Changes in the frequency or intensity of rainfall due to climate always affect the conservation of soil resources, which leads to land degradation. The importance of assessing past and future climate differences plays an important role in future planning in relation to climate change. The spatiotemporal variability of erosivity depending on precipitation using the rainfall erosivity (R) of Universal Soil Loss Equation under the global circulation model (GCM) scenarios in the Chirchik–Akhangaran Basin (CHAB), which is in the northeastern part of the Republic of Uzbekistan, was statistically downscaled by using the delta method in Representative Concentration Pathways (RCPs) 4.5 and 8.5 during the periods of the 2030s, 2050s and 2070s. The (R) was used to determine the erosivity of precipitation, and the Revised Universal Soil Loss Equation (RUSLE) itself determined the effects of changes in erosivity. Ten weather station observational data points for the period from 1990 to 2016 were used to validate the global circulation models (GCMs) and erosion model. The assessment results showed an increase in precipitation from the baseline by an average of 11.8%, 14.1% and 16.3% for all models by 2030, 2050 and 2070, respectively, while at the same time, soil loss increased in parallel with precipitation by 17.1%, 20.5 % and 23.3%, respectively, in certain scenarios. The highest rainfall was observed for the models ACCESS1–3 and CanESM2 on both RCPs and periods, while more intense rainfall was the main reason for the increase in the spatial and temporal erosion activity of the rainfall-runoff. This study is a useful reference for improving soil conservation, preventing water erosion and ensuring the future sustainability of agricultural products, as well as improving the operational management and planning of agriculture.

The expansion of urban areas due to population increase and economic expansion creates demand and depletes natural resources, thereby causing land use changes in the main cities. This study focuses on land cover datasets to characterize impervious surface (urban area) expansion in select cities from 1993 to 2017, using supervised classification maximum likelihood techniques and by quantifying impervious surfaces. The results indicate an increasing trend in the impervious surface area by 35% in Bishkek, 75% in Osh, and 15% in Jalal-Abad. The overall accuracy (OA) for the image classification of two different datasets for the three cities was between 82% and 93%, and the kappa coefficients (KCs) were approximately 77% and 91%. The Landsat images with other supplementary data showed positive urban growth in all of the cities. The GDP, industrial growth, and urban population growth were driving factors of impervious surface sprawl in these cities from 1993 to 2017.Landscape Expansion Index (LEI) results also provided good evidence for the change of impervious surfaces during the study period. The results emphasize the idea of applying future planning and sustainable urban development procedures for sustainable use of natural resources and their management, which will increase life quality in urban areas and environments.

Masofadan zondlash ma’lumotlari asosida o‘simlik qoplamini baholashda kengqo‘llaniladigan NDVI indeksi vaevapotranspiratsiya (ET)ko‘rsatkichlari o‘rtasidagi o‘zaro bog‘liqlik,o‘simliklarning fiziologiyasi, xlorofill miqdori, biomassa va stress darajasini baholashda samaraliindikator hisoblanib, ET tuproq va o‘simliklar orqali suv sarfini aks ettiradi. Tadqiqotda Google EarthEngine (GEE) platformasi yordamida Qashqadaryo viloyati uchun 2016-2025 yillardagi NDVI va ETko‘rsatkichlarining zamon va makon (fazo-vaqt) dinamikasi tahlil qilindi. Olingan natijalar asosidamazkur ko‘rsatkichlar o‘rtasidagi korrelyatsion bog‘liqlik baholandi hamda ularning qo‘rg‘oqchiliqlim sharoitidagi o‘ziga xos xususiyatlari aniqlandi. Tadqiqot natijalari mintaqada suv resurslariniboshqarish va qishloq xo‘jaligi samaradorligini oshirish uchun ilmiy asos yaratadi.