Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Using genetic algorithms to calibrate a water quality model.
AU - Liu, Shuming
AU - Butler, David
AU - Brazier, Richard E.
AU - Heathwaite, A. Louise
AU - Khu, Soon-Thiam
PY - 2007/3/15
Y1 - 2007/3/15
N2 - With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.
AB - With the increasing concern over the impact of diffuse pollution on water bodies, many diffuse pollution models have been developed in the last two decades. A common obstacle in using such models is how to determine the values of the model parameters. This is especially true when a model has a large number of parameters, which makes a full range of calibration expensive in terms of computing time. Compared with conventional optimisation approaches, soft computing techniques often have a faster convergence speed and are more efficient for global optimum searches. This paper presents an attempt to calibrate a diffuse pollution model using a genetic algorithm (GA). Designed to simulate the export of phosphorus from diffuse sources (agricultural land) and point sources (human), the Phosphorus Indicators Tool (PIT) version 1.1, on which this paper is based, consisted of 78 parameters. Previous studies have indicated the difficulty of full range model calibration due to the number of parameters involved. In this paper, a GA was employed to carry out the model calibration in which all parameters were involved. A sensitivity analysis was also performed to investigate the impact of operators in the GA on its effectiveness in optimum searching. The calibration yielded satisfactory results and required reasonable computing time. The application of the PIT model to the Windrush catchment with optimum parameter values was demonstrated. The annual P loss was predicted as 4.4 kg P/ha/yr, which showed a good fitness to the observed value.
KW - Diffuse pollution
KW - Genetic algorithm
KW - Model calibration
KW - Phosphorus Indicators Tool
U2 - 10.1016/j.scitotenv.2006.12.042
DO - 10.1016/j.scitotenv.2006.12.042
M3 - Journal article
VL - 374
SP - 260
EP - 272
JO - Science of the Total Environment
JF - Science of the Total Environment
SN - 0048-9697
IS - 2-3
ER -