12. Water Quality Modelling and Prediction by Jorge Arturo Hidalgo Toledo

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Water Quality Modelling and Prediction

7. Conclusions: Implementing a Water Quality Management Policy This chapter has provided only a brief introduction to some of the relationships contained in water quality models. As can be said for the other chapters as well, it summarizes a subject on which entire texts, and very good ones, have been written (see, for example, Chapra, 1997; McCutcheon, 1989; Orlob, 1983; Schnoor, 1996; Thomann and Mueller, 1987). Water quality modelling and management demand skill and data. Skill comes with experience. Sufficient expertise will not be gained by working just with the material introduced in this chapter. It serves only as an introduction to surface water quality models, their assumptions and their limitations. If accompanied by field data and uncertainty analysis, many existing models can be used to assist those responsible for developing water quality management plans in an adaptive implementation or management framework. Adaptive implementation or management will allow for both model and data improvements over time. Such approaches strive toward achieving water quality standards while relying on monitoring and experimentation to reduce uncertainty. This is often the only way one can proceed, given the complexity of the real world compared to the predictive models and the data and time usually available at the time a water quality analysis is needed. Starting with simple analyses and iteratively expanding data collection and modelling as the need arises is a reasonable approach. An adaptive management process begins with initial actions that have reasonable chances of succeeding. Future actions must be based on continued monitoring of the water body to determine how it responds to the actions taken. Plans for future regulation and public spending should be subject to revision as stakeholders learn more about how the system responds to actions taken. Monitoring is an essential aspect of adaptive water quality management and modelling (see Appendix B). Regardless of what immediate actions are taken, there may not be an immediate measurable response. For example, there may be significant lags between the time when actions are taken to reduce nutrient loads and the resulting changes in nutrient concentrations. This is especially likely if nutrients from past activities are tightly

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bound to sediments or if nutrient-contaminated groundwater has a long residence time before its release to surface water. For many reasons, lags between actions taken and responses must be expected. Water bodies should be monitored to establish whether the ‘trajectories’ of the measured water quality criteria point toward attainment of the designated use. Wasteload allocations will inevitably be required if quality standards are not being met. These involve costs. Different allocations will have different total costs and different distributions of those costs; hence they will have different perceived levels of fairness. A minimum-cost policy may result in a cost distribution that places most of the burden on just some of the stakeholders. But until such a policy is identified, one will not know this. An alternative may be to reduce loads from all sources by the same proportion. Such a policy has prevailed in the United States over the past several decades. Even though not very cost-effective from the point of view of water quality management, the ease of administration and the fulfilment of other objectives must have made such a policy politically acceptable, even though expensive. However, these types of wasteload allocations policies will not in themselves be sufficient for many of the ecosystem restoration efforts that are increasingly being made. Restoration activities are motivated in part by the services ecosystems provide for water quality management. Our abilities to include ecosystem components within water quantity and quality management models are at a fairly elementary level. Given the uncertainty, especially with respect to the prediction of how ecosystems will respond to water management actions, together with the need to take actions now, long before we can improve these capabilities, the popular call is for adaptive management. The trial and error aspects of adaptive management based on monitoring and imperfect models may not satisfy those who seek more definitive direction from water quality analysts and their predictive models. Stakeholders and responsible agencies seeking assurances that the actions taken will always work as predicted may be disappointed. Even the best predictive capabilities of science cannot ensure that an action that will lead to the attainment of designated uses will be initially identified. Adaptive management is the only reasonable option in most cases for allowing water quality management programmes to move forward in the face of considerable uncertainties.