Watersheds regulate hydrological processes, support biodiversity, and provide essential ecosystem services, but are increasingly affected by land-use change, climate variability, and human activities. In the Dinki Watershed of the central highlands of Ethiopia, agricultural expansion, habitat loss, and hydrological changes have increased pressure on watershed ecosystems, while information on biophysical characteristics, LULC dynamics, ecosystem services, climate variability, aquatic biodiversity, long-term ecological changes, and watershed management remains limited. Therefore, this study assessed watershed ecosystem health and macroinvertebrate responses to climate and land-use change by characterizing biophysical attributes, evaluating LULC changes and their effects on ecosystem services, examining spatial and temporal changes in macroinvertebrate communities and ecosystem health between 2016 and 2023, identifying key environmental drivers, and assessing potential future vulnerability. A comparative spatiotemporal research design was employed, with hydrological characteristics analyzed using ArcGIS 10.5, LULC dynamics from 1994 to 2023 assessed using supervised Support Vector Machine (SVM) classification, and ecosystem service values estimated by integrating remote-sensing outputs, global ecosystem evidence, and socioeconomic perceptions from key informant interviews (KIIs) and focus group discussions (FGDs) analyzed using QDA Miner Lite. Climate variability was evaluated using 30 years of rainfall and temperature data from the Ethiopian Meteorology Institute and analyzed in Python, while soil physicochemical properties, including pH, EC, nutrients, texture, and bulk density, were obtained from EthioSIS and analyzed using R. Macroinvertebrates were sampled following South African guidelines, with 100 composite samples collected from 25 sites during wet and dry seasons in 2016 and 2023 and identified to family level. Ecological responses were assessed using paired t-tests, ANOVA, rmANOVA, and MANOVA, while community patterns were examined using PCA, NMDS, and RDA, and indicator taxa were identified using IndVal analysis. A multimetric index (MMI) was developed from 37 candidate metrics, with five core metrics selected through statistical screening and validation: %EOT, %Trichoptera, Hemiptera abundance, ASPT, and FBI. Pollution-sensitive taxa (Perlidae and Philopotamidae) were modeled using ensemble approaches, including BRT, RF, GLM, GAM, and MaxEnt, incorporating bioclimatic and LULC i predictors to project distributions for the 2050s and 2070s under SSP2-4.5 and SSP5-8.5 scenarios. Model performance was evaluated using AUC and TSS, and integrated analyses in R and Python examined relationships among climate variability, LULC change, hydrology, and macroinvertebrate biodiversity. The result showed a complex stream network, consisting of 45 first-order, 9 second-order, and one third-order stream, and the Dinki River extended 30.35 km before joining the Awash River. The overall ecological improvement was reflected by the habitat visual assessment scores (HVAS), which improved from 10 in 2016 to 11-15 in 2023, considered as suboptimal, and the Ecosystem Health Index, which gradually increased from 1.40 in 2016 to 2.05 in 2023. The soils were mainly clay (70%) and black cotton soils (26%) and were very variable in chemical properties, such as iron (Fe) content (144.45mg/kg) and carbon/nitrogen (C/N) ratio (13.94). The hydrological analysis showed that the discharge increased significantly in the wet season (p < 0.05). From the long-term climate analysis, the annual rainfall ranged between 800 and 1000 mm, and the temperature was 18 to 21 °C. LULC analysis showed that agriculture, grazing land, and water bodies continued to be dominant land use types. Cropland, however, decreased 22.54% from 1994 to 2023, with an increase in sparse vegetation, grazing land, and water bodies. Even though there were some reductions in agricultural lands and forest ecosystems, the ecosystem service value increased from US$ 200.32 thousand in 1994 to US$ 310.33 thousand in 2023. A total of 9,479 macroinvertebrates were recorded, with more abundant numbers (6526) recorded during the dry season in 2023. Pollutionsensitive taxa were related to forested streams with high oxygen levels, while tolerant taxa, such as Chironomidae, Gomphidae, and Tabanidae, were more abundant in degraded water bodies with high EC, TDS, and turbidity levels. Multivariate analyses (PCA, NMDS and RDA) showed good site separation along environmental gradients, reflecting environmental responses at intra- and inter-annual scales. Taxon-specific responses were observed, with increases of the Heptagenidae and Perlidae associated with an increase in vegetation, while Odonata decreased with an increase in temperature. The overall water quality enhanced as evidenced by the high value of ecological indices, EPT and EOT, and the Odonata index remained stable or decreased. The macroinvertebrate communities were impacted by both change in land use and climate variability, and cumulative impacts affecting the distribution of indicator sensitive taxa in the ii Dinki watershed. The general linear model (GLM) results indicated that climate, particularly temperature, is a key determinant (especially for families Tabanidae and Dytiscidae), and combined effects with land use determined overall ecological patterns, with the Variation Partitioning Analysis (VPA) results indicating this. The developed MMI was found to be an effective discriminating index between reference and impacted sites, ranging from 10.22 (poor) to 22.43 (very good). The ensemble habitat suitability models for the Perlidae and Philopotamidae performed very well in terms of predictive performance (AUC and TSS), and they showed climate refuges in the Ethiopian highlands. The SSP5-8.5 scenario, however, suggested habitat losses of 50-59% by the 2070s, exposing a high sensitivity to climate and land use change. The Ecosystem Health Index increased from 1.40 in 2016 to 2.05 in 2023, means the Dinki Watershed under recovering, though it is highly dependent on the continued changes in the environment. The results highlight the significance of prioritizing riparian vegetation restoration and protection of forested headwater streams in order to maintain a pollution-sensitive macroinvertebrate community. This will need a coordinated approach between watershed managers, regional environmental agencies, and communities. Continued ecological monitoring, based on the developed MMI, over a longer timeframe is acceptable, and climate-based habitat projections need to be improved for use in adaptive watershed management strategies.