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Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/figure_01.txt

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+Location of rivers.

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/figure_02.txt

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+Comparison of mean daily minimum flows in winter (black bars) and summer (red bars) in the three hydroclimatic regions of southern Quebec.

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/figure_03.txt

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+Interannual variability of winter and summer daily minimum-specific flows (l/s/km²) in the southeastern hydroclimatic region from 1930 to 2019. Châteaugay River: orange curve; Eaton River: yellow curve; Nicolet River: black curve; Etchemin River: green curve; Beaurivage River: blue curve; Du Sud River: gray curve. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10. 2166/nh.2022.070.

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/figure_04.txt

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+Interannual variability of winter and summer daily minimum-specific flows (l/s/km²) in the Eastern hydroclimatic region from 1930 to 2019. Ouelle River: orange curve; Du Loup River: red curve; Trois-Pistoles River: green curve; Rimouski River: blue curve; Matane River: gray curve; Blanche River: black curve. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh. 2022.070.

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/figure_05.txt

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+Interannual variability of winter and summer daily minimum-specific flows (l/s/km²) in the Southwestern hydroclimatic region from 1930 to 2019. Petite Nation River: black curve; Du Nord River: Red curve; L’Assomption River: gray curve; Matawin River: yellow curve; Vermillon River: blue curve. Please refer to the online version of this paper to see this figure in colour: http://dx.doi.org/10.2166/nh.2022.070.

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+}

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_01.txt

@@ -0,0 +1 @@
+Analyzed rivers

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_02.json

@@ -0,0 +1,28 @@
+{
+  "kind": "table",
+  "label": "table_02",
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+}

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_02.txt

@@ -0,0 +1 @@
+Correlation coefficients (R) calculated between physio-climatic factors and daily minimum flows in winter and summer

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_03.json

@@ -0,0 +1,28 @@
+{
+  "kind": "table",
+  "label": "table_03",
+  "number": 3,
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+}

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_03.txt

@@ -0,0 +1 @@
+Results of the various M–K tests applied to daily minimum flow series in winter between 1930 and 2019

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_04.json

@@ -0,0 +1,28 @@
+{
+  "kind": "table",
+  "label": "table_04",
+  "number": 4,
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Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_04.txt

@@ -0,0 +1 @@
+Results of the various MK tests applied to daily minimum flow series in summer between 1930 and 2019

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_05.json

@@ -0,0 +1,937 @@
+{
+  "kind": "table",
+  "label": "table_05",
+  "number": 5,
+  "caption": "Comparison of spatio-temporal variability of minimum daily flows during the four seasons in southern Quebec from 1930 to 2019",
+  "page": 12,
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+    },
+    {
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+      "bbox_points": [
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+        143.89,
+        566.03,
+        151.91
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+            90.98,
+            151.91
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+          "bbox_points": [
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+            143.89,
+            143.45,
+            151.91
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+          "bbox_points": [
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+            143.89,
+            166.59,
+            151.91
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+        {
+          "text": "Wetlands",
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+            278.11,
+            151.91
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+            143.89,
+            296.69,
+            151.91
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+          "text": "Agriculture",
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+            143.89,
+            366.1,
+            151.91
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+            143.89,
+            386.48,
+            151.91
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+        {
+          "text": "Agriculture",
+          "bbox_points": [
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+            143.89,
+            455.9,
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+        },
+        {
+          "text": "(NC)",
+          "bbox_points": [
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+            143.89,
+            476.22,
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+          "text": "Agriculture",
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+        }
+      ]
+    },
+    {
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+      "bbox_points": [
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+        157.89,
+        296.17,
+        165.91
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+      "words": [
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+          "text": "Main",
+          "bbox_points": [
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+            157.89,
+            90.98,
+            165.91
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+        },
+        {
+          "text": "climatic",
+          "bbox_points": [
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+            157.89,
+            121.84,
+            165.91
+          ]
+        },
+        {
+          "text": "factor",
+          "bbox_points": [
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+            157.89,
+            144.99,
+            165.91
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+        },
+        {
+          "text": "Snowfall",
+          "bbox_points": [
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+            157.89,
+            275.82,
+            165.91
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+        },
+        {
+          "text": "(NC)",
+          "bbox_points": [
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+            157.89,
+            296.17,
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+      ]
+    },
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+      "bbox_points": [
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+        139.31,
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+            171.87,
+            99.29,
+            179.87
+          ]
+        },
+        {
+          "text": "variability",
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+            171.87,
+            139.31,
+            179.87
+          ]
+        }
+      ]
+    },
+    {
+      "text": "Southeastern region STP þ þ þ þ",
+      "bbox_points": [
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+        185.62,
+        511.35,
+        193.91
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+      "words": [
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+          "text": "Southeastern",
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+            118.91,
+            193.91
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+        },
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+          "text": "region",
+          "bbox_points": [
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+            185.9,
+            143.97,
+            193.91
+          ]
+        },
+        {
+          "text": "STP",
+          "bbox_points": [
+            174.9,
+            185.9,
+            189.64,
+            193.91
+          ]
+        },
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+          "text": "þ",
+          "bbox_points": [
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+            185.62,
+            250.51,
+            193.62
+          ]
+        },
+        {
+          "text": "þ",
+          "bbox_points": [
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+            185.62,
+            331.8,
+            193.62
+          ]
+        },
+        {
+          "text": "þ",
+          "bbox_points": [
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+            185.62,
+            421.6,
+            193.62
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+        },
+        {
+          "text": "þ",
+          "bbox_points": [
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+            185.62,
+            511.35,
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+        }
+      ]
+    },
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+        511.35,
+        204.4
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+            196.39,
+            189.89,
+            204.4
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+            250.51,
+            204.11
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+        },
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+            196.11,
+            331.8,
+            204.11
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+          "bbox_points": [
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+            196.11,
+            511.35,
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+          ]
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+      ]
+    },
+    {
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+        210.11,
+        250.51,
+        218.41
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+      "words": [
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+            210.39,
+            99.24,
+            218.41
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+        },
+        {
+          "text": "region",
+          "bbox_points": [
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+            210.39,
+            124.25,
+            218.41
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+        },
+        {
+          "text": "STP",
+          "bbox_points": [
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+            210.39,
+            189.64,
+            218.41
+          ]
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+          "bbox_points": [
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+            210.11,
+            250.51,
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+      ]
+    },
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+      "bbox_points": [
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+        220.6,
+        509.6,
+        228.89
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+      "words": [
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+            220.88,
+            189.89,
+            228.89
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+          "bbox_points": [
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+            220.6,
+            250.51,
+            228.6
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+        },
+        {
+          "text": "0",
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+    },
+    {
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+        234.6,
+        511.35,
+        242.9
+      ],
+      "words": [
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+          "text": "Southwestern",
+          "bbox_points": [
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+            234.88,
+            120.95,
+            242.9
+          ]
+        },
+        {
+          "text": "region",
+          "bbox_points": [
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+            234.88,
+            145.96,
+            242.9
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+          "text": "STP",
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+            234.88,
+            189.64,
+            242.9
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+          "bbox_points": [
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+            234.6,
+            250.51,
+            242.6
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+        },
+        {
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+            234.88,
+            330.06,
+            242.9
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+        },
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+            234.6,
+            511.35,
+            242.6
+          ]
+        }
+      ]
+    },
+    {
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+      "bbox_points": [
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+        245.09,
+        509.61,
+        253.38
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+          "text": "LTP",
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+            189.89,
+            253.38
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+            198.25,
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+            256.42,
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+        },
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+        },
+        {
+          "text": "term",
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+            532.6,
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+          ]
+        },
+        {
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+            267.75
+          ]
+        }
+      ]
+    }
+  ],
+  "detection_error": null
+}

Media/2022/A. Assani et al. - 2022 - Spatial–temporal variability of seasonal daily minimum flows in southern Quebec synthesis on the im/table_05.txt

@@ -0,0 +1 @@
+Comparison of spatio-temporal variability of minimum daily flows during the four seasons in southern Quebec from 1930 to 2019

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_01.txt

@@ -0,0 +1 @@
+Map of the Cumberland, MD area annotated with the city’s 11 CSO outfalls and 3 watersheds (blue shading ¼ Wills Creek, yellow shading ¼ Potomac Lower North, unshaded ¼ Evitts Creek). Wills Creek outfalls are labelled in blue in the legend, while the Potomac Lower North and Evitts Creek outfalls are labelled in black. This figure is adapted from the public document ‘CSO Status in Maryland’, a 2019 Maryland Department of the Environment (MDE) presentation (Cheng 2019), with approximate watershed boundaries (blue) from MDE’s official Map of 8-Digit Watersheds (Maryland Department of the Environment undated).

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_02.txt

@@ -0,0 +1 @@
+Logistic regression curves for CSO incidence on each predictor in the Wills Creek (a–d) and Potomac Lower North (e–h) water- sheds, for all rainfall events (2005–2020). The logistic regressions for CSO incidence on total precipitation depth (a,e), maximum precipitation intensity (b,f), and average rainfall intensity (c,g) all show traditional probabilistic S-curves, but the logistic regressions for CSO incidence on preceding dry period (d,h) indicate an ineffective logistic predictor. As a result, we discounted antecedent dry period as a predictor for CSO incidence.

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_03.txt

@@ -0,0 +1 @@
+Yearly odds ratios for logistic regressions of CSO incidence on each of total event precipitation depth (green), maximum event intensity (blue), and average event intensity (yellow) in each of the Wills Creek (a) and Potomac Lower North (b) watersheds.

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_04.txt

@@ -0,0 +1 @@
+(a) The determined annual values of critical maximum rainfall intensity (Icrit, mm/hr), above which a CSO was likely to occur, in each of the Wills Creek and Potomac Lower North watersheds in Cumberland, MD, in each year (2005–2020). Significant changes in these values between years are rare, and investigation of their causes would require more data regarding CSO mitigation interventions or other structural changes made to the CSS. (b) The probability of the critical intensity in each year correctly predicting whether a given incident will trigger a CSO; or, the fraction of rainfall events correctly discriminated into CSO or non-CSO events. This reflects the predictive ability of Icrit.

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_05.txt

@@ -0,0 +1 @@
+Ordinary least-squares regression of Ncrit (lighter) and Icrit (darker) values on total annual rainfall (sum of depth of all rainfall events) over the Wills Creek (a) and Potomac Lower North (b) watersheds. Annual values of Icrit are independent of changes in annual rainfall, whereas Ncrit is sensitive to such changes.

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/figure_06.txt

@@ -0,0 +1 @@
+R2 coefficients of determination for the multiple regression model in the Wills Creek (blue) and Potomac Lower North (orange) watersheds in each year (2005–2020), and coefficients of determination for the simpler regression of lnV on lnP for each watershed (dashed) for comparison. The multiple regression model can dependably explain 30–60% of variance in CSO volumes. Data on interventions or other changes made in the system may help tease out reasons for variation in these results.

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/manifest.json

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+      "caption": "Ordinary least-squares regression of Ncrit (lighter) and Icrit (darker) values on total annual rainfall (sum of depth of all rainfall events) over the Wills Creek (a) and Potomac Lower North (b) watersheds. Annual values of Icrit are independent of changes in annual rainfall, whereas Ncrit is sensitive to such changes.",
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+          "bbox_points": [
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+          ]
+        },
+        {
+          "text": "(CD,",
+          "bbox_points": [
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+            158.42,
+            707.04
+          ]
+        },
+        {
+          "text": "h)",
+          "bbox_points": [
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+            699.03,
+            168.33,
+            707.04
+          ]
+        },
+        {
+          "text": "2,696",
+          "bbox_points": [
+            223.14,
+            699.03,
+            242.81,
+            707.04
+          ]
+        },
+        {
+          "text": "1.004",
+          "bbox_points": [
+            297.64,
+            699.03,
+            317.3,
+            707.04
+          ]
+        },
+        {
+          "text": "[1.002–1.005]",
+          "bbox_points": [
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+            698.75,
+            367.2,
+            707.04
+          ]
+        },
+        {
+          "text": "2,709",
+          "bbox_points": [
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+            699.03,
+            441.69,
+            707.04
+          ]
+        },
+        {
+          "text": "1.003",
+          "bbox_points": [
+            496.46,
+            699.03,
+            516.12,
+            707.04
+          ]
+        },
+        {
+          "text": "[1.002–1.005]",
+          "bbox_points": [
+            518.46,
+            698.75,
+            566.07,
+            707.04
+          ]
+        }
+      ]
+    },
+    {
+      "text": "CI confidence interval",
+      "bbox_points": [
+        64.01,
+        715.37,
+        128.15,
+        721.41
+      ],
+      "words": [
+        {
+          "text": "CI",
+          "bbox_points": [
+            64.01,
+            715.41,
+            69.31,
+            721.41
+          ]
+        },
+        {
+          "text": "confidence",
+          "bbox_points": [
+            76.31,
+            715.37,
+            106.07,
+            721.41
+          ]
+        },
+        {
+          "text": "interval",
+          "bbox_points": [
+            108.11,
+            715.41,
+            128.15,
+            721.41
+          ]
+        }
+      ]
+    }
+  ],
+  "detection_error": null
+}

Media/2022/A. Bizer and Kirchhoff - 2022 - Regression modeling of combined sewer overflows to assess system performance/table_01.txt

@@ -0,0 +1 @@
+Odds ratios resulting from logistic regression of CSO incidence on each predictor in each Cumberland watershed, for all rainfall

Media/2022/A. Shahin et al. - 2022 - Occurrence of Naegleria fowleri and faecal/figure_01.txt

@@ -0,0 +1 @@
+Lake Pontchartrain sampling sites.

Media/2022/A. Shahin et al. - 2022 - Occurrence of Naegleria fowleri and faecal/figure_02.txt

@@ -0,0 +1 @@
+Taxonomic classification of sequences from bacterial communities of the sediment samples. (a) Relative abundance of the dominant phyla in each sample. (b) Relative abundance of the dominant families in each sample.

Media/2022/A. Shahin et al. - 2022 - Occurrence of Naegleria fowleri and faecal/figure_03.txt

@@ -0,0 +1 @@
+Monthly water (a) temperature, (b) dissolved oxygen, (c) conductivity, (d) salinity and sediment, (e) HF183, (f) E. coli, and (g) N. fowleri QPCR concentrations (Log GC/g) recorded for samples collected from Lake Pontchartrain (December 2017–July 2018). Logarithmic axis applied for conductivity.