); [EMAIL_ADDRESS] (S.P)  
Salmia Parveen  
5 Department of Agriculture, Food and Resource Sciences, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA; [EMAIL_ADDRESS] (F.H. ); [EMAIL_ADDRESS] (S.P.) [PERSON]  
5 Department of Agriculture, Food and Resource Sciences, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA; [EMAIL_ADDRESS] (F.H. ); [EMAIL_ADDRESS] (S.P)  
[PERSON]  
5 Department of Agriculture, Food and Resource Sciences, University of Maryland Eastern Shore, Princess Anne, MD 21853, USA; [EMAIL_ADDRESS] (F.H. For spatio-temporal monitoring purposes in environmental studies, it is desirable to determine the locations representing the entire observation area. These representative locations aid in determining the persistent spatial patterns in deviations of individual observations from the mean across the observation area. Locations where such deviations from the mean are consistently close to zero best represent the mean across the observation area [10]. Two commonly used techniques to find spatial patterns in deviations from average are the mean relative difference (MRD) method and the empirical orthogonal function (EOF) method. The EOF method can identify and rank several patterns, allowing the user to gauge the impact of each pattern, whereas the MRD method generates a single pattern. As an efficient method to uncover spatial patterns of variability [11; 12], the EOF analysis was used in oceanography and climate studies [13; 14], hydrogeology [15], soil hydrology [16], crop yield as related to the access to groundwater and nutrient management [17], and other fields. For example, persistent spatial patterns were found with EOF analysis of _Escherichia coli_ and _Enterococcus_ spp. levels along a Pennsylvania creek [18]. To our knowledge, EOF analysis has not been used to analyze patterns of enteric pathogens across several water bodies. The spatiotemporal dynamics of microbial water quality are affected by many environmental factors that can manifest the superposition of several spatial patterns. Hence, the EOF method may be preferable to the MRD method in microbial water quality studies. Weather provides strong controls for the fate and transport of enteric pathogens. In particular, the weather was shown to affect _S. enterica_ and _L. monocytogenes_ populations in surface waters [7; 19; 20; 21; 22]. Previous studies have shown that precipitation and storm events may drive pathogens into waterways from agricultural and urban land [23; 24]. Some studies have suggested that the prevalence of pathogens may change after precipitation and storm events when they are released from sediments in water [25; 26]. Correlations were established between rainfall events and the prevalence of _Salmonella_ in stream water [19]. Several other studies showed that levels of _Salmonella_ in pond water increased after rain events [20; 21; 22]. Similarly, _Listeria monocytogenes_ levels also increased after storm events in Austria [7]. To our knowledge, no attempt has been made so far to relate spatial weather patterns to spatial patterns in pathogen concentrations. _Salmonella enterica_ and _Listeria monocytogenes_ were detected at quantifiable levels in streams and ponds of Maryland and Delaware [27; 28; 29]. The availability of the monitoring dataset [28] and weather data allowed us to set the objectives of this study as (i) use EOF analysis to explore the persistent spatial patterns of _Salmonella enterica_ and _Listeria monocytogenes_ concentrations at four different sites (two ponds, two streams) in Maryland and Delaware over a two-year period (2016-2018) and (ii) compare persistent patterns of precipitation and pathogen concentrations.