This research focused on integrating GIS into energy alternatives for climate change mitigation by creating a GIS-based hydrologic model that can be used to identify sites that have significant potential for micro hydropower development within the River Perkerra catchment area. Hydropower is a clean and renewable energy source that remains largely untapped in the country and its development can be used to mitigate anthropogenic climate change by reducing reliance on fossil or biomass derived fuels. This research established the extent of this resource and whether the available sites with significant micro hydropower potential within the study area were amply copious to warrant further development. Currently, such identification is done physically using means that are menial, costly and significantly time consuming. A 90-metre resolution Digital Terrain Model (DTM) data obtained from the Shuttle Radar Topography Mission and various GIS tools were used to create a hydrologic framework which was used to identify potential sites along River Perkerra that suited any desired head requirement for the purposes of locating micro hydropower plants. The derived model demonstrated that it was possible to identify sites at discrete geographic locations along any stream drainage network using GIS. In addition, the model also provides a decision support system that integrates a powerful graphical user interface, spatial database management system and a generalized river basin network flow model for the purposes of exploiting and developing micro hydropower. With sufficient data on catchment discharge and use of higher resolution DTM, the model can be further enhanced to accurately obtain the total microhydro potential of River Perkerra by aggregating the respective potentials of every steam segment.
Kenya hopes to industrialize by 2030 [
Climate variability is already having a large negative effect on the region’s socio-economic development. This is likely to worsen with climate change hence the need to vigorously pursue adaptation to climate change. Together with other factors including rapidly growing population, poor management of natural resources and limited use of technologies, climate variability or long-term climate change could worsen the poverty situation in Kenya. Due to the many and diverse impacts likely to result from climate change, a combination of mechanisms including both technical and social strategies would be needed to promote adaptation [
The causes of climate change are related to energy use and as such, it has been established that anthropogenic factors mainly resulting from greenhouse gas emissions associated with energy use and generation are the key causes of climate change. Currently, CO2 concentrations stand at 380 ppm and the global average temperature has risen by 0.6˚C over the past 100 years with related impacts being observed. With status quo prevailing, continued use of fossil fuels and destruction of bio-mass to satisfy the ever growing energy demand, the global average temperature is expected to rise by between 1.4˚C and 5.8˚C this century [
Energy is indeed necessary for economic development and the level or intensity of its use is synonymous to any country’s economic growth and development. Countries with low per capita consumption of commercial energy would typically have correspondingly low per capita Gross Domestic Product (GDP) [
Since factors related to energy use are the main contributors to climate variability, any technical intervention needs to focus more on greener sources of energy. Some of these green energy sources include the solar, geothermal, and hydro-power. These are already being used in the Kenya but siting of the points for harnessing energy including hydropower has been a challenge. This research aimed at providing a means of identifying potential micro hydropower sites using GIS to enable further evaluation and development to harness this clean energy source.
Climate change is an issue of global impact and concern which is driven mainly by anthropogenic causes. There is need to adopt cleaner energy and at the same time reduce demand for biomass energy that has driven destruction of forests which naturally act as carbon banks whilst sequestering atmospheric carbon dioxide, one of the major greenhouse gases [
Considering that Geographic Information System (GIS) technology is evolving, its use is expected to steadily increase across a multitude of domains as it provides an efficient framework for geo-referencing information enabling expedited and accurate decision making based on location and innate relationships hence reducing the costs associated with extensive fieldwork and manual office work.
The overall problem addressed by this study is that while the use of GIS has been commonplace in disciplines such as forestry, hydrology, environmental management, geology and mining, it has not been used extensively in the exploitation of renewable energy sources. Currently, identification of suitable micro hydropower sites within river drainage networks is conducted through abstract and manual means that do not provide the entirety of crucial hydrological information needed to support decision making. This process is menial, time consuming and costly hence in order to hasten and improve the process of locating and planning micro hydropower projects within a given river basin there are pertinent research questions such as: Could GIS be used as a proactive planning tool that could lay ground for a quicker assessment of micro hydropower potential and identification of suitable sites where this source of renewable energy can be effectively exploited? The objective of this research study was to identify sites along the gauged stream segments within River Perkerra catchment area in Baringo County, Kenya with significant potential for micro hydropower development and subsequently estimate the electric power generation potential.
Hydropower has been in use since ancient times from before 200 B.C. by the Greeks and Chinese where this form of energy was harnessed for basic tasks such as irrigation, grinding of grains into flour [
Electricity is a secondary energy source, obtained through conversion of primary sources of energy such as hydropower, thermal, wind or solar [
To date, there is still no internationally agreed definition of small-hydro. Some school of thought applies the term small-hydro to collectively cover small, mini, micro and pico hydropower schemes. Conventionally, small- hydro refers to between 2.5 and 25 MW, mini-hydro typically refers to schemes below 2 MW, micro-hydro below 500 kW and pico-hydro below 10 kW. These are arbitrary demarcations though most principals cut across smaller and larger schemes [
While the process of identifying potential micro hydropower sites can be an overwhelming exercise, remote sensing and GIS technology can play a pivotal role in the scientific assessment of drainage networks to accurately identify locations with the highest potential for hydropower development hence increasing access to affordable energy [
Das, S. & Paul, P. K. note the difficulty of site selection for small hydro in the inaccessible tracts of Himalayan region while using conventional methods leading to considerable loss of time and money. Their research demonstrated the use GIS and Remote Sensing technology to arrive at various alternative sites available in the study area and finally to select the most technically suitable site [
A study by Jha, R. used the hydro-meteorological data from Department of Hydrology and Meteorology for hydrological analysis of all the rivers in Nepal. By incorporating hydrological analysis, GIS and a purposely developed hydropower model as shown on
A paper by Feizizadeh & Haslauer [
This research proposes to adopt both models by Jha, R. [
Hydrologic Analysis was carried to obtain the respective flow duration curves at gauging station points along the Perkerra River. The flow duration curves were necessary for calculations to determine the average flow magnitude in a year that could be expected to be equal or exceed 40, 50 and 60 percentile of the time. The exercise involved use of primary data containing river flows from gauging stations supplied by the Water Resource Management Authority (WRMA) and the Rift Valley Water Services Board.
Delineation of River Perkerra drainage network through GIS hydrologic modelling was done using ArcGIS Model Builder & ArcHydro tools to process DEM data from the Shuttle Radar Topography Mission (SRTM) containing elevation data at a 90 m resolution in ASCII format. Ground truthing and topographic maps from the Survey of Kenya were used to validate the derived river network.
A hydropower model was developed by further processing the delineated drainage network of River Perkerra within ArcGIS to:
1) Identify sites along delineated stream network that have suitable head requirement for the purposes of locating micro hydropower plants.
a) Drop points within the area of interest were obtained by subtracting minimum neighbours from the area of interest DEM. The minimum neighbours were derived by applying 3 by 3 cell focal statistics against each pixel on the area of interest DEM.
b) Drop points along the river network were obtained through extracting by mask, drop points within the area of interest from a 3D raster representation of the river network. The river drop was colour coded and classified in terms of head as either high (>50 m), medium (10 - 50 m) or low (<10 m) which would guide the type of turbine as illustrated on
2) Identify potential hydropower sites along gauged stream segments within the study area.
a) To establish the hydropower potential, the river drop was multiplied by gravitational acceleration 9.81 ms-2.
b) The product of hydropower potential and river discharge would yield the extractable hydropower output of any identified site.
3) Estimate the power potential of selected hydropower sites along the gauged stream segments in the drainage basin. Using hydropower potential and discharge calculation from hydrologic analysis of the Perkerra River, the extractable Q40, Q50 & Q60 hydropower output potential was obtained for high head sites along the Tigeri, Lelgel and Eldama Ravine gauged sections of the River Perkerra. A high-level flow chart of the model is shown in
For each gauging station with data flow-duration curves were derived with the cumulative frequency curve that showed the percent of time specified discharges were equaled or exceeded over the period which readings were recorded. The flow-duration curve represents the long-term characteristics of the gauged stream segments hence were used to predict the distribution of future flows for hydropower estimation. The respective Q40, Q50 and Q60 are tabulated on
The River Perkerra watershed and its stream network were delineated the from digital elevation model data.
In addition, the GPS coordinates for gauging station obtained during site visits all fell within the derived river network confirming accuracy of the model.
Gauging Station Code | Name | Location | Q40 m3∙s−1 | Q50 m3∙s−1 | Q60 m3∙s−1 |
---|---|---|---|---|---|
2EB01 | WASEGES | KISANANA | 0.37 | 0.34 | 0.31 |
2EC02 | RONGAI | RONGAI | 0.111 | 0.078 | 0.056 |
2EC03 | RONGAI | RONGAI | 0.093 | 0.062 | 0.045 |
2EC04 | RONGAI | RONGAI | 0.02 | 0.02 | 0.019 |
2ED01 | TIGERI | KAPCHOLOI | 0.82 | 0.8 | 0.8 |
2ED02 | LELGEL | POROR | 0.35 | 0.30 | 0.28 |
2ED03 | ELDAMA RAVINE | ELDAMA RAVINE | 0.0.30 | 0.28 | 0.24 |
2EE07 | PERKERRA | KIMOSE | 2.718 | 1.7515 | 1.187 |
2EE07A | PERKERRA | MARIGAT BRIDGE | 6.612 | 5.766 | 4.788 |
2EE07B | PERKERRA | MARIGAT BRIDGE | 0.907 | 0.687 | 0.525 |
2EE08 | PERKERRA | KIMNGOROM | 1.589 | 1.2 | 0.91 |
2EF04 | NAROSURA | KABIMOI | 0.907 | 0.687 | 0.525 |
2EG01 | MOLO RIVER | KELELWA | 0.863 | 0.575 | 0.404 |
respect to the derived stream network.
River drop points were extracted from the DEM and stream net-work in order to identify sites along delineated stream network that potentially have suitable head requirement for locating micro hydropower plants.
The extractable Q40, Q50 & Q60 hydropower output potential for sites along the Tigeri, Lelgel and Eldama Ravine gauged sections of the River Perkerra identified to have a head drop of 50 metres and above are tabulated on
This research demonstrated the use of GIS in accurately identifying and assessing the extent of hydropower
Reference Gauging Point (s) | Head Drop (m) | Hydro Site Coordinates (Decimal Degrees) | Total Available Discharge (m3∙s−1) | Total Potential Power Output (MW) | ||||
---|---|---|---|---|---|---|---|---|
Q40 | Q50 | Q60 | Q40 | Q50 | Q60 | |||
TIGERI 2ED01 | 51 | 35.712236, 0.102368 | 0.82 | 0.80 | 0.80 | 0.410 | 0.400 | 0.400 |
ELDAMA RAVINE 2ED03 | 52 | 35.711548, 0.035348 | 0.30 | 0.28 | 0.24 | 0.153 | 0.143 | 0.122 |
ELDAMA RAVINE 2ED03 | 50 | 35.712513, 0.036192 | 0.30 | 0.28 | 0.24 | 0.147 | 0.137 | 0.118 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 58 | 35.725049, 0.069461 | 0.65 | 0.58 | 0.52 | 0.370 | 0.330 | 0.296 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 63 | 35.725772, 0.069943 | 0.65 | 0.58 | 0.52 | 0.402 | 0.358 | 0.321 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 55 | 35.726978, 0.071630 | 0.65 | 0.58 | 0.52 | 0.351 | 0.313 | 0.281 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 62 | 35.728304, 0.074523 | 0.65 | 0.58 | 0.52 | 0.395 | 0.353 | 0.316 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 51 | 35.729388, 0.075126 | 0.65 | 0.58 | 0.52 | 0.325 | 0.290 | 0.260 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 58 | 35.739343, 0.086141 | 0.65 | 0.58 | 0.52 | 0.370 | 0.330 | 0.296 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 78 | 35.742660, 0.092853 | 0.65 | 0.58 | 0.52 | 0.497 | 0.444 | 0.398 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 69 | 35.743586, 0.093778 | 0.65 | 0.58 | 0.52 | 0.440 | 0.393 | 0.352 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 79 | 35.744357, 0.094704 | 0.65 | 0.58 | 0.52 | 0.504 | 0.449 | 0.403 |
LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 85 | 35.746131, 0.099024 | 0.65 | 0.58 | 0.52 | 0.542 | 0.484 | 0.434 |
TIGERI 2ED01 & LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 73 | 35.748615, 0.103190 | 1.47 | 1.38 | 1.32 | 1.053 | 0.988 | 0.945 |
TIGERI 2ED01 & LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 67 | 35.754556, 0.110750 | 1.47 | 1.38 | 1.32 | 0.966 | 0.907 | 0.868 |
TIGERI 2ED01 & LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 62 | 35.755250, 0.111599 | 1.47 | 1.38 | 1.32 | 0.894 | 0.839 | 0.803 |
TIGERI 2ED01 & LELGEL 2ED02 & ELDAMA RAVINE 2ED03 | 55 | 35.756253, 0.112370 | 1.47 | 1.38 | 1.32 | 0.793 | 0.745 | 0.712 |
resources, including whether the availability of sites with micro hydropower potential within the study area was sufficiently large to warrant further development.
Based on the results it is established that:
1) GIS can be used to accurately identify sites at discrete geographic locations along any stream drainage network.
2) Potential sites for hydropower development are numerous within the study area and can reliably generate electricity all year round. These sites have hydropower potential characteristic of pico, micro, mini and small hydropower installations.
The use of GIS in identification and assessment of a country’s hydropower potential should be adopted. With sufficient data on catchment discharge, the model can be further enhanced to obtain the total micro hydropower potential of River Perkerra whereby the potentials of every stream segment are aggregated. This research can be replicated to assess hydropower potential for any river network
Gerald C. K. Chelelgo,David N. Siriba,Elijah K. Biamah, (2016) Micro Hydro Potential Modelling: Integrating GIS into Energy Alternatives for Climate Change Mitigation. Journal of Geoscience and Environment Protection,04,47-59. doi: 10.4236/gep.2016.48005