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

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Table 3.5: Flow Adjusted Seasonal Mann-Kendall Test for Trend Results. Station Slope (units/year) p-value Calcium, dissolved (mg/l) 1. 0.1710 < 0.001 2. n/a n/a 3. n/a n/a Sodium, dissolved (mg/l) 1. 0.2580 < 0.001 2. n/a n/a 3. n/a n/a Potassium, dissolved (mg/l) 1. 0.0460 < 0.001 2. n/a n/a 3. n/a n/a Magnesium, dissolved (mg/l) 1. 0.3567 < 0.001 2. n/a n/a 3. n/a n/a slopes at all three monitoring stations and an extremely large slope at the south floodway monitoring station and specific conductivity produced an increasing significant slope at the Emerson station and insignificant slopes at the south floodway and Selkirk monitoring stations. Certain constituents were also weighted for flow and trends re-examined using this non-parametric method. Flow adjusting data shows how streamflow relates with the constituents and by flow adjusting we can remove flow effects. Slopes from the four constituents selected increased slightly and remained significant. The question is how one would handle such increases; if the slope is only increasing slightly relative to others with large increases the latter should be looked at and evaluated first. Although the slopes are significant, the p-values given in Table 3.4 and Table 3.5 are that of Kendall’s τ. 26
Chapter 4 Parametric Methods used for Water Quality Trend Analysis In the previous section non-parametric methods of water quality trend analysis was examined, namely the seasonal Mann-Kendall test. The advantages to such methods are that it is easy to compute, requires few assumptions, they are robust to outliers and can handle numerous data from many stations. A weakness of the seasonal Mann-Kendall test is that it assumes monotonic trend and seasons must be defined. Some advantages of parametric methods are: they can be used to model complex trends; and are good for explanatory and not just exploratory analysis. Introducing ancillary data such as livestock or farming data can help better explain certain trends. These methods use the full power and flexibility of maximum likelihood theory, and flow and concentration are modeled jointly (Vecchia, 2004). However disadvantages of parametric methods are: they require specification of a parametric model; usually are computationally intensive; require care in fitting the model and verifying assumptions and may require more data than non-parametric methods do. QWTREND, developed by Aldo Vecchia (USGS), was used to analyze trends in water quality. There are specific data requirements for this program: 1. Record length at least 15 years (not necessarily consecutive) 27
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 and 16: Mann-Kendall or Seasonal Mann-Kenda
Page 17 and 18: Using ancillary data, data obtained
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: Table 3.4: Seasonal Mann-Kendall Te
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 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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