Evaluations of Stream Flow Response to Land use and Land Cover Changes in Wabe Watershed, Omo-Gibe Basin, Ethiopia

Land Use and Land Cover Change (LU/LC) is one of the notable human induced worldwide changes. Hence, understanding the stream flow responses of a watershed to this dynamic change is becoming fundamental for water resources management planning. The study was conducted with the objective to analyses the impact of Land use and Land cover changes on stream flow response of Wabe watershed, in Omo-Gibe basin. Land use and land cover maps were developed using satellite image of Landsat5 TM 1988, Landsat7 ETM+ 2001 and Landsat8 OLI/TIRS 2018 through maximum likelihood algorithm of supervised classification using ERDAS Imagine 2014 and ArcGIS software for satellite image processing and map preparation. A physical based, semi-distributed hydrological model SWAT was used to simulate LU/LC change effects on the stream flow responses of watershed. During the study period the land use and land cover has changed due to natural and anthropogenic activity. The results depicted that there was an incessant expansion of agricultural land, built-up area and forest cover, on the other hand declining of agroforestry; grassland and woodland were happened during from the 1988 to 2018 periods. Due to the occurred LU/LC changes, the mean monthly stream flow were increased by 5.97m 3 /s for wet season and similarly the dry season flow showed increasing by 0.96m 3 /s during the study periods from 1988 up to 2018. Generally the result indicated that large changes of the stream flow in the watershed. Hence result notified an urgent intervention, so as to regulate the LU/LC change and to reduce its strong impacts on the stream flow of the Wabe watershed. Keywords: Land use/Land covers, stream flow, Wabe watershed, SWAT Model DOI: 10.7176/CER/12-10-02 Publication date: October 31 st 2020


INTRODUCTION
Water is an essential natural resource for all forms of life in our biosphere, which has great economic, environmental and social value and is fundamental to the livelihood, welfare of human beings and the earth's ecosystems. A fluctuation in stream flow may possibly have severe consequences for the water demand and supply of both for ecosystems and societies (Cuo, 2016;Lopes et al., 2016). It is widely recognized that land use change is an important factor that affect water resources and freshwater ecosystems (Gashaw et  International Journal of Civil, Mechanical and Energy Science, 6(6) Nov-Dec, 2020 | Available: http://ijcmes.com/ ISSN: 2455-5304 https://dx.doi.org/10.22161/ijcmes.66. 2 25 In the past decades, water resources shortages have become increasingly severe in many parts of the world, associated with the impacts of natural and anthropogenic activity. And this may be seriously affecting the economic growth of the world. Ethiopia is one of the well-endowed countries in Sub-Saharan Africa in terms of natural resources and appreciated diversity production in the environment. But now; Ethiopia's natural resources is under considerable pressure due to a rapidly increasing population, development of infrastructures, expanding agricultural activities and increasing deforestation (Kelbessa, 2014). Human based interventions are the main factors affecting water resources availability and distribution for centuries. Land use and land cover (LU/LC) change is one of the human manifested factors and a global challenge because it drives various environmental changes at all spatial and temporal scales Joyce et al., (2017) and these factors affect the quantity and distribution of both surface and ground water resources and the amount of water available for both ecosystem function and human use. As the watershed becomes more developed, it also becomes more hydrological active, changing the flood volume and runoff components as well as the origin of stream flow (Andualem & Gebremariam, 2015).
In Ethiopia currently many studies revealed that hydrologic models provide a framework for investigating the influences of land use and land cover change aspects on stream flow (Gashaw et al., 2018;Wakjira et al., 2016;Jemberie et al., 2016;Temesgen et al., 2014;Geremew, 2013). Land use and land cover change occurs in the country Ethiopia, as a whole and in the study area in particular was primarily allied with natural and anthropogenic activity such as proximate and underlying causes and rapidly increasing population, which has almost doubled in the country over the past 40 year (CSA, 2008). Hence, analyzing the potential impacts of these changes at deferent scale was found to be fundamental and thereby different thematic maps of land use change were used to assess the impact of these LU/LC change in the watershed. Previously, information on the regular monitoring watershed quality and stream flow response to land use and land cover changing aspects and their drivers are not available for the Wabe watershed. Therefore, this study were utilized SWAT model on ArcGIS platform to quantify and analyses the stream flow response to land use and land cover changes in Wabe watershed, Omo-gibe basin, Ethiopia and its implication on water resources of the watershed.

Description of the Study Area
Wabe watershed is found in the south western and central part of Ethiopia in Omo Gibe River basins. It is situated between 08°10'00" and 08° 30' 00"N latitudes and 37° 50' 00" and 38° 20' 00"E longitudes (see Figure 1). It covers a drainage area of about 1860 km 2 . Wabe River (also known as Wabi River or Uabi River) is a west-southwest flowing river of south-central Ethiopia, entirely confined within the reaches of Gurage Zone of the Southern Nations, Nationalities, and Peoples' Region (SNNPR). The mountainous highland divides the Gurage zone into east and west. The mountain chain forms a watershed boundary between the Gibe River sub basin in the West, the Great East African Rift Valley in the East, the Awash River basin in the North, and the Bilate River catchment in the South. The watershed is an area of rich environmental variety, but with increasing levels of environmental pressure in recent years from a rapidly expanding human population. The watershed topography as the entire is characterized by its physical variation. The highest elevation of 3612 m above sea level, accounts for the highest area in the river sub basins and the lowest elevation of 1646 m are found in the watershed and covers slope range from flat 0º to steep 75º separately. Based on the traditional classification system, DEM and contours developed, Wabe watershed laid in a climatic zone between Wurch and Woina-dega. The maximum temperature varies between 20°C to 39°C and the minimum temperature ranges from 0°C to 19°C. Also the data obtained from the Ethiopian Metrological Services Agency between 1988 and 2018 depicted that the long-term mean annual rainfall of the Wabe watershed ranges from 1000mm to 1500mm. The watershed soil is mainly formed from pellic vertisols (55%), chromic luvisols (7.9%), eutric fluvisols (9.41%), calcic fluvisols (13.44%), leptosols (5.59%), calcic xerosols (7.31%), calcaric flubisols (0.97%) and eutric nitisols (0.38%).

Data Sources and Materials Used
In order to ensure reliability and to meet the objectives of this research, different kinds of data were collected from different organizations, fields and satellite imagery. The two important types of data collected were spatial and time series data from both primary and secondary sources. The data from primary sources include spatial data and acquired from the United State Geological Survey (USGS) source (see Table 1) and field data. Secondary data contains time series data such as precipitation, temperature, wind speed, relative humidity, solar radiation and stream flow data was collected from Ethiopian ministry of water, irrigation and energy. Besides different previous research works and different tools such as ERDAS Imagine 14.0 was used for image process techniques, and ArcGIS 10.3 software was implemented for the production land use land cover maps. Dry season images were selected in order to get clear images, not having clouds to facilitate the image classification without difficulty, along years the same cropping season. Additionally, Google Earth, GPS, SWAT model and SWAT-CUP were used as supportive tools. 31 years period was grouped into two periods (1988-2001 and 2001 -2018) and used 30m spatial resolution imagery. In general, the Wabe watersheds covered by one scene and were downloaded from https://earthexplorer.usgs.gov/ in the path and row shown below (see Table 1). Then the panchromatic bands in the scene were stacked together to produce a multispectral image for each scene. At that time geometric and radiometric corrections and image enhancement were done. Before image classification the above stated preprocess were entirely executed on ERDAS Imagine 14.

Image Classification Methods and Processing
There are two general methods available used for satellite image classification. These are the supervised and unsupervised classifications. The classifications were conducted using ERDAS Imagine 14 software. The main difference between the two methods is how the classification was executed, in the case of supervised classification the software package carries out the classification based on signature edited or training sites and providing a signature is mandatory to classify the satellite image. On the other hand, the unsupervised classification has no training sites or signature not necessary to classify. After all the layers were stacked together and referenced the satellite image clipped or masking using watershed shape file. For this study, a supervised classification was selected using ERDAS Imagine 14 accompanied by the Google Earth software. After the signature was taken the classification conducted for every class with maximum likelihood classification algorithm at the pixel level and classified class name with their description can be stated as follows. The Six major LU/LC classes identified by using the field data and satellite images of Landsat TM 1988, ETM+ 2001 and OLI/TIRS 2018 includes agriculture land, agroforestry, built-up area, forest, grassland and woodland covers.
Agriculture: Made to include areas allotted to rain fed cereal crops (e.g. Corn, Teff, and Wheat), cash crops (chat) and horticultural crops particularly vegetables (e.g. onion, potato and cabbage). Crop cultivation both annuals and perennials, mostly in subsistence farming and the land covered by rural villages and scattered rural settlements.

Built-up area:
Built up area actually incorporates residential houses, building, small industrial areas and other man-made structures.
Forest: Areas that are covered with dense growth of trees with closed canopies. It was made to include human made plantation forest, riverine forests, dry ever green forest and moist mountain forest.
Grassland: Both communal and private grazing lands that are used for livestock grazing. The land is basically covered by small grasses, grass like plants and herbaceous species. It also includes land covered with mixture of small grasses, grass like plants and shrubs less than 2m and it is used for grazing.
Woodland: The land covered with both open and closed (high) woodland vegetation. It also includes the scattered rural settlements found within the Woodland.

Accuracy Assessment
Accuracy assessment is an important step in the image classification process. The objective of this process is to quantitatively determine how effectively pixels were grouped into the correct feature classes in the area under investigation. In this study, accuracy assessment was done for satellite imagery of Landsat8 OLI/TIRS 2018, for which the ground truth data is likely corresponding. An overall accuracy was calculated by summing the number of pixels classified correctly and dividing by the number of pixels considered. Therefore, an overall classification accuracy of 90.35% with overall kappa statistics of 0.86 was achieved.

Influences of Land Use and Land Cover Change on Stream Flow
Land use change is the key causes that could considerably alter the stream flow availability and this is accredited due to different natural and anthropogenic activities.

Land Use/ Land Cover Change Analysis
Land use and land cover classes categorized from Landsat TM 1988, ETM+ 2001 and OLI-TIRS 2018 contains agricultural land, agroforestry, built-up area, and forest, grassland and woodland cover (Figures 2, 3 and 4)  the increase in forest cover in Europe and North America was mainly related to economic development. But, increases in forest cover in some Asian countries not extensively depend on economic development level; rather it depends on social and political factors at work in their distinctive national conditions and capacities (for example China, India, Vietnam and South Korea). Moreover the reason of the increased forest cover, might be uncommon outside this study area, was due to the inhabitants started to grow eucalyptus trees on an increasing scale, which has increased the amount of land being covered with trees Woldetsadik and Muluneh, (2004) and the regeneration of previously degraded natural forests, since plantations have reduced the pressure on natural forests by substituting the demand for fuel wood and charcoal were the key and foremost factors manipulating the increase of forest cover, which are designed for sustainable livelihoods and a land recovery strategy in the study area.

Land Use/Land Cover trend in Wabe watershed
Wabe watershed experienced various LU/LC trends during the study periods. The land covers under agroforestry and woodland declined slightly whereas grassland decreased incessantly between the indicated years. In contrast the area of agricultural land, built-up and forest showed an increasing trend between 1988 up to 2018 (see Figure 5).

Evaluation of Stream Flow Due to Land Use/ Land Cover Change
One of the most important parts of the study was to assess the impact of land use and land cover changes on stream flow of the Wabe watershed. The assessment was done in terms of the impact of land use and land cover changes on the annual and monthly stream flow basis and the differences was assessed at the watershed outlet. The processes might be affected with changing LU/LC and it was done to perceive the stream flow change through incessant evolution of LU/LC change throughout the study period. Simulated average annual stream flow during calibration and validation period for the thematic map of 1988, 2001 and 2018 was presented in Table 3. The result has shown that, increase of stream flow both in calibration and validation period. The stream flow simulated for the three thematic maps were compared and judgment has been made based on the validation result. Stream flows exhibited a higher increase in the second period (2.80m 3 /s) than the former period (0.63m 3 /s). Generally, the stream flow has increased with a magnitude of 3.43m 3 /s during the study period (1988 to 2018). The result has noticeably indicated augmentation of stream flow associated with a prompt change of LU/LC in the watershed. Mainly the exacerbate increase of agriculture land contributed a lot more (see Table 2) and is in agreement with studies of (Andualem & Gebremariam, 2015). In Figure  6 presented the simulation result of mean monthly stream flow for 1988, 2001 and 2018 land use and land cover map.  Table 4 presented the wettest and driest mean monthly stream flow for the three prepared land use and land cover maps and their variability throughout the study period below. showed that the annual and the high flows of the catchment were increased by 13% and 46%, respectively while the low flows decreased by 35%. Unlike to other studies, dry season stream flows has depicted slightly an increasing trend for the whole study period with a magnitude of (+) 0.96m3/s, which has reflected due to soil moisture content and lateral flow increased in the watershed; but as compared to wet seasonal flows the dry season flows were found to be smaller associated with intense agricultural expansion ground water flow influence were decreased in dry season.

IV. CONCLUSIONS
During the study period Wabe watershed has been undergoing different LU/LC changes and main finding of this study depicted an incessant increase in agriculture land, built-up area and forest cover at the expense of agroforestry, grassland and woodland between 1988 and 2018. Mostly, the major LU/LC change observed in the last 31 years from 1988 up to 2018, agriculture land, built-up area and forest cover expanded by 66.90, 160.80 and 34.90% respectively whereas agroforestry, grassland and woodland declined by 20.53, 96.33 and 15.52% separately over the analysis period. The reason is mainly due to the population growth. This might be due to the population pressure has caused a high demand for additional land result absence of agriculture land is the major problem for farmers in the study area. Due to the occurred LU/LC changes, the mean monthly stream flow were increased by 5.97m 3 /s for wet season and similarly the dry season flow showed increasing by 0.96m 3 /s during the study periods from 1988 up to 2018. Therefore curving the trends of LU/LC towards increasing vegetation covers is very important so as to regulate the LU/LC change and to reduce the seasonal flow and thereby to control the large changes of the flow regime in the Wabe watershed.