Designing performance assessment systems for climate-adaptive agricultural extension initiatives in drought-prone areas

Introduction

Climate-smart agriculture extension programs are expanding rapidly across drought-prone regions, but the systems meant to track their performance have not kept pace [1] . Without functional performance assessment frameworks, extension agencies struggle to determine which CSA practices are actually reaching farmers, whether adoption rates match program targets, and how climate variability affects intervention outcomes [2] . The result is a growing disconnect between program investment and demonstrable results. Existing M&E approaches for agricultural extension were largely designed for conventional programs and do not adequately capture the multi-dimensional nature of CSA outcomes -which span productivity, adaptation, and mitigation goals simultaneously [3] . Semi-arid regions present additional challenges: rainfall variability makes year-to-year comparisons difficult, farmer populations are often dispersed, and program impacts may take several seasons to materialize [4,5] . This research addressed these gaps by developing and fieldtesting an integrated M&E framework tailored to CSA extension programs in drought-prone settings. Cambodia's drought-prone provinces provided the research context, where multiple CSA extension programs were operating with varying levels of monitoring capacity [6,7] .

Material and Methods

Research Area

The research was conducted across four drought-prone provinces in Cambodia: Battambang, Banteay Meanchey, Siem Reap, and Kampong Thom. These provinces fall within the dry zone receiving 1,000-1,400 mm annual rainfall concentrated in the May-November wet season. Mean temperatures ranged from 24.3°C to 33.8°C during the research period (April 2021 to June 2022). The 2021 wet season brought below-average rainfall in Battambang and Banteay Meanchey (deficit of 18-22%), creating conditions that tested M&E responsiveness.

Material

All 48 CSA extension program units operating in the four provinces were included through a census approach. Additionally, 36 program managers were purposively selected for in-depth interviews. Multiple regression identified which framework components best predicted program effectiveness. Qualitative data from interviews were analyzed thematically. A composite program outcome index was constructed from adoption rates, yield changes, and farmer satisfaction scores [8] . Only 16.7% of programs scored above 60% on impact analysis. The gap index measuring the distance between current and target performance was largest for impact analysis (0.69) and smallest for output assessment (0.39). Programs with M&E scores above 70% consistently achieved outcome indices above 60%, while those below 40% showed highly variable and generally weaker outcomes. Process monitoring was the strongest predictor (Beta = 0.34), followed by outcome evaluation (Beta = 0.28).

Results

Output assessment approached significance (p = 0.052), while impact analysis did not reach significance independently. www.extensionjournal.com

Discussion

The finding that process monitoring was the strongest predictor of program effectiveness aligns with Thornton et al. [9] who argued that consistent activity tracking enables early course corrections in CSA programs. The weak independent contribution of impact analysis likely reflects its longer time horizon most CSA impacts in drought-prone areas take 2-3 seasons to materialize, exceeding the typical annual reporting cycle [10] . The strong correlation (r = 0.73) between M&E implementation and program outcomes is consistent with evidence from Lamanna et al. [11] that structured accountability mechanisms improve extension performance.

The gap analysis revealed that most programs had basic output tracking but lacked the capacity for outcome-level assessment a pattern also documented by Rosenstock et al. [12] in East African CSA programs. The feedback loop component was identified by program managers as the most valuable but least implemented element [13] .

Conclusion

This research presents an integrated M&E framework for CSA extension programs that addresses the specific challenges of drought-prone settings. Process monitoring and outcome evaluation were the strongest drivers of program effectiveness, while impact analysis capacity remained the weakest area across programs. The framework's feedback loop mechanism provides a practical pathway for adaptive management. Extension agencies should prioritize building process monitoring systems as the foundation and progressively add outcome and impact components as institutional capacity grows [14] .

References

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