Search

In this study, the dynamics of green spaces and land surface temperature patterns in four cities in Ethiopia were investigated using Landsat imagery. The typical characteristics of LST over the past three decades (1990-2020) in relation to green space dynamics were first investigated; subsequently, the spatial distribution of LST was characterized based on hybrid geospatial techniques and mono-window algorithm analysis, in which the contributions of green spaces to LST were studied. In addition, the multiple linear regression method and spatial regression models (SRMs) were employed to investigate and predict the spatial dependence of LST and urbanization-induced green space dynamics. Results show that cities horizontally expanded unceasingly from 1990 to 2020, with a substantial discrepancy in expansion rates and the spatial patterns of UHI intensities among the cities (p < 0.05). Moreover, the area proportion of the UHI is significantly larger than that of the UGS, and the differences in the UGS cooling contribution were found in different land uses and zones of the cities. In the study periods, the spatial pattern of LST was significantly controlled by NDBI, and its coefficient in the OLS followed the pattern NDVI > MNDWI > latitudes > longitudes > population density > DEM. Due to the large proportions of buildings While green land and water bodies show significant capability to mitigate UHI effects, cooling effects are not apparent when their sizes are small. Besides, the SRMs show that UHI intensities were significantly influenced by MNDWI in Bahir Dar and Hawassa (p < 0.01).Cities' LAMBDA coefficients have a positive relationship with UHII (p < 0.01). Our study could help city planners and the government understand the current cooling potential of existing UGS to mitigate the dynamics of UHI and sustain the sustainability of green space management in cities., Competing Interests: The authors declare no competing interests., (© 2023 The Authors.)

Currently, the depletion of natural resources and contamination of the surrounding environment demand a paradigm shift to resource recycling and reuse. In this regard, phosphorus (P) is a model nutrient that possesses the negative traits of depletion (will be exhausted in the next 100 years) and environmental degradation (causes eutrophication and climate change), and this has prompted the scientific community to search for options to solve P-related problems. To date, P recovery in the form of struvite from wastewater is one viable solution suggested by many scholars. Struvite can be recovered either in the form of NH 4 -struvite (MgNH 4 PO 4 •6H 2 O) or K-struvite (MgKPO 4 •6H 2 O). From struvite, K (MgKPO 4 •6H 2 O) and N (MgNH 4 PO 4 •6H 2 O) are important nutrients for plant growth, but N is more abundant in the environment than K (the soil's most limited nutrient), which requires a systematic approach during P recovery. Although K-struvite recovery is a promising approach, information related to its crystallization is deficient. Here, we present the general concept of P recovery as struvite and details about K-struvite, such as the source of nutrients, factors (pH, molar ratio, supersaturation, temperature, and seeding), advantages (environmental, economic, and social), disadvantages (heavy metals, pathogenic organisms, and antibiotic resistance genes), and challenges (scale-up and acceptance). Overall, this study provides insights into state-of-the-art K-struvite recovery from wastewater as a potential slow-release fertilizer that can be used as a macronutrient (P-K-Mg) source for plants as commercial grade-fertilizers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Estimating crop biomass is critical for countries whose primary source of income is agriculture. It is a valuable indicator for evaluating crop yields and provides information to growers and managers for developing climate change adaptation strategies. The objective of the study was to model the impacts of agroclimatic indicators on the performance of aboveground biomass (AGB) in Arabica coffee trees, a critical income source for millions of Ethiopians. One hundred thirty-five coffee tree stump diameters were measured at 40 cm above ground level. The historical (1998-2010) and future (2041-2070) agroclimatic data were downloaded from the European Copernicus climate change services website. All datasets were tested for missing data, outliers, and multicollinearity and were grouped into three clusters using the K-mean clustering method. The parameter estimates (coefficients of regression) were analyzed using a generalized regression model. The performance of coffee trees' AGB in each cluster was estimated using an artificial neural network model. The future expected change in AGB of coffee trees was compared using a paired t-test. The regression model's results reveal that the sensitivity of C. arabica to agroclimatic variables significantly differs based on the kind of indicator, RCP scenario, and microclimate. Under the current climatic conditions, the rise of the coldest minimum (TNn) and warmest (TXx) temperatures raises the AGB of the coffee tree, but the rise of the warmest minimum (TNx) and coldest maximum (TXn) temperatures decreased it (P < 0.05). Under the RCP4.5, the rise of consecutively dry days (CDD) and TNx would increase the AGB of the coffee tree, while TNx and TXx would decrease it (P < 0.05). Except for TXx, all indicators would significantly reduce the AGB of coffee trees under RCP8.5 (P < 0.05). The average values of AGB under the current, RCP4.5, and RCP85 climate change scenarios, respectively, were 26.66, 28.79, and 24.41 kg/tree. The predicted values of AGB under RCP4.5 and RCP8.5 will be higher in the first and third clusters and lower in the second cluster in the 2060s compared to the current climatic conditions. As a result, early warning systems and adaptive strategies will be necessary to reduce the detrimental consequences of climate change. More research into the effects of other climatic conditions on crops, such as physiologically effective degree days, cold, hot, and rainy periods, is also required., Competing Interests: The authors declare no conflict of interest., (© 2022 The Author(s).)

Climate suitability is important for coffee (Coffea arabica L.) production in climate variability-prone regions like Ethiopia. The aim of this study was to assess the current and future climate suitability for the species in the Jimma zone under moderate (RCP4.5) and worst (RCP8.5) climate change scenarios. Field surveys and Worldclim and Paleoclim databases were used to capture 224 C. arabica species' location points and 9 bioclimatic data, respectively. The MaxEnt model with integration of ArcGis was used to simulate and characterize these data. The diagnostic outcome of the model showed that the anticipated climate change will increase the areas of suitability in the first and third coffee sub-zones, while there will be a decrease in the second sub-zone. Net suitability under the RCP4.5 would be decreased by 4.75 and 6.09% in the 2050s and 2070s, respectively. Indeed, under the RCP8.5, total suitability will be expected to be increased by 2.52% and 2.25% in the 2050s and 2070s, respectively. For the 2050s and 2070s, the suitability gap between RCP4.5 and RCP8.5 was estimated to be 401 km 2 and 1567 km 2 , respectively. To summarize, with the exemption of RCP 8.5 within the 2070s, the suitability would be improved and come up short in all circumstances. To keep Arabica coffee in its original habitat, we suggest that the entire climate change adjustment procedures that are prearranged under the RCP4.5 ought to be executed to sustain the crop trees in its origin. Otherwise, moving the crop plant from impeded areas to suitable ones is crucial., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

In Ethiopia, more prevalent drought happenings have been documented in the past century. The problem has gradually expanded from the north to the rest parts with deepened intensity. The study aimed to examine the magnitudes of spatiotemporal patterns of drought at the Bilate watershed from 1981 to 2016. Monthly rainfall and temperature data were used for the analysis. The Standardized Evapotranspiration Indexes (SPEI) at SPEI-03 and SPEI-12 timescales were applied to evaluate the drought patterns. Among different drought indices, the SPEI is the most valuable and preferred Index for drought studies. The SPEI method considers the role of temperature than other indices to compare drought in time and space. The Mann-Kendall test was used for trend analysis. Accordingly, the result revealed that 1988-2016 were years of continuous drought events in both timescales with (SPEI = -2.5 to -1.2) drought value. Drought severity and frequency were highly detected at Wulberag areas (SPEI: -2.5). Durame, Angacha, and Alaba experienced increasing drought trends ( Z  = -1.96-1.6) and Welayita Sodo is Z  = -0.07-0.03. Bilate-Tena and Hossana area of the watershed were less affected by drought than other areas. Spatially, the drought occurrences were observed in all areas of the watershed with varying magnitude. In the SPEI-12 timescale, more frequent drought occurrences were observed than SPEI-03. It was found that severe drought was observed in 1987, 1993/94, 2000-2005, and 2010. Moreover, the watershed experienced an Aridity Index (AI) of 0.43 (43%) and was subjected to potential high evapotranspiration (PET). The highest PET was observed at Bilate-Tena, Angacha, Hosanna, Wulberag, Alaba, Welayita Sodo, and Durame (151.6, 119.6, 119.3, 140.8, 142, 127.5, and 125.7 mm/year, respectively. Hence, the finding of this study could initiate a further inquiry on drought risk management, early warning responses, and local scale planning., Competing Interests: The authors declare that there are no conflicts of interest regarding the publication of this article., (Copyright © 2022 Bereket Tesfaye Haile et al.)

Climate extremes are becoming more prevalent and hazardous as global climate change increases. The purpose of this study was to find out how often severe rainfall and temperature events occur, as well as the study area's spatial vulnerability indexes to extremes of both indices. Thirty years of daily rainfall and temperature data from 10 national meteorological stations were used. Four rainfall and eight temperature extremes were extracted using Climpact2 software tools. These variables were calculated for standardized anomaly and vulnerability indices and mapped using ArcMap. The results showed that the spatial variation of climatic extremes in the study area was significantly varied. Avery high rainfall (R95P) and extremely high rainfall (R99P) were widely experienced in the study area's west-south, but in the southeast, similar trends were rare. R95P had a statistically significant growing trend, but R99P did not. The warmest night temperature (TNx) event was widely observed in the east, southeast, and northwest, but the coldest night temperature (TNn) was only found in the eastern part. Extremely cold daytime temperatures (TXn) were more prevalent in the south and southeast of the study area, whereas extremely warm daytime temperatures (TXx) were more prevalent in the north. The number of dry spells (CDD), R95P, R99P, cold spells at night (TN10P), warm spells at night (TN90P), cold spells during the day (TX10P), and warm spells during the day (TX10P) frequency bell curves were skewed to the left side of the histogram. This suggests that the distribution of the variables was not symmetrical due to the fact that the negative anomaly frequencies of the variables were higher than the positive ones. The results of the spatial vulnerability study show that all provinces were vulnerable to the combined effects of climatic extremes, with scores ranging from 0.20 to 0.8, with none of them vulnerable and extremely vulnerable areas. Omo-Nada and Chora-Botor were particularly sensitive to climate change with an average score of 0.61. Only 12 of the 27 severe climate indexes were taken into account in this study, and the remaining 15 extreme indices will have to be investigated further., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The provision of freshwater is essential for sustaining human life. Understanding the water provision modelling associated with the Land Use/Cover (LUC) change and climatic factors is vital for landscape water resource management. The Winike watershed is the largest tributary in the upper Omo Gibe basin of Ethiopia. This research aims to analyze the spatial and temporal change in the water yield to investigate the water yield contribution from the watershed based on the variation in input parameters. The Integrated Valuation of Ecosystem Services and Tradeoffs Tool (InVEST) water yield model was used to evaluate the spatial and temporal variation of the water yield in different years (1988, 1998, 2008 and 2018). The data required for this model include LUC data from satellite images, reference evapotranspiration, root depth, plant available water, precipitation, season factor (Z), and a biophysical table. The analysis of LUC change shows a rapid conversion of grazing land, shrubland, and forest land into cultivated land. There has been a significant variation in water provision, which increased from 1.83 × 10 9  m 3 in 1988 to 3.35 × 10 9  m 3 in 2018. Sub-watersheds 31, 32, and 39 in the eastern part of the watershed contributed more water due to higher precipitation and lower reference evapotranspiration. The major increase in the contribution of water yield was in built-up land by 207.4%, followed by bare land, 148.54%, and forest land by 63%. Precipitation had a greater impact on water yield estimation compared with the other input parameters. Hence, this research helps decision-makers to make informed decisions regarding new policies for LUC change improvement to maintain the water resources in the Winike watershed., (© 2021. The Author(s).)

Understanding the dependence of ecosystem services (ESs) on the dynamics of human-semi nature-coupled ecosystems is crucial for urban ecosystem resilience. In the present study, the responses of ESs to land use land cover transitions were explored and compared, selecting Addis Ababa, Adama, Hawassa, and Bahir Dar cities in Ethiopia. The geospatial data and benefit transfer approach was used to estimate the nexus over a three-decade period (1990-2020). Moreover, the bivariate Moran's I and spatial regression models were employed to analyze the spatial dependence of ESV on urbanization. The findings showed that the built-up increased by 17,341.0 ha (32.2%), 2151.3 ha (19.6%), 2715.2 ha (12.2%), and 2599.7 ha (15.7%) for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively over the investigated periods. Besides, the total ESV weighed by 24.8%, 8.9%, 0.7%, and 3.9% from the US$ 277.9, 55.5, 100.3, and 90.9 million for Addis Ababa, Adama, Bahir Dar, and Hawassa cities, respectively from1990 to 2020. Synergies occurred among local climate regulation and recreation services, and trade-offs existed among other services. A persistent rising trend in the ESVt was found for all cities the upsurge in Addis Ababa being much sturdier than in others. However, the elasticity of ecosystem of land use (EEL) showed that 1% of the LULC transformation was caused by 8.9% changes in ESV. Besides, the results from the global bivariate Moran's I show substantial positive spatial correlations between ESV, and Integrated Land use Dynamic Degree (ILUDD), Land-Use Intensity (LUI), and Land Use Diversity (LUD) (p < 0.001). Spatial lag model and special error model were shown to be fitting more than the Ordinary Least Square in establishing relationships among the spatial dependence of ESV on urbanization. In contrast, the aggregated ESV is significantly influenced not only by LULC dynamics but also by the spatial spillover effect. Thus, overall findings suggested an antagonistic nexus between the aggregated ESV and ESVf, since 98% of individual ESs were negatively declined as the built-up ecosystem expanded., Competing Interests: Declaration of competing interest There is no any conflict of interest among authors., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Allometric equations are used to estimate biomass and carbon stock of forests. In Ethiopia, despite the presence of large floral diversity, only a few site-specific allometric equations have been developed so far. This study was conducted in the Omo-Gibe woodland of south-western Ethiopia to develop an allometric equation to estimate the Above-ground Biomass (AGB) of the four Acacia species (Senegalia polyacantha, Vachellia seyal, Vachellia etbaica and Vachellia tortilis). Fifty-four (54) Acacia trees were sampled and measured within 35 temporarily established square plots. In each plot, dendrometric variables were measured to derive the models based on combinations of Diameter at Breast Height (DBH), height, and wood density as predictor variables. Model performance was evaluated using goodness-of-fit statistics. The biomass was compared using four allometric biomass models that have been widely used in the tropics., Results: The model containing DBH alone was more accurate to estimate AGB compared to the use of multiple predictor variables. This study, therefore, substantiated the importance of site-specific allometric equations in estimating the AGB of Acacia woodlands. This is because a site-specific allometric equation recognizes the environmental factors, vegetation types and management practices., Conclusions: The results of this study contribute to a better understanding of allometric equations and an accurate estimate of AGB of Acacia woodlands in Ethiopia and similar ecosystems elsewhere., (© 2021. The Author(s).)

Information on soil loss and sediment export is essential to identify hotspots of soil erosion to inform conservation interventions in a given watershed. This study investigates the dynamics of soil loss and sediment export associated with land-use/land cover changes and identifying soil loss hotspot areas in the Winike watershed of the Omo-Gibe Basin of Ethiopia. Spatial data collected from satellite images, topographic maps, meteorological and soil data were analyzed. The land-use types in the study area were categorized into six: cultivated land, woodland, forest, grazing, shrubland, and bare land. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) of the sediment delivery ratio (SDR) model was used based on the analysis of land use/land cover and RUSLE factors. The results show that total soil loss increased from 774.86 thousand tons in 1988 to 951.21 thousand tons in 2018 while the corresponding sediment export increased by 3.85 thousand tons for the same period. These were subsequently investigated in each land-use type. Cultivated fields generated the highest soil erosion rate, increasing from 10.02 t/ha/year in 1988 to 43.48 t/ha/year in 2018 when compared with the grazing, shrub, forest, wood land and bare land-use types. This corresponds with the expansion of the cultivated area. This is logical as the correlation between soil loss and sediment delivery and expansion of cultivated area is highly significant (p < 0.001). Sub-watershed six (SW-6) showed the highest soil loss (23.17 t/ha/year) while sub-watershed two (SW- 2) has the lowest soil loss (5.54 t/ha/year). This is because SW-2 is situated in the lower reaches of the watershed under dense vegetation cover experiencing less erosion. The findings on the erosion hotspots presented in this study allow prioritizing the segments of the watershed that need immediate application of improved management interventions and informed decision-making processes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Our study examines the urban vegetation - air temperature (T a ) - land surface temperature (LST) nexus at micro- and regional-scales to better understand urban climate dynamics and the uncertainty in using satellite-based LST for characterizing T a . While vegetated cooling has been repeatedly linked to reductions in urban LST, the effects of vegetation on T a , the quantity often used to characterize urban heat islands and global warming, and on the interactions between LST and T a are less well characterized. To address this need we quantified summer temporal and spatial variation in T a through a network of 300 air temperature sensors in three sub-regions of greater Los Angeles, CA, which spans a coastal to desert climate gradient. Additional sensors were placed within the inland sub-region at two heights (0.1m and 2m) within three groundcover types: bare soil, irrigated grass, and underneath citrus canopy. For the entire study region, we acquired new imagery data, which allowed calculation of the normalized difference vegetation index (NDVI) and LST. At the microscale, daytime T a measured along a vertical gradient, ranged from 6 to 3°C cooler at 0.1 and 2m, underneath tall canopy compared to bare ground respectively. At the regional scale NDVI and LST were negatively correlated (p<0.001). Relationships between diel variation in T a and daytime LST at the regional scale were progressively weaker moving away from the coast and were generally limited to evening and nighttime hours. Relationships between NDVI and T a were stronger during nighttime hours, yet effectiveness of mid-day vegetated cooling increased substantially at the most arid region. The effectiveness of vegetated T a cooling increased during heat waves throughout the region. Our findings suggest an important but complex role of vegetation on LST and T a and that vegetation may provide a negative feedback to urban climate warming., (Copyright © 2016 Elsevier B.V. All rights reserved.)