https://orcid.org/0000-0003-3157-6312
Figures
Abstract
Understanding long-term drought dynamics in regions dominated by rain-fed agriculture systems is essential for climate adaptation planning. Thus, monitoring drought enables the provision of data for informed decision-making, which is critical to reducing drought risk. This study reconstructs spatiotemporal drought variability in the eastern Amhara region of Ethiopia over 120 years (1901–2020) using the self-calibrating Palmer Drought Severity Index (scPDSI). Data from the Royal Netherlands Meteorological Institute (KNMI) (https://climexp.knmi.nl/start.cgi) at 0.5° resolution were analyzed across 11 representative meteorological stations. Spatial interpolation using universal Kriging was applied to identify geographical patterns of drought. Temporal trends, recurrence intervals, and spatial patterns were assessed, and results were triangulated with key informant interviews. The region experienced drought conditions of varying severity approximately every 2.4 years. Mild and moderate droughts occurred more frequently, while severe and extreme droughts recurred roughly once per decade. A marked clustering of severe and extreme drought episodes was observed after 1970, indicating intensification in the late 20th and early 21st centuries. In peak years such as 1922 and 1984, over 80–90% of stations recorded severe to extreme drought conditions. Within the Eastern Amhara Region, particularly the Northern, northeastern, eastern, south-central, and southwestern areas, have frequently experienced severe and extremely severe drought, reflecting sensitivity to large-scale climate drivers. Interview participants confirmed that drought incidents have become increasingly frequent which has impeded the livelihoods of subsistence farmers. We recommend establishing comprehensive drought-monitoring and early-warning systems to inform the design of proactive measures.., Shifting to drought-tolerant crop varieties, promoting small-scale irrigation, diversifying crops to reduce reliance on high-risk crops, and developing alternative livelihoods for communities heavily dependent on agriculture are crucial. By bridging climate science with agricultural practice, this research contributes evidence for designing policies that strengthen resilience farming systems in one of Africa’s most drought-prone regions.
Citation: Asfaw Eshetu A, Moges G, Ahmed N, Adane A, Mohammed Ali A, Derese Nigussie B (2026) Long-term drought dynamics and agricultural implications in eastern Amhara Region of Ethiopia (1901–2020): Insights from the Self-Calibrating Palmer Drought Severity Index. PLOS Clim 5(4): e0000878. https://doi.org/10.1371/journal.pclm.0000878
Editor: Lindonne Telesford, Saint George's University, GRENADA
Received: December 18, 2025; Accepted: March 9, 2026; Published: April 8, 2026
Copyright: © 2026 Asfaw Eshetu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The necessary data is attached as a supporting information.
Funding: The authors received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist.
1. Introduction
Drought is a natural phenomenon that occurs worldwide due to climate change, negatively affecting human social standing, the environment, and the economy [1,2]. Climate change-related shifts in weather patterns and rising water demand have exacerbated drought [3]. Drastic precipitation reduction, groundwater or surface water scarcity, abnormally dry conditions, or other hydrometeorological processes that reduce moisture availability to a potentially hazardous level are among the many processes that can cause droughts [1]. The intensity, duration, and frequency of drought events have increased worldwide, exacerbating vulnerabilities, particularly in regions where livelihoods depend on rain-fed agriculture and where adaptive capacity is limited [1,4]. In sub-Saharan Africa, drought is a recurrent hazard with widespread consequences for food security, water availability, and human well-being, often compounding poverty and environmental degradation [5,6]. Svoboda and Fuchs [1] claimed that droughts can negatively affect a variety of aspects of life, including access to education, agriculture and food security, hydropower production and use, human and animal health, livelihood security, personal security, and women’s access to education, among others. Ethiopia is considered a nation most vulnerable to severe weather [6–8]. Thus, gaining a deeper understanding of climate extremes over short and long timescales is imperative to mitigate the potential effects of such events [9].
As global warming is believed to have caused high temperatures, changing rainfall patterns, increased variability, and increased extreme weather events in practically every region, drought is becoming a growing concern [2]. Consequently, as [10] boldly pointed out, developing strategies for efficient monitoring and timely identification of drought events is essential for making informed decisions on water management and drought mitigation, especially for agricultural sectors that rely on water. Monitoring drought, defined as collecting, evaluating, and reporting data to inform decision-makers on the state of droughts, is essential to reducing the risk of droughts and developing an early warning system [11,12]. Drought monitoring is a crucial component of drought mitigation where long-term drought analyses using multiple indices and models must inform dependable and effective conservation planning strategies and agricultural policies [2,13].
Using drought indicators, the intensity, duration, and spatial extent of a drought can be quantitatively described [14]. Macro-level drought assessments cannot account for the location-specificity of smaller areas, so in-depth research at a finer spatial scale is required. So, the micro-level drought trend must be closely studied to develop policies to mitigate the vulnerability it causes. Dehghan et al. [15] emphasized that to minimize the negative consequences of drought, it is critical to precisely and scientifically identify the characteristics of future droughts. Planning is crucial for making informed water management and drought mitigation decisions, particularly for the water-dependent agricultural sector. This includes developing strategies to monitor and promptly identify drought events [10] effectively.
Various indices and parameters estimate drought length, intensity, and frequency. One of the most widely used drought indicators is the Standardized Precipitation Index (SPI) [16]. One of the primary drawbacks of SPI is that it only monitors droughts using one climate variable, rainfall [17–20]. The Standardized Precipitation Evaporation Index (SPEI), developed by [21], which accounts for the effects of rising temperatures on water, is more appropriate than SPI for addressing its drawbacks [11,14]. The Palmer Drought Severity Index (PDSI), created by Palmer in 1965, is another indicator that estimates the extent of cumulative departure from the surface water balance. The PDSI is dependent on temperature, precipitation, soil available water content, and other meteorological factors [15,22]. A common criticism of the PDSI, however, is that it behaves inconsistently across locations, making spatial comparisons of PDSI values challenging [18–20]. Another parameter frequently used to quantify drought is the self-calibrated Palmer Drought Severity Index (scPDSI), which accounts for all PDSI constants and determines the station-specific characteristics. The self-adjusting characteristics of sc-PDSI are tailored to each station and vary with the local climate regime. Its scales are both dry and wet. It can be used in hydrological, agricultural, and meteorological drought conditions [2,23]. Because of this, we used scPDSI techniques that accounted for evapotranspiration, following the recommendations of [2,24–30].
Ethiopia is among the most vulnerable countries to drought in Africa, mainly due to its high dependence on rain-fed agriculture and its low adaptive capacity [31,32]. Historical droughts, such as those of 1974, 1984, and 2015/16, have resulted in catastrophic famines and mass displacement, underscoring the central role of drought in shaping a country’s socioeconomic trajectory [8]. Although several studies have characterized drought in Ethiopia [5–7], drought monitoring is not adequately conducted [11]. Much of the focus has been on water-abundant regions [5,9] or at national-scale assessments. By contrast, northeastern Ethiopia-one of the most chronically drought-prone areas of the country-remains understudied despite its high vulnerability [33]. Moreover, many previous studies have relied on a single index, mainly SPI [5–7,9,34], which failed to account for evapotranspiration and soil water balance, thereby limiting their ability to capture agricultural drought dynamics [17,21]. The self-calibrating Palmer Drought Severity Index (scPDSI) offers a more robust alternative because it integrates precipitation, temperature, and soil moisture processes, and dynamically adjusts to local climate regimes [25,27]. Applying scPDSI over long temporal scales provides valuable insights into historical drought dynamics and their implications for agricultural livelihoods.
Drought characterization studies in Ethiopia mainly relied on empirical data, with little triangulation with the community’s lived experiences. Although drought variability in Ethiopia has been widely examined, few studies have provided century-scale (1901–2020) analyses focused specifically on Eastern Amhara using self-calibrating PDSI. Existing studies focus on shorter temporal scales [5,7,35] or at the micro-level [36–38], limiting region-specific agricultural interpretation and failing to identify drought hotspots. This study addresses this gap by (i) reconstructing long-term drought dynamics using scPDSI, (ii) quantifying recurrence intervals and severity patterns, and (iii) linking these patterns explicitly to agricultural vulnerability in Eastern Amhara by triangulating with interview results from development agents. By placing local drought histories within larger climatological processes and directly linking findings to the challenges faced by rain-fed smallholder farmers, this research adds to both the scientific understanding of drought dynamics and the development of practical adaptation and policy responses in Ethiopia and similar semi-arid areas. This study is anchored in quantifying long-term drought trends (1901–2020), estimating recurrence intervals and the severity distribution, identifying spatial hotspots of drought persistence, and assessing agricultural implications. Specifically, the study aims to answer the following research questions:
- What are the long-term patterns and recurrence intervals of drought events in northeastern Ethiopia?
- How do spatial distributions of drought severity align with known zones of smallholder agricultural vulnerability?
- What implications do these patterns hold for drought risk management and climate-resilient agricultural strategies?
2. Materials and methods
2.1 Location and biophysical situation
The study area is located between 8043’9.66“-13015’26.42” N and 38019’41.41’- 40026’55.3” E, in the eastern parts of Amhara National Regional State (ANRS), Ethiopia (Fig 1). Geographically, it consists of North and South Wollo, North Shewa, Wag Hamra, and Oromia special zones of the regional state. This area exhibits a diverse topography, characterized by diverse agroecological zones ranging from Kola (500–1500 m, warm semi-arid lowland) accounts for 17.36%, Woinadega (1500–2300 m, cool sub-humid midland) comprises 40.54%, Dega (2300–3200 m, cool and humid highland) constitutes 38.58%, and Wurch (above 3200 m, cool and moist highland) makes up 3.52% of the land area (Fig 2c). The study area is marked by diverse physiographic features, including prominent mountainous regions, deeply incised canyons, gorges, valleys, and steep-sloped plateaus. As a result, the area experiences a range of climatic conditions, from the hot, arid lowlands to the cold, humid highlands [36].
The base map of Ethiopia, the administrative boundaries, and the study area were produced in ArcGIS using publicly available shapefiles from EthioGIS (public domain) available at https://www.ethiogis-mapserver.org/.
Reprinted from the base map of Ethiopia in ArcGIS using publicly available shapefiles from EthioGIS (public domain) available at https://www.ethiogis-mapserver.org/.
The study area has three seasons: kiremt, the primary rainy season (from June to September); small belg rains (from March to May); and the dry bega season (from October to February) [31,32,36,39,40]. Rainfall during the belg is highly erratic and unstable compared to the primary growing season [36]. In terms of onset, cessation, and the length of the growing season, the area has experienced significant variability, mainly due to climate change [39]. The area receives an annual rainfall ranging from 750mm in the driest areas to 2000mm in the wettest areas. The yearly mean temperature of the study area ranges from 8 °C in the central highlands to 30 °C in the western lowlands (39, 40) (Fig 2a and 2b).
The long-term rainfall pattern shows significant variability (See S1 Data). Overall, Guguftu and Woreillu stations receive more rainfall. At the same time, the least is recorded in Kobo and Sekota (Fig 3). In the study area, the soil depth is very shallow due to prolonged erosion and poor vegetation cover [31,36]. The vegetation cover of the area is very scanty, ranging from evergreen to deciduous and shrubs to grasslands [41,42]. The primary factors driving land degradation in the area include the expansion of agriculture into marginal lands, land insecurity, deforestation, unmanaged grazing, and poverty [43].
2.2 Socioeconomic setting
According to [31,43], the eastern part of the Amhara regional state is one of the country’s chronically food-insecure areas. This food insecurity leads to out-migration, overexploitation of remaining natural resources, social and political instability, and ecological imbalance [43]. The area’s diverse agroecology supports the production of cereals, pulses, and oil crops, although root and permanent crops are limited [31]. Rainfall deficiency and variability are significant causes of recurrent droughts and significantly affect crop production [31]. Furthermore, high population pressure forces people to cultivate marginal and steeper lands at the expense of remaining forests. They also use crop residues and animal dung for household energy rather than enhancing land productivity and preventing land degradation [43].
2.3 Data sources and data analysis techniques
Self-calibrated Palmer Drought Severity Index (scPDSI) values from 1901 to 2020 for 11 stations were obtained from the Royal Netherlands Meteorological Institute (KNMI) (https://climexp.knmi.nl/start.cgi) at 0.50 resolutions, which provides globally gridded, bias-corrected scPDSI time series derived from the Climatic Research Unit (CRU TS) dataset [44,45]. Based on continuous observation and geographic representativeness, 11 first-order meteorological stations were purposively selected. The study area features a highly varied topography, which ensures the spatiotemporal characterization and captures the variability of drought response across the region’s distinct climate regimes, validating the study’s goal of meso-scale characterization. The Anderson-Darling normality test was used to assess the data’s normality. Correlations among different stations were determined using the Pearson correlation test to examine the spatial homogeneity of drought. The scPDSI, which self-calibrates, automatically adjusts the index’s behavior at any given location by dynamically calculating values to replace empirical constants in the index computation. We used the scPDSI to estimate the duration, intensity, and frequency of droughts in the Eastern Amhara region. This index is intended for the identification of meteorological and agricultural drought. The method uses the concept of adequate precipitation, which considers the quantity of water that contributes to plan development [10]. The scPDSI estimates relative dryness using readily available temperature and precipitation data. By accounting for potential evapotranspiration, scPDSI can capture the fundamental impact of global warming on drought using temperature data and a physical water balance model. The scPDSI was chosen as the primary drought indicator because it incorporates both precipitation supply and atmospheric demand (via temperature-driven evapotranspiration) and soil water-holding capacity, and adjusts to local climate conditions, making it more representative of agricultural drought conditions than precipitation-only indices such as SPI [21,25]. ScPDSI has been widely used to detect hydrological and long-term agricultural droughts and determine the abnormality of a specific drought in a given area. According to [25,46,47], scPDSI has been classified as wet (greater than 2.00), normal or near normal (-1.99 up to 1.99), and drought (less than -2.00) (see Table 1).
Various spatial interpolation techniques, such as Kriging, Inverse Distance Weighted, and modified Inverse Distance Weighted, are used to map droughts from point data [48]. In geographically heterogeneous areas with complex terrain, scholars recommend the Kriging method [49,50] as the most appropriate interpolation technique due to its capability to interpolate the residuals based on spatial autocorrelation, provide higher predictive accuracy, account for environmental drivers of variation, and generate uncertainty assessments essential for decision-making [50–53]. Since our study exhibits a very heterogeneous topography [36,39] with diverse agroecologies and rainfall regimes [39,40], we employed the Universal Kriging interpolation technique.
For each station, drought frequency, intensity, and recurrence intervals were calculated based on the scPDSI time series. Drought events were defined as consecutive months with scPDSI ≤ −1.0. Event duration was calculated as the number of continuous drought months, while severity was computed as the cumulative scPDSI anomaly over the event period. Recurrence intervals were estimated as the inverse of the event frequency over the 120 years. Parameters were selected following sensitivity analysis in which alternative calibration baselines (30-year vs 50-year periods) were tested. The chosen configuration minimized calibration bias and maximized the temporal stability of drought classification. Descriptive statistics characterized the distribution of mild, moderate, severe, and extreme drought events over the 120 years. Temporal clustering of droughts was examined by identifying peak drought years and comparing them with documented famine and ENSO episodes in the historical record. A key informant interview (KII) with eight purposely selected individuals who have worked for more than 10 years as development agents was conducted to triangulate the statistical results with the lived experiences of the experts, based on data saturation criteria.
Ethical Statement: Verbal informed consent was obtained from all key informant participants before data collection. Consent was documented by recording the date and location of the interview, the participant’s anonymized identifier, and confirmation by a trained field assistant who served as a witness. As the study relied mainly on data derived from freely available satellite sources, formal institutional ethical approval was not required.
3. Results and discussion
3.1 Long-term patterns and recurrence intervals of drought events
This study quantified drought occurrences in the eastern Amhara region of Ethiopia, one of the country’s most drought-prone areas, using data obtained from 11 purposively selected first-order meteorological stations (S1 Data and S2 Annex). The results of the Anderson-Darling normality test indicated no significant departures from normality across all stations at the 5% level of significance (see S3 Annex). Additionally, the data revealed no significant outliers. As depicted in (Figs 4-6 and S1 Annex), the study area experienced recurrent drought episodes that ranged from mild to extreme droughts. The frequencies of mild (-1.0 to -1.99) and moderate (-2.0 to -2.99) were higher than the frequencies of severe (-3.0 to -3.99) and extreme (-4.0 and less) droughts (Fig 4 and S1 Annex). Most areas had experienced 3–9 mild droughts and 10–20 moderate droughts. On the other hand, the frequencies of severe and extreme droughts ranged from 3 to 16 and 1–8 times, respectively. Sekota, Shewarobit, and Lalibela experienced the highest incidence of extreme drought, while the frequency of severe drought was highest for Shewarobit, Kobo, Kemissie, Mekaneselam, Sekota, Woreillu, Lalibela, and Kombolcha (Fig 6). This indicated both spatial and temporal variations in drought incidence in the study area. On average, the region has experienced 11 severe and extreme drought episodes, occurring approximately once every decade. Additionally, the average frequency of mild and moderate drought episodes in the study area was 21.7 occurrences, equivalent to every 5.5 years, and 16.5 occurrences, corresponding to every 7.3 years, respectively. On average, the study region experienced drought conditions of varying severity approximately every 2.4 years. The results are consistent with [12], who reported that droughts in Ethiopia have occurred approximately once every 3 years in recent decades, compared to once per decade in the 1950s. The incidence of severe and extreme droughts was higher in the latter half of the 20th century (especially the last quarter) than before 1950. This result is consistent with [11,38], which reported increases in the frequency and severity of drought. In line with these empirical results, KII3 and KII8 observed that drought events have intensified and are now occurring at shorter intervals, approximately every 2–3 years. This recurrence interval suggests a shrinking recovery window for farming households, limiting their capacity to restore soil fertility, rebuild livestock holdings, and replenish savings between successive climatic shocks. The informant further noted that the near-regular occurrence of drought has altered farmers’ seasonal expectations and increased uncertainty in planting decisions.
The year-specific results revealed that severe to extreme droughts occurred during the study period at the majority of stations in 1913, 1919, 1920–1922, 1951–1953, 1974, 1984–1987, 1900, and 2018–2020. On the other hand, almost all stations experienced moderate droughts during 1923, 1939–1942, 1970, 1991, 2002, and 2009 (Figs 5 and 6).
The scPDSI result aligns with the findings of [54], who reported severe drought episodes in northern Ethiopia in 1957/58, 1971–75, 1982–1985, 1987/89, 1991/92, 2003/04, 2008/09, 2015/16, and 2018. Similarly, [28] reported severe drought events three times during the 1941–1950 period, four times during 1951–1960, five times during 1980–1990, two times during 1991–2000, and three times during 2001–2010 in the northern part of Ethiopia. Mohammed et al. [36] noted that most of north Ethiopia had experienced drought episodes in the last century, mainly in 1984, 1987/1988, 1992/1993, and 2003/2004, which were among the worst drought years in the history of Ethiopia. Burka et al. [8] also noted 1984/85 as the worst drought episode in the history of Ethiopia. Mera [32] indicated that the droughts in 1974, 1984, and 2002 had a devastating impact on many regions of Ethiopia, leading to significant food shortages and famine and affecting a substantial portion of the population. Furthermore, the incidence of droughts from 2018 to 2020 was consistent with the predictions made by [55]. Likewise, [12] reported that 1953, 1961–1964, 1972–1976, 1984, 1986, 2002, and 2014/15 were the driest years with extreme drought occurrences in most parts of Ethiopia, where the spatial extent of drought frequency was the highest in the central and northern parts of the country. Behailu et al. [40] also reported 1983, 1985, 1988, 1991/92, 2005/06, 2009, and 2016 as the driest years in Sekota (part of the current study area). Findings from the KIIs with development agents consistently indicate an increasing trend in both the incidence and severity of drought over recent decades. The qualitative evidence aligns with the quantitative drought trend analysis and reinforces the growing vulnerability of smallholder farming systems in the study area. KII1 and KII2 reported that both the frequency and intensity of drought events have increased over time, significantly affecting the livelihoods of smallholder farmers. According to the informant, drought episodes are no longer isolated climatic shocks but recurring stressors that disrupt agricultural production cycles, reduce crop yields, and erode household asset bases. The informant emphasized that repeated drought exposure has weakened farmers’ resilience, particularly among those dependent on rain-fed subsistence agriculture. According to their observations, drought incidents have become more apparent since the late 20th century.
Critically, the analysis demonstrates a statistically visible elevation in the clustering of severe (scPDSI −3.0 to −3.99) and extreme (scPDSI ≤−4.0) drought episodes in the latter quarters of the study period (specifically 1976–2000 and 2001–2020). The observed rising trend in drought frequency and intensity post-1950 is not simply a statistical observation, but an empirical confirmation of scPDSI’s utility in capturing climate change impacts. Since scPDSI inherently accounts for temperature-driven PET, this upward trend reflects heightened atmospheric moisture demand driven by warming temperatures. This factor would not be accurately quantified using rainfall-only indices. The spatial visualization of drought (Fig 7) indicates that severe and extremely severe conditions frequently affect most parts of the study area. Key vulnerable hotspots with the highest incidence of severe or extreme drought include Shewarobit (12 severe events), Mekaneselam (16 severe events), Kobo (11 severe events), and Sekota (8 severe events, including 2 extreme events). For example, in the catastrophic year of 1984, 90.9% of the monitoring stations recorded severe to extremely severe drought conditions, and in 2020, 45.5% of stations were similarly affected. Interview participants affirmed that 1984 was the worst drought ever recorded in the study area, claiming the deaths of thousands of people and their livestock. This spatial consistency and high recurrence in specific zones underscore the need for differentiated, targeted policy interventions based on agroecological vulnerability (S2 Annex).
Reprinted from the base map of Ethiopia in ArcGIS using publicly available shapefiles from EthioGIS (public domain) available at https://www.ethiogis-mapserver.org/.
Pearson correlation analysis (Table 2) confirmed statistically significant positive correlations among the scPDSI time series at all 11 stations, ranging from moderate (0.35) to very high (0.942). This correlation pattern suggests a notable spatial homogeneity in the distribution of drought conditions throughout the study area. Such high levels of correlation among the scPDSI results imply that drought conditions are prevalent and exhibit similar characteristics across different locations within the region. While regional coherence is expected, this analysis serves a vital methodological function by confirming two critical aspects. First, the high coherence indicates that the sampled stations are representative of the large-scale climatic drivers affecting Eastern Amhara, supporting the feasibility of using a unified regional drought index (scPDSI). Second, it validates the foundational assumption of spatial continuity required for using the Kriging interpolation technique for drought mapping (Fig 7). This spatial consistency enhances our understanding of drought dynamics and underscores the interconnectedness of environmental factors influencing drought severity in the area under investigation.
3.2 Spatial distribution of drought severity
The spatial distribution of drought across the selected years in the study area indicates that many monitoring stations have experienced varying degrees of drought severity over time. Notably, in 1913, approximately 81.8% of these stations reported severe or extremely severe drought conditions. Subsequent years also exhibited alarming trends: in 1922, a complete 100% of the stations were affected, while in 1951, 81.8%; in 1952, 63.6%; in 1953, 90.9%; in 1984, 90.9%; and in 2020, 45.5% of the stations recorded severe to extremely severe drought conditions (Fig 7). Geographically, the northern, northeastern, eastern, south-central, and southwestern regions of the eastern Amhara region appear to be particularly vulnerable to drought, as illustrated in Fig 7. Consistent with this result, KII participants identified the northern, northeastern, and eastern areas of the study areas as the most drought-prone areas of the region. These findings corroborate the conclusions of [12,32,36,56], which identified 1974, 1984, and 1987 as among the most catastrophic years in Ethiopia’s historical context. Furthermore, research by [56,57] explicitly highlights the area’s northern regions, particularly the North Wollo and Wag Hamra zones, as frequently affected by severe drought. This consistent pattern of drought underscores the critical need for targeted interventions to mitigate the impacts of such climatic events in these vulnerable regions.
The analysis provides compelling evidence that drought in eastern Amhara has evolved from a periodic climatic fluctuation into a persistent, spatially extensive, and increasingly severe environmental stressor over the 1901–2020 period. The robustness of the underlying meteorological data, as evidenced by the absence of significant departures from normality and outliers, reinforces the reliability of the scPDSI for long-term drought diagnostics in this region. This statistical soundness, combined with the century-long observational record, offers a rare opportunity to trace both the cyclical nature and the long-term intensification of drought in one of Ethiopia’s most climate-sensitive landscapes. Drought recurrence follows a clear directional pattern. Mild and moderate droughts remain the most frequent, occurring on average every 5.5 and 7.3 years, respectively. Severe and extreme droughts recur approximately once per decade. However, temporal disaggregation reveals a sharp escalation in both the frequency and clustering of severe and extreme droughts after the 1950s, with the most pronounced accumulation occurring in the periods 1976–2000 and 2001–2020. This shift mirrors nationwide and global observations that droughts, once primarily rainfall-driven, are increasingly intensified by anthropogenic climate change. Because the scPDSI accounts for temperature-driven increases in potential evapotranspiration, the upward trend observed here represents a genuine climatic signal rather than a statistical artifact.
Spatial patterns reveal pronounced heterogeneity, with the northern, northeastern, and eastern portions of the region, such as Sekota, Shewarobit, Kobo, Lalibela, and Mekaneselam, consistently emerging as drought hotspots. These areas are characterized by fragile agroecological conditions, including variable, often low rainfall, shallow soils, and a heavy reliance on rain-fed agriculture. Their recurrent classification as drought-prone zones suggests the influence of broader climatic drivers, including ENSO variability, shifts in the Intertropical Convergence Zone, and warming of the western Indian Ocean. Spatially continuous drought conditions in peak years such as 1922 and 1984, when 80–100% of stations experienced severe to extreme drought, further affirm the region’s susceptibility and align with historical famine epicenters in North Wollo and Wag Hamra. Key informants consistently underscored the intensification of drought since the late 20th century, identifying 1984 as the most catastrophic event in living memory, a perspective substantiated by the finding that 90.9% of stations recorded severe to extremely severe drought that year. The recurrence of widespread drought in 2018–2020, mirroring earlier periods of acute climatic stress, underscores that extreme drought remains a contemporary and escalating threat. This pattern aligns with regional climate change projections predicting increased drought persistence and severity.
3.3 Implications of observed drought patterns
Taken together, these findings illustrate a clear trajectory: eastern Amhara has transitioned from experiencing periodic, rainfall-sensitive droughts in the early 20th century to enduring climate-change-intensified drought regimes in the modern era. The observed intensification of drought post-1980 may be associated with increased temperature-driven evapotranspiration and variability in Belg and Kiremt rainfall regimes, consistent with regional climate projections. The combination of persistent regional coherence and highly localized hotspots underscores the need for a dual-level adaptation strategy. Region-wide measures, such as strengthened drought early warning systems, coordinated climate information services, and integrated water resource planning, must be complemented by location-specific interventions that address micro-scale vulnerabilities. These should include water-efficient agricultural practices, livelihood diversification, soil and watershed restoration, and enhanced land management systems. Without such differentiated and forward-looking strategies, the recurrent, severe, and spatially pervasive droughts documented here will continue to erode the socioecological resilience of one of Ethiopia’s most vulnerable regions, deepening livelihood insecurity in its predominantly rain-fed agrarian communities. KII4 and KII6 also affirmed the increasing severity of drought and highlighted its direct impact on agricultural activities. The informant indicated that erratic rainfall distribution, prolonged dry spells during critical crop growth stages, and early cessation of rainfall have collectively undermined productivity. These climatic irregularities have disrupted traditional planting calendars, reduced germination rates, and increased the risk of crop failure. Moreover, water scarcity has constrained livestock production, compounding the vulnerability of mixed farming systems. KII5 and KII8 underscored the long-term livelihood risks posed by recurrent drought, particularly in formerly degraded and drought-prone areas. The informant cautioned that, without robust, context-specific adaptation strategies, the sustainability of smallholder subsistence farming systems is increasingly at risk. Special concern was raised regarding areas with pre-existing land degradation, where diminished soil moisture retention capacity exacerbates drought impacts. The informant emphasized the urgent need for integrated adaptation measures, including soil and water conservation, drought-tolerant crop varieties, and improved water harvesting infrastructure. The study’s empirical contribution thus extends beyond documenting historical patterns; it provides an essential evidence base for designing climate-resilient development pathways in eastern Amhara and similar drought-prone environments.
Studying long-term drought trends provides an empirical foundation for proactive drought risk management and climate-resilient agriculture. Trend analysis enables the detection of shifts in frequency, duration, intensity, and spatial distribution of drought events. Such evidence supports the design of early warning systems, risk-informed contingency planning, and targeted resource allocation. In agriculture, understanding long-term drought dynamics informs crop diversification, selection of drought-tolerant cultivars, adjustment of planting calendars, expansion of small-scale irrigation, and investments in soil–water conservation. It also strengthens climate-smart policy formulation, index-based agricultural insurance schemes, and livelihood diversification strategies. Ultimately, integrating long-term drought analytics into planning processes enhances adaptive capacity, reduces vulnerability, and promotes sustainable food systems under increasing climate variability and change.
4. Conclusion and policy recommendations
4.1 Conclusion
This study reconstructed 120 years (1901–2020) of drought variability in the Eastern Amhara Region using the self-calibrating Palmer Drought Severity Index (scPDSI). The findings demonstrate that drought is a recurrent and structurally embedded climatic feature of the region. On average, drought conditions of varying intensity occurred approximately every 2.4 years with little recovery window. While mild and moderate droughts were most frequent, severe and extreme droughts recurred roughly once per decade and exhibited significant clustering after the 1970s. Peak drought years-including 1913, 1918–1919, 1922, 1974, 1984–1987, and 2018–2020-affected the majority of monitoring stations simultaneously, confirming the spatial coherence of extreme drought episodes. The post-1950 increase in drought frequency and severity indicates a shift toward temperature-amplified moisture deficits, as scPDSI incorporates evapotranspiration effects.
Spatial analysis identified persistent drought hotspots in northern and northeastern Eastern Amhara, particularly in Sekota, Kobo, Shewarobit, and Mekaneselam, areas characterized by fragile agroecological systems and high dependence on rain-fed agriculture. These results underscore the urgency of strengthening region-wide drought monitoring and early warning systems while implementing locality-specific adaptation strategies. Sustainable water harvesting, expansion of small-scale irrigation, soil moisture conservation, adoption of drought-tolerant crops, and livelihood diversification are essential to buffer smallholder farmers against recurrent shocks. The century-scale evidence presented here provides a robust empirical foundation for integrating drought risk management into Ethiopia’s climate adaptation frameworks and long-term agricultural development planning. The qualitative evidence from the KIIs indicated a clear perception of an escalating drought risk, characterized by increasing frequency, severity, and shorter recovery periods. The convergence of these insights across multiple informants strengthens the credibility of the observed long-term drought trend and underscores the pressing need for climate-resilient agricultural interventions. The KIIs corroborate the statistical evidence of increasing drought frequency and severity in the study area. Development agents consistently reported that drought now occurs more frequently, reducing the recovery window for smallholder farmers. Informants also emphasized intensifying drought severity, characterized by prolonged dry spells, erratic rainfall distribution, and early cessation of rains during critical crop growth stages. Such observations are consistent with studies indicating that rising temperatures and increased evapotranspiration are amplifying agricultural drought across sub-Saharan Africa. This reinforces the role of temperature-driven moisture deficits in exacerbating production risks. Overall, the convergence of qualitative insights and empirical literature suggests that drought is shifting from an episodic climatic hazard to a structural constraint on agricultural productivity and rural livelihoods. Without robust adaptation measures-such as soil and water conservation, drought-tolerant varieties, and improved climate services-smallholder farming systems face escalating vulnerability.
The findings are immediately applicable to regional drought risk planning, climate-resilient agricultural policy design, and the refinement of long-term early warning systems in semi-arid highland environments. The study provides valuable insights into the temporal and spatial patterns of drought since the beginning of the 20th century, serving as a benchmark for predicting and preparing for future drought events. Thus, to cope with the extremes of climate and enhance agricultural productivity, it is highly recommended that decision-makers and smallholder farmers improve the existing water management and farming practices. In addition, the results of this study provide a scientific basis for policymakers to recapitalize the drought management strategy by integrating climate change adaptation and mitigation programs, preparedness plans, and systematic early warning systems across drought-prone areas.
4.2 Evidence-based policy recommendations
4.2.1 Implications for drought risk management.
The vulnerability mapping identifies distinct geographical and agroecological hotspots requiring zone-specific, differentiated policy responses rather than generalized regional strategies. Based on the persistent drought history and rising severity trend, the following methods are strongly supported by the evidence. Establishing comprehensive monitoring and early warning Systems is needed. The identified 2.4-year drought recurrence interval indicates a limited recovery window between consecutive drought events, constraining ecological regeneration and agricultural recovery cycles. This pattern underscores the urgency of shifting from reactive crisis response to anticipatory risk management. Coordinated, multi-institutional drought monitoring systems integrating meteorological, hydrological, and soil moisture indicators are essential to enhance early warning accuracy, improve preparedness planning, and support timely decision-making at national and sub-national levels. This requires integrating advanced technologies such as remote sensing and satellite data alongside local meteorological observations. Real-time data collection must be prioritized to provide timely alerts based on physically driven indices such as scPDSI, enabling proactive measures rather than reactive disaster relief.
4.2.2 Implications for the development of climate-resilient agriculture.
The observed temperature-driven evapotranspiration stress highlights the growing influence of warming trends on agricultural water balance, even in the absence of significant rainfall decline. This dynamic contributes to shortened growing seasons and increased crop moisture stress, necessitating adaptive agronomic practices. Strengthening soil moisture conservation through mulching, conservation tillage, and agroforestry becomes critical for sustaining productivity. Given the findings of rising drought intensity, adaptation strategies focusing on sustainable water resource management practices are essential to buffer production risks and stabilize yields under increasingly variable hydro-climatic conditions. This includes constructing rainwater-harvesting systems, developing small-scale irrigation projects, and promoting water-conservation techniques such as efficient irrigation (e.g., drip irrigation) and soil moisture retention. Maximizing water-use efficiency is paramount to reducing reliance on erratic rainfall in this chronically vulnerable region. Strategies focusing on agricultural adaptation and livelihood diversification should be undertaken. The identification of specific high-risk zones demands targeted agricultural resilience programs. Policymakers should support a shift to drought-tolerant crop varieties and promote crop diversification to reduce dependency on high-risk, water-intensive crops. Collaborations between research institutions and agricultural extension services are crucial for facilitating the adoption of agroecological practices and climate-resilient farming. Furthermore, for communities heavily reliant on rainfed agriculture, developing alternative livelihoods is crucial to mitigate the socioeconomic impacts of recurrent drought.
4.3 Limitations of the study
Several limitations should be acknowledged. First, scPDSI relies on model-based soil moisture estimation, which may not fully capture local hydrological heterogeneity. Second, gridded historical climate datasets may introduce interpolation uncertainty, particularly in early 20th-century observations. Third, agricultural implications are inferred from climatic indices rather than direct yield data, which may moderate causal interpretation. Although limited by reliance on a single drought index, descriptive methods, and the absence of agricultural yield linkages, the study provides a valuable empirical baseline of historical drought dynamics in one of Ethiopia’s regions. Future research should integrate multiple drought indices, employ advanced spatial interpolation, and explicitly connect drought metrics to agricultural productivity. Such approaches would enhance scientific rigor and provide policymakers with actionable insights. Ultimately, building resilience among smallholder farmers will require not only technical solutions but also institutional and policy frameworks that prioritize long-term adaptation to a future characterized by increased droughts.
Supporting information
S1 Data. Raw rainfall data and self-calibrated Palmer Drought Severity Index.
https://doi.org/10.1371/journal.pclm.0000878.s001
(XLSX)
S1 Annex. Spatial and temporal frequency of mild, moderate, severe, and extreme drought events (1901–2020) across 25-year quarters for each of the 11 study stations.
https://doi.org/10.1371/journal.pclm.0000878.s002
(DOCX)
S2 Annex. Location, altitude, and agroecology type of the 11 selected representative meteorological stations in Eastern Amhara, Ethiopia.
https://doi.org/10.1371/journal.pclm.0000878.s003
(DOCX)
S3 Annex. Anderson-Darling (AD) normality test output.
https://doi.org/10.1371/journal.pclm.0000878.s004
(DOCX)
Acknowledgments
Disclaimer: The author’s views and opinions are presented in this article and may not accurately represent any associate agency’s official policy or stance.
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