MiniGlades

INTRODUCTION

Climate change is no doubt a major pressing issue in every part of the world. Every country in the world continues to experience the drastic effects of climate change, which is impacting public health, food, and water security, migration, peace and security. The effect of global warming is much worse than before, adverse weather conditions are causing impaired economic growth, loss of life and properties.

According to the Ghana climate change profile (2018), current projections for climate change predict a continuous rise in temperature and rainfall variabilities, which will lead to more incidents of flooding and droughts. In the past 50 years, 22 major hydrometeorological events in Ghana have affected 16 million people with over 400 deaths, of which 19 were flood events (NCCR, 2020).

Ghana’s 2020 population was estimated at 30.9 million, which represents a 26% increase over 2010 levels of 24.6 million at an annual growth rate of 2.3% compared to the 1.5% target for 2020 (NCCR, 2020). The rapid and unpredicted population growth has led to unplanned urbanization and the high rate of migration to the urban centers in search of urban benefits (Amo et al, 2017). This has greatly affected the original layout of the country, especially in the big cities like Accra and Kumasi. There is an increase in demand for housing and infrastructure which has led to informal settlements and illegal slum communities in flood prone areas.

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Area of Study: Accra Ghana

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On 3rd June 2015, days of torrential rain around Accra resulted in widespread flooding and left 159 people dead, a day that will never be forgotten in the history of the country. It was the most significant disaster to affect the city in recent times. An important fraction of the city was affected, and the impact on livelihoods and well-being was very large. Almost half of the households (44%) in the surrounding communities reported being directly affected by the 2015 flood ((Poverty & Equity Global Practice Working Paper 156, 2018). 

According to the report presented on the disaster, the main reason why the Kwame Nkrumah Circle got flooded was the inadequate discharge capacity of the lined Odaw drain, because the southern part of the Odaw basin is densely populated and includes the informal settlements Nima and Old Fadema, as well as the industrial and business areas in Kwame Nkrumah Circle and Kaneshie. Based on estimates from NADMO and World Bank, the flood caused damages of around 100 million USD (Poverty & Equity Global Practice Working Paper 156, 2018).

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Problem Statement

One of the major impacts of rapid urbanization is the resulting landscape transformation due to the expansion of cities and land use to meet the demand for housing, accommodation and infrastructural development. This has led to major construction activities on wetland areas, which otherwise were made up of natural vegetation, plant and animal species, and were supposed to be restricted areas creating an ecological balance.

There are numerous hazards associated with building on wetlands, however, has not prevented the numerous settlements and buildings that are now being developed on most wetlands in the city. Some existing wetlands are also being exploited by inhabitants in surrounding communities. For example, inhabitants of James Town close to the lagoons of the Densu Delta employ a great variety of fishing methods in the Densu delta, resulting in severe exploitation of fish stock (Kondra, 2018). Other degrading factors that have been associated with wetlands in Accra include human waste disposal and pollution, salt mining, deforestation for fuelwood or building materials, bushmeat hunting among others (Kondra, 2018).

In Kumasi, the second-largest city in Ghana which was referred to as ‘the Garden City of West Africa’, construction activities are the highest emerging factor of wetland degradation. The beauty of the vegetation that the city was well known for has been completely destroyed by commercial and residential infrastructure (Amo et al, 2017).

It is evident that little can be done to reverse the destruction of natural wetlands that have been overtaken by urban development. In any case, it is going to take a huge sum of investment and major loss of assets to undo the damage and move inhabitants and businesses out of these informal settlements to elevated grounds. It is due to this reason that we are focusing on proposing a solution to help reduce flood risks using constructed wetlands, well connected to reinforce the protection and conservation of currently existing natural wetlands.

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The Solution and Design of Constructed Wetlands

The Proposed Solution

With respect to flooding and natural wetland conversion issues in Accra, constructed wetlands was identified as a major tool to help reduce stormwater runoff intensity, hence reducing flooding impacts. These systems will be placed around flood-prone areas and in-between low lying and high lying areas in Accra, Ghana. Constructed wetlands are a sustainable means of treating stormwater and have proven to be more economical and energy-efficient than traditional centralized treatment systems (Scholz et al., 2005). 

A constructed wetland is an artificial habitat, most visibly made up of vascular plants and algal colonies, which also provide structural and nutritional support for an associated, highly heterogeneous microbial community. They act as natural sponges, soaking up and holding water until it can infiltrate into the ground.  Increased infiltration in urban areas is significant, as most of the runoff is derived from previous groundwater withdrawals.  Water that does not infiltrate into the groundwater is slowly released into nearby streams by the wetland.  This slow-release helps prevent flooding during storm events.

The vegetation in wetlands also helps reduce the speed of water as it flows over the lands. Locations to place the constructed wetlands will be defined by the susceptibility of an area to flood and its closeness to a suitable discharge system, i.e., rivers, streams, lakes et cetera.  Discharge from constructed wetlands in areas that are not close to such water systems can however be stored and used for residential and commercial purposes.

Design of a Constructed Wetland

The effectiveness and capacity of constructed wetlands for flood abatement vary, it depends on the size of the area, type and condition of vegetation, slope, location of the wetland in the flood path and the saturation of wetland soils before flooding. A one-acre wetland can typically store about three-acre feet of water, or one million gallons. An acre-foot is one acre of land, about three-quarters the size of a football field, covered one foot deep in water. Three acre-feet describes the same area of land covered by three feet of water. Trees and other wetland vegetation help slow the speed of flood waters. This action, combined with water storage, can lower flood heights and reduce the water’s destructive potential. (Source: EPA).

In events where there are very high run-off levels, intermediate detention tanks will be used to collect and store storm water runoff during a storm event, then released at controlled rates to the constructed wetlands. With this system in place, the drainage system can cater for higher intensity storms brought about by increasing uncertainties due to climate change.

The excess water stored in these tanks can also ensure that the wetland does not dry out during the dry season, as constant water supply is needed to conserve it. Detention tanks may be located above ground on buildings, on ground levels and even underground depending on the landscape of the area.

The control system of the constructed wetland will consist of flow sensors to monitor the rate of incoming and discharged water, level sensors to monitor the level of water in the basin, detention and storage tanks, and alarm systems to detect the risk of flooding.

Typical design features based on the design factors and the type of wetland under construction are shown in the below:

Design Factor	Surface Water Flow	Subsurface Water flow
Minimum Surface Area	8.7-43 ha/m*10^3 d	0.8 -17 ha/m*10^3 d
Maximum water depth	Relatively shallow	water level below ground surface
Bed Depth	Not Applicable	12.30m
Minimum Hydraulic Residence time	7 days	7 days
Maximum hydraulic loading rate	0.008-0.041 m3pd/m2	0.020-0.405 m3pd/m2
minimum-treatment	Primary (secondary optional)	Primary
Range of organic loading as BOD	10-20 kg/ha/d	2-157 kg/ha/d

OBTAINING DATASETS FOR FLOOD PRONE AREAS USING GIS TECHNOLOGY

For this study, Level-1 ground range detected images will be used, which belongs to the IW mode with dual polarization (VV/VH) (Cazals et al., 2016), of which the SAR images from Sentinel-1 satellites will be freely produced by Sentinel-1A in 2021 over the Greater Accra Region.

Methodology for Locating Water Systems

Sentinel application platform software (SNAP) will be used to pre-process Sentinel-1A imagery to acquire the backscattering coefficients for VH and VV polarizations. Time series of backscattering coefficients will then be generated using the seasonal synthesis method. Afterward, the thresholds for the backscattering coefficients for VH and VV polarizations will be calculated based on the training samples. The thresholds will be used to extract the surface water at Greater Accra Region based on the backscattering coefficient for VH and VV polarizations. After assessing the classification accuracy, the dynamic change of surface water area at Greater Accra Region will be analyzed (Xing, L., et al. 2018). The methodology is showed in figure below:

Step 1: Pre-Processing

The Level-1 product of Sentinel-1 GRD data will be calibrated, filtered by a 5X5 kernel using gamma map approach and terrain corrected before application. During terrain correction a 25m SRTM data will been used and the data will be resampled to a pixel size of 20m ground resolution. The digital numbers values (DN) of SAR data will then be converted into backscattering values in decibel (db) scale (Abdikan, S., & Sanli, F. B. 2016). The median value of all pixels will be used to extract the surface water. Pre-processing will be conducted in the Sentinel Application Platform provided by ESA.

Step 2: Threshold-based Image Classification

Unsupervised classification approach will be used for the image classification with the Iso Cluster Unsupervised Classification tool in ArcGIS 10.7. No prior definitions of the classes will be used (Lu, D., & Weng, Q. 2007). The image will be classified using ISODATA algorithm, which is one of the most frequently used unsupervised classification algorithm (Bhatt and Rao, 2016).

Step 3: Accuracy Assessment

The classification accuracy will be assessed using Confusion Matrix. In this study, overall accuracy (OA), user’s accuracy (UA), producer’s accuracy (PA), and Kappa coefficient will be used to evaluate the classification accuracy of Sentinel-1A (Congalton, 1991).

Step 4: Post-Processing

Dynamic change analysis of the surface water will be applied. For water classification maps, the water inundation frequency (p) can be counted for each pixel in the total time series by a multi-map overlay.

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The Business Model

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Expected Outcome

We aim to achieve a reduction in flooding and its associated impacts, which will contribute to climate change, protection of the environment, and improved access to quality water for household and commercial activities.

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References

1. Amo, M., Bih, F.K., Atta, A.J., Adu Gyamfi, T. and Mensah, M. (2017). Investigation into the Acquisition and Development of Wetlands in Built Environment Industry: A Case Study in Kumasi Metropolis. International Journal of Civil Engineering, Construction and Estate Management Vol.5, No.4, pp.1-20, December 2017. Published by European Centre for Research Training and Development UK, www.eajournals.org.
2. Amoako, C., & Boamah, E. F. (2015). The three-dimensional causes of flooding in Accra, Ghana. International Journal of Urban Sustainable Development, 7(1), 109–129. https://doi.org/10.1080/19463138.2014.984720
3. Asumadu-Sarkodie, S., Owusu, A.P. and Jayaweera H.M.P.C. (2015). Flood risk management in Ghana: A case study in Accra. Advances in Applied Science Research, 2015, 6(4):196-201, Available online at www.pelagiaresearchlibrary.com
4. Britannica, The Editors of Encyclopedia. “Accra”. Encyclopedia Britannica, 19 Apr. 2017, https://www.britannica.com/place/Accra. Accessed 4 May 2021.
5. Brydon, J., Roa, M. C., Brown, S. J., & Schreier, H. (2006). Integrating Wetlands into Watershed Management: Effectiveness of Constructed Wetlands to Reduce Impacts from Urban Stormwater. Environmental Role of Wetlands in Headwaters, 143–154. doi:10.1007/1-4020-4228-0_121000. (n.d.).
6. Clifford Amoako & E. Frimpong Boamah (2015) The three-dimensional causes of flooding in Accra, Ghana. International Journal of Urban Sustainable Development, 7:1, 109-129, DOI: 10.1080/19463138.2014.984720
7. Climate Change Profile Ghana (April, 2018) Published by Ministry of Foreign Affairs of the Netherlands, www.government.nl/foreign-policy-evaluations.
8. Ellis, J. B., Shutes, R. B. E., & Revitt, D. M. (2003). Guidance Manual for Constructed Wetlands. 112.
9. Keddy, P.A. (2010). Wetland ecology: principles and conservation (2nd ed.). New York: Cambridge University Press. ISBN 978-0521519403
10. Kenneth Quah. (2013). On site stormwater detention tank system. Agencia Nacional de Agua de Singapure, 80.
11. Kondra, Maria (2016). The status of the wetlands in the Greater Accra Region. WaterPower Working Paper, No. 9. Governance and Sustainability Lab. Trier University. Trier. Second edited version (2018).
12. National Climate Change Report (NCCR, 2020). Ghana’s Fourth National Communication to the United Nations Framework Convention on Climate Change. Available at www.epa.gov.gh.
13. The World’s Largest Wetlands: Their Ecology and Conservation. Cambridge, UK: Cambridge University Press. ISBN 978-0521834049ne and Freshwater Research. 65 (10): 934–941. doi:10.1071/MF14173
14. World Bank Group Poverty and Equity (June, 2018). The Road to Recovery: The Role of Poverty in the Exposure, Vulnerability and Resilience to Floods in Accra. Poverty & Equity Global Practice Working Paper 156
15. Young, R. D., & Dahl, T. E. (1993). Use of GIS in assessing areas of rapid wetland change. 851–859.

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