to be self-sufficient. It is important to understand how these changes affect water availability in CA especially under climate change. This dissertation uses lakes as proxy indicators of water availability and assesses how climate and human activities have affected lakes in CA. Seventeen lakes located in three former Soviet republics and western China from seven basins are examined using remote sensing and hydrologic modeling to estimate their changes in area, water level and volume. Agriculture area changes in these basins from seven countries are also examined using remote sensing. It is found that 1) lakes located in the mountains have generally expanded due to the melting glaciers and snow; 2) lakes located in the lowlands have remained relatively stable due to the relative stability of agriculture area; 3) reservoirs exhibit different seasonal patterns due to their major function as power generation reservoirs release water during the winter while irrigation reservoirs release water during the summer; 4) agriculture area in the former Soviet Central Asia republics is highly dependent on precipitation due to the lack of efficient irrigation infrastructure while agriculture in China has continuously expanded due to the adoption of drip irrigation and groundwater extraction. In conclusion, climate is the more dominant factor affecting water availability especially in the mountains causing the lakes to expand while agriculture irrigation has offset some of the surplus in the lowlands causing the lakes to remain relatively stable

Assessing and Forecasting Chlorophyll Abundances in Minnesota Lake using Remote Sensing and Statistical Approaches

Harmful algae blooms (HABs) can negatively impact water quality, lake aesthetics, and can harm human and animal health. However, monitoring for HABs is rare in Minnesota. Detecting blooms which can vary spatially and may only be present briefly is challenging, so expanding monitoring in Minnesota would require the use of new and cost efficient technologies. Unmanned aerial vehicles (UAVs) were used for bloom mapping using RGB and near-infrared imagery. Real time monitoring was conducted in Bass Lake, in Faribault County, MN using trail cameras. Time series forecasting was conducted with high frequency chlorophyll-a data from a water quality sonde. Normalized Difference Vegetation Index (NDVI) was generally well correlated to chlorophyll-a measured by a sonde (R2 = 0.678 for all data from 5 flights, between 0.323-0.986 for individual flights), while Visible Water Residence Index (VWRI) showed a weaker and less consistent correlation with chlorophyll-a (R2 = 0.027 for all data from 5 flights, between 0.17-0.866 for individual flights). While RGB cameras (trail cameras or UAVs) were useful for visual inspection and spotting blooms, these results suggest that quantitative remote sensing of chlorophyll in Minnesota Lakes should use near-infrared cameras at a minimum. Univariate time series forecasts using sonde chlorophyll-a data were compared using classical (ARIMA, wavelet-ARIMA) and machine learning techniques (LSTM, wavelet-LSTM). Chlorophyll-a was positively correlated to temperature and precipitation, while negatively correlated to conductivity and turbidity. Peak summer chlorophyll concentrations also appeared to be positively correlated to recent precipitation totals. 10-day chlorophyll-a forecasts using univariate LSTM and ARIMA outperformed a multivariate forecast (using conductivity, turbidity, temperature, and precipitation as predictors), suggesting that lower cost monitoring setups (a single chlorophyll probe) may be practical. To assist in understanding meteorological factors impacting interannual variability of blooms in Bass Lake, the relationship between peak summer chlorophyll-a (from Sentinel-2 satellite imagery) and temperature and precipitation were analyzed at Bass Lake. The impact of meteorological factors on patterns in chlorophyll-a for lakes in the Western Corn Belt Plains (WCBP) was also examined, using Sentinel-2 imagery (imagery was available for 160 lakes in the WCBP during 2019 and 2020). Peak summer Chlorophyll-a (from Sentinel-2 imagery) at Bass Lake was positively correlated to 2-week precipitation totals, suggesting a potential role of precipitation induced nutrient loading in initiating blooms; a negative correlation between peak chlorophyll-a and 60-day precipitation totals also suggested that increased residence time during drier periods may be a driving factor as well. While a slight negative correlation between precipitation and peak summer chlorophyll-a was present in a larger scale analysis of 160 WCBP lakes, too many confounding factors were present to show the impact of precipitation on blooms at a broader scale in Minnesota

A pan-Canadian comparison of cyanobacteria bloom management policies, programs, and practices

Across the globe, reports of cyanobacteria blooms are on the rise. The increasing occurrence of cyanobacteria blooms and cyanotoxins is attributed to phosphorous (P) loading, climate change, among a mix of other factors. While eutrophic lakes have a higher risk of blooms, oligotrophic and mesotrophic lakes are also experiencing blooms. This means governments’ need to develop a robust cyanobacteria management strategy (prevent, control, and mitigate) to protect public health. In Canada, water management is a shared responsibility among the federal, provincial, and local governments; however, cyanobacteria management is mainly a provincial and local government responsibility. This research compares and contrasts five provincial cyanobacteria management strategies from Alberta, Manitoba, Nova Scotia, Ontario, and Saskatchewan. Using a policy analysis framework, the methods of data collection include a review of grey and academic literature, legislation/regulations, and interviews with actors involved in cyanobacteria bloom management in each province. Also, three case studies – Lake Erie, Ontario; Lake Winnipeg, Manitoba; and Pigeon Lake, Alberta – were selected to analyze the policies and programs in practice. A robust cyanobacteria management strategy involves prevention, control, and mitigation to avoid public health risks. All jurisdictions in Canada have initiatives to manage cyanobacteria blooms. Nutrient management continues to be the cornerstone of bloom prevention by controlling point and diffuse sources of P runoff control. Nutrient management mostly relies on voluntary participation, so reductions in nutrient loading are heavily dependent on financial incentives, and education and outreach programs; however, there is little to no understanding or tracking of implementation. Also, P control will not reduce the risk of blooms in low P lakes. Monitoring programs and targets should include dissolved oxygen. Public health risks associated with cyanotoxins are mitigated through public reporting or monitoring drinking water sources and recreational waters. The monitoring and reporting programs vary by province. For instance, certain drinking water sources and recreational waterbodies are routinely monitored, whereas in other provinces sampling is driven by public reporting

A Pan-Canadian Comparison of Cyanobacteria Bloom Management Policies, Programs, and Practices

Across the globe, reports of cyanobacteria blooms are on the rise. The increasing occurrence of cyanobacteria blooms and cyanotoxins is attributed to phosphorous (P) loading, climate change, among a mix of other factors. While eutrophic lakes have a higher risk of blooms, oligotrophic and mesotrophic lakes are also experiencing blooms. This means governments need to develop a robust cyanobacteria management strategy (prevent, control, and mitigate) to protect public health. In Canada, water management is a shared responsibility among the federal, provincial, and local governments; however, cyanobacteria management is mainly a provincial and local government responsibility. This research compares and contrasts five provincial cyanobacteria management strategies from Alberta, Manitoba, Nova Scotia, Ontario, and Saskatchewan. Using a policy analysis framework, the methods of data collection include a review of grey and academic literature, legislation/regulations, and interviews with actors involved in cyanobacteria bloom management in each province. Also, three case studies Lake Erie, Ontario; Lake Winnipeg, Manitoba; and Pigeon Lake, Alberta were selected to analyze the policies and programs in practice. A robust cyanobacteria management strategy involves prevention, control, and mitigation to avoid public health risks. All jurisdictions in Canada have initiatives to manage cyanobacteria blooms. Nutrient management continues to be the cornerstone of bloom prevention by controlling point and diffuse sources of P runoff control. Nutrient management mostly relies on voluntary participation, so reductions in nutrient loading are heavily dependent on financial incentives, and education and outreach programs; however, there is little to no understanding or tracking of implementation. Also, P control will not reduce the risk of blooms in low P lakes. Monitoring programs and targets should include dissolved oxygen. Public health risks associated with cyanotoxins are mitigated through public reporting or monitoring drinking water sources and recreational waters. The monitoring and reporting programs vary by province. For instance, certain drinking water sources and recreational waterbodies are routinely monitored, whereas in other provinces sampling is driven by public reporting