scholarly journals Diet composition of the African manatee: Spatial and temporal variation within the Sanaga River Watershed, Cameroon

2021 ◽  
Author(s):  
Aristide Takoukam Kamla ◽  
Dylan G. E. Gomes ◽  
Cathy A. Beck ◽  
Lucy W. Keith‐Diagne ◽  
Margaret E. Hunter ◽  
...  
Keyword(s):  
Temporal Variation ◽  
Diet Composition ◽  
Spatial And Temporal Variation ◽  
River Watershed

scholarly journals Spatial and temporal variation of water quality in a watershed in center-west Paraná, Brazil

2021 ◽  
Author(s):  
Rodrigo Felipe Bedim Godoy ◽  
Enzo Luigi Crisiogiovanni ◽  
Elias Trevisan ◽  
Fernando Aparecido Dias Radomski
Keyword(s):  
Water Quality ◽  
Temporal Variation ◽  
Total Phosphorus ◽  
Oxygen Demand ◽  
Water Quality Monitoring ◽  
Spatial And Temporal Variation ◽  
River Watershed ◽  
Microbiological Parameters ◽  
Quality Water ◽  
The Relationship

Abstract Water quality monitoring is an essential strategy for water resources management. Physicochemical and microbiological parameters play an important role in the characterization of water quality. They are helpful tools for the identification of pollution in aquatic ecosystems, being natural sources or because of anthropogenic actions, and contribute to making decisions as well as sustainable development in a hydrographic basin. This study analyzed the water quality variation over a period of 20 years in Piquiri River watershed. Total phosphorus (TP) concentration from affluent rivers was estimated using a linear regression model. The relationship between total nitrogen and TP presented a Person's linear correlation of 0.80, while turbidity and total suspended solids presented a correlation of 0.79. The relationship between the predicted and observed values for turbidity and TP presented r² higher than 0.60. Spatial–temporal variation of water quality in Piquiri River watershed has shown good quality over the years, although unacceptable values for Escherichia coli, biochemical oxygen demand, chemical oxygen demand and total phosphorus levels appeared. Most unacceptable values were identified in affluent rivers, suggesting the improvement in the water quality closer to downstream of the Piquiri River. Water quality index also showed good quality water for all stations.

scholarly journals Spatial and Temporal Variation Characteristics of Snowfall in the Haihe River Basin from 1960 to 2016

Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu
Keyword(s):  
Temporal Variation ◽  
River Basin ◽  
Spatial And Temporal Variation ◽  
Haihe River Basin ◽  
Temperature Threshold ◽  
Threshold Method ◽  
Exponential Equation ◽  
Haihe River ◽  
The Haihe River Basin ◽  
Different Levels

The spatio-temporal variation of precipitation under global warming had been a research hotspot. Snowfall is an important part of precipitation, and its variabilities and trends in different regions have received great attention. In this paper, the Haihe River Basin is used as a case, and we employ the K-means clustering method to divide the basin into four sub-regions. The double temperature threshold method in the form of the exponential equation is used in this study to identify precipitation phase states, based on daily temperature, snowfall, and precipitation data from 43 meteorological stations in and around the Haihe River Basin from 1960 to 1979. Then, daily snowfall data from 1960 to 2016 are established, and the spatial and temporal variation of snowfall in the Haihe River Basin are analyzed according to the snowfall levels as determined by the national meteorological department. The results evalueted in four different zones show that (1) the snowfall at each meteorological station can be effectively estimated at an annual scale through the exponential equation, for which the correlation coefficient of each division is above 0.95, and the relative error is within 5%. (2) Except for the average snowfall and light snowfall, the snowfall and snowfall days of moderate snow, heavy snow, and snowstorm in each division are in the order of Zones III > IV > I > II. (3) The snowfall and the number of snowfall days at different levels both show a decreasing trend, except for the increasing trend of snowfall in Zone I. (4) The interannual variation trend in the snowfall at the different levels are not obvious, except for Zone III, which shows a significant decreasing trend.

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