The Tuul River Basin is the most important socioeconomic and political base area of Mongolia. Therefore, studying the interrelationships between changes in the ecohydrological processes of this basin and its land cover is of great importance for maintaining sustainability and the environment. This study investigated the annual average air temperature, total annual precipitation, and river discharge variability, and land cover changes at selected stations of the basin by using the hydrometeorological analysis, satellite analysis, and land cover determination statistical analysis. During the study period, the average annual air temperature rose from −1.5 °C to +0.3 °C (1.8 °C 361 °C). The average annual precipitation exhibits relatively low change during this period. River discharge varied during the study period. A significant decreasing trend in river discharge was observed at the Terelj (φ = −2.72) and Ulaanbaatar (φ = −5.63) stations, whereas the other stations, Altanbulag, Lun, and Orkhontuul, showed a significant increasing trend. During the study period, changes in land cover were directly related to main hydrometeorological parameters. Between 2000 and 2020, the amount of grassland decreased by 319.67 km², while the area of water bodies increased by 28.36 km². In the study area, mainly water bodies and sensitive areas of the land cover types were changed due to changes in precipitation. Studies in the arid and semiarid regions of Central Asia show that changes of ecohydrological processes have a significant impact on land cover changes.

The Great Lakes Depression region basin is among the most sensitive regions to vegetation change due to climate change. This study estimated spatial-temporal changes and relationships in hydro-climate and vegetation dynamics in the basin. Studying the spatial-temporal variation between vegetation dynamics and hydro-climate in this basin is essential for assessing climate change and sustainability. This research involved an examination of the mean yearly air temperature, overall annual rainfall, fluctuations in river discharge, vegetation cover, and alterations in vegetation types within the selected basin stations. This was accomplished through the utilization of hydro-meteorological analysis, satellite assessment, land cover determination, and statistical analysis. Over the course of the study, it was observed that the average annual air temperature increased at all stations (with a positive change of Z = +1.16). The amount of precipitation decreased (Z = −0.79), especially from 2000 to 2014, and its statistical significance decreased. During the study period, average river discharge significantly decreased (Z = −3.51). Due to these combined factors, the lake’s water level also decreased (Z = −2.03). Vegetation cover change varied in high mountains, near river and lake water surfaces, and in arid regions. Changes in air temperature and precipitation in the current year determine vegetation cover. Because of the large amount of precipitation in the summer months from 2000 to 2010 and 2020, the growth of vegetation cover during that period was relatively good. This study was conducted in arid and semi-arid regions of Central Asia and demonstrates the impact of climate change on changes in vegetation cover.

This study used the Innovative trend analysis method, Mann-Kendall, and Sen’s slope estimator test to investigate the mean annual precipitation, annual mean air temperature, and river discharge at selected stations of the sub-basin. The results showed that the trend of annual precipitation trend was significantly increased in Nizhneangarsk station (ф = 0.88 and Z = –0.64) and Bolshoe Goloustnoe (ф = 0.24 and Z = 1.14*) whereas, the other stations showed a decreasing trend. The most decreasing trend was observed in the Ust Barguzin station (ф = –0.68, Z = –2.38**, and β = –0.95). The average air temperature has increased by 1.7°C from 1970 to 2019. All stations showed an increasing trend of annual air temperature during the study period. The most increasing condition was observed in the Ulan Ude station (ф = 9.20***, Z = 7.78***, and β = 0.04). The river discharge showed an increasing trend in Utulik River, Upper Angara River, and Barguzin rivers. The most decreasing is in the Selenga river gauge station (ф = –2.25**, Z = –2.16**, and β = –2.96**). The warming rates in the Selenga river sub-basin of the study area were higher than those in the other four sub-basins and the global climate change more affects the semi-arid region.

Due to the intensification of climate change around the world, the incidence of natural disasters is increasing year by year, and monitoring, forecasting, and detecting evolution using satellite imaging technology are important methods for remote sensing. This study aimed to monitor the occurrence of fire disasters using Sentinel-2 satellite imaging technology to determine the burned-severity area via classification and to study the recovery process to observe extraordinary natural phenomena. The study area that was sampled was in the southeastern part of Mongolia, where most wildfires occur each year, near the Shiliin Bogd Mountain in the natural steppe zone and in the Bayan-Uul sub-province in the forest-steppe natural zone. The normalized burn ratio (NBR) method was used to map the area of the fire site and determine the classification of the burned area. The Normalized Difference Vegetation Index (NDVI) was used to determine the recovery process in a timely series in the summer from April to October. The results of the burn severity were demonstrated in the distribution maps from the satellite images, where it can be seen that the total burned area of the steppe natural zone was 1164.27 km², of which 757.34 km² (65.00 percent) was classified as low, 404.57 km² (34.70 percent) was moderate-low, and the remaining 2.36 km² (0.30 percent) was moderate-high, and the total burned area of the forest-steppe natural zone was 588.35 km², of which 158.75 km² (26.98 percent) was classified as low, 297.75 km² (50.61 percent) was moderate-low, 131.25 km² (22.31 percent) was moderate-high, and the remaining 0.60 km² (0.10 percent) was high. Finally, we believe that this research is most helpful for emergency workers, researchers, and environmental specialists.

Wildfire is a natural disaster that harms human and animal habitats and the socio-economy. Remote sensing techniques are commonly used in the research of natural disasters, natural resources and monitoring. Timely and accurate estimation of the location of forest fires is particularly important for post-fire management and decision-making. Sentinel-2 satellite images of the European Space Agency ‘ESA’ were used to estimate the area affected by forest fires at Bayan-Uul and Bayandun soums in Dornod province, and classified the burn severity levels and comparison with other influencing factors in this study.  The normalized burn ratio ‘NBR' and indices on pre-fire and post-fire were calculated.  The total burned area was calculated as 58,131.6 ha, and low, moderate-low, moderate-high, and high burn severity levels cover 15,423.7 ha (26.3%), 29,529.4 ha (50.4%), 13,160.2 ha (22.5%), and 18.3 ha (0.03%), respectively. The 87.6% of the burned area is situated in Mongolian territory, while the remaining area (12.4%) belongs to the Russian Federation. Comparing 10 natural and geographical factors that can influence the burn severity and calculating the correlation coefficients by Pearson.  Four of them related a positive lower, and six of them related negative lower. The weak relationships of Normalized Difference Vegetation Index ‘NDVI’, elevation were 0.4 and 0.23. However, the precipitation correlation was -0.22 (negative weak). The distribution of wildfire is strongly influenced by the wind, and the correlation coefficient demonstrates a negative correlation with no effect on combustion. The conditions of socio-economic and ecological disastrous consequences such as loss of plant species and resources, changes in plant structure, depletion of pasture resources, extinction of rare animals and plants, reduction of forest resources, and large-scale air pollution resulting in the loss of human and animal in post-fire. Therefore, this research is important to due for studying the burning, distribution and, coverage area of the fire, and create conditions for the prevention of future risks.