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Article

Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation

by
Asset Yegizbayeva
1,*,
Nurgul Aitekeyeva
1,
Kristina Konstantinova
1,*,
Nurlan Bekmukhamedov
1,
Nurdaulet Zhumabay
1,2 and
Nurlan Balgabayev
3
1
National Center of Space Research and Technology, No. 15 Shevchenko, Almaty 050010, Kazakhstan
2
Department of Geoinformatics and Cartography, Faculty of Geography and Environmental Sciences, Al-Farabi Kazakh National University, No.71 Al-Farabi Avenue, Almaty 050040, Kazakhstan
3
Kazakh Scientific Research Institute of Water Economy, No. 12 Koigeldy Str., Taraz 080003, Kazakhstan
*
Authors to whom correspondence should be addressed.
Sustainability 2025, 17(22), 10131; https://doi.org/10.3390/su172210131
Submission received: 24 September 2025 / Revised: 5 November 2025 / Accepted: 7 November 2025 / Published: 12 November 2025
(This article belongs to the Section Sustainable Agriculture)
Browse Figures
Versions Notes

Abstract

Land is a limited yet vital resource, which is fundamental for food security and national stability. Ensuring its effective use requires modern tools to support informed decision making. This study evaluates land suitability for irrigation in the Kyzylorda region of Kazakhstan, with the objective of identifying areas appropriate for crop expansion. A multidimensional approach was employed, integrating soil properties, topography, proximity to water sources, and existing land use patterns, with suitability classes defined according to the Food and Agriculture Organization’s framework. The Analytic Hierarchy Process, based on pair-wise comparisons and Saaty’s scale, was used to assign weights to each factor. The findings reveal that 30% of highly suitable land and 80% of suitable land remain uncultivated. Conversely, 10% of the current cropland is located in marginally suitable area—likely a result of historical land use decisions or the limited availability of optimal land. This research responds to the specific challenges of arid climates and water scarcity by providing a decision-support tool that promotes sustainable land use, strengthens food security, and encourages responsible land management.

1. Introduction

1.1. Brief Literature Review

Remote sensing integrated with Geographic Information Systems (GIS) is seeing growing use in modern agricultural management and planning [1], while GIS has become an indispensable tool for assessing land use and irrigation suitability. This geospatial capability enables researchers and planners to evaluate the potential of land for irrigation and agricultural development with increased precision. The practical value of GIS has been demonstrated in multiple studies, where strong alignment was found between GIS-based suitability maps and existing irrigation practices [2].
When properly applied, geospatial tools can help identify and prioritize large areas suitable for development. For example, a GIS-based weighted overlay analysis conducted in an Ethiopian watershed revealed that the majority of the area was classified as moderately to highly suitable for irrigation [3,4].
In addition to general land assessment, software applications like ALES-arid enhance GIS data analysis by enabling evaluation of land suitability for specific crops. A study from Egypt [5] showed that the assessed area was most suitable for crops such as date palm, alfalfa, and tomato, although factors like soil salinity and poor drainage presented significant constraints. This highlighted the need for land reclamation efforts, such as improving drainage and reducing salinity, to maximize agricultural productivity.
GIS-based evaluation also supports more informed decision making in irrigation planning. A study from Ghana [6] emphasized that farmer-led irrigation systems often operate informally, with little institutional support and limited data. The study demonstrated that, while biophysical variables (e.g., groundwater availability, slope, soil characteristics) are critical, socio-economic factors such as proximity to roads, travel time to markets, and population density play an equally important role in determining land suitability. This underscores the importance of integrating infrastructure and market access into irrigation development strategies.
Recent literature has shown that remote sensing and GIS technologies, combined with multi-criteria analytical approaches such as the Analytic Hierarchy Process (AHP) and FAO land evaluation frameworks, offer powerful tools for assessing land suitability for irrigation [2,7,8,9]. These methods integrate diverse datasets—including soil characteristics, climatic variables, topography, and infrastructure—to generate spatially explicit assessments that support efficient irrigation planning and sustainable water resource management. The resulting suitability maps identify areas with high potential for irrigation development, providing valuable guidance for the expansion of agricultural activities. Furthermore, land suitability evaluations serve as critical inputs for informed water allocation policies and management practices, contributing to the optimization of land and water use in agricultural systems.
Land suitability assessment for irrigation is increasingly vital in Central Asia, where climate change, water scarcity, and land degradation pose serious threats to food security and agricultural sustainability. Recent studies in the region highlight the growing role of GIS and remote sensing in optimizing land use and informing agricultural planning. Extensive land degradation due to the unsustainable use of irrigation was revealed in the Kazaly region of the Syrdarya basin, Kazakhstan [10]. Crop placement scenarios developed using QGIS 3.8 and ArcPy (free open source) helped reduce resource use and increase crop yields in the Chimbay district of The Republic of Karakalpakstan, Uzbekistan demonstrating the potential of spatial decision support systems for improving productivity under ecological stress [11]. A land suitability model identified optimal zones for cotton cultivation in southern Uzbekistan, reinforcing its relevance for precision agriculture and crop planning by high validation accuracy [12].
Irrigation suitability and efficient water use remain central issues in the sustainable development of arid and semi-arid regions of Kazakhstan. A growing body of research has sought to identify optimal pathways for improving irrigation practices in Kazakhstan, conserving scarce water resources, and strengthening agricultural resilience. Previous studies have approached this problem from multiple perspectives, reflecting the complexity of hydrogeological, ecological, and socio-economic factors influencing irrigation systems in the region. Abraliyev et al. analyzed the optimization of irrigated land use through system analysis and resource management, emphasizing improvements in policy, infrastructure, and regional water governance [13]. Murtazin et al. evaluated the quality and potential of groundwater for irrigation in Western Kazakhstan and proposed practical schemes for its efficient and sustainable use [14]. Zhang et al. examined the surface water chemistry of the Syrdarya river and assessed suitability for irrigation based on sodium content, salinity, and total dissolved solids, highlighting the effects of water quality on soil conditions [15]. While these studies provided important insights into institutional, hydrogeological, and hydrochemical aspects of irrigation suitability, they were based on localized or site-specific analyses. The present study differs by applying remote sensing and geospatial modeling to identify and map areas most suitable for irrigation expansion, providing a spatially comprehensive and data-driven approach for the efficient and sustainable use of water resources in Kazakhstan’s arid and semi-arid regions.
Land suitability assessment plays a pivotal role in the optimization of agricultural land utilization, particularly in regions grappling with water scarcity and arid environmental conditions [16]. This study is dedicated to the systematic evaluation and categorization of designated land areas, with the primary objective of determining their appropriateness for crop expansion. Drawing from the framework established by the Food and Agriculture Organization (FAO) [17], land suitability analysis holds substantial significance in the sphere of regional development, as it provides indispensable insights into the diverse constraints and potential opportunities associated with land utilization. The theoretical significance of this study lies in demonstrating the applicability of established spatial assessment methods for evaluating irrigation suitability under the specific environmental conditions of Kazakhstan’s arid regions. The practical significance lies in the application of these methods to the Kyzylorda region, supporting evidence-based decision making for agricultural development and sustainable water management.

1.2. Study Area

Kazakhstan aspiring towards self-sufficiency in staple crops like wheat, barley, maize, and sorghum [18]. Therefore, the adoption of efficient land evaluation techniques aligned with government priorities is of paramount importance [16]. The nation’s ambitious agricultural goals necessitate a detailed assessment of land suitability factors, particularly in arid and semi-arid landscapes such as Southern Kazakhstan, where limited water resources and unpredictable weather patterns underscore the critical role of effective irrigation systems [19].
The study area encompasses the Kyzylorda region, situated in Southern Kazakhstan (Figure 1). This region is characterized by its semi-arid climatic zone, featuring hot summers and cold winters [20]. Its geographic location presents notable challenges related to water resources, with the Syrdarya river serving as the primary source of irrigation [21]. Despite the constraints imposed by limited water availability, the Kyzylorda region has developed a resilient irrigation infrastructure that effectively supports agricultural activities across an extensive land area exceeding one million hectares [22]. The study area falls within the southern part of Kazakhstan, positioned within the vast Central Asian region. It shares borders with the Turkistan region to the east and the Aktobe region to the north. Additionally, it shares its southern border with the neighboring country Uzbekistan. Covering an expansive area of approximately 226,000 square kilometers, the Kyzylorda region represents a significant portion of Kazakhstan’s territory, accounting for 8.3% of the country’s landmass [23]. The topography of the study area is predominantly characterized by the Turan lowland, with elevations ranging from 50 to 200 m [24]. This region exhibits degraded dryland landscapes and is largely covered by extensive sand deposits. It is administratively divided into multiple districts and cities, with Kyzylorda serving as the regional capital.
The diverse geography of the study area includes segments of the vast Eurasian Steppe and the deserts typical of Central Asia. To the west, the region is partially bordered by the Aral Sea, although the sea has considerably diminished in size due to environmental factors [25]. The Syrdarya river flows through the northern part of the region, playing a crucial role in its irrigation system.
The climate in the study area follows a continental desert pattern, featuring hot summers with temperatures often exceeding 40 °C and cold winters with temperatures dropping below freezing. Precipitation is limited, averaging between 100 and 190 mm annually, with uneven distribution across seasons. Strong northeast winds are a common meteorological feature, contributing to dust storms, particularly in the summer months [26].
The economy of the Kyzylorda region primarily relies on agriculture, with the cultivation of cereals, legumes and fodder crops being significant [27]. The historical importance of fishing, attributed to the presence of the Aral Sea, has declined due to the sea’s shrinking size, leading to adverse effects on the fishing industry [22]. Addressing environmental and agricultural challenges of the Aral Sea requires qualified scientific and technical personnel; however, the region faces a shortage of experts [28], which is further exacerbated by the inefficiency of public policy on training and retaining scientific personnel [29]. These factors limit the region’s capacity to implement sustainable land and water management solutions.
The environmental challenges in the study area are substantial, primarily stemming from the shrinking of the Aral Sea, resulting in the formation of the Aral Sea crisis. Desertification and water scarcity remain ongoing issues [30], presenting complex challenges for sustainable land and water resource management.
The study area within the Kyzylorda region of Kazakhstan offers a scientifically significant landscape characterized by its unique geography, climatic conditions, water resource challenges, and environmental complexities. It serves as an intriguing and relevant subject for geographical research and exploration, particularly in the context of sustainable resource management and climate adaptation [31]. This study endeavors to provide valuable insights into land suitability for irrigation development, catering to the specific needs and priorities of Kazakhstan’s agricultural sector. These insights serve as a robust framework for the optimization of agricultural land use in regions characterized by water scarcity and arid conditions, fostering sustainable agricultural practices and advancing food security initiatives.

2. Materials and Methods

A comprehensive evaluation of land suitability for irrigation is imperative, accompanied by the identification of areas where strategic improvements in irrigation infrastructure can be made. To address these pressing concerns, this study employs a multidimensional approach, integrating diverse land suitability factors such as soil characteristics, topographic attributes, proximity to water sources, and land use patterns [32].

2.1. Land Suitability Classification System

The land suitability classes devised by the FAO in their publications from 1976 and 2007 delineate the degrees of suitability of specific land types for precise agricultural purposes [17]. These classes are determined through suitability ratings that span from highly suitable to unsuitable, with assessments based on the compatibility of land characteristics with various crop types. Following FAO guidelines, land suitability maps are broadly categorized into two primary groups: “suitable” (S) and “unsuitable” (N), with group S further subdivided into three classes (“highly suitable”—S1, “suitable”—S2, “moderately suitable”—S3, “marginally suitable”—S4). The overarching conceptual methodology employed in the study is described in Table 1 furnishes details regarding the assigned weightings for each contributing parameter and their respective categories.

2.2. Land Suitability Factors for Irrigation Development

Land suitability assessment for irrigation involves evaluating various factors that in-fluence the feasibility and effectiveness of irrigation systems. These factors include topography, soil properties, water availability, and land use and land cover (LULC), which collectively determine the suitability of land for irrigation infrastructure and practices. Identifying and analyzing these factors helps optimize water use, enhance agricultural productivity, and minimize environmental impacts, which is especially crucial in arid and semi-arid regions where water resources are limited.
LULC: The analysis utilized the European Space Agency (ESA) WorldCover dataset (version 2.0, year 2024), derived from Sentinel-1 and Sentinel-2 imagery with a spatial resolution of 10 m [33]. The dataset was reprojected to WGS 84/UTM Zone 42N, clipped to the Kyzylorda Region boundary, and resampled to match the DEM resolution before analysis. Land use categories were then classified into five distinct suitability groups, denoted as S1, S2, S3, S4, and N (see Table 1).
Topographic elements: The topographic attributes, specifically the gradient of the study area, were utilized for the assessment of land suitability. The slope exerts a direct influence on various facets, encompassing irrigation methodologies, susceptibility to erosion, land development, soil cultivation practices, utilization of agricultural machinery, design of on-farm irrigation systems, adaptability of plant species, and drainage requisites [34]. To ascertain the gradient of the region, the Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM) with a 30 m spatial resolution [2], was employed, and it was categorized into five groups based on the classification schemes outlined by FAO (1996) and 0–8 percent corresponds to flat terrain, 8–15 percent signifies sloping terrain, 15–25 percent designates slightly steep terrain, 25–40 percent represents steep terrain, and greater than 40 percent characterizes very steep terrain.
Soil: Soil is an important factor in determining land suitability for sustained irrigation, as its texture, drainage, depth, and type influence productive capacity, crop growth, water infiltration, and overall production and development costs.” [35]. The evaluation of the soil’s appropriateness for irrigation was undertaken using the updated soil map of Kazakhstan from the year 2010 [36]. Soil characteristics, particularly the soil type, were employed to determine whether the soil fulfilled the prerequisites for suitability for irrigation.
Distance from the water source: In the scientific evaluation of land suitability for irrigation, proximity to a water source, as emphasized by Paul et al. [37], emerges as a critical determinant. The distance from the water source was quantified and subsequently classified into five distinct categories through the application of the Euclidean distance method within ArcGIS 10.8 [38]: close proximity (0–500 m), distances spanning from 501 up to 1000 m, from 1001 up to 1500 m, from 1501 up to 2000 m, and exceeding 2001 m.

2.3. Assigning Weights Through the Analytic Hierarchy Process (AHP)

The AHP, a well-established method for evaluating multiple criteria, is harnessed to systematically assign weights to each contributing factor and ensure consistency in decision making [39]. In this study, the AHP was applied using Saaty’s 1–9 scale [40] to compare the relative importance of factors affecting land suitability for irrigation. Each factor was evaluated against the others based on expert judgment, forming a structured pairwise comparison matrix.
The resulting matrix was normalized to calculate the weights of each factor, reflecting their contribution to the overall assessment. This systematic approach ensures objectivity and consistency when evaluating multiple criteria. In the context of spatial planning decisions in the present study, AHP facilitated the construction of a comparison matrix for parameters influencing land suitability for agricultural purposes and determined the parameter weights through a consistency analysis using the Random Consistency Index (RI) and the Consistency Ratio (CR) [2].
The AHP implementation followed these steps:
  • Identification of criteria: The main factors affecting irrigation suitability were defined—slope, soil texture, distance to water sources, and LULC.
  • Pairwise comparison: Each criterion was compared with every other criterion using Saaty’s 1–9 scale to form the pairwise comparison matrix (refer to Table 2).
  • Expert evaluation: Five local experts specializing in irrigation management, soil science, and GIS provided judgments on the relative importance of each factor. The geometric mean of their matrices was used to construct the final matrix.
  • Normalization and weight derivation: Each matrix element was divided by its column sum, and the average of each row was computed to obtain the relative weight of each criterion.
  • Consistency check: The Consistency Index (CI) and CR were calculated using the maximum eigenvalue (λ_max) and the RI. A CR < 0.1 indicated an acceptable level of consistency.
  • Integration of weights: The validated weights were incorporated into the GIS-based multi-criteria evaluation to generate the final land-suitability map.
The overall consistency ratio (CR = 0.06) confirmed the reliability of expert evaluations.

3. Results

3.1. Land Suitability Factors and Weight Assignment in AHP

Factors selected for land suitability assessment for irrigation development are primarily determined by the local region’s topography, soil characteristics, distance from water source, and LULC map (refer to Figure 2).
The prevalent land use categories identified within the research area include arable lands, pasturelands, shrublands, bare soil, wetlands, water bodies, and urban areas (refer to Figure 2a).
Based on weights assigned using Saaty’s scale [40], the most influential ones have been identified. In the context of this study, the distance from water sources is the key determinant due to the region’s aridity (refer to Figure 2d), with an influence of 62% (refer to Table 3).
Soil type is the second most important factor (refer to Figure 2c), contributing 21%, followed by LULC, with an influence of 11%. While slope is often considered a critical factor in land suitability assessments, it is less significant in this case due to the region’s relatively flat terrain and low variability (refer to Figure 2b), with an influence of 6%. The resulting weight values are presented in Table 3. Following the creation of the pairwise comparison matrix, calculations confirmed that CR is less than 0.1, ensuring the reliability of the comparisons made.

3.2. Land Suitability Results for Irrigation Development

By utilizing geospatial data classified by suitability and integrating the AHP, the analysis categorizes land into distinct suitability classes (Table 4 and Figure 3).
Within the study region highly suitable areas (S1) account for 5% of the total land area (11,300 km2) (refer to Figure 3). These zones are primarily concentrated along the Syrdarya river and its tributaries, where access to irrigation water is reliable, and topographic conditions are highly favorable. Proximity to perennial water sources and fertile alluvial soils make these territories exceptionally advantageous for intensive agricultural production. However, around 30% of the S1 lands remain uncultivated, mainly distributed across the Karmakshy, Shieli, and Zhalagash districts. The limited utilization of these highly suitable areas is largely attributed to insufficient irrigation infrastructure, poor transportation accessibility, and the high costs associated with developing new irrigation systems. Suitable areas (S2) cover 10.6% of the total land area (23,956 km2). These areas present minor, manageable constraints and generally favorable farming conditions. Moderately suitable areas (S3) comprise 36.1% of the land (81,586 km2). While these areas exhibit agricultural potential, overcoming specific limitations requires strategic planning and efficient resource management. Marginally suitable areas (S4) represent 43.9% of the total land area (99,214 km2). Severe constraints hinder traditional farming practices, but innovative methods could unlock their latent potential for limited agricultural use. Not suitable areas (N) constitute 4.4% of the total land (9944 km2). These regions are unsuitable for agriculture due to poor soil quality, challenging topography, or lack of water resources.

4. Discussion

The current study on identifying suitable regions for irrigation revealed that 70% of the existing cropland is located within areas classified as highly suitable, while 20% falls within areas classified as suitable. Notably, 30% of the highly suitable land and 80% of the suitable land remain uncultivated. Additionally, 10% of the current cropland is situated in marginally suitable zones, likely due to historical land use patterns or the limited availability of more suitable land locally. These findings highlight the potential for optimizing land use by utilizing the available suitable regions for crop cultivation.
However, a formal statistical correlation analysis between the existing cultivated land and the suitability classes was not performed, as a portion of the agricultural land was deliberately excluded from the study area. This decision was made to focus on identifying new potential zones for future irrigation expansion rather than analyzing already developed areas. Therefore, the study emphasizes the delineation of new prospective irrigable lands rather than assessing the spatial dependence of the current cropland distribution.
The combination of the AHP and spatial analysis tools has proven effective for evaluating land suitability for irrigation, although regional characteristics strongly influence the results. For instance, the study by Abdel Rahman et al. in Egypt emphasizes soil and slope constraints under rain-fed or irrigated conditions [41], whereas our assessment of the Kyzylorda region identifies water availability as the primary determinant in arid areas. This contrast highlights how local environmental conditions shape the prioritization of factors in land suitability assessments, underscoring the importance of tailoring evaluation criteria to specific regional contexts for effective agricultural planning. As assessed in this study and corroborated by other scholars, the region holds potential for expanding cropland areas and irrigation. For instance, Zhang et al. examined cropland development potential at a regional scale in Central Asia and found that current cropland largely aligns with natural conditions, identifying over 1,008,000 km2 of potential irrigated cropland and 217,124 km2 of rain-fed cropland, mainly in Kazakhstan and Turkmenistan [42]. Our localized assessment of the Kyzylorda region also confirms substantial potential for agricultural land development, although, much of this agricultural capacity is heavily dependent on water availability. In the study region, this dependence is primarily on the Syrdarya river, which serves as the main water source. The river is mainly fed by glaciers and snowmelt, supporting irrigation and agricultural activities. Climate change, which accelerates glacier melt, may initially increase water supply, potentially enabling short-term cropland expansion. However, the ongoing reduction in Central Asian glaciers presents a critical long-term challenge [43,44,45,46]. As glacial reserves diminish, water flows will decrease, undermining the sustainability of agriculture in the region. Given this trajectory, future research should urgently focus on quantifying the impacts of climate change on long-term agricultural suitability, particularly under various water availability scenarios. Furthermore, the establishment of a joint hydrological monitoring mechanism among riparian countries would be highly valuable in addressing transboundary data gaps and fostering more coordinated and sustainable water resource management.
Effective management of irrigation and cropland expansion must be accompanied by the development of a shared understanding among key stakeholders, including agronomists, hydrologists, policymakers, local farmers, and others. Such a collective cognitive framework is critical for facilitating collaboration and enhancing decision-making processes, thereby ensuring that water management strategies are adaptive and sustainable. GIS technology facilitates informed planning and resource allocation, and its effective use requires that diverse stakeholders develop a common vision and shared mental models regarding the tasks and responsibilities involved [47]. Therefore, while the potential for cropland expansion is evident, the feasibility of this growth depends not only on the implementation of technical solutions but also on the capacity of multidisciplinary teams to operate cohesively under a unified vision [47], enabling them to address the challenges posed by declining glacial contributions and evolving hydrological regimes.
Transitioning to crops better suited to local conditions and improving land management practices are essential for sustainable agricultural productivity in arid regions. However, one of the most critical factors is selecting the right irrigation method [48]. Drip irrigation, which delivers water directly to plant roots, is particularly effective in water-scarce areas as it minimizes evaporation, runoff, and the risk of soil salinization. Other options, such as localized sprinkler systems and subsurface irrigation, may also be viable, though they can be more prone to evaporation losses and require higher installation and maintenance costs. Currently, only 12% of the Kyzylorda region is equipped with controlled irrigation systems. However, Kazakhstan plans to expand drip and sprinkler irrigation, with a goal to cover 80% of irrigated croplands by 2030 [25].
The limitations of this study include the lack of river flow data, which is crucial for understanding water availability. Water flow information plays a key role in assessing sustainability measures, particularly in regions where crop cultivation has led to significant land cover changes as in Central Asia [21,22]. Access to long-term river flow data, including maximum, minimum, and average flows, would improve the input parameters for calculations and provide a more comprehensive analysis. Furthermore, due to the transboundary nature of the river, cooperation among Central Asian countries is essential for obtaining accurate and consistent water flow data. Sharing water data across borders would enhance decision making and enable more effective management of water re-sources, adopting regional collaboration and a timely response to water-related challenges.

5. Conclusions

This study presents an assessment of land suitability for irrigation development within Kazakhstan’s critical agricultural sector. The distance from water sources is identified as the most significant factor impacting irrigation, accounting for over 50% of the overall influence. This is followed by soil type, LULC, and slope, which together contribute to less than 50% of the impact. Slope emerged as the least influential factor, primarily due to the predominance of flat terrain across much of the region, which reduces its effect on the assessment.
Suitable and unsuitable regions for crop irrigation were identified, with a clear de-lineation of areas most conducive to sustainable agricultural development. The analysis indicates significant potential for expanding land available for irrigation: over half of the region (52%), or 116,842 km2, is classified as highly suitable, suitable, or moderately suitable for irrigation. This represents a substantial opportunity for the development of irrigated agriculture. With appropriate infrastructure and investment, expanding irrigated areas could significantly enhance agricultural productivity and contribute to improved food security in the region.

Author Contributions

Conceptualization, A.Y., N.A. and K.K.; methodology, A.Y. and N.A.; software, A.Y. and N.Z.; validation, A.Y., N.B. (Nurlan Bekmukhamedov) and N.B. (Nurlan Balgabayev); formal analysis, A.Y. and N.A.; investigation, N.A. and N.Z.; resources, N.B. (Nurlan Bekmukhamedov) and N.B. (Nurlan Balgabayev); data curation, A.Y.; writing—original draft preparation, A.Y., N.A. and K.K.; writing—review and editing, K.K.; visualization, N.Z. and N.B. (Nurlan Balgabayev); supervision, N.B. (Nurlan Bekmukhamedov); project administration, K.K.; funding acquisition, N.B. (Nurlan Bekmukhamedov) and N.B. (Nurlan Balgabayev). All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Water Resources and Irrigation of the Republic of Kazakhstan under Grant No. BR23791322 for the period 2024–2026.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data used in this manuscript can be requested for research purposes from the first author sin.asset@gmail.com.

Acknowledgments

The authors used ChatGPT (GPT-5), an AI language model developed by OpenAI, to assist with language polishing and grammar correction during the manuscript preparation. The authors take full responsibility for the content and interpretation of the work.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
AHPAnalytic Hierarchy Process
CIThe Consistency Index
CRConsistency Ratio
DEMDigital Elevation Model
FAO Food and Agriculture Organization
GISGeographic Information System
LULC Land Use and Land Cover
RIRandom Consistency Indices

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Figure 1. The study area: (a) Location of Kyzylorda region within Kazakhstan; (b) enlarged view of the Kyzylorda region.
Figure 1. The study area: (a) Location of Kyzylorda region within Kazakhstan; (b) enlarged view of the Kyzylorda region.
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Figure 2. LULC map (a); slope map (b); soil type (c); distance from water (d).
Figure 2. LULC map (a); slope map (b); soil type (c); distance from water (d).
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Figure 3. Land suitability map of study region.
Figure 3. Land suitability map of study region.
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Table 1. Criteria for evaluating land suitability for surface irrigation.
Table 1. Criteria for evaluating land suitability for surface irrigation.
Primary DeterminantCriteriaSuitability Classes
S1S2S3S4N
TopographySlope, %0–22–55–88–10>10
SoilTypeSoil Types in Mountainous
Areas		SerozemBrown Desert-Steppe SoilsSandy Soils with Low DevelopmentTakyrs and Salt Marshes
Distance
from Water
Source		Euclidian distance, m0–500500–10001000–15001500–2000>2000
Land Use Land CoverClassFarmlandFarmland GrasslandBarrenShrub-covered landForest, built-up, water, wetland
Table 2. Pairwise comparison matrix.
Table 2. Pairwise comparison matrix.
FactorDistance from
Water Source		Soil TypeLULCSlope
Distance from water source1369
Soil Type1/3123
LULC1/61/212
Slope1/91/31/21
Table 3. Normalized pairwise comparison matrix and criteria weights.
Table 3. Normalized pairwise comparison matrix and criteria weights.
FactorDistance from
Water Source		Soil TypeLULCSlopeCriteria Weight
Distance from water source0.620.620.630.600.62
Soil Type0.210.210.210.200.21
LULC0.100.100.110.130.11
Slope0.070.070.050.070.06
Table 4. Land Suitability Classification and its Findings in the Study Area.
Table 4. Land Suitability Classification and its Findings in the Study Area.
Land Suitability ClassificationFindings in the Kyzylorda Region
Level of SuitabilityDescription EvaluationArea (sq.km)Percentage
Highly suitableLand without limitations80–10011,3005.0
SuitableLand with minor restrictions60–8023,95610.6
Moderately suitableModerately severe limitations on otherwise suitable land40–6081,58636.1
Marginally suitableLand with collectively severe restrictions20–4099,21443.9
Not suitableLand characterized by stringent limitations0–2099444.4
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Yegizbayeva, A.; Aitekeyeva, N.; Konstantinova, K.; Bekmukhamedov, N.; Zhumabay, N.; Balgabayev, N. Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation. Sustainability 2025, 17, 10131. https://doi.org/10.3390/su172210131

AMA Style

Yegizbayeva A, Aitekeyeva N, Konstantinova K, Bekmukhamedov N, Zhumabay N, Balgabayev N. Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation. Sustainability. 2025; 17(22):10131. https://doi.org/10.3390/su172210131

Chicago/Turabian Style

Yegizbayeva, Asset, Nurgul Aitekeyeva, Kristina Konstantinova, Nurlan Bekmukhamedov, Nurdaulet Zhumabay, and Nurlan Balgabayev. 2025. "Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation" Sustainability 17, no. 22: 10131. https://doi.org/10.3390/su172210131

APA Style

Yegizbayeva, A., Aitekeyeva, N., Konstantinova, K., Bekmukhamedov, N., Zhumabay, N., & Balgabayev, N. (2025). Geospatial Technology Utilization for Evaluating Land Suitability for Irrigation. Sustainability, 17(22), 10131. https://doi.org/10.3390/su172210131

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