Multi-scale assessment of land changes in Ethiopia : understanding the impact of human activities on ecosystem services

Remote sensing provides land-cover information on a variety of temporal and spatial scales. The increasing availability of remote sensing data is now a major factor in land-change analysis and in understanding its impact on ecosystem services and biodiversity. This wider accessibility is also leading to improvements in the methods used to integrate these data into land-cover modelling and change analysis. Despite these developments in current technology and data availability however, there are still questions to be addressed regarding the dynamics of land cover and its impact, particularly in areas such as Ethiopia where the human population is expanding and there is a need for improvement in the management of natural resources. Multi-scale approaches (from the national to the local) were used in this thesis to assess change in land cover and ecosystem services in Ethiopia, specifically in terms of provisioning (the production of food, i.e. cash crops) and regulating (climate control for vegetation cover). These assessments were based on multi-scale remote sensing (very high spatial resolution remote aerial sensing, high-resolution SPOT 5 satellite imaging and products of medium-resolution satellite remote sensing) and climate data (e.g., precipitation, temperature). The main focus in this thesis is on mapping and modelling the spatial distribution of vegetation. This includes: (i) forest mapping (indigenous and exotic forests), (ii) modelling the probabilistic presence of understory coffee, (iii) Coffea arabica species distribution modelling and mapping and (iv) simulating pre-agricultural-expansion vegetation cover in Ethiopia. The results of the applied predictive modelling were robust in terms of: (i) identifying and mapping past vegetation cover and (ii) mapping understory shrubs such as coffee plants that grow as understory. I present a reconstruction of earlier vegetation cover that mainly comprised broadleaved evergreen and deciduous forest but was replaced in the course of agricultural expansion. Given the spatial scale of the latter, the environmental modelling was complemented with high spatial resolution satellite (2.5m) and aerial images (0.5m). The results of the Object Based Image Analysis show that indigenous forests were separated from exotic forests. Current and future suitable locations that are environmentally favourable for the growth of understory coffee were identified and mapped in the coffee-growing areas of Ethiopia. In conclusion, the information presented in this thesis, based on the multi-scale assessment of land changes, should lead to the better-informed management of natural resources and conservation, and the restoration of major areas affected by human population growth.Kaukokartoituksen avulla kerätään informaatiota maanpeitteestä ja maankäytöstä eri temporaalisilla ja spatiaalisilla resoluutiolla. Kaukokartoituksella on tärkeä rooli analysoitaessa maankäytön muutosta ja sen vaikutusta ekosysteemipalveluihin ja luonnon monimuotoisuuteen. Huolimatta siitä että kaukokartoitusaineistojen saatavuus on parantunut ja menetelmät kehittyneet, maailmassa on kuitenkin vielä alueita joiden maanpeitteen muutoksen dynamiikkaa ei vielä hyvin tunneta. Tässä väitöskirjatutkimuksessa tutkittiin Etiopian maankäytön muutosta ja sen vaikutusta ekosysteemipalveluihin ja luonnon monimuotoisuuteen usealla eri spatiaalisilla mittakaavoilla (paikallistasolta alueelliselle tasolle). Pääpaino tässä työssä oli kartoittaa ja mallintaa kasvillisuuden alueellista levinneisyyttä hyödyntäen eri erotuskyvyn omaavia kaukokartoitusaineistoja ja erilaisia kaukokartoitusmenetelmiä. Työssä kehitettiin kaukokartoitusperusteisia luokitusmenetelmiä, joilla pystyttiin: (i) erottelemaan tutkimusalueella sijaitsevat alkuperäismetsät istutusmetsistä ja (ii) saadun tiedon avulla edelleen mallintaa alkuperäiskahvin Coffea arabican spatiaalista levinneisyyttä, sillä alkuperäiskahvi kasvaa alkuperäismetsien pensaskerroksessa; (iii) muodostaa bioklimaattisia ja geospatiaalisia muuttujia sisältävän todennäköisyysmallin alkuperäiskahvin levinneisyyden arvioimiseksi muuttuvissa ilmasto-olosuhteissa; sekä (iv) simuloida Etiopian kasvillisuuspeitettä ajalta ennen maanviljelyksen voimakasta leviämistä. Alueellisella tasolla tulokset osoittavat, että Etiopian pinta-alasta ikivihreät metsät ja lehtimetsät ovat peittäneet huomattavasti laajemman alueen kasvillisuuspeitteestä ennen maanviljelyksen voimakasta leviämistä. Paikallistason tutkimuksessa objektipohjaisella kaukokartoitusaineiston luokitusmenetelmällä pystyttiin erottelemaan alkuperäismetsät istutusmetsistä ja edelleen mallintaa alkuperäiskahvin Coffea arabican spatiaalista levinneisyyttä hyödyntäen alkuperäismetsien erottelua, bioklimaattisia ympäristömuuttujia sekä spatiaalis-tilastollisia todennäköisyysmalleja. Yhteenvetona voidaan todeta että tämä väitöskirjatutkimus antaa näkökulmia monimittakaavaisen maankäytönmuutoksen vaikutusten ymmärtämiseksi ekosysteemipalveluihin ja luonnon monimuotoisuuteen. Tämän tutkimuksen tuloksia voidaan hyödyntää esimerkiksi voimakaan väestönkasvun alueilla, joissa tarvitaan tehokkaita menetelmiä luonnonvarojen hallintaan ja ympäristön suojeluun

Improved detection of abrupt change in vegetation reveals dominant fractional woody cover decline in Eastern Africa

While cropland expansion and demand for woodfuel exert increasing pressure on woody vegetation in East Africa, climate change is inducing woody cover gain. It is however unclear if these contrasting patterns have led to net fractional woody cover loss or gain. Here we used non-parametric fractional woody cover (WC) predictions and breakpoint detection algorithms driven by satellite observations (Landsat and MODIS) and airborne laser scanning to unveil the net fractional WC change during 2001-2019 over Ethiopia and Kenya. Our results show that total WC loss was 4-times higher than total gain, leading to net loss. The contribution of abrupt WC loss (59%) was higher than gradual losses (41%). We estimated an annual WC loss rate of up to 5% locally, with cropland expansion contributing to 57% of the total loss in the region. Major hotspots of WC loss and degradation corridors were identified inside as well as surrounding protected areas, in agricultural lands located close to agropastoral and pastoral livelihood zones, and near highly populated areas. As the dominant vegetation type in the region, Acacia-Commiphora bushlands and thickets ecosystem was the most threatened, accounting 69% of the total WC loss, followed by montane forest (12%). Although highly outweighed by loss, relatively more gain was observed in woody savanna than in other ecosystems. These results reveal the marked impact of human activities on woody vegetation and highlight the importance of protecting endangered ecosystems from increased human activities for mitigating impacts on climate and supporting sustainable ecosystem service provision in East Africa.Peer reviewe

The Ripple Effect of Climate Change: Assessing the Impacts on Water Quality and Hydrology in Addis Ababa City (Akaki Catchment)

This research aimed to evaluate the effects of climate change on the hydrology and water quality in the Akaki catchment, which provides water to Addis Ababa, Ethiopia. This was performed using the soil and water assessment tool (SWAT) model and an ensemble of four global climate models under two Shared Socioeconomic Pathways (SSP) emission scenarios from Coupled Model Intercomparison Project Phase 6 (CMIP6). The climate data were downscaled and bias-corrected using the CMhyd tool and calibrated and validated using the SWAT-CUP software package. Change points and patterns in annual rainfall and temperature were determined using the homogeneity test and Mann–Kendell trend test. Water quality data were obtained from Addis Ababa Water and Sewerage Authority (AAWSA), and more samples were taken and analyzed in accordance with APHA recommended procedures. The SWAT model output was then used to assess the impacts of climate change on hydrological components and water quality. Rainfall increased by 19.39 mm/year under SSP2-4.5 and 12.8 mm/year under SSP8.5. Maximum temperature increased by 0.03°C/yr for SSP2-4.5 and 0.04°C/yr for SSP5-8.5. Minimum temperature increased by 0.03°C/yr under SSP2-4.5 and 0.07°C/yr under SSP5-8.5. This warming will augment the evapotranspiration rate which in turn will have a negative impact on the freshwater availability. Streamflow will increase by 5% under SSP2-4.5 and 9.49% under SSP5-85 which may increase sporadic flooding events. Climate change is expected to contribute to the deterioration of water quality shown by 61%, 36%, 79%, 115%, and 70% increased ammonia, chlorophyll-a, nitrite, nitrate, and phosphorus loadings, respectively, from 2022. The increase in temperature results in increases in nutrient loading and a decrease in dissolved oxygen. Overall, this research demonstrated the vulnerability of the catchment to climate change. The findings of this research can offer vital knowledge to policymakers on possible strategies for the sustainable management of water

Implications of land use/land cover dynamics on urban water quality: Case of Addis Ababa city, Ethiopia

Water resources are often at the center of urban development but, as the city expands, the environmental pressure on its water resources increases. Therefore, in this study, we looked into how various land uses and changes in land cover affect the water quality in Addis Ababa, Ethiopia. Land use and land cover change maps were generated from 1991 to 2021 at intervals of five years. On the basis of the weighted arithmetic water quality index approach, the water quality for the same years was likewise divided into five classes. The relationship between land use/land cover dynamics and water quality was then evaluated using correlations, multiple linear regressions, and principal component analysis. According to the computed water quality index, the water quality decreased from 65.34 in 1991 to 246.76 in 2021. The built-up area showed an increase of over 338%, whereas the amount of water decreased by over 61%. While barren land exhibited a negative correlation with nitrates, ammonia loadings, total alkalinity, and total hardness of the water, agriculture and built-up areas positively correlated with water quality parameters such as nutrient loading, turbidity, total alkalinity, and total hardness. A principal component analysis revealed that built up areas and changes in vegetated areas have the biggest impact on water quality. These findings suggest that land use and land cover modifications are involved in the deterioration of water quality around the city. This study will offer information that might help reduce the dangers to aquatic life in urbanized environments

Evaluation of the physical, chemical, and biological characteristics of surface water in urban settings and its applicability to SDG 6: The case of Addis Ababa, Ethiopia

In this study, an analysis of physicochemical and microbiological water quality parameters was carried out to evaluate the water quality status of the city from the two major reservoirs that supply drinking water to the city. Unlike most studies which only report on the water quality from the source or final treated water, this study assessed the water quality from the raw water source, the treatment plant as well as the treated water from taps. The analysis was conducted in accordance with the American Public Health Association's recommended procedures. Silica varied between 8.85–15.1 mg/l for Legedadie reservoir which is less than the stipulated limit of 25 mg/l and 72.2 to 111.77 mg/L for Gefersa. With the exception of turbidity, total phosphorus and dissolved oxygen which recorded mean values of 252.4 NTU, 2.76 mg/l and 5.46 mg/l respectively, nitrate, nitrite, ammonia, total soluble solids, total alkalinity, pH, electrical conductivity and temperature were discovered to be within the WHO permitted range with mean values of 0.36 mg/l, 0.11 mg/l, 0.067 mg/l, 0.01 mg/l, 53.13 mg/l, 8.14 mg/l, 148.9 μS/cm and 18.57 °C respectively. Total coliforms were found in all waters samples whilst faecal coliforms and Escherichia coli were recorded in the range 20–3000 CFU/100 mL. Ammonia, turbidity, pH and electrical conductivity were found to significantly influence microbial densities in the drinking water. Filtered and treated water sample recorded a 0 CFU/100 mL for faecal coliforms value which indicates that the water is in conformity to water quality standards. However, total coliforms in the range of 3000 to 5000 CFU/100 mL were found in all water samples indicating contamination hence treatment is recommended before drinking it. In contemporary times of increased urbanization and water pollution, this research will assist in the effort to provide safe water and sanitation for all city residents

Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia

Enset (Ensete ventricosum) feeds around 20 million people in Ethiopia and is arguably the most important crop for food security and rural livelihoods in the country. Therefore, it is significant to know its spatial characterization and distribution in the country. We use spatial overlay analysis and the maximum entropy (MaxEnt) model for characterizing and modelling, respectively. Inputs for the model include 26 environmental variables—19 bioclimatic and seven biophysical—in addition to the geospatial location of enset field data. The model result was validated using Receiver Operating Characteristic curve method and the area under the curve (AUC) with 0.842 for cultivated enset and 0.760 (wild enset). The highest prediction (>0.5) of both varieties occurred in the southwestern, south-central and north-eastern parts of Ethiopia—17,293.67 km2 (cultivated) and 40,402 km2 (wild) area. The presence of both enset is probabilistically higher at the tropic-cool/sub-humid Agroecological Zones

Detection of geothermal anomalies in the Northern Lake Abaya geothermal field, Main Ethiopian Rift

The detection of geothermal anomalies using Thermal Infrared (TIR) remote sensing data is challenging because of how sensor specifications (such as the infrared wavelength used for the measurement, spectral dependence of the emissivity, angle at which the measurement is made, state of the surface and height of the sensor above the surface) and physical parameters (such as solar radiation, topography, albedo, soil compaction and coherence of rocks) affect Land Surface Temperature (LST) retrieval and analysis. This work tests whether TIR remote sensing measurements with thorough spatial and temporal sampling can improve LST retrievals. Multi-temporal TIR data from 2000 through 2019 from Landsat 7 and 8 TIR instruments and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to detect geothermal areas in the geologically active region of the southern Main Ethiopian Rift. In addition, field-based temperature data from 19 sites were evaluated for comparison to the remotely detected geothermal anomaly areas. We have used the single-channel algorithm and Normalized Difference Vegetation Index (NDVI) method of emissivity retrieval to derive LST for each year. The result shows that the mean LST is highest in 2003 (320.1 K) and lowest in 2019 (303.1 K). The change in mean LST was between −9 K to 13 K. These LST results from ASTER images were validated with MODIS LST products and showed a correlation coefficient >0.6. LST of the year 2003 has been much closer to the actual temperature value from field data. Fifteen sites (79%) fit with the identified geothermal anomaly areas. LST values in known geothermal activity sites show no correlation (< 0.5) with time attesting. That is, even though LST varies with time (e.g., day and night and seasonal changes), the LST of areas with geothermal potential remain more or less constant on yearly basis.Peer reviewe

Modeling and Mapping Habitat Suitability of Highland Bamboo under Climate Change in Ethiopia

Highland bamboo (Oldeania alpina formerly Arundinaria alpina or Yushania alpina) is a species of significant conservation value in Afromontane ecosystems across Africa. It also plays a significant role in the livelihoods of local communities. However, global climate change is anticipated to alter its ecological niche, leading to range shifts and possible habitat contractions. This study aimed to identify potentially suitable habitats for highland bamboo in Ethiopia, determine the resilience of the species under climate change, and establish the environmental factors affecting its habitat. Species distribution modeling (SDM) was implemented in the SDM R package using 231 georeferenced presence records together with climate, topographic, and soil data. To assess climate change risks to the species, predictive models were developed assuming climate scenarios for 2061–2080 under two shared socio-economic pathways (SSPs), namely, SSP2-45 and SSP5-85. The results indicated that highland bamboo mainly grows in high elevation areas with altitudes of 2100–3100 m asl with mean annual temperatures of 11.5–19.3 °C, annual precipitation of 873–1962 mm, precipitation of the driest quarter of 36–147 mm, soil pH of 5.6, and soil CEC of 30.7 cmolc/kg. The current potentially suitable habitat for this species in Ethiopia was estimated at 61,831.58 km2, with the majority of habitats being in the southern and southwestern parts of the country. Our models predicted that the suitable habitat will shrink by 13.4% under the SSP5-85 scenario, while potential new suitable areas for this species were identified under the SSP2-45 scenario. Future vulnerable areas were mostly found in central Ethiopia. Based on the predictions, we conclude that most of the suitable habitats for highland bamboo will remain suitable between the years 2061 and 2080