Hydraulic modelling of sewage exfiltration

2009 ◽  
Vol 59 (8) ◽  
pp. 1559-1565 ◽  
Author(s):  
Christian Karpf ◽  
Jens Traenckner ◽  
Peter Krebs

Exfiltration of waste water in sewer networks represents a potential danger for the soil and the aquifer. Various modelling approaches have been proposed to quantify sewerage exfiltration and its spatial and temporal variation. Common models are based on the law of Darcy, extended by a more or less detailed consideration of the expansion of leaks, the characteristics of the soil and the colmation layer. In the paper investigations are introduced, which are focused on the actual water content of the soil and its influence on exfiltration rates. Modelling results with HYDRUS 1D show, that under unsaturated conditions initial exfiltration rates are increased compared to saturated conditions. In experiments it was found, that the matrix potential increases the tightness of the colmation layer. Further a colmation model was deduced, which allows the calculation of the thickness and conductivity of the colmation layer.

2011 ◽  
Vol 63 (10) ◽  
pp. 2294-2299 ◽  
Author(s):  
Christian Karpf ◽  
Peter Krebs

Exfiltration of waste water from sewer systems represents a potential danger for the soil and the aquifer. Common models, which are used to describe the exfiltration process, are based on the law of Darcy, extended by a more or less detailed consideration of the expansion of leaks, the characteristics of the soil and the colmation layer. But, due to the complexity of the exfiltration process, the calibration of these models includes a significant uncertainty. In this paper, a new exfiltration approach is introduced, which implements the dynamics of the clogging process and the structural conditions near sewer leaks. The calibration is realised according to experimental studies and analysis of groundwater infiltration to sewers. Furthermore, exfiltration rates and the sensitivity of the approach are estimated and evaluated, respectively, by Monte-Carlo simulations.


Water ◽  
2021 ◽  
Vol 13 (13) ◽  
pp. 1798
Author(s):  
Xu Wu ◽  
Su Li ◽  
Bin Liu ◽  
Dan Xu

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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