Smallholder farmers' vulnerability to climate change and variability: Evidence from three agroecologies in the Upper Blue Nile, Ethiopia

Heliyon, Год журнала: 2024, Номер 10(7), С. e28277 - e28277

Опубликована: Март 22, 2024

This study delves into the profound impact of climate change on agriculture in Ethiopia, particularly vulnerabilities faced by smallholder farmers and resulting implications for poverty. Focusing three distinct agroecologies, namely: highland, midland, lowland zones. The employed a robust methodology, combining cross-sectional survey, spatial-temporal trend analysis using GIS, development an overall vulnerability index through balanced weighted average method. study, encompassing 646 households, combines data from variety sources analytical tools like index, ArcGIS 10.8, ERDA's IMAGINE 2015. Utilizing LVI-IPCC scale, shows that is immediate all agroecological It identifies highland areas as most sensitive exposed regions, while households are found to be vulnerable terms vulnerabilities. research reveals specific challenges communities, such inadequate health facilities insufficient food water supplies both agroecosystems. Additionally, our investigation has observed significant alteration land use practices, specifically shift communal grazing private cultivation plantations, emphasizing eucalyptus. enhances ecosystem's disturbances. suggests targeted interventions, advocating sustainable land-use afforestation, adopting climate-smart practices. important implement policy measures prioritize conserving restoring shrubland, land, natural forests ensure long-term socio-economic ecosystem resilience. study's nuanced insights instrumental understanding diverse posed Ethiopian agriculture, supporting informed policymaking interventions.

Язык: Английский

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Crop water requirement and irrigation scheduling under climate change scenario, and optimal cropland allocation in lower kulfo catchment

Heliyon, Год журнала: 2024, Номер 10(10), С. e31332 - e31332

Опубликована: Май 1, 2024

Crop water requirement and irrigation scheduling in Lower Kulfo Catchment of southern Ethiopia have not assessed under climate change scenarios, the allocation crop land also optimal that signifcantly challenges to productivity.Therefore, this study was conducted evaluate effects on future requirements, scheduling, allocate cropland optimally. Bias projected precipitation temperature were corrected by utilizing Climate Model data with hydrologic modeling tool (CMhyd). Alongside, requirements using Water Assessment Tool. After estimating requirement, allocated optimally General Algebraic Modeling System programming non-negativity constraints (scenario 1), based farmers adaptation 2). Average reference evapotranspiration from 2030 2050 2060 2080 increased 11.9%, 16.2%, respectively compared period (2010-2022). The total seasonal 4,529mm, 4,866.7mm, 5,272.2mm 2010 2022, 2050, respectively. meean interval scenarios 8 days, 7 5 This decreased 14% (2030 2050), 34% (2060 2080) period. In 2026 required at inlet main canal 6.8%, 18%, area for tomato (60.4%), maize (20.8%), watermelon (18.8%) scenario 1 net benefit 1.47*108 Ethiopian Birr. areas 2 (48%) maize, (31.6%) tomato, (20.4%) 1.34*108 Birr it reduced 19.1% 1. Fruit crops alone may suffice local food needs address this, small should grow watermelon. research aids policymakers encouraging climate-resilient agriculture improving small-scale farmers' awareness through conducting workshops training. Agriculture plays an important role driving economic growth within economy covers 40% gross domestic product [1Tesema T. Gebissa B. Multiple Agricultural Production Efficiency Horro District Guduru Wollega Zone, Western Ethiopia, Using Hierarchical-Based Cluster Data Envelopment Analysis.Sci. World J. 2022; 2022https://doi.org/10.1155/2022/4436262Crossref Scopus (1) Google Scholar]. Irrigation dry or semi-dry environments is used sustain agricultural productivity when available rainfall insufficient [2Zhang et al.Challenges opportunities precision decision-support systems center pivots.Environ. Res. Lett. 2021; 16https://doi.org/10.1088/1748-9326/abe436Crossref (39) Effective management across conveyance system demand-based are basic activities improve schemes [3Létourneau G. Caron scale application method yield field-grown strawberries.Agronomy. 2019; 9https://doi.org/10.3390/agronomy9060286Crossref (14) amount equal what lost cropped field [4Adamtie Temesgen F. selie Abeba H. Mitku Demeke season irrigated Pawe district, lowland hot humid Ethiopia.Int. Sch. Life Sci. 1: 009-021https://doi.org/10.56781/ijsrls.2022.1.1.0022Crossref Soil type, change, topographical location, type highly affect quantity [5Mirzaei A. Azarm Naghavi S. Optimization cropping pattern fluctuations surface multistage stochastic programming.Water Supply. 22: 5716-5728https://doi.org/10.2166/ws.2022.224Crossref (9) denotes significant enduring shifts Earth's climate, driven human due emitting greenhouse gases like CO2, CH4, N2O, altering temperature, precipitation, wind patterns [6Boatemaa Incoom M. Kwadwo E. Odai S.N. Impacts Savannah regions Ghana.J. Clim. Chang. 13: 3338-3356https://doi.org/10.2166/wcc.2022.129Crossref estimation change's impact suggest possible mitigation measures sustainable resources development [7Soares D. Paço T.A. Rolim Assessing Change Requirements Mediterranean Conditions—A Review Methodological Approaches Focusing Maize Crop.Agronomy. 2023; 13https://doi.org/10.3390/agronomy13010117Crossref (10) Coupled Intercomparison Project (CMIP) model organized Research Program (WCRP) produces ensembles Earth (ESM) conditions different CO2 emission [8Tian X. Dong Jin He Yin Chen impacts regional use semi-arid environments.Agric. Manag. 281108239https://doi.org/10.1016/j.agwat.2023.108239Crossref (8) comparison CMIP5, CMIP6 most recent phase high spatial temporal resolutions offer more intricate representation processes [9Oyelakin Analysing Urban Flooding Risk CMIP5 Projections.Water. 2024; 16Crossref (0) To forecasting (SSP585) demonstrates better performance contrasted [10Feyissa Demissie Saathoff Evaluation Circulation Models Performance Future over Omo River Basin , Ethiopia.Sustainability. 15Crossref (3) Tool (CropWat model) estimate historical [11Sen Determining Changing Demands Cukurova Plain Scenarios CROPWAT Model.Water. (CMhyd) utilize bias correction between [12Yeboah K.A. Akpoti K. Kabo-bah A.T. Ofosu E.A. Siabi E.K. projections Volta CORDEX- Africa simulations statistical bias-correction CORDEX-Africa bias-correction.Environ. Challenges. 6100439https://doi.org/10.1016/j.envc.2021.100439Crossref (21) Scholar] as input CropWat model. Proper increase yields manage amount, frequency [13Betele Gebul M.A. Andries Plessis allocation.Koftu Ethiopia. 18: 1331-1342https://doi.org/10.2166/wpt.2023.080Crossref gives a direction adapted resilience agriculture. Optimizing utilization satisfy household security providing economical specific [14Pal J.S. al.Regional developing world: ICTP RegCM3 RegCNET.Bull. Am. Meteorol. Soc. 2007; 88: 1395-1409https://doi.org/10.1175/BAMS-88-9-1395Crossref (835) optimization contains objective function, decision variables [15Zenis F.M. Supian Lesmana farms Sumedang regency linear models.IOP Conf. Ser. Mater. Eng. 2018; 332https://doi.org/10.1088/1757-899X/332/1/012021Crossref Scholar], depending nature problems [16Sofi N.A. Ahmed Ahmad Bhat B.A. Decision Making Agriculture: A Linear Programming Approach.Int. Mod. Math. homepage www.ModernScientificPress.com. 2015; 13 ([Online]. Available:): 160-169www.ModernScientificPress.com/Journals/ijmms.aspxGoogle can consider availability [17Nimah M.N. Bsaibes Alkahl Darwish M.R. Bashour I. maximize productivity.River Ii. 2003; 7: 187-198Google aims per unit [18Hao L. Su Singh V.P. Cropping considering uncertainty saving potential.Int. Agric. Biol. 11: 178-186https://doi.org/10.25165/j.ijabe.20181101.3658Crossref (20) (GAMS) code best strategy considers water, land, crop, [19Jayne T.S. Chamberlin Headey D.D. Land pressures, evolution farming systems, strategies Africa: synthesis.Food Policy. 2014; 48: 1-17https://doi.org/10.1016/j.foodpol.2014.05.014Crossref (336) During season, there conflict among users scarcity demand showed increasing trend observed during problem investigation be change. Absence estimated lack proper practices significantly disturbed distribution. Addition variability shifting wet major lower catchment hinder rainfed/irrigated area. Stream flow will 2.99% 2050s 5.28% 2080s [20N. Demmissie, Demissie, Tufa, "Predicting Impact Flow," vol. 6, no. 3, pp. 78–87, 2018, doi: 10.11648/j.hyd.20180603.11.Google But no any scheduling. Both Arba Minch low [21Reta B.G. Hatiye S.D. Finsa M.M. Management Indicators Mitigation Measure Irrigation.Adv. knowledge about user-friendly tools identifying Traditional adopted understanding regarding affordable GAMS code. Poor multiple undermines effectiveness scheme, leading yields, operational costs, market value fluctuations, environmental degradation [22Yubing Fan S.C.P. R. M.Multi-Crop Decisions Economic Use : Effects Climatic Determinants.Water. 10https://doi.org/10.3390/w10111637Crossref (12) These agricultural-related solved reasonable identify Therefore, worst three programming. significance lies its potential critical catchment, offering solutions optimizing resources, productivity, fostering face located 6 2' 0" 5' North latitude 37 33'0" 36'0" East longitudes Southern (Figure 1). Elevation thestudy varied 1200 1203.8m above mean sea. near town, running alongside road connecting Mirab Abaya Wolayita Sodo location holds importance efficient transportation fruit production market. irrigation, University (AMU) farmland, smallhold farmer Kola Shara private farmland airport included farm, Kolla shara 1, 835.22ha, 109.17ha, 160.23ha, 18.44ha, 52.76ha, respectively, irrigable 1175.82ha source annual minimum, maximum 2.35m3/s 50.73m3/s, Market survey collect price dominant both sellers buyers which helps people since only prices justify whether profitable not. Field observation around investigate practical understand agronomic quantitative qualitative such size, costs production, existing practices, hectare collected questionnaires, key informant interviews, focus group discussions. revenues each crop. Based [23A. Wright, Hudson, Mutuc, "A Spatial Analysis Technology," 2013, 307–318, 2013.Google simplified formula, sample size interviews Kebele calculated described Eq 1.(1) Where n N population e expected error (5%) 95% confidence level. Zuria Woreda office. ArcGIS software after collecting ground control point (Table 1).Table 1population conduct interview shareTotal population10,794Number farmers886Available (ha)1,974Probable (ha)160.2Number (N)72Expected (e)5% @95% levelSample interview61 Open table new tab Methods soil sampling composite techniques depth 0.9m. texture evaluateing hydrometer test bulk density evaluated dividing mass volume drying oven 105 24 hours. chemical properties organic matter electric conductivity laboratory present status fertility. capacity permanent wilting pressure plate apparatus laboratory. [24Goebel Lascano R.J. Acosta-Martinez V. Stable Isotopes Determine Rainwater Infiltration Soils Conservation Reserve Program.J. Chem. Environ. 2016; 05: 179-190https://doi.org/10.4236/jacen.2016.54019Crossref infiltration characteristics determined double-ring infiltrometer. physical [25Chen C. Hsu Liang simulating extreme Pacific Asia.Weather Extrem. 31https://doi.org/10.1016/j.wace.2021.100303Crossref (92) (CMIP6) has good Phase 3 (CMIP3) five (CMIP5) predicting trends. As result, current derived sixth (CMIP6). utilized correction, meteorological station. Temperature, network Common Form (netCDF) files extracted coordinate elevation employed [26Leander Buishand Resampling output simulation river flows.J. Hydrol. 332: 487-496https://doi.org/10.1016/j.jhydrol.2006.08.006Crossref (353) addressed 3.(2) p* bias-corrected rainfall, P uncorrected & b power regression factors.(3) T*, Tobs, Trcm, δ stand standard deviation where P* amount; factors assessment (CropWat) computer program soil, input. [27R. Allen, Pereira, Raes, Smith, "FAO Drainage Paper No. 56 - Evapotranspiration," November 2017, 1998.Google (ETo), (CWR), effective (Pe), (IWR), (i) scenarios. 2022 (reference), 2060-2080 rainfall. Projected solar radiation, humidity, speed sunshine hours result all driest January April evapotranspiration, condition coefficients initial, mid, late stages drainage manual paper number (FAO 56) presented Table but teff found FAO paper. Length growing stage, root depth, reduction factor, allowable depletion, planting harvesting date central Rift Valley Lake Basin, 0.46 (initial stage), 0.88 (development 1.03 (mid-stage), 0.57 (late stage) [28T. Hordofa, "Crop Requirement Coefficient Tef ( Eragrostis tef ) Central Ethiopia," 11, 15, 34–39, 2020, 10.7176/JNSR/11-15-0.Google Reference evapotranspartion, 4, 5, 6/7, 9, respectively.Where; Rn=net radiation (MJ m-2 day-1), G=Soil heat flux T=Mean daily air 2m height (oc), U2=Wind (ms-1), es =Saturation vapour (kPa), ea= actual (kpa), (es -ea) =Saturated deficit, Δ=slope curve (kPa oc-1) r=psychrometric constant oc-1), Kc=crop (-), (mm), d CWR (mm/day).Table 2crop function stage 27R. Scholar(4) (5) (6) (7) Crop/Growth stageInitial stageMid-stageLate-stageWheat0.31.150.25-0.4 (0.325)Maize0.31.20.6Watermelon0.410.75Pepper0.61.050.9Onion0.71.050.75Banana0.61.11.05Tomato0.151.10.6-0.8 (0.7) solve mixed-integer, linear, nonlinear [29Hooper B.P. Integrated Resources Governance.Water Resour. (Updat): 12-20Google Objective profits develop [30Bowen R.L. Young R.A. Financial Net Benefit Functions Egypt's Northern Delta.Water 1985; 21: 1329-1335https://doi.org/10.1029/WR021i009p01329Crossref (23) 10..(10) Where; Pi, Yi, Xi, Ci "i" (birr/ton), (ton/ha), (ha) cost (birr/ha), Total including labor, fertilizer, pesticides, insecticides availability, outcome, function. Lengths various periods start according guidelines outlined banana persist year-round. Onions harvested end March, while wheat require months time stope four except perennial sum exceed (At) describe 11.(11) X1, X2, X3, X4, X5, X6, X7, X8 onion, watermelon, pepper, wheat, banana, Teff, At=total (ha). (mm) calculate water. less than minimum could obtained sources. (2010 2022) Equation constraint (Eq 12).(12) CWR=crop (m), Peff=effective Vmin= supply (ha-m). represents highest achievable quality optimal, managed effectively, sufficient available. sourced Manual Number 33 33). primary aim overall 13).(13) YI average (ton/ha) TYc=Expected (ton). 14.(14) PCi TPC I (Birr/ha) (Birr) Non-negativity had two 1) remaining depend small-hold (such yield, cost) common considered 1).X1>=0, X2>=0, X3>=0, X4>=0, X5>=………………………………………………………………………….X8>=0 interview, covered 564.9ha (48% area). Because vegetable cover consumption maize. other 48% ordered 2).X1>=0, X2>=564.9ha, X5>=………………………………………..……X8>=0 clay density, matter, conductivity, capacity, point, 1.32 gm/cm3, 0.87%, 0.16ds/m, 38.3%, 25.9%, 124mm/m, 3). 110 160mm/m, recommended 127mm/m. suitable uncompacted 1.63gm/cm3 [31Twum E.K.A. Nii-Annang Compaction Bulk Density Root Biomass Quercus petraea Reclaimed Post-Lignite Mining Site Lusatia, Germany.Appl. 2015https://doi.org/10.1155/2015/504603Cross

Язык: Английский

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GIS-based spatio-temporal analysis of rainfall trends under climate change in different agro-ecological zones of Wolaita zone, south Ethiopia

Heliyon, Год журнала: 2024, Номер 10(13), С. e33235 - e33235

Опубликована: Июнь 19, 2024

Understanding the spatiotemporal dynamics of climatic conditions within a region is paramount for informed rural planning and decision-making processes, particularly in light prevailing challenges posed by climate change variability. This study undertook an assessment spatial temporal patterns rainfall trends across various agro-ecological zones (AEZs) Wolaita, utilizing data collected from ten strategically positioned rain gauge stations. The detection their magnitudes was facilitated through application Mann–Kendall (MKs) test conjunction with Sen's slope estimator. Spatial variability were further analyzed ArcGIS10.8 environment XLSTAT R programming tools. outcomes derived ordinary kriging analyses unveiled notable disparities coefficient (CV) mean annual distinct AEZs. Specifically, observations indicated that lowland regions exhibit relatively warmer climates lower precipitation levels compared to highland counterparts. Within AEZs, majority stations showcased statistically non-significant positive (p > 0.05) rainfall, whereas approximately two-thirds midland AEZ depicted negative trends. Conversely, over half situated AEZs displayed rainfall. During rainy season, experienced higher levels, while south-central areas received moderate amount In contrast, northeast southeast consistently diminished all seasons other regions. underscores necessity resilient development implementation spatiotemporally interventions implementing region-specific adaptation strategies, such as water conservation measures crop diversification, mitigate potential impact changing on agricultural productivity Wolaita.

Язык: Английский

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The effect of sustainable agricultural practices on crop productivity in Ethiopia: insights from a meta-analysis

Frontiers in Sustainable Food Systems, Год журнала: 2025, Номер 8

Опубликована: Янв. 29, 2025

Conventional agriculture harms the environment and threatens sustainability. To address these issues, sustainable agricultural practices (SAPs) have become imperative. This study utilizes a meta-analysis approach to comprehensively assess empirical studies, investigate impact of SAPs on crop productivity, identify influencing factors, examine their temporal evolution. The findings reveal that (1) SAP adoption significantly positively influences with multiple exhibiting most substantial impact, followed by technology. Individuals who adopted achieved productivity was 980 kilograms per hectare higher than those did not. (2) Factors such as age, farm size, family livestock units, credit access, off-farm income, market distance, cooperative membership negatively affect whereas education extension services positive impact. (3) effects strengthen over time. strengthening variables time implies gradual increase in farmer awareness, access resources, SAPs, highlighting evolving role driving them. Accordingly, none past researchers identified any patterns productivity. Therefore, promoting prioritizing can offer farmers experience support, thereby enhancing Future initiatives should therefore combine interdisciplinary methods, technology, community involvement for ensuring SAP’s sustainability scalability.

Язык: Английский

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Contrasting hydro-climatic trends and drought dynamics in Ethiopia and South Africa under climate change

Climate Dynamics, Год журнала: 2025, Номер 63(2)

Опубликована: Янв. 28, 2025

Язык: Английский

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Climate change impact and adaptation options in Sub-Saharan Africa: a systematic review

Environment Development and Sustainability, Год журнала: 2025, Номер unknown

Опубликована: Март 12, 2025

Язык: Английский

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Farmers’ Perceptions of the Efficacy of Current Climate Risk Adaptation and Mitigation Strategies on Agriculture in The Gambia

Land, Год журнала: 2025, Номер 14(3), С. 622 - 622

Опубликована: Март 15, 2025

Agricultural systems face increasing challenges due to climate change, necessitating effective adaptation and mitigation strategies. This study investigates smallholder farmers’ perceptions of the efficacy these strategies in The Gambia, employing a mixed-method approach that includes perception index (PI), effectiveness score (ES), importance–performance analysis (IPA), statistical analysis. A structured survey was conducted among 420 farmers across three agricultural regions. Farmers rated using Likert scale, PI developed quantify their responses. 0.66, indicating moderate level perceived effectiveness. Additionally, ES calculated assess performance various strategies, while IPA categorized based on adoption impact. Chi-square tests factor were applied explore differences perceptions. findings reveal such as crop diversification, pesticide application, irrigation, use inorganic fertilizers are widely adopted effective. matrix identified key needing improvement, particularly those with high importance but low performance. Barriers include limited financial resources (77%), lack government support (64%), insufficient knowledge (52%), no significant gender-based underscores need for policy interventions integrate enhance resilience. Targeted investments adaptive technologies, support, knowledge-sharing platforms can improve research provides valuable insights into interplay between farmer perceptions, sustainability Gambia.

Язык: Английский

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Effect of climate change and variability-induced shocks and stresses on rural household livelihoods and their adaptation practices in West Arsi Zone, South-Central Ethiopia

Climate Services, Год журнала: 2025, Номер 38, С. 100561 - 100561

Опубликована: Апрель 1, 2025

Язык: Английский

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Risk aversion or adaptation? Public choices in sports participation under climate risks

Frontiers in Public Health, Год журнала: 2025, Номер 13

Опубликована: Апрель 9, 2025

Introduction The increasing frequency and severity of climate risks have significantly impacted public health behaviors, particularly sports participation. Understanding how individuals respond to these environmental shocks is crucial for designing effective adaptation policies. This study examines the short-term long-term effects on participation among middle-aged young adults, exploring underlying mechanisms driving behavioral changes. Methods Using data from 2014 2022 China Family Panel Studies (CFPS), this employs fixed-effects models, two-stage least squares (2SLS) estimation, a four-stage mediation model address potential endogeneity uncover causal relationships. Climate are assessed using multiple proxy variables, robustness checks ensure reliability findings. Results In short term, reduce effect remains consistent across different specifications estimation methods. Mechanism analysis reveals that lower life satisfaction increase digital engagement, both which influence individuals' physical mental health. While initially discourage participation, occurs through engagement indoor exercise, leading improved outcomes. Heterogeneity indicates negative more pronounced in urban western regions, with rural areas experiencing no significant positive effects. Discussion highlights inhibitive adaptive responses findings provide insights into adjust their health-related behaviors under stress offer policy recommendations promote targeted interventions.

Язык: Английский

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Modeling climate change impacts on blue and green water of the Kobo-Golina River in data-scarce upper Danakil basin, Ethiopia

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 53, С. 101756 - 101756

Опубликована: Март 27, 2024

Kobo-Golina River, Upper Danakil Basin, Ethiopia. It is crucial to understand the spatiotemporal distribution of blue water (BW) and green (GW) for optimal use resources, especially in data-scarce regions. This study aims evaluate extent which future climate changing, its impact on blue-green resources area. Projected changes were predicted based latest Coupled Model Intercomparison Project Phase 6 (CMIP6) Global Climate Models (GCMs) three periods (2015–2044, 2045–2075, 2076–2100) under two shared socio-economic pathways (SSP2–4.5 & SSP5–8.5). Compromise programming technique was employed rank select best performing GCMs. The multi-variable calibrated SWAT+ model forced with projections from top-ranked CMIP6 GCMs ensemble simulate projected Compared baseline period (1984–2014), declined while exhibited an increasing trend all SSPs. also noted that spatial BW GW remains uneven Precipitation significantly impacted than resources. provides valuable insights into utilization recent coupled hydrological models better simulation Blue-Green basins changing climate.

Язык: Английский

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