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All quantitative data, except for the number of SWIs, are open source and accessible at the source cited in Table1. The number of SWIs are available from the Namibe Provincial Government (Governo Provincial Do Namibe), but restrictions apply to the availability of these data, which were used ...
Table of Contents How to cite Requirements How to install necessary compilers How to use the Toolkit How to fix/report bugs Licenses Contributors List of Matlab Class Functions List of EPANET 2.1 Functions Supported List of EPANET 2.012 Functions Supported List of EPANET 2.2 Functions Supported How...
by forests (Tedela et al., 2012; Im et al., 2020; Walega et al., 2020). Similar ‘curve’ types of models have been developed using empirical data from watershed vegetation manipulation experiments (e.g.,Douglass, 1983) (See Water Yield Response Curve, WYRC, in Table S1). The WY...
shortages, drought, and other problems which, hopefully, will be investigated by another research paper and compared with the regions investigated by this one; 3) Several studies cited in this paper also focused on the water–food Nexus (Table 1) without giving attention to the energy element....
(2014), such sinkholes, with their associated subsidence fractures, probably lead infiltrated water directly to the basal part of the Muschelkalk aquifer, thus recharging groundwater below the Haßmersheimer layers. The level of the water table is in the upper dolomite of the Middle Muschel...
Present address: Stanford University, Stanford, USA Authors and Affiliations Massachusetts Institute of Technology, Cambridge, USA Shujuan Mao, Robert D. van der Hilst & Michel Campillo Institut des Sciences de la Terre, Saint Martin d’Hères, France ...
by lead pipes in household plumbing. Within a week, however, Snyder had announced a $12 million plan to switch back to the DWSD as Flint’s water supplier. Experts noted that such a move would do nothing to address the damage already done to Flint’s water supplyinfrastructureby more than...
As indicated in Table 3, the application of machine learning in water resource modeling has progressed steadily, offering novel ideas and methods to address intricate water resource challenges. For instance, in the context of rainfall prediction, factors including pressure, temperature, humidity, ...
24 study. The mean weight values are shown in Table A6 (in Supplementary Materials) along with the standard criteria. A relative weight of 1 was given the least importance, while a weight of 4 was given the most. (b) In this step, the relative weight (RW) is found by diving the ...