BACKGROUND AND OBJECTIVES: Accurate evaluation of aquatic ecosystem suitability is critical for sustainable environmental management, particularly in regions that prioritize aquaculture and biodiversity conservation. Although Geographic Information System–based modelling is increasingly used to classify water bodies according to morphometric and ecological parameters, experimental validation across extensive lake networks remains limited. This study merged geospatial suitability modeling with on-site evaluations to develop a validated framework for evaluating the environmental quality and aquaculture potential of inland lakes in Northern Kazakhstan.METHODS: A total of 286 lakes were evaluated using a Geographic Information System–based multi-criteria approach that incorporated surface area, water depth, pollution indicators, macrophyte cover, and algal bloom intensity to classify lakes into high, medium, and low suitability categories. Over the course of two years, thirty representative lakes, comprising ten from each category, were sampled seasonally. In six lakes identified as suitable for medium, microcosm experiments investigated the effects of nutrient enrichment and the removal of macrophytes on the water quality. Statistical analyses examined correlations between Geographic Information System–derived suitability scores and measured environmental quality indices.FINDINGS: High-suitability lakes exhibited significantly higher dissolved oxygen concentration (7.8 ± 0.9 milligrams per liter) and water transparency (1.6 ± 0.3 meters), and lower total phosphorus (0.045 ± 0.012 milligrams per liter) and total nitrogen (0.48 ± 0.11 milligrams per liter) compared with low-suitability lakes (dissolved oxygen 3.5 ± 0.7 milligrams per liter; transparency 0.6 ± 0.2 meters; total phosphorus 0.122 ± 0.029 milligrams per liter; total nitrogen 1.21 ± 0.25 milligrams per liter). Microcosm experiments revealed that nutrient enrichment and macrophyte removal increased chlorophyll-a concentration by 41 percent and reduced dissolved oxygen concentration by 25 percent, indicating the sensitivity of medium-suitability lakes to nutrient loading and vegetation loss. The suitability scores from the geographic information system were found to correlate significantly with the measured environmental indices (coefficient of determination 0.74, p-value less than 0.01), which confirms the predictive power of the spatial model. CONCLUSION: Integrating Geographic Information System–based modelling with empirical validation creates a reliable strategy for determining inland lake suitability and promoting sustainable management of freshwater resources.
Doskenova et al. (Thu,) studied this question.