Bloom it | To Bloom or Not to Bloom
Project Details
The Challenge | To Bloom or Not to Bloom
Bloom it
“Bloom it app" a multi-sided data exchange applications that connects earth and space. It offers a platform where users can start sharing data as ocean pH, nitrogen, phosphorus concentrations in order to reinforce the satellite predict HABS
Abstract
The out-of-control growth of algae results in Harmful Algal Blooms (HABS). HABS’ growth causes severe damage to both humans and marine organisms, Produce extremely dangerous toxins that can sicken or kill people and animals, create dead zones in the water,..etc. Current HABS detection methods monitor only the change in ocean color, which is a post-HABS effect and it is way too late to protect these water bodies from further deterioration. Our research shows that a series of interconnected factors contribute to the occurrence of the blooms. So In order to increase the accuracy of such predictions, we have to consider more factors. our ,underdevelopment, application combines satellite data, climate maps and a collection of citizen-reported databases to give rise to an end for this mystery.
Factors Affecting/Indicating HABS
In order for HABs to occur three steps
- Getting there
- Being there
- Staying there
Getting there:
One of the main causes for the contamination of water with algae is ballast water discharge/ waste water contamination [1]
We can classify the factor into :
- Natural factors
- Anthropological factors (caused by humans)
However, the anthropological factors affects the natural factors and all factors interplay with each other contributing to the occurence of HABs
Nutrients excess (eutrophication):
For algae to grow, it’s essential to inhabit an environment rich with various natural and anthropogenic nutrients. A principal link was found between some nutrients’ concentrations (specifically Nitrogen, and Phosphorous) and nurture of different algae strain. In order to effectively predict HABS threat, we may calculate N/P ratio and compare the resultant value to the optimal HABS growth conditions (redfield ratio). [2]
The form of the excess Nutrients:
Different kind of algae requires different conditions for growth
So the form of this excess nutrients. For example the existence of the excess nitrogen in the form of ammonia is favoured by cyanobacteria and chlorophytes (toxic cyanobacteria), while NO3 in organic form is favored by diatoms [3]
Weather and Climate change
It was found that the climate change induce the growth of HABs. the temperature is increasing (global warming) which is causing warmer water. Warmer water speeds the growth of HABs, also warm water prevent the mixing of water which help the HABs to stay and grow . Also change of wind speed and direction was caused which led to the bringing of more deep water to coast which cause more HABs.[4]
pH
The pH also is a great parameter to be monitored to determine presence of HABs or not. The HABS cause fast and noticeable elevation of the pH of the water. That is because of the high usage of CO2 by the HABs which decrease oxygen, also at some point HABs consume that little O2. That cause the high basicity of water and death of fish and marine creatures. as the ph increase more than 8 it leads to an increase in the phosphorus concentration and high efflux of NH4 [4]
Critical Point of HABs
The cyanobacterial blooms corresponded to a threshold water temperature range, pH, total phosphorus (TP), ammonium nitrogen level, chemical oxygen demand, and dissolved oxygen levels of 19.5–32.5 °C, 7.0–9.38, 0.13–0.22 mg L−1, 0.38–0.63 mg L−1, 10.5–17.5 mg L−1, and 4.97–8.28 mg L−1, respectively.[5]
Color
The growth of HABS induces changes in ocean color, thus, scientists believe these changes be used to monitor the evolution of HABS. However, color change is a really sizable factor and includes a lot of uncertainties. Using water color only to predict HABS produce good, not-so-accurate results, besides being a result of HABS itself and, hence, it just indicates its presence (doesn’t predict).[4]
Water currents:
Blooms only occur in low flow rate water. So any natural or human factors as high water consumption and dam building, will lead to the decrease in the flow and combined with the other factors can contribute to the occurrence of HABs [3]
https://doi.org/10.1002/9781118994672.ch14
Current methods addressing this problem
- Current available method use satellite data/user data detecting ocean color change only
- these current methods only act as an alarm after the occurrence of HABS through the change in the ocean color resulting from the blooms
- They detect the result/effect not the cause
- They only consider one parameter (color change)
- They act as an After-bloom warning through taking blooms picture from the users and reporting it.
Our solution
- BLOOM It
In order to increase the accuracy of such predictions, we have to consider more factors. we introduce to you the "bloom it app" a multi-sided data exchange applications that connects, earth and space. The bloom it app offers a platform where users can take picture from their surrounding water bodies and start sharing data as ocean ph, nitrogen and phosphorus concentrations in order to reinforce the satellite predictions for the occurrence of HABs. The main idea is that there are many contributing factors that satellites cannot predict, so we believe that a simple camera photo can offer many data as PH of water by visualization, we will use standardization techniques, where we will start taking picture of certain known water ph lakes and use machine learning in order for the app to be able to assess the approximate ph from a photo, another main important factor to HABs is the redfield ratio or the N/P ratio. There are available strips that change their color giving an indication to the concentration of nitrite in water. With the same standardization and machine learning methods,
the app will read the color and determine the conc of N and P and further calculate the ratio. With the combination of these large set data that contribute to the early predictiOn to algal blooms we believe satellites can offer higher accuracy and earlier warning so that we can prevent these blooms as early as we can.
DATA Resources:
Censoos Data Set Temperature maps.
https://data.cencoos.org/?fbclid=IwAR0yYFBC1jxmU_OkRJ7tsbuZ0hUukIAA2trH-igVT95JR2T4VkhvL6ehlpo#map
Censoos Data Set Temperature Graphs.
Nasa EarthData Map view For ChloroPhyll Concentration and Water colour
References:
Retrieved from
[1]https://ioccg.org/group/habs/
[1]S. Bernard, "Harmful Algal Blooms and Ocean Colour - IOCCG", IOCCG, 2019. [Online]. Available: https://ioccg.org/group/habs/. [Accessed: 19- Oct- 2019].
[2]https://www.sciencedirect.com/science/article/pii/S030147971400334X
[2]K. Davidson, R. Gowen, P. Harrison, L. Fleming, P. Hoagland and G. Moschonas, "Anthropogenic nutrients and harmful algae in coastal waters", Journal of Environmental Management, vol. 146, pp. 206-216, 2014. Available: 10.1016/j.jenvman.2014.07.002 [Accessed 19 October 2019].
[3] https://doi.org/10.1002/9781118994672.ch14
[5]"Climate Change and Harmful Algal Blooms | US EPA", US EPA, 2017. [Online]. Available: https://www.epa.gov/nutrientpollution/climate-change-and-harmful-algal-blooms#targetText=Warmer%20temperatures%20prevent%20water%20from,warmer%20and%20promoting%20more%20blooms. [Accessed: 19- Oct- 2019].
[7]S. Smith, "Harmful Algal Blooms | Everything You Need To Know", Ysi.com, 2016. [Online]. Available: https://www.ysi.com/ysi-blog/water-blogged-blog/2016/09/harmful-algal-blooms-everything-you-need-to-know. [Accessed: 19- Oct- 2019].
[9]C. Zhao et al., "Predicting cyanobacteria bloom occurrence in lakes and reservoirs before blooms occur", Science of The Total Environment, vol. 670, pp. 837-848, 2019. Available: 10.1016/j.scitotenv.2019.03.161 [Accessed 19 October 2019].