Analysis of the Efficiency of Irrigation Technologies in Kermanshah Province Based on the Technology Atlas Model

Introduction

Water is the most critical input in agricultural production. In many regions worldwide, especially arid and semi-arid areas, water scarcity poses a primary challenge to achieving sustainable agricultural development. In addition to this difficulty, insufficient attention to the appropriateness and efficiency of irrigation systems—stemming from the continued use of improper technologies—has become a fundamental barrier on the path to sustainable agricultural development. An accurate understanding of the current status of each system and its associated processes is a critical first step for informed decision-making and policy formulation to optimize technology management. This principle applies equally to decisions and investments concerning equipment, human resources, and knowledge related to irrigation-focused technologies. The integration of these factors within the context of technology implementation requires precise and strategic management. Effective management depends on thorough evaluation, comprehensive knowledge, and a deep understanding of the technology’s condition and performance. Technology evaluation models are essential tools for effective technology management, enabling proper oversight of technology components and ensuring the overall success of the system (Keramatzadeh et al., 2016; Munguia et al., 2021; Xudayev et al., 2021). The current study seeks to examine and evaluate the irrigation technologies currently utilized in the agricultural sector of Kermanshah Province (Located in the west of Iran), with a specific focus on the unique role of each technological dimension.

Method

The Atlas Technology Model, leveraging its robust capabilities, was employed for this study. This research is applied in purpose and utilizes a survey-based approach for data collection. The study population consisted of three groups: farmers, experts, and trade associations (implementing companies and water-based technology design companies). Experts who were knowledgeable and experienced in the field of water and irrigation technologies, as well as two groups of designers and farmers who were recognized as competent by the regional water company (127 people). In the experts section; it included the Department of Agricultural Jihad, Regional Water Affairs of Kermanshah Province, faculty members of the Water Department of Razi University, and the Agricultural Jihad and Natural Resources Research Center. In the farmers section, the irrigated farmers of Kermanshah Province, according to different climates and geographical divisions, were the counties (Kermanshah, Kangavar, Ravansar, Islamabad Gharb, and Sarpol Zahab) with the largest area of irrigated cultivation according to the dominant cropping pattern (wheat, barley, rapeseed, corn, tomato, potato) in the 2023-2024 crop year, which were considered to be the leading farmers in terms of using irrigation technology. Therefore, the sample selection method was judgmental and in total, 90 questionnaires were completed for all three respondent groups without any statistical problems and analysis was conducted based on them (n = 90). The main data collection tool was the standard Atlas model questionnaire, which was adapted to the agricultural context. The content validity of the questionnaire was confirmed by experts and its reliability was also confirmed with the help of Cronbach's test (α = 0.78). Data analysis was then performed using Excel software, the Critical Method, and the Atlas Technology Method.

Results

The Atlas Technology Model evaluated the contribution of each technological dimension individually. The contribution of each technological dimension—Orgaware (OβO = 0.21), Technoware (Tβt = 0.20), Humanware (Hβh = 0.08), and Infoware (Iβi = 0.05)—was assessed for irrigation technologies in Kermanshah Province. Based on these contributions, the irrigation technology dimensions in Kermanshah Province are prioritized as follows: Orgaware > Technoware > Humanware > Infoware (O > T > H > I). The collective importance of the technological dimensions was assessed using the Technology Contribution Coefficient (TCC), a composite index, which yielded a value of 0.54. To compare the technological dimensions, the THIO diagram is utilized. The THIO diagram not only enables comparison of the four technological dimensions but also illustrates the gap between each dimension and the optimal level of 100% (Figure 1). The collective importance of the technological dimensions was evaluated using the Technology Contribution Coefficient (TCC), a composite index, which yielded a value of 0.54. The Technology Contribution Coefficient (TCC), a composite index reflecting the cumulative status of the four technological dimensions, indicates that the current attention and investment in irrigation technologies in Kermanshah Province have achieved only 54% of their optimal capacity. This indicates that over half of the potential capacity remains unrealized.



Figure1: THIO chart



Conclusions

The findings from the analysis conducted through the Atlas Technology method indicated a relatively positive evaluation of all factors by the respondents. However, from the respondents’ perspective, some factors have greater importance in technology advancement. Technology is not merely a technical phenomenon; it is a four-dimensional system, each component of which has been individually examined and evaluated. Analyzing only a single dimension, even a critical one like hardware (e.g., irrigation systems), results in an incomplete understanding of the technology’s status. The evaluation of the Infoware dimension reveals that the information, data, and tacit knowledge associated with the technology remain below optimal levels. This may arise from challenges such as deficiencies in information infrastructure, limited access to consistent and updated training, or inefficiencies in agricultural information systems. The information gap may stem from inadequate knowledge exchange structures among stakeholders, deficiencies in transferring knowledge to farmers, or limited communication channels. Therefore, enhancing knowledge exchange infrastructure, developing knowledge-based networks, and providing ongoing user training are critical for improving the effectiveness of technological information.