VICAIRE - Module 2

Qualitative Hydrology - Chapter 9

 

exercise 1 - solution

1. Make plot between flow and phosphorus concentration!
2. Analyze the tendency of variety of phosphorus concentration in dependence of the flow!
3. Point the questionable measures, which are declined from the common tendency!

1.

2. The phosphorus concentration increases when the flow decreases. The phosphorus concentration decreases when the flow increases. The observed monitoring data are measured in the cases of low water in the period 30.07.1993 to 15.03.1994. The measured phosphorus concentrations vary in range from 0.084 mg/L (24.08.93) to 0.96 mg/L (14.09.93). The differences are more than 10 times during this period while the measured discharges are practically constant - 0.15-0.2 m3/s. This shows that the variations of the phosphate concentrations are mainly product of point sources of pollution with changeable monthly working regime.

3. Some of the measured monitoring data in the period 30.07.93 to 15.03.94 are not in accordance with the basic tendency of variation between flow and phosphate concentration.

 

exercise 2 - solution

1. The first step is the correlation between the calculated daily phosphorus loads (P) in kg/day and measured daily discharges in m3/day to be established. This means the flow to be calculated in m3/day and in l/day and the phosphorus concentration to be diverted in phosphorus load in kg/day as follows:

Flow [m3/day] = Flow [m3/s]·86400 [s/day];
Flow [l/day] = Flow [m3/day]·1000;
Phosphate load [kg/day] = Phosphate concentration [mg/L] · Flow [l/day] / 1000000.

2. The correlation (linear, logarithmic, polynomial, power and exponential) between flow in m3/day and phosphorus load in kg/day is made (Figure 1 to 5).

Figure 1 Linear Correlation

Figure 2 Logarithmic Correlation



Figure 3 Polynomial Correlation

Figure 4 Power Correlation


Figure 5 Exponential Correlation

The best regression is turned out linear with correlation coefficient 0.6342 and polynomial - with correlation coefficient 0.6386. The observed mean monthly phosphorus loads of the river for Rossitza subbasin for the investigated period 1990-1995 is prepared using linear and polynomial correlation, presented in Figure 6 and Table 2.

Attention: In common case the best correlation's dependencies between flow and nutrient load are linear and power.

Month

Observed
monthly flow
m3/s

Observed
monthly flow
m3/day

Days per month

ObsP,Polyn.
R2=0.6386
kg/day

ObsP,Polyn.
R2=0.6386
kg/month

ObsP,Polyn.
R2=0.6342
kg/day

ObsP,Polyn.
r2=0.6342
kg/month

HYDROLOGICAL YEAR
90,APR 1.580 136512.000 30 23.173 695.177 25.488 764.637
MAY 5.890 508896.000 31 62.814 1947.245 99.965 3098.906
JUN 3.220 278208.000 30 37.930 1137.894 53.827 1614.813
JUL 0.670 57888.000 31 15.157 469.877 9.763 302.656
AUG 0.560 48384.000 31 14.197 440.101 7.862 243.731
SEP 0.710 61344.000 30 15.507 465.211 10.454 313.629
OCT 0.530 45792.000 31 13.935 431.990 7.344 227.661
NOV 0.610 52704.000 30 14.633 438.995 8.726 261.789
DEC 5.580 482112.000 31 59.871 1855.986 94.608 2932.845
JAN 0.990 85536.000 31 17.962 556.815 15.293 474.074
FEB 1.350 116640.000 28 21.135 591.781 21.514 602.378
MAR 4.400 380160.000 31 48.796 1512.683 74.218 2300.743
91,APR 8.140 703296.000 30 84.611 2538.326 138.845 4165.341
MAY 26.400 2280960.000 31 289.459 8973.222 454.378 14085.703
JUN 10.300 889920.000 30 106.247 3187.397 176.170 5285.085
JUL 22.200 1918080.000 31 237.933 7375.933 381.802 11835.847
AUG 5.200 449280.000 31 56.282 1744.727 88.042 2729.287
SEP 0.360 31104.000 30 12.455 373.652 4.406 132.189
OCT 1.530 132192.000 31 22.729 704.597 24.624 763.341
NOV 2.300 198720.000 30 29.602 888.057 37.930 1137.885
DEC 1.330 114912.000 31 20.958 649.706 21.168 656.205
JAN 1.840 158976.000 31 25.485 790.045 29.981 929.402
FEB 2.510 216864.000 29 31.492 913.259 41.558 1205.191
MAR 7.010 605664.000 31 73.570 2280.660 119.318 3698.867
92,APR 16.500 1425600.000 30 172.218 5166.551 283.306 8499.165
MAY 4.390 379296.000 31 48.703 1509.801 74.045 2295.386
JUN 26.200 2263680.000 30 286.945 8608.364 450.922 13527.645
JUL 3.920 338688.000 31 44.351 1374.878 65.923 2043.616
AUG 0.900 77760.000 31 17.171 532.315 13.738 425.863
SEP 0.440 38016.000 30 13.151 394.532 5.789 173.661
OCT 0.430 37152.000 31 13.064 404.984 5.616 174.093
NOV 0.760 65664.000 30 15.945 478.336 11.318 339.549
DEC 0.820 70848.000 31 16.470 510.570 12.355 383.008
JAN 0.950 82080.000 31 17.610 545.922 14.602 452.647
FEB 0.980 84672.000 28 17.874 500.469 15.120 423.357
MAR 3.680 317952.000 31 42.141 1306.375 61.776 1915.053
93,APR 7.280 628992.000 30 76.191 2285.715 123.984 3719.517
MAY 29.400 2540160.000 31 327.875 10164.129 506.218 15692.743
JUN 2.860 247104.000 30 34.656 1039.680 47.606 1428.189
JUL 1.100 95040.000 31 18.929 586.809 17.194 532.999
AUG 0.290 25056.000 31 11.847 367.253 3.197 99.098
SEP 0.230 19872.000 30 11.326 339.784 2.160 64.797
OCT 0.250 21600.000 31 11.500 356.490 2.506 77.671
NOV 0.480 41472.000 30 13.499 404.982 6.480 194.397
DEC 0.990 85536.000 31 17.962 556.815 15.293 474.074
JAN 0.550 47520.000 31 14.110 437.397 7.690 238.375
FEB 0.820 70848.000 28 16.470 461.160 12.355 345.943
MAR 2.500 216000.000 31 31.402 973.448 41.386 1282.951
94,APR 8.470 731808.000 30 87.871 2636.137 144.547 4336.413
MAY 4.860 419904.000 31 53.089 1645.746 82.166 2547.155
JUN 4.000 345600.000 30 45.089 1352.682 67.306 2019.165
JUL 10.700 924480.000 31 110.330 3420.219 183.082 5675.527
AUG 1.270 109728.000 31 20.428 633.274 20.131 624.064
SEP 0.230 19872.000 30 11.326 339.784 2.160 64.797
OCT 1.290 111456.000 31 20.605 638.750 20.477 634.778
NOV 1.250 108000.000 30 20.252 607.549 19.786 593.565
DEC 3.360 290304.000 31 39.208 1215.453 56.246 1743.635
JAN 7.878 680659.200 31 82.034 2543.051 134.317 4163.838
FEB 7.968 688435.200 28 82.918 2321.703 135.873 3804.431
MAR 9.073 783907.200 31 93.871 2909.996 154.967 4803.975

Where:
Obs P [kg/day, Linear correlation] = 0.0002·Flow [m3/day] - 1.8145;
Obs P [kg/day, Polynomial correlation] = 1E-11·Flow [m3/day] + 0.0001·Flow [m3/day] + 9.335;
Obs P [kg/month] = Obs P [kg/day] · (Days/month).

Figure 6 Observed Monthly Phosphorus Load for the Period 1990-1995