Application of Index Analysis to Evaluate the Water Quality of the Tuul River in Mongolia

A study of water pollution determinands of the Tuul River was carried out in surrounding area of Ulaanbaatar, the capital of Mongolia at 14 monitoring sites, using an extensive dataset between 1998 and 2008. An index method, developed by Ministry of Nature and Environment of Mongolia, applied for assessment and total, seven hydro-chemicals used in the index calculation. The research indicates that the Tuul River is not polluted until the Ulaanbaatar city and the contamination level spike appears when the river entering the city. The upper reaches of the river and tributaries have relatively good quality waters. Several pollution sources exist in the study area. Among them, the Central Wastewater Treatment Plant (CWTP) is a strongest point source in the downstream section of the river, recently. Pollutions at sites 7-10 are strongly dependant effluent treatment levels from the plant, and it contains a high amount of chemicals that can cause of major decrement of the water quality. This would definitely kill aquatic fauna in the stretch of the river affected. It certainly happened in 2007. The general trend of water quality gradually has been decreased in the study period. Clearly, there is a need to improve the water quality in the Tuul River in surrounding area of the Ulaanbaatar. In order to change this situation, operation enhancement of treatment plants, a water quality modeling and artificial increment of dissolved oxygen concentrations become crucial to improve the water quality significantly. Perhaps a new wastewater treatment plant is needed for Ulaanbaatar city.

Zavkhan River and Its Catchment Area Delineation Using Satellite Image

The purpose of this research is to define initial parameters of Khyargas Lake-Zavkhan River and its catchment area using satellite images. The study has been done by two datasets: 1) Shuttle Radar Topography Mission (SRTM) at a horizontal spatial resolution of 90 meters, 2) The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at a horizontal spatial resolution of 30 meters, using two different models of ArcHydro and Integrated Land and Water Information System (ILWIS) softwares. Main methods of models, that were used in this research are the Deterministic-8, the steepest slope, the spread, the seek computations and the trace analysis. Moreover, input data of the modeling are digital elevation model (DEM) and lake position, outlet location of the river. DEM based ArcHydro model was run on the both datasets, and ILWIS model was run on SRTM data. Several intermediate results were produced while the models run, and initial parameters of the Zavkhan River, its catchment area have been defined at the end of the model. Moreover, final results of the models were compared with each other and with the result of previous research, and with the reality. The result of this study can be used in baseline and advanced research on the catchment area. Besides of that, the result can define a spatial boundary of study on Zavkhan River and its catchment area. Moreover, it would have support for decision-making on ground and surface water resource, distribution and management. Further research, which will cover the entire territory of Mongolia, has to be done using same methodology. The 332nd decision on “River catchment areas of Mongolia” of the Minister of Nature, Environment and Tourism in 2009 has to renew, if a result of that study would be accepted from vocational organization and experts.

Tuul River and Its Catchment Area Delineation from Satellite Image

The purpose of this research is to define basic parameters of Tuul River and its catchment area using satellite images. The study has been done by two datasets 1) Shuttle Radar Topography Mission (SRTM) at a horizontal spatial resolution of 90 meters, 2) The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) at a horizontal spatial resolution of 30 meters, using two different models of ArcHydro and Integrated Land and Water Information System (ILWIS) softwares. Main methods of models, that were used in this research are the Deterministic-8, the steepest slope, the spread, the seek computations and the trace analysis. Moreover, input data of the modeling are digital elevation model (DEM) and outlet location of the river. DEM based ArcHydro model was run on the both datasets, and ILWIS model was run on SRTM data. Several intermediate results were produced while the models run, and basic parameters of the Tuul River, its catchment area have been defined at the end of the model. Moreover, final results of the models were compared with each other and with the result of previous research. The result of this study can be used in baseline and advanced research on the catchment area. Besides of that, the result can define a spatial boundary of study on Tuul River and its catchment area. Moreover, it would have support for decision-making on ground and surface water resource, distribution and management. Further research, which will cover the entire territory of Mongolia, has to be done using same methodology. The 332nd decision on “River catchment areas of Mongolia” of the Minister of Nature, Environment and Tourism in 2009 has to renew, if a result of that study would be accepted from vocational organization and experts.

Characteristics of Spatial and Temporal Vegetation Index Variability and Its Responses to Temperature and Precipitation in Mongolia

The Mongolian Plateau,a vital ecological barrier in northern China,is of great importance for studying vegetation dynamics in Mongolia against the background of climate warming.Such studies can enhance our understanding of regional vegetation responses to global warming and contribute to the establishment of a stronger ecological barrier in northern China.Here,we analyzed the spatial and temporal characteristics of the NDVI(normalized difference vegetation index)in Mongolia using 8 km resolution GIMMS NDVI3g data from 1990 to 2022,along with temperature,precipitation,and elevation data.Trend analysis and correlation methods were used to examine the relationships between the NDVI and temperature,as well as precipitation.The results showed four important aspects of these relationships.(1)The NDVI in Mongolia increased significantly from 1990 to 2022 at a rate of 0.0015 yr^(-1)(P<0.05).(2)Mongolia’s NDVI increased from 1990 to 2022 in 60.73%of the country.Of this total,the area with a significant increase accounted for 31.67%and was concentrated on the eastern and western edges.The area experiencing a significant decrease accounted for 15.67%and was mainly located on the southwestern edges.(3)The NDVI analysis revealed significant increasing trends in all regions except for those at elevations of 1500-2000 m.The greatest rate of increase was observed between 500 and 1000 m,and the increasing trend weakened as elevation continued to increase before gradually becoming significant again.Additionally,the NDVI increased significantly across different slopes,and the rate of increase decreased as the slope increased.(4)From 1990 to 2022,Mongolia’s NDVI was mostly negatively correlated with temperature.This occurred over 66.75%of the total land area,with 17.21%of the region exhibiting a significant negative correlation,mainly in the southwest.Conversely,the NDVI demonstrated a positive correlation with precipitation,encompassing 86.71%of the total land area.Approximately 40.44%of the region had a significant positive correlation,primarily in the southwest.In conclusion,throughout the experimental period,the vegetation state in Mongolia improved.However,due to the warming and drying climate,more attention should be paid to vegetation degradation in the south-central region.

Issues,Progress,and Recommendations in the Construction of Ecological Barrier on the Mongolian Plateau from the Perspective of Big Data

The Mongolian Plateau(MP),situated in the transitional zone between the Siberian taiga and the arid grasslands of Central Asia,plays a significant role as an Ecological Barrier(EB)with crucial implications for ecological and resource security in Northeast Asia.EB is a vast concept and a complex issue related to many aspects such as water,land,air,vegetation,animals,and people,et al.It is very difficult to understand the whole of EB without a comprehensive perspective,that traditional diverse studies cannot cover.Big data and artificial intelligence(AI)have enabled a shift in the research paradigm.Faced with these requirements,this study identified issues in the construction of EB on MP from a big data perspective.This includes the issues,progress,and future recommendations for EB construction-related studies using big data and AI.Current issues cover the status of theoretical studies,technical bottlenecks,and insufficient synergistic analyses related to EB construction.Research progress introduces advances in scientific research driven by big data in three key areas of MP:natural resources,the ecological environment,and sustainable development.For the future development of EB construction on MP,it is recommended to utilize big data and intelligent computing technologies,integrate extensive regional data resources,develop precise algorithms and automated tools,and construct a big data collaborative innovation platform.This study aims to call for more attention to big data and AI applications in EB studies,thereby supporting the achievement of sustainable development goals in the MP and enhancing the research paradigm transforming in the fields of resources and the environment.