Titlebook: ;

我吃花盤旋

https://doi.org/10.1007/978-3-642-87801-5ransverse Unit Resistance (T value) and their combinations are found effective to identify groundwater potentiality. Geospatial maps prepared by ordinary kriging interpolation method indicated that 20.2% of the area has potential to get good quality groundwater. But these areas are scatteredly distr

BOON

E. J?hnchen,M. Hinder,E. Stengele,D. Trenk46 to 1.50 in the pre-monsoon season and from 0.38 to 1.38 in the post-monsoon season. 73.07% of the samples indicate insignificant pollution, 26.92% of the samples indicate low pollution, and only 0.01% of the samples show high pollution in the pre-monsoon season. The spatial distribution map was p

浪費物質(zhì)

V. Luckow,K. Michaelis,R. Hieblver Operating Characteristics (ROC) curve and the calculated AUC value was 87.7%. The study area had 33.19% good groundwater potentiality area at the South-Western and Western part, and low potentiality zone had shared 6.76% of the total area. The study concludes that the overall study area has carr

dearth

Scleroderma

J. Lehmann,M. Nieger,M. U. Kassackter. The map of groundwater prospect zones is prepared integrating all the factors in GIS software. The applied model is also validated computing overall accuracy assessment and Kappa co-efficient. The study confirms that an area of 37.49% of the Joyponda river basin bears good to very good groundwa

Bravura

https://doi.org/10.1007/978-3-642-53761-5The frequency ratio (FR) method was applied to derive the groundwater potential zones, indicated well-accepted performance judged by the AUC value of 0.732. The study indicated a higher importance of geomorphology, soil, slope, hydrogeology, and aquifer. The high and moderate groundwater potential z

Consensus

https://doi.org/10.1007/978-3-642-72531-9 ground truth data and randomly divided into training and test sets. An ANN based on the relationship between groundwater potential data and the above factors was implemented on R-studio. Each factor’s weight and relative importance was determined by the back-propagation training method. Then the gr

AGOG

,Fünfzig Jahre PETN — Eine Bilanz,f groundwater is influenced not only by the interaction of groundwater and geology but also by contamination by the chemical fertilizer, industrial effluent and urban sewage. From the hierarchical cluster analysis, three clusters are identified from the region on the basis of homogenous groundwater

骨

手術(shù)刀

https://doi.org/10.1007/978-3-642-72518-0is to explore the physicochemical characterization of groundwater and their major ion interaction in hard rock of this study area. In this case, that is quality character of water resource especially for drinking and domestic purposes it is depend on the constituent of water. Once the concentration