scholarly journals Water quality variation of Lake Hongjiannao and its driving force analysis from 1973 to 2013

2016 ◽  
Vol 28 (5) ◽  
pp. 982-993 ◽  
Author(s):  
ZHAO Ning ◽  
◽  
MA Chao ◽  
YANG Yali
Keyword(s):  
Water Quality ◽  
Driving Force ◽  
Force Analysis ◽  
Water Quality Variation ◽  
Driving Force Analysis ◽  
Quality Variation

Characteristics of physical water quality variation under heat storage in closed saline water aquaculture ponds in the tropics

2021 ◽  
Author(s):  
Akinori Ozaki ◽  
Panitan Kaewjantawee ◽  
Nguyen Van Thinh ◽  
Masaru Matsumoto ◽  
Masayoshi Harada ◽  
...  
Keyword(s):  
Water Quality ◽  
Heat Storage ◽  
Saline Water ◽  
Aquaculture Ponds ◽  
Water Quality Variation ◽  
The Tropics ◽  
Quality Variation

scholarly journals High-frequency monitoring reveals seasonal and event-scale water quality variation in a temporally frozen river

2018 ◽  
Vol 564 ◽  
pp. 619-639 ◽  
Author(s):  
M. Kämäri ◽  
S. Tattari ◽  
E. Lotsari ◽  
J. Koskiaho ◽  
C.E.M. Lloyd
Keyword(s):  
Water Quality ◽  
High Frequency ◽  
Event Scale ◽  
Water Quality Variation ◽  
Frequency Monitoring ◽  
Quality Variation

Water Quality Variation and Biotic Community Characteristics in Juam Lake (2011)

2013 ◽  
Vol 31 (1) ◽  
pp. 37-44 ◽  
Author(s):  
Hyo-Jeong Song ◽  
◽  
Kyung-Sub Hwang ◽  
Jong-Hwan Park ◽  
Hak-Young Lee ◽  
...  
Keyword(s):  
Water Quality ◽  
Community Characteristics ◽  
Biotic Community ◽  
Water Quality Variation ◽  
Quality Variation

scholarly journals An Integrated Investigation of Spatiotemporal Habitat Quality Dynamics and Driving Forces in the Upper Basin of Miyun Reservoir, North China

2018 ◽  
Vol 10 (12) ◽  
pp. 4625 ◽  
Author(s):  
Shengjun Yan ◽  
Xuan Wang ◽  
Yanpeng Cai ◽  
Chunhui Li ◽  
Rui Yan ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Habitat Quality ◽  
Driving Force ◽  
North China ◽  
Population Change ◽  
Driving Forces ◽  
Policy Formulation ◽  
Force Analysis ◽  
Miyun Reservoir ◽  
Driving Force Analysis

Understanding changes in habitat quality and the driving forces of these changes at landscape scales is a critical part of effective ecosystem management. The present study investigated spatiotemporal habitat quality dynamics and related driving forces from 2005 to 2015 in the upper basin of Miyun Reservoir in North China by constructing an effective framework integrated InVEST and binary logistic regression models. This framework expanded the driving force analysis into an assessment of changes in habitat quality and intuitively verified the effectiveness of relevant environmental policies. The proposed method of combining the equidistant random sampling method and the method of introducing spatial lag variables in logistic regression equation can effectively solve spatial autocorrelation with a large enough number of sampling points. Overall, habitat quality improved during the study period. Spatially, a concentrated loss of habitat occurred in the southeastern part of the basin between the reservoir and mountainous areas, while other areas gradually recovered. Driving force analysis showed that lower elevation mountain land, gentle slopes, locations near rural land or roads, larger areas of grain cultivation, and areas with little population change had a higher likelihood of having changed in habitat quality in the upper basin of Miyun Reservoir. These results suggested that the present policy of protecting the ecosystem had a positive effect on improving habitat quality. In the future, the human activity management related to habitat quality needs to be strengthened. The present study would provide a reference for land use policy formulation and biodiversity conservation.

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