**2. Materials and Methods**

*2.1. Data Collection*

#### 2.1.1. Literature Search Strategy

A literature search was conducted using Science Direct and Scopus databases. The search was limited to only research articles written in the English language and published in peer-reviewed journals between 2000 and 2021. Articles prior to 2000 were excluded as the global irrigation dataset used in this analysis is based on the nationally reported statistics from around the year 2000 (more details about this dataset are presented in Table 1). Moreover, this also reflects the broader trends in irrigation adoption globally because the percentage of reported data on irrigation use from around the world is largest from the year 2000 onwards compared to the earlier years [81]. The steps taken in the search and screening process are presented in Figure 1. First, a target set of 10 articles containing both 'true positives' and 'true negatives' was assembled from a wide range of disciplines to represent the full range of publications in this research domain and assemble a set of search keywords. Target set articles are listed in Appendix A. Different keywords such as irrigation, technology adoption, agriculture, farmer decisions, water management, and climate change adaptations were combined using Boolean operators to download relevant studies. The specific search terms used were: (("irrigation") AND ("technology" OR "adoption") AND (("reasons and constraints") OR ("attitudes") OR ("drivers") OR ("perception") OR ("barriers")) AND ("climate change adaptation" OR "climate smart agriculture" OR "climate change" OR "adaptive capacity") AND (("drought") OR ("water management practices")) AND (("farmers") OR ("farmer decisions"))).


**Table 1.** Description and sources of all the datasets used in this analysis.

**Figure 1.** Steps involved to assemble research articles for this analysis.

#### 2.1.2. Selection of Case Studies

After the literature search, the resulting dataset consisted of 438 publications. The next step was article screening to identify case studies that should be used in this metastudy. Both study titles and abstracts were checked and critically reviewed for suitability for this analysis. Articles were excluded if they did not (1) investigate the different factors/reasons affecting technology adoption within the agricultural sector, and (2) present an assessment of farmers' views or opinions. Conference proceedings, grey literature, reports, and duplicate articles were also excluded from the dataset. The initial screening reduced the number of eligible articles to 119. The second round of screening was performed using the full text of each remaining article. Articles were primarily screened to determine specifically if irrigation adoption by farmers was studied or not, irrespective of the type of irrigation system. For instance, many studies examined the adoption of several different agricultural practices together, in the form of climate change adaptation strategy, conservation agriculture, or as sustainable farming practices adopted by farmers including high-yielding crop varieties, different soil, and water management practices see, e.g., [87–89]. All the studies that did not include irrigation as one of the technologies or practices being studied were discarded. Moreover, studies that were conducted at a very large-scale and reported aggregated results (e.g., for entire U.S. mid-west region [90] or 11 African countries together [91]), were excluded to ensure comparability of results, since the goal was to examine the geographic contexts of these studies that would otherwise have been difficult to capture. Additionally, studies that investigated the benefits of irrigation adoption, assessed its impact on crop production under climate change, or estimated future adoption rates were also not considered, e.g., [92–95]. As a result, 50 case studies, which passed the inclusion and exclusion criterion were selected and used in this meta-study. A complete list of the studies included in this review is also provided in Appendix A.
