1 Modelling infrastructure and markets for zonation of cage aquaculture in Lake Volta, Ghana. Thesis submitted for the degree of MSc in Sustainable Aquaculture By Mohammed Madhafar Al Wahaibi Supervised by Professor Lindsay Ross Institute of Aquaculture University of Stirling Stirling, FK9 4LA Scotland August 2014
40
Embed
Modelling infrastructure and markets for zonation of cage ...
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
1
Modelling infrastructure and markets for zonation of cage aquaculture in
Lake Volta, Ghana.
Thesis submitted for the degree of MSc in Sustainable Aquaculture
By
Mohammed Madhafar Al Wahaibi
Supervised by
Professor Lindsay Ross
Institute of Aquaculture
University of Stirling
Stirling, FK9 4LA
Scotland
August 2014
2
Abstract
The demand for fish products in Ghana has increased in last few years. However the fish
production from fisheries cannot satisfy this local demand. The solution could be the
establishment of cage aquaculture in Lake Volta, which is the largest artificial lake in the
world with area of 8500 km2. For that, cage farms should be located in an area close to
market in order to reduce transportation cost of fish produced and larvae and feed required.
Geographical Information Systems are used to locate the optimum sites for three different
cages size: small cages (5*5*4m), medium cages (15*15*5m) and large cages
(30*30*6m), based on three sub-models bathymetry, hydrography (physical parameters)
and market access (social parameter). The market access sub-model was developed from
transportation cost for both road and water starting from 170 districts, and the populations
in each district. The overall model was developed with using four different weightings for
marketing to illustrate the effect of market access for site selection. The number of sites for
small cages in suitable and highly suitable areas which achieved the highest market access
weight (0.6) was 310 sites. However, for medium and large cage size this was only
achieved for 272 and 228 locations respectively. These models for different cage sizes and
market access weight provide qualitative and quantitative guidelines for decision makers
for sites selection and aquaculture development.
Keywords
GIS, Cage aquaculture, Lake Volta, Ghana, Site selection, Market access
1. Introduction
Ghana is located north of the equator in West Africa. It has high potential for freshwater
aquaculture in Volta Lake which is one of the largest man-made lakes in the world. It
extends from the Akosombo Dam in southeastern Ghana to the town of Yapei, 520
3
kilometers to the north. The lake generates electricity, provides inland transportation and is
a potential source for irrigation and an important source of inland fish production.
According to the FAO FishStatJ database (2015), Aquaculture production increased from
938 metric tons in 2003 to over 32513 metric tons in 2013. In 2012, aquaculture
production from cages was over 24249 metric tons compared to less than 1772 metric tons
from ponds and tanks. The main fish species cultivated are Nile tilapia (Oreochromis
niloticus) and African catfish (Clarias gariepinus) with Tilapia species representing over
90 percent of farmed fish production.
In 2003 domestic fish production only met 51.7% of Ghana's requirements from its
domestic sources and it reached only 68.1% in 2004 from both domestic production and
imports. (Awity, 2005). In 2007, Ghana imported 212000 tons of fish with value of US$
262 million. (Kwadjosse , 2009). Fisheries around the world are declining because of
overfishing, pollution and habitat destruction, whereas, human demand for fish as a source
of protein is increasing. Aquaculture is the way to cover this gap between demand and
supply of fish and in Ghana, Lake Volta provides a substantial resource for fish production
which can cover the shortfall in fish demand.
Lake Volta is a man-made reservoir created when the World Bank and International
Financial Groups built Akosombo Dam in 1961. It supplies local communities with a wide
range of freshwater fish. In order to increase fish production in Ghana, the Ghanaian
government developed a National Aquaculture Development Plan with the target to
increase farmed fish production by 1000% within 5 years (GNADP, 2012).
In lakes, cage aquaculture is an efficient method to increase fish production. Unlike ponds
and tanks, cage-culture requires lower investment costs in both capital and production. In
sites with optimum waves and currents, the fish waste and uneaten feed will wash away
from the cage, requiring less effort for net cleaning and good water exchange enables better
4
fish growth. According to Kassam (2014), production from cage farms in Ghana grew from
4000 tons in 2009 to over 24000 tons in 2012 with a total production of 27451 tons.
Site selection is an important factor for sustainable production. There are many parameters
involved in site selection which include: bathymetry, hydrography (wave height and
currents), water quality (temperature, pH, dissolved oxygen and nutrients, etc),
infrastructure (transport, electricity supply systems) and socio-economic factors (potential
market, labour sources, goods and services) (Nath et al., 2000). A Geographic information
systems (GIS) is an integrated assembly of computer hardware, software, geographic data
and personnel designed to efficiently acquire, store, manipulate, retrieve, analyze, display
and report all forms of spatially referenced information geared towards a particular set of
purposes (Nath et la., 2000). The use of GIS allows combination and processing of many
variables to select the optimum aquaculture sites. This technique is relatively new and it
has been used previously for site selection such as tilapia cages in Mexico (Ross et al.,
2010), sea bream and sea bass cages in Tenerife (Pérez, 2005), Shrimp ponds in Vietnam
(Giap et al., 2005).
GIS-based site selection has most often focused upon physical and biological parameters
with few attempts to incorporate and model market influences. The aim of this study was
to construct a spatial database of relevant parameters to enable modelling of optimal
locations for cage aquaculture in Lake Volta, Ghana based on market access, coupled with
key environmental parameters. This will allow to identification of optimal sites for
development of aquaculture.
2. Materials and Methods
2.1. Study area
Lake Volta is located in West Africa within the Republic of Ghana. It is the largest artificial
lake by surface area in the world with a total length of 520 km and covering approximately
5
8,500 km2
(Zwieten, 2011). The study area covers the main body of the lake from the
Akosombo Dam to the three main river inflow locations (White Volta River, Black Volta
River and Oti River) and has a surface area of 5895 km2. There are around 148 fish farm in
the lake found from Google Earth (Fig. 1). Ghana has two main seasons: wet and dry. In
the north there is a single wet season (May – November) and the dry season is between
(December and March). In the south, there are two wet seasons, one in March to July, and
a shorter wet season in September to November (McSweeney et al, 2010).
Figure 1. Fish cage farms locations at Lake Volta, Ghana.
6
2.2. GIS systems
Data analysis and model development used IDRISI SELVA edition (Version of 17.02)
[Clarks Labs, MA, USA] as well as QGIS software. The software operated on an Intel(R)
Xeon(R) CPU X5460 @ 3.16 GHz workstation with 8.00 GB RAM, 3 TB hard disk, and
twin Dell 21” 2408WFP monitors.
2.3. Model Development
Baseline satellite imagery was developed from a mosaic of six recent LANDSAT 8 OLI
images which were pansharpened to 15m resolution (Xia, 2014). The study area straddles
two UTM sectors, UTM 30N and UTM 31N. All data were re-projected to the UTM 31N
georeference system, as four of the six images were UTM-31N and this is the projection
used in the field surveys.
Three sub-models were used in the development of the site selection models: bathymetry,
hydrography and market access (Fig. 2). In each sub-model the results maps were
reclassified to a scoring system where 1 is highly unsuitable and 5 is highly suitable for
cage aquaculture. Similar studies have used other scoring systems, such as a 1-4 scoring
system developed for southwestern Bangladesh (Salam et al., 2003); 1-8 scoring system
used in Tenerife, Canary Islands (Pérez et al., 2005) and a 1 to 15 scoring system used in
the State of Sinaloa, Mexico (Aguilar-Manjarrez and Ross, 1995). However, a 5 point
system was adopted in order to link with a previous study for Lake Volta in Ghana by Xia
(2014). This allowed data sensitivity but was not too complex to manage. Scores were
assigned based on values from the literature and/or expert opinion.
Three cage sizes were selected for use in the modeling process: small cages (5*5 m, depth
of 4 m and 2 m for net hang); medium cages (15*15 m, depth of 5 m and 2.5 m for net
7
hang) and large cages (30*30 m, depth of 6 m and 3 m for net hang). Those sizes can all
potentially be used in Lake Volta and the range allows decision makers to evaluate the
suitability of the lake for three different scales of aquaculture. The small cages are suitable
for local market farming, while the medium and large cages are more suitable for
commercial farming for local and international markets. The data was reclassified in terms
of suitability for each of the three cage types.
Figure 2: Structure of the overall model processes for cage site selection in Lake Volta,
Ghana.
2.4. Bathymetry sub-model
Bathymetry is an important parameter for cage farming. They should not be in areas that
are too shallow or too deep. In the previous study (Xia, 2014) there were no bathymetric
datasets available for Lake Volta and so a new bathymetric map using an empirical
approach based on Landsat 8 images and partially verified using bathymetric data collected
from the lake. It is based on the principle that light passing through water becomes
attenuated so shallow water areas appear bright and deep areas look dark in an image
(Gholamalifard et al., 2013).
8
Landsat 8 band 3 (Green, wavelength from 0.525 to 0.600 um) was used to calculate water
depth while band 6 (Short Wavelength Infrared) was used to locate the water body
borderline because of its clear reflection from the water surface and minimal atmospheric
interference. Water depth was calculated using a model described by Landmap
Geoknowledge (2005) and depends on the empirical tuning by Jerlov (1976), Lyzenga
(1981) and Jupp (1988). Field data was collected by the Water Research Institute (Accra,
Ghana) and used to partially verify the results. The final bathymetric map is shown in
Figure 3.
Figure 3: The bathymetric map of Lake Volta, Ghana in meter (from Xia et al, 2014).
9
The satellite data was collected in March 2014 near the start of the rainy season so the
depth of the water in Lake Volta was the lowest of the year which allowed development of
a model which avoided any damage to cages due to depth change as well as allowing for
sufficient water exchange and discharge of wastes (Beveridge, 2004). However areas that
are too deep can also generate problems because of increase costs associated with mooring
systems (Beveridge, 2004; Pérez et al., 2005). According to Beveridge (2004) the nets
should be at least 4-5 m above the sediments. However, Lake Volta is a man-made
reservoir which covers submerged trees, buildings and other obstacles. This could result in
problems for cage aquaculture and to allow for that the depth under cages should be twice
the cage depth. A reclassified scheme for the three cage sizes modeled is shown in Table 1.
Table 1: Water depth (in meters) with classification for three different cage size (from Xia,
2014).
2.5. Hydrography sub-model
2.5.1 Wave height
Wave height is an important factor for cage siting because it can damage and make stress
Falconer, L.., Hunter, D.C., Scott, P.C., Telfer, T., & Ross, L. (2013). Using physical
environmental parameters and cage engineering design within GIS-based site suitability
models for marine aquaculture. Aquaculture Environment Interactions, 4(3), 223-237.
Falconer, L.L., Hunter, D.C., Scott, P.C., Telfer, T., & Ross, L. (2013). Using physical
environmental parameters and cage engineering design within GIS-based site suitability
models for marine aquaculture. Aquaculture Environment Interactions, 4(3), 223-237.
FAO FishStatJ (2014). FishStatJ: Software for Fishery Statistical Time Series. Available
at:<http://www.fao.org/fishery/statistics/software/fishstatj/en/>[Accessed 3rd August 2014].
Gholamalifard, M., Kutser, T., Esmaili-Sari, A., Abkar, A.A. & Naimi, B. (2013). Remotely
Sensed Empirical Modeling of Bathymetry in the Southeastern Caspian Sea. Remote
Sensing, 5(6), 2746-2762.
Giap, D.H., Yi, Y., & Yakupitiyage, A. (2005). GIS for land evaluation for shrimp farming in
Haiphong of Vietnam. Ocean & coastal management, 48(1), 51-63.
Global petrol prices (2015). Ghana Diesel prices, liter [Online] Available from :< http://www.globalpetrolprices.com/Ghana/diesel_prices/> [Accessed 25th May 2015]
GNADP. (2012). Ghana National Aquaculture Development Plan (GNADP). Fisheries
Commission. Ministry of Food and Agriculture, Ghana. 78pp.
Gulbrandsen, O. (2012). Fuel savings for small fishing vessels - a manual. Rome, FAO. 57 pp.
Huang, C.C., Tang H.J. & Liu, J.Y. (2008). Effects of waves and currents on gravity-type
cages in the open sea. Aquacultural Engineering, 38(2), 105-116.
Jerlov, N.G. (1976) Marine optics, Elsevier Sci., New York. 231pp.
Jupp, D.L.B. (1988). Background and extensions to depth of penetration (DOP) mapping in
shallow coastal waters. Proceedings of the Symposium on Remote Sensing of the Coastal
Zone, Queensland, SIV2.1-IV2.29.
Kassam, L. (2014). Aquaculture and food security, poverty alleviation and nutrition in Ghana:
Case study prepared for the Aquaculture for Food Security, Poverty Alleviation and
Nutrition project. WorldFish, Penang, Malaysia. Project Report: 2014-48. 9-13pp.
39
Kwadjosse T (2009) The law of the sea: impacts on the conservation and management of
fisheries resources of developing coastal states – the Ghana case study. Division for Ocean
Affairs and the Law of the Sea. Office of Legal Affairs, the United Nations, New York. 16pp
Landmap Geoknowledge (2005). Landmap Water Depth Equation [Online] Available at: <
Pérez, O.M., Telfer, T.C. & Ross, L.G. (2003). On the calculation of wave climate for
offshore cage culture site selection: a case study in Tenerife (Canary Islands). Aquacultural
Engineering, 29(1), 1-21.
Pérez, O.M., Telfer, T.C., & Ross, L.G. (2005). Geographical information systems‐based models for offshore floating marine fish cage aquaculture site selection in Tenerife, Canary