Evaluation of Uncertainty Propagation Predictions in River Water Quality Modeling

doi:10.21203/rs.3.rs-386752/v1

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Evaluation of Uncertainty Propagation Predictions in River Water Quality Modeling

https://doi.org/10.21203/rs.3.rs-386752/v1

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The uncertainty on model predictions to evaluate river water quality is often high to delineate appropriate conclusions. This study presents the statistical evaluation of the water quality modeling system Hydrologic Simulation Program FORTRAN as a tool to improve monitoring planning and mitigate uncertainty in water quality predictions. It also presents findings in determining HSPF model’s sensitivity analysis concerning water quality predictions. The computer model was applied to Ave River watershed, Portugal. The hydrology was calibrated at two stations from January 1990 to December 1994 and validated from January 1995 to December 1999. A two-step statistical evaluation framework is presented based on the most common hydrology criteria for model calibration and validation and, a Monte Carlo methodology uncertainty evaluation approach coupled with multi parametric sensitivity analyses to assess model uncertainty and parameter sensitivity. Fourteen HSPF water quality parameters probability distributions are used as input factors for the Monte Carlo simulation. The simulation results for in stream fecal coliform concentrations was found to be most sensitive to parameters that represent first order decay rate and surface runoff that removes 90 percent of fecal coliform from pervious land surface rather than accumulation and maximum storage rates. Regarding oxygen governing process (DO, BOD, NO₃, PO₄), benthal oxygen demand and nitrification/denitrification rates were the most sensitive parameters.

Environmental Chemistry

Toxicology

Water Resources

Uncertainty Analysis

Sensitivity Analysis

River Water Quality Modeling

HSPF

Table 1. Range and distribution of uncertain of HSPF water quality parameters and their respective description.

Parameter	Description	Range	Distribution
FSTDEC	First order decay rate of bacteria (day^-1)	(0.1,5)	Uniform
WSQOP	Rate of surface runoff that will remove 90% of stored fecal coliform from pervious land use	(0.5,1.0)	Uniform
WSQOP*	Rate of surface runoff that will remove 90% of stored quality constituent from pervious land use	(0.5,2.4)	Uniform
KBOD20	BOD decay rate at 20ºC (hr^-1)	(0.0001,1)	Uniform
KODSET	Rate of BOD settling (ft hr^-1)	(0,1)	Uniform
BENOD	Benthal oxygen demand at 20ºC (mg m^-2 hr^-1)	(0,500)	Uniform
REAK	Empirical constant to calculate the reaeration coefficient (hr^-1)	(0.01,2)	Uniform
KTAM20	Nitrification rate of ammonia at 20ºC (hr^-1)	(0.001,1)	Uniform
KNO220	Nitrification rate of nitrites at 20ºC (hr^-1)	(0.001,1)	Uniform
KNO320	Nitrate denitrification rate at 20ºC (hr^-1)	(0.001,1)	Uniform
ACQOP**	Accumulation of fecal coliform on pervious land per day (CFU day^-1)	(2×10⁸,2×10¹⁰,2×10¹²)	Triangular
SQOLIM Factor	Factor which is multiplied to ACQOP to obtain maximum accumulation of fecal coliform on pervious land	(2,10)	Triangular
ACQOPNO₃**	Accumulation of nitrates on pervious land per day (lb ac^-1 day^-1)	(0.05,30)	Triangular
ACQOPPO₄**	Accumulation of nitrates on pervious land per day (lb ac^-1 day^-1)	(0.001,1)	Triangular
* Constituents: nitrates, orthophosphates and biochemical oxygen demand; ** For the months of January.

Table 2a. Statistical criteria results for calibration and validation at Ave River station.

Parameters	D_v	E	R²	MSE	RMSE	R4MS4E	RVE	IOAD	RSR
Calibration
Q_daily	0.10	0.54	0.67	1.31	0.66	1.36	0.09	0.90	0.68
Q_monthly	0.10	0.69	0.74	0.80	0.40	0.68	0.09	0.92	0.55
T	0.00	0.70	0.72	7.99	2.83	4.05	0.00	0.92	0.55
FC	-0.13	0.71	0.72	8.0×10⁷	8966	13327	-0.16	0.90	0.54
DO	-0.10	0.38	0.53	3.47	1.86	2.61	-0.11	0.82	0.79
BOD₅	0.07	0.63	0.64	6.76	2.60	3.22	0.06	0.89	0.61
NO₃	-0.01	0.60	0.68	3.02	1.74	2.16	-0.01	0.90	0.63
PO₄	0.09	0.72	0.75	0.11	0.32	0.42	0.08	0.93	0.53
Validation
Q_daily	-0.09	0.72	0.75	1.28	0.64	1.16	-0.10	0.93	0.53
Q_monthly	-0.09	0.87	0.90	0.62	0.31	0.41	-0.10	0.97	0.37
T	-0.03	0.69	0.73	7.08	2.66	3.78	-0.04	0.92	0.56
FC	-0.12	0.33	0.34	3.6×10⁷	6031	9839	-0.13	0.73	0.82
DO	-0.01	0.56	0.58	1.92	1.39	1.76	-0.01	0.87	0.66
BOD₅	0.08	0.28	0.21	5.79	2.41	2.80	0.08	0.69	0.96
NO₃	-0.08	0.37	0.46	9.34	3.06	3.96	-0.09	0.81	0.79
PO₄	-0.13	0.63	0.70	0.12	0.35	0.46	-0.15	0.91	0.61

Table 2b. Statistical criteria results for calibration and validation at Este River station.

Parameters	D_v	E	R²	MSE	RMSE	R4MS4E	RVE	IOAD	RSR
Calibration
Q_daily	0.04	0.60	0.64	0.38	0.19	0.45	0.04	0.89	0.63
Q_monthly	0.04	0.92	0.93	0.11	0.06	0.09	0.04	0.98	0.28
T	0.02	0.50	0.77	7.50	2.74	3.54	0.02	0.91	0.71
FC	-0.13	0.43	0.46	9.6×10⁷	9815	16489	-0.15	0.81	0.75
DO	-0.01	0.42	0.67	1.02	1.01	1.18	-0.01	0.88	0.76
BOD₅	0.00	0.43	0.62	1.68	1.30	1.72	0.00	0.88	0.75
NO₃	-0.02	0.42	0.61	69.51	8.34	10.78	-0.02	0.87	0.76
PO₄	-0.02	0.55	0.56	0.04	0.19	0.29	-0.02	0.86	0.67
Validation
Q_daily	0.08	0.58	0.64	0.28	0.14	0.34	0.07	0.89	0.65
Q_monthly	0.08	0.70	0.81	0.01	0.01	0.01	0.08	0.94	0.54
T	0.00	0.41	0.68	8.70	2.95	3.57	0.00	0.89	0.77
FC	-0.31	0.64	0.77	4.5×10⁷	6690	9671	-0.45	0.86	0.60
DO	0.02	0.49	0.56	1.02	1.01	1.31	0.02	0.86	0.72
BOD₅	0.01	0.45	0.54	2.04	1.43	1.75	0.01	0.85	0.74
NO₃	-0.11	0.27	0.66	67.28	8.20	8.68	-0.12	0.86	0.86
PO₄	-0.13	0.63	0.70	0.12	0.35	0.46	-0.15	0.91	0.61

Table 3. Behavioral parameter sets from the uncertainty analysis and respective contingency.

	FC	NO₃	PO₄	BOD	DO
Parameter Sets
Ave	309	66	85	276	623
Este	112	63	104	38	62
Contingency
Ave	29%	36%	48%	61%	58%
Este	27%	48%	27%	26%	28%

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