Diagnosis of Compound Stress-Induced Crop Failure through Integrated Geospatial, Climate, and Vegetation Diagnostics in Aburin, Somaliland

Acknowledgements

This study was undertaken with the technical collaboration and analytical support of TerraTech Solutions, whose expertise in geospatial analytics, climate diagnostics, and remote-sensing workflows significantly contributed to the successful completion of this assessment.

The Somaliland Institute of Agricultural Research (SIAR) extends its sincere appreciation to the TerraTech analytical team for their contributions in data processing, long-term climatology reconstruction, vegetation trend analysis, and the development of compound-stress diagnostic frameworks used in this report.

We also acknowledge the operational assistance provided by local field staff, community informants, and institutional partners who offered valuable contextual insights into agricultural conditions and environmental challenges across the Aburin region.

Special recognition is given to the developers and maintainers of open-access datasets and platforms—including Google Earth Engine, CHIRPS, ERA5-Land, Landsat, and MODIS—which made it possible to conduct a 42-year climate and vegetation analysis with high scientific rigor.

Finally, SIAR appreciates all stakeholders whose support, collaboration, and shared commitment to strengthening Somaliland's agricultural resilience made this research possible.

Executive Summary

This report presents a comprehensive assessment of long-term climate and vegetation dynamics in the Aburin agricultural zone of Somaliland using 42 years of data (1984–2025). The analysis was undertaken to understand how recurring droughts, heat stress, and other environmental pressures interact to affect agricultural performance and ecosystem health.

Findings show that Aburin experiences a predominantly arid to semi-arid climate, with an annual average rainfall of about 397 mm and strong seasonal and year-to-year variability. A slight upward rainfall trend (~+1.8 mm/year) is detectable, but drought remains a persistent hazard: approximately one in three years shows meteorological drought conditions (SPI < -0.5). Major drought events, especially those in 1984 and 2009, coincide with significant declines in vegetation health.

Vegetation indices indicate a broad greening trend over the past two decades, reflecting periodic recovery during wetter years. A high NDVI-based Climate Resilience Index (~99/100) suggests strong vegetation rebound following droughts. However, this resilience is fragile and highly dependent on the timing and distribution of rainfall rather than on structural ecosystem stability.

The study identifies critical compound stress interactions—such as low soil moisture combined with high land surface temperatures and elevated evapotranspiration—that intensify vegetation decline beyond what rainfall alone would indicate. These stress sequences explain several periods of reduced crop performance in Aburin.

The report concludes that enhancing agricultural resilience requires proactive measures including soil-moisture conservation, improved water harvesting, drought-tolerant crop varieties, and operational early warning systems based on integrated climate-vegetation monitoring.

This long-term evidence base provides SIAR with a scientific foundation for planning climate-smart interventions and strengthening food security in Somaliland's dryland environments.

1. Introduction

Somaliland is characterized by an arid to semi-arid climate with highly variable rainfall, recurrent droughts, and increasing climate-induced stresses on agricultural systems. The region experiences four distinct seasons: the main rainy season, Gu (April–June), which contributes approximately 50–60% of the annual rainfall; the shorter Deyr rains (late August–November), contributing 20–30%; and two dry seasons—Jilaal (December–March) and Hagaa (July–August).

1.1 Background

Compound drought and heatwave (CDHW) events—characterized by the simultaneous or sequential occurrence of meteorological drought, extreme temperatures, and associated atmospheric stresses—have emerged as one of the most formidable threats to agricultural systems worldwide. The intensification of these compound events is closely linked to anthropogenic climate change, which has altered precipitation regimes, increased temperature variability, and exacerbated evapotranspiration demand across various agro-ecological zones.

1.2 Problem Statement

Agricultural productivity in the Aburin region of Somaliland has been persistently undermined by the compounded effects of climatic and environmental stressors. Across the 42-year period from 1984 to 2025, recurring episodes of vegetation decline and reduced crop performance have raised concerns regarding the underlying causes and temporal dynamics of stress-induced crop failure.

1.4 Research Gaps

Despite increasing availability of satellite-based climate and vegetation data, significant knowledge gaps persist regarding the diagnosis of compound stress events in Somaliland's dryland agricultural zones. Existing studies often address individual stressors—such as drought or heat—in isolation, overlooking the interactive effects that more accurately characterize real-world crop failure dynamics.

1.5 Objectives

The overarching goal of this study is to diagnose the drivers, sequence, and severity of compound environmental stress events that have impacted agricultural productivity in the Aburin region of Somaliland between 1984 and 2025.

The specific objectives are to:

1. Diagnose the Root Causes of Vegetation and Crop Performance Decline
2. Integrate Geospatial and Climate Datasets
3. Determine the Sequence and Timing of Stress Events
4. Quantify Water Deficits and Vegetative Responses
5. Generate Evidence-Based Recommendations for Adaptation and Early Warning

1.6 Conceptual Framework

2. Materials and Methods

2.0 Study Area Location

The study was conducted at the Somaliland Institute of Agricultural Research (SIAR) Research Center, located in Aburrin within the central agricultural belt of Somaliland.

3.0 Biophysical and Environmental Characteristics of the Study Area

3.1 Landform Characteristics

The Abuurriin landscape is dominated by low-relief plains and gently undulating terrain, interspersed with shallow depressions, seasonal drainage channels (toggas), and minor escarpments.

3.7 Data Sources

3.9 Analysis Framework

The analysis incorporated multiple approaches:

• Vegetation Indices: NDVI, EVI, and SAVI calculated and normalized
• Compound Stress Indicators: VCI, TCI, and VHI computed
• Water Balance Analysis: Rainfall – ET₀ estimated monthly
• NDVI–SM–LST Interactions: Correlation matrices developed
• Statistical Modelling: Regression and Random Forest models

4. Results

4.1 Historical Climate Patterns (1984–2025)

The historical climate analysis for Aburin over the 42-year period reveals the overarching arid-to-semi-arid nature of the region with strong interannual and seasonal variability.

Rainfall Trends

• The mean annual rainfall across Aburin from 1984 to 2025 is approximately 397 mm
• Rainfall follows a bimodal distribution, with the Gu season contributing 50–60% and Deyr season 20–30%
• A slight upward linear trend in annual rainfall was detected (~+1.8 mm/year)
• Severe droughts observed in 1984, 1991, 2001, 2009, and 2016

4.2 Vegetation Trends

Vegetation health and productivity in the Aburin region were evaluated using MODIS NDVI data for the period 1984–2025.

Decadal NDVI Dynamics

• 1984–1994: Mean NDVI ~0.22
• 1995–2004: Mean NDVI ~0.24
• 2005–2014: Mean NDVI ~0.27
• 2015–2025: Mean NDVI ~0.30

4.3 Stress Severity, Frequency, and Ranking

Compound stress events were assessed using integrated drought indices—primarily the Vegetation Health Index (VHI).

Frequency of Compound Stress

• 34% of all months from 1984–2025 exhibited compound stress (VHI < 40)
• Stress events were most frequent during Gu seasons
• Notable clusters of stress occurred during: 1984–1985, 2001–2002, 2008–2009, 2016–2017, 2021–2022

4.4 Compound Stress Sequence

Understanding the temporal sequence of biophysical stressors is essential for diagnosing the precise causes of crop failure.

Identified Sequence Pattern

1. Soil Moisture Drop - SM levels declined below 0.12 m³/m³
2. LST Spike - LST anomalies exceeded +4°C above climatological baseline
3. High Wind Periods - Wind gusts >6 m/s observed during May–June
4. NDVI Collapse - Sharp NDVI drop followed, especially in June–July

4.5 Water Balance and Moisture Deficit

An assessment of seasonal water availability was conducted using the difference between precipitation (P) and reference evapotranspiration (ET₀).

Key Results

• Long-Term Mean P − ET₀ Deficit: Average April–August deficit is -180 mm
• Most Deficit Years: 1984, 1991, 2009, and 2017 recorded extreme deficits (-250 mm or worse)
• Critical Months: The June–July window consistently exhibits the deepest deficits

4.6 Identification of Dominant Stress Drivers

To understand which biophysical variables most significantly contributed to vegetation decline, we applied both correlation analysis and a Random Forest (RF) regression model.

Top Stress Drivers (by RF importance score):

1. Soil Moisture (SM)
2. LST (Land Surface Temperature)
3. VPD (Vapor Pressure Deficit)
4. Wind Speed
5. Precipitation (P)

5. Discussion

5.1 Interpretation of the Compound Stress Event

The analysis of 42 years (1984–2025) of climate and vegetation data reveals that crop failure in the Aburin agricultural zone results from a sequential cascade of climatic stressors. The typical compound event begins with below-normal rainfall during the Gu or Deyr season, leading to soil moisture deficits, followed by heatwaves and sometimes dry winds, culminating in NDVI collapse during critical phenological stages.

5.2 Comparison with Global Studies

These findings are consistent with other multi-stressor agricultural studies in regions such as Lorestan (Iran), the Mississippi Delta (USA), China's Huang-Huai-Hai Plain, and East Africa. Aburin's case reinforces these findings in a previously understudied agro-ecological context.

5.3 Implications for Land, Water, and Crop Management

Understanding the dominant drivers of crop stress enables better-targeted interventions:

• Soil moisture conservation is crucial in buffering against rainfall variability
• Windbreaks and shading systems could reduce canopy stress
• Rainwater harvesting and supplemental irrigation can maintain root-zone moisture
• Adjusting sowing calendars to avoid peak stress periods

5.4 Limitations and Uncertainties

Several caveats must be acknowledged, including limited access to local in-situ data, wind data resolution challenges, vegetation index interpretation limitations, and compound stress index simplification.

6. Recommendations

7. Conclusion

8. References

1. Placeholder for MODIS NDVI/EVI-based yield prediction study — Mississippi Delta region.
2. Placeholder for Lorestan drought monitoring research using VCI, TCI, VHI indices.
3. Placeholder for compound drought and heatwave (CDHW) analysis in the Huang-Huai-Hai Plain, China.
4. Placeholder for East African arid zone remote sensing studies and early warning systems.
5. Placeholder for FAO guidance on climate resilience and dryland agriculture.
6. Placeholder for NASA Earth Observatory datasets and CHIRPS rainfall data.
7. Placeholder for ERA5-Land surface temperature and soil moisture records.
8. Placeholder for SIAR internal reports and yield data (if available).

Note: Full citation formatting will be applied once references are finalized.

9. Appendices

• Appendix A — Agro-Ecological Zone (AEZ) Classification Table
• Appendix B — Full Monthly Rainfall and Temperature Statistics (1984–2025)
• Appendix C — GIS Maps
• Appendix D — Code Snippets
• Appendix E — Figures and Tables

List of Abbreviations