Seasonal water quality variations in two pristine headwater lakes, boreal coniferous forest area, eastern Finland

Abstract. Forest cover rate is the principal indice to reflect the forest acount of a nation and region. In view of the difficulty of accurately calculating large-scale forest area by traditional statistical survey methods, it is proposed to extract China forest area based on Google Earth Engine platform. Trained by the enough samples selected through the Google Earth software, there are nine different random forest classifiers applicable to their corresponding zones. Using Landsat 8 surface reflectance data of 2018 year and the modified forest partition map, China forest cover is generated on the Google Earth Engine platform. The accuracy of China's forest coverage achieves 89.08%, while the accuracy of Global Forest Change datasets of Maryland university and Japan’s ALOS Forest/Non-Forest forest product reach 87.78% and 84.57%. Besides, the precision of tropical/subtropical forest, temperate coniferous forest as well as nonforest region are 83.25%, 87.94% and 97.83%, higher than those of other’s accuracy. Our results show that by means of the random forest algorithm and enough samples, tropical and subtropical broadleaf forest, temperate coniferous forest and nonforest partition can be extracted more accurately. Through the computation of forest cover, our result shows that China has a area of 220.42 million hectare in 2018.

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Impact of Spring Freshet Flooding and Summer Rainfall Flooding on the Water Quality of an Alpine Barrier Lake

10.21203/rs.2.18667/v1 ◽

2019 ◽

Author(s):

Chun-hua LI ◽

Chun Ye ◽

Ji-xuan LI ◽

Wei-wei WEI ◽

Ye ZHENG ◽

...

Keyword(s):

Water Quality ◽

Flow Field ◽

Summer Rainfall ◽

Lake Area ◽

Quality Model ◽

Barrier Lake ◽

Pollutant Concentrations ◽

Spring Freshet ◽

Seasonal Water Quality ◽

Flooding Period

Abstract Background: Among the many types of lakes, the barrier lake attracts special attention. China’s Lake Jingpo is one of the world’s rare such alpine lakes. Spring freshet flooding and summer rainfall flooding are factors that significantly increase barrier lake instability while also impacting water quality. Results: This study constructed a hydrodynamic water-quality model to simulate the impacts of spring freshet flooding, summer rainfall flooding, and 30-year frequency rainfall flooding on the flow-field and water quality at Lake Jingpo. Results showed that the lake-area flow field was generally weak (mostly lower than 0.015 m/s), but spring freshet flooding in April and summer rainfall flooding in August-September increase flow velocities to 0.045 m/s and above, much higher than in other months. Mudanjiang is the largest river that enters Lake Jingpo. Its flow reaches 4.81×10 8 m 3 , 29.77×10 8 m 3 , and 58.4×10 8 m 3 during the spring freshet flooding, summer rainfall flooding and 30-year frequency rainfall flooding period, respectively. The longest diffusion distances were measured from the lake mouth to the point of impact; these were 16.3 km, 33.1km, and 43.6km for the above periods, respectively. Our research revealed that precipitation played an important role in seasonal water quality at Lake Jingpo, and larger amounts of precipitation, longer diffusion distances, and increased pollutant concentrations. Conclusions: Compared to the effects of the spring freshet flooding period, the summer rainfall flooding and 30-year frequency rainfall flooding period more significantly affected water quality at Lake Jingpo. There was more overall precipitation, longer diffusion distances, and increased pollutant concentrations in the lake area. Alpine barrier lake environments are very fragile, which need greater care efforts and more stringent measures to control pollution sources throughout entire catchment area.

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