Statistical Analysis of Trends in the Red River Over a 45 Year Period

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significant positive trend with the non-parametric and parametric methods, total dissolved solids and specific conductance were also highly significant using both methods at the Emerson monitoring station. Dissolved Magnesium produced a significant trend using non-parametrics however, did not meet the all the requirements of the parametric method. There is approximately ten years of missing data from 1965-1975 thus a trend was fitted for the data from 1975 to 2007 and yielded significant results with both the non-parametric and parametric methods. Dissolved sulphate produced a highly significant trend at the Emerson station using non-parametric methods, but significance using parametric methods could not be determined by a single linear trend. Dissolved Chloride showed an insignificant trend using non-parametric methods, while the parametric methods produced a significant trend. In regards to the South Floodway and Selkirk monitoring stations the only constituent with a complete data set that meet the requirements of QWTREND was specific conductance. This was where the remaining inconsistencies were exhibited between the two statistical methods. Using the non-parametric methods the trends in this constituent were insignificant however, once the parametric methods were applied to these constituents the trends at both stations were highly significant. In such situations it is uncertain whether the non-parametric methods are powerful enough at finding trends. There are certain recommendations that can be made in order to achieve the most accurate results possible. Due to the scarcity of the data from the provincially monitored stations it should be said that in order to have accurate results and interpretation, a statistically sound sampling scheme should be implemented. If the parametric methods are chosen QWTREND will compute sampling designs in order to combat this problem and will allow almost 80% of trends to be detected when they exist. If a comparison is to be made between the original data and data weighted for flow, the non-parametric approach can deal with this and then compare results between the two. When data is adjusted for flow, one is able to see the magnitude and significance of a trend that is not explained by streamflow. xv
Using ancillary data, data obtained from agriculture around the basin of study, the significance and magnitude of trends can be better explained. Not all trends can be explained by a simple linear model, the parametric methods allow for fitting more than just a single linear trend. For example, Dissolved Sulphate is one such constituent that would best be modeled with two monotonic trends in this case. The parametric approach can test a wide variety of trends other than linear and is more powerful at detecting trends. Using QWTREND with a properly devised sampling scheme and the inclusion of ancillary variables will be the best method of explaining the statistical significance of trends in water quality. xvi
Page 1 and 2: Statistical Analysis of Trends in t
Page 3 and 4: 5 Comparison of Non-Parametric and
Page 5 and 6: List of Figures 1.1 The Red River B
Page 7 and 8: A.8 Boxplot of Specific Conductance
Page 9 and 10: A.41 Dissolved Calcium Flow Adjustm
Page 11 and 12: A.67 Dissolved Sulphate Flow Adjust
Page 13 and 14: A.93 Specific Conductance Flow Adju
Page 15: Mann-Kendall or Seasonal Mann-Kenda
Page 19 and 20: Chapter 1 Introduction The Red Rive
Page 21 and 22: oped by Aldo Vecchia (United States
Page 23 and 24: Chapter 2 Streamflow Data and Conce
Page 25 and 26: Table 2.1: Selected characteristics
Page 27 and 28: of testing for seasonality. If it y
Page 29 and 30: Table 2.3: Sample size of stations
Page 31 and 32: Figure 3.1: Mean monthly streamflow
Page 33 and 34: v.1.56. CAS# n/a WQStat Plus TM BOX
Page 35 and 36: concentrations of major anions and
Page 37 and 38: Table 3.3: Kruskal-Wallis test for
Page 39 and 40: The N ′ individual slope estimate
Page 41 and 42: As most parameters consistently exh
Page 43 and 44: Table 3.4: Seasonal Mann-Kendall Te
Page 45 and 46: Chapter 4 Parametric Methods used f
Page 47 and 48: log denotes the base-10 logarithm;
Page 49 and 50: Figure 4.1: Daily Streamflow at Eme
Page 51 and 52: Figures 4.3-4.8 depict the recorded
Page 53 and 54: 1 1 CONCENTR CONCENTR 1955 1960 196
Page 55 and 56: Table 4.1: Fitted Single Linear Tre
Page 57 and 58: Chapter 5 Comparison of Non-Paramet
Page 59 and 60: 5.2 Future Recommendations First an
Page 61 and 62: • Uses full power of the maximum
Page 63 and 64: Hamed, Khaled.,; 2008, Trend Detect
Page 65 and 66: Appendix A Figures A.1 Boxplots of
Page 67 and 68:
v.1.56. CAS# n/a WQStat Plus TM BOX
Page 69 and 70:
Figure A.7: Boxplot of Total Dissol
Page 71 and 72:
v.1.56. CAS# n/a WQStat Plus BOX &
Page 73 and 74:
Figure A.13: Seasonality pattern of
Page 75 and 76:
A.3 Non-Parametric Trend Results Th
Page 77 and 78:
Figure A.19: Long term temporal tre
Page 79 and 80:
Page 81 and 82:
Page 83 and 84:
Page 85 and 86:
A.4 Parametric Trend Results The fo
Page 87 and 88:
Figure A.31: Dissolved Sodium at Em
Page 89 and 90:
Figure A.33: Dissolved Magnesium at
Page 91 and 92:
Figure A.35: Dissolved Chloride at
Page 93 and 94:
Figure A.37: Specific Conductance a
Page 95 and 96:
05102500 RED RIVER OF THE NORTH AT
Page 97 and 98:
1 1 CONCENTR CONCENTR 500 RED RIVER
Page 99 and 100:
CONCENTR 500 RED RIVER OF THE NORTH
Page 101 and 102:
Page 103 and 104:
CONCENTR ● CONCENTR 0 0 1955 1960
Page 105 and 106:
CONCENTR CONCENTR 00 RED RIVER OF T
Page 107 and 108:
Page 109 and 110:
CONCENTR 1 1.5 ! ! ! ! !! ! ! ! ! !
Page 111 and 112:
CONCENTR 0.5 1 ! ! ! ! !! ! !! ! !
Page 113 and 114:
Page 115 and 116:
CONCENTR ! ! ! ! ! ! ! ! ! ! ! ! !
Page 117 and 118:
CONCENTR ! CONCENTR 2 2 1955 1960 1
Page 119 and 120:
A.5.2 South Floodway at St. Norbert
Page 121 and 122:
CONCENT ! CONCENT 2 2 floodway dspc
Page 123 and 124:
A.5.3 Selkirk Monitoring Station 10
Page 125 and 126:
CONCENT ! CONCENT 2 2 selkirk dspc
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Statistical Analysis of Trends in the Red River Over a 45 Year Period

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