Based on the quantitative assessment methodology, the study examined the socio-economic impact of tourism in the region. The study proposed and tested on the example of the Issyk-Kul region, as it is the most visited region of Kyrgyzstan. Accordingly, economic and social efficiency was estimated by the integral indicators formed at the use of the weight coefficients calculated on the statistical data, and the forecast for tourism development in the region. The study showed that the impact of tourism on economic and social growth in the Issyk-Kul region is positive. Tourism in the region as a whole supports the growth of the economy, and the economic sphere of tourism has a strong impact on the social. According to forecasts, tourism will have a stable growth trend. Unlike previous studies, this study promotes a new understanding of the socio-economic impacts of tourism in the region.

The article presents a methodical approach based on an integrated assessment of the social and economic impacts of tourism for East Kazakhstan Region. The assessment was done using indicators such as the number of tourists, accommodation units, tourism facilities’ billing, and other statistical data for the period of 2009–2018. Integrated assessment performed using weighted sums of considered parameters and ordinary least squares linear regression method is applied for effectiveness prediction. Applied approaches of arithmetic (calculated) and multivariate regression modeling of the integral tourism efficiency demonstrated the same results, which mean the approach can be transferred and applied for other regions of Kazakhstan. Growing trends in tourism efficiency are derived and conclusions made on their importance for regional development. The economic and social impacts of tourism in East Kazakhstan Region increased significantly during the period from 2003 to 2018.

Endorheic lakes are sensitive indicators of climate variability and water-management pressure, yet their response in data-scarce Central Asian basins remains poorly quantified. This study examines long-term climate trends (1981–2020) and satellite-altimetry-based water-level dynamics (2002–2026) of the Alakol–Sasykkol lake system in eastern Kazakhstan. Meteorological data from five stations were analyzed using the Mann–Kendall test, Sen’s slope estimator, and the Pettitt test. Significant warming of 0.025–0.034 °C year⁻¹ was found at four of five stations, while precipitation trends were spatially heterogeneous and potential evapotranspiration increased significantly only at Zhalanashkol. A catchment moisture deficit index ($\Delta =P-{ET}_0$) was derived. For Lake Sasykkol, the strongest lagged relationship was between $\Delta (t-1)$ and lake volume $V\left(t\right)$ ($r=0.602$, nominal $p=0.008$). This relationship was stable in bootstrap, permutation, and autoregressive checks, but it was not significant after correction for multiple comparisons and is therefore presented as an exploratory working hypothesis. Satellite altimetry for 2016–2026 showed that Lake Alakol declined at −14.07 cm year⁻¹ faster than Lake Sasykkol (−3.75 cm year⁻¹). Because both lakes experience similar climatic forcing, this difference suggests a probable additional anthropogenic contribution to Alakol’s decline, most plausibly irrigation water withdrawal, although quantitative attribution is not possible with the available data. DAHITI altimetry for Alakol was compared with in situ gauge records ($r=0.997, n=9, p<0.001);$ this supports the use of the product but does not conclusively validate it due to the small sampling number. The results highlight the need for integrated monitoring of tributary inflow, irrigation withdrawals, and groundwater to separate climatic and human drivers. The paper describes an integrated system for water resource monitoring based on station data, satellite data, and trend estimation under conditions of uncertainty. Results are compared with available measurements to guide sustainable management of the water resources. A summary of the main problems that need to be resolved is provided—inflow, groundwater level, water consumption, variations in lake levels—in a terminal sensitive basin subject to climate change. It is a valuable insight for providing knowledge to support the implementation of SDG 6, 13, and 15—Water Resource Management, Climate Resilience, and Wetland Protection.