Probabilistic goal driven watershed management

Water quality management decisions are often based on objectives to achieve strict water quality standards generally defined by numerical values for constituents of interest. However, strict adherence to these qualitative standards is impossible in many instances. The current study proposes a probabilistic approach for water quality management that utilizes water quality standards as goals. A simulation-optimization model is used to achieve this objective. The simulation model is first calibrated and validated for a specific water quality constituent of interest and then is used to develop probability density function (PDF) of that constituent. A separate PDF based on water quality standards is derived and is referred to as required PDF. An optimization model is formulated to achieve the objective of minimizing the difference between derived and required PDF. To demonstrate this concept a Discrete volume method (DVM) based simulation model used for modeling the fate and transport of fecal coliform in streams is adopted and is linked with a genetic algorithm based optimization model. Two 8-digit USGS watersheds that comprise of several 11-digit USGS HUC watersheds in the Big Sandy region of southeastern Kentucky are used to assess the applicability of the model. Straight pipes and failing septic systems are identified as two main sources of pathogen impairment in this region and are used as decision variables in the management model. The management model can be used to estimate reductions in the contributions of point and non-point sources pathogen loads to achieve pre-set probabilistic goals.