Soil quality assessment is valuable for evaluating agroecosystem sustainability, soil degradation, and identifying sustainable land management practices. This study compared soil quality within culturally protected forest areas and adjacent grassland, grazing land, and farmland in Abo-Wonsho, Southern Ethiopia. A total of 40 soil samples (4 land uses × 5 replications × 2 soil depth layers: 0 to 10cm and 10 to 20cm) were collected for analysis. Soil textural fractions (i.e., sand, silt, and clay percentage) varied with land use and soil depths even though the textural class across all land use types was sandy loam. Bulk density, soil organic carbon (SOC), and available potassium (K) varied significantly: , , and , respectively, with land use and soil depth, but other indicators showed no significant difference. We conclude soil quality can be protected and maintained by improving existing land use practices within both agricultural and modern forest management areas.

Vegetation dynamics have been visibly influenced by climate variability. The Normalized Difference Vegetation Index (NDVI) has been the most commonly used index in vegetation dynamics. The study was conducted to examine the effects of climatic variability (rainfall) on NDVI for the periods 1982–2015 in the Gojeb River Catchment (GRC), Omo-Gibe Basin, Ethiopia. The spatiotemporal trend in NDVI and rainfall time series was assessed using a Theil–Sen (Sen) slope and Mann–Kendall (MK) statistical significance test at a 95% confidence interval. Moreover, the residual trend analysis (RESTREND) method was used to investigate the effect of rainfall and human induction on vegetation degradation. The Sen’s slope trend analysis and MK significant test indicated that the magnitude of annual NDVI and rainfall showed significant decrement and/or increment in various portions of the GRC. The concurrent decrement and/or increment of annual NDVI and rainfall distributions both spatially and temporarily could be attributed to the significant positive correlation of the monthly (R_NDVI-RF = 0.189, P≤0.001) and annual (R_NDVI-RF = 0.637, P≤0.001) NDVI with rainfall in almost all portions of the catchment. In the GRC, a strongly negative decrement and strong positive increment of NDVI could be derived by human-induced and rainfall variability, respectively. Accordingly, the significant NDVI decrement in the downstream portion and significant increment in the northern portion of the catchment could be attributed to human-induced vegetation degradation and the variability of rainfall, respectively. The dominance of a decreasing trend in the residuals at the pixel level for the NDVI from 1982, 1984, 2000, 2008 to 2012 indicates vegetation degradation. The strong upward trend in the residuals evident from 1983, 1991, 1998 to 2007 was indicative of vegetation improvements. In the GRC, the residuals may be derived from climatic variations (mainly rainfall) and human activities. The time lag between NDVI and climate factors (rainfall) varied mainly from two to three months. In the study catchment, since vegetation degradations are mainly caused by human induction and rainfall variability, integrated and sustainable landscape management and climate-smart agricultural practices could have paramount importance in reversing the degradation processes.

Land degradation is a global negative environmental process that causes the decline in the productivity of land resources’ capacity to perform their functions. Though soil and water conservation (SWC) technologies have been adopted in Geshy subcatchment, their effects on soil quality were limitedly studied. The study was conducted to evaluate the effects SWC measures on soil quality indicators in Geshy subcatchment, Gojeb River Catchment, Ethiopia. A total of 54 soil samples (two treatments–farmlands with and without SWC measures ∗ three slope classes ∗ three terrace positions ∗ three replications) were collected at a depth of 20 cm. Statistical differences in soil quality indicators were analyzed using multivariate analysis of variance (ANOVA) following the general linear model procedure of SPSS Version 20.0 for Windows. Means that exhibited significant differences were compared using Tukey’s honest significance difference at 5% probability level. The studied soils are characterized by low bulk density, slightly acidic with clay and clay loam texture. The results revealed that farmlands with SWC measures had significantly improved soil physical (silt and clay fractions, and volumetric soil water content (VSWC)) and chemical (pH, SOC, TN, C : N ratio, and Av. phosphorus) quality indicators as compared with farmlands without SWC measures. The significantly higher VSWC, clay, SOC, TN, C : N ratio, and Av. P at the bottom slope classes and terrace positions could be attributed to the erosion reduction and deposition effects of SWC measures. Generally, the status of the studied soils is low in SOC contents, TN, C : N ratio, and Av. P (deficient). Thus, integral use of both physical and biological SWC options and agronomic interventions would have paramount importance in improving soil quality for better agricultural production and productivity.

This study aimed to assess and model soil erosion for sustainable landscape management using the Revised Universal Soil Loss Equation (RUSLE) across six diverse landscapes in the Abaya-Chamo Sub-Basin of Ethiopia’s Rift Valley Lakes Basin. The study spans six landscapes: Abaya Guangua, Arba Minch, Chencha, Hobicha, Loka Abaya, and Mierab Abaya during 2016 and 2021. The RUSLE integrates five key factors: rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices. By leveraging ArcGIS software, spatial analyses were performed to estimate annual soil loss across the studied landscapes. The main results accentuate both the spatial and temporal dynamics of soil loss. In 2016, estimated soil loss ranged from 0.08 to 1652 with an average of 128.39 t/ha/year. By 2021, soil loss ranged from 0.08 to 1474.08 with a reduced mean of 63.91 t/ha/year. In 2016, Abaya Guangua experienced minimal soil loss, with 90.36% of the area seeing <5 t/ha/year. This trend improved slightly by 2021, with 91.46% of the extent falling below the same threshold. In contrast, Chencha experienced severe erosion, reaching up to 1445.73 t/ha/year in 2016 with a notable decline by 2021. In Arba Minch, soil loss increased from 265.08 in 2016 to 292.71 t/ha/year in 2021, indicating improved erosion control. The Mierab Abaya exhibited severe soil loss in 2016, with slight improvements by 2021. Ethiopia’s soil loss tolerable limit of 2–18 t/ha/year reveals that erosion in several landscapes, especially Chencha, Mierab Abaya, and Arba Minch, exceeds sustainable levels. In the studied landscapes, the spatial–temporal variability of soil loss underscores the critical importance of tailored strategies for sustainable landscape management. Decision-makers can leverage these insights to implement effective erosion control measures across diverse agroecological zones.

Land degradation caused by improper land use management is a critical worldwide problem that has revived the issue of resources sustainability. Soil degradation, which involves physical, chemical, and biological degradation, is the key component of land degradation. Assessment of soil quality (SQ) indicators that distinguish soil degradation in different land use (LU) types is enviable to achieve sustainable land management strategies. The objective of this study was to assess the effects of land uses on soil quality indicators in the Geshy subcatchment of the Gojeb River Catchment, Omo-Gibe Basin, Ethiopia. The LU types identified for evaluation included natural forest, cultivation, and grazing lands. Accordingly, a total of 54 soil samples (three LU types × three slope classes (blocks) × three replications × two soil depths) were collected with an “X” plot design for data analysis. Statistical differences in SQ indicators were analyzed among LU types, slope classes, and soil depths and tested using univariate analysis of variance and Pearson’s correlation coefficient, following the general linear model. The results showed that a number of SQ indicators were significantly influenced by LU changes and soil depths. The sand, dry soil bulk densityρb, volumetric soil water contents (VSWC), total porosity, water infiltration rates, cumulative infiltration, and total nitrogen showed significant variations between the natural forest and the other LU types and soil depths (p<0.05). However, silt, clay, soil pH, SOC contents, carbon-to-nitrogen ratio, and available phosphorus did not show significant variations between LU types and soil depths (p>0.05). The overall qualities of the soils under the cultivation land were inferior in VSWC, TP, water infiltration rates, SOC contents, and TN soil attributes of the adjacent natural forest and grazing lands. The studied soils were found to be dominantly of clays with slightly acidic and low SOC contents and slow in their infiltration rate. Thus, integrated and sustainable land management, aimed at enhancing proper LU systems, is crucial for the sustainable ecosystem functioning and is the most effective way in reversing of soil quality deterioration.