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Stream temperatures have been increasing worldwide, in some cases reaching unsustainable levels for aquatic life. Riparian revegetation has been identified as a strategy for managing stream temperatures by blocking direct solar radiation. In this study, the effects of riparian vegetation on stream temperatures were included within the Soil & Water Assessment Tool (SWAT) model through a shade factor parameter. An equilibrium temperature approach was used to integrate the shade factor in an energy balance context. The stream temperature sub-model was improved using the new energy balance equation and integrated into SWAT. Unlike existing models, the modified SWAT model enables improved representation of two processes – mass and heat transfer – that influence stream temperature change and enables simulation of shading and its effects on stream temperatures at sub-basin scales. The updated SWAT model was tested in Dairy McKay Watershed, OR, USA, for four scenarios: current conditions of riparian vegetation, full restoration, efficient restoration, and no vegetation. The model calibration under current riparian vegetation showed good performance (Nash–Sutcliffe efficiency NSE > 0.74). Stream temperature reduction and number of days with stream temperatures above survival limits (NDSTASL) for aquatic species were also evaluated as measures of riparian shade performance. Findings showed average temperature reductions of 0.91 ∘ C (SD = 0.69 ∘ C) and reductions in NDSTASL of 17.1 d over a year for full riparian restoration and average reductions of 0.86 ∘ C (SD = 0.67 ∘ C) and 16.2 d for efficient restoration. Notwithstanding the similar benefits, efficient restoration was 14.4 % cheaper than full riparian vegetation restoration. [ABSTRACT FROM AUTHOR]

Stream temperatures have been increasing worldwide, in some cases, reaching unsustainable levels for aquatic life. Riparian re-vegetation has been identified as a strategy for managing stream temperatures by blocking direct solar radiation. In this study, the effects of riparian vegetation on stream temperatures were included within the Soil Water Assessment Tool (SWAT) model through a shade factor parameter. An equilibrium temperature approach was used to integrate the shade factor in an energy balance context. The stream temperature sub-model was improved using the new energy balance equation and integrated into SWAT. Unlike existing models, the modified SWAT model developed enables improved representation of two processes - mass and heat transfer - that influence stream temperature change and enables simulation of shading and its effects on stream temperatures at sub-basin scales. The updated SWAT model was tested in Dairy McKay Watershed, OR, USA, for four scenarios: current conditions of riparian vegetation, full restoration, efficient restoration, and no vegetation. The model calibration under current riparian vegetation showed good performance (NSE>0.74). Stream temperature reduction and number of days with stream temperatures above survival limits (NDSTASL) for aquatic species were also evaluated as measures of riparian shade performance. Findings showed average temperature reductions of 0.91 °C (SD = 0.69 °C) and reductions in NDSTASL of 17.1 days over a year for full riparian restoration, and average reductions of 0.86 °C (SD = 0.67 °C) and 16.2 days for efficient restoration. Notwithstanding the similar benefits, efficient restoration was 14.4% cheaper than full riparian vegetation restoration. [ABSTRACT FROM AUTHOR]

Optimization for water resources management typically requires many simplifying assumptions about the definition and characteristics of the policy or design application in order to express decision makers' criteria as mathematical objectives and constraints. However, real-world applications often involve important subjective information that cannot be reflected in mathematical expressions accurately or completely. This can result in mathematically optimized solutions that are less meaningful or desirable to decision makers. To address this issue, this paper presents the standard interactive genetic algorithm (SIGA) methodology that enables human decision makers to effectively analyze subjective information that is not easily quantifiable and make decisions about the quality of a design based on their preferences. These decisions are used as continuous run-time subjective feedback, along with the mathematically defined objectives and constraints, to search for optimal designs that reflect both quantitative and qualitative objectives. Although this interactive optimization methodology is applicable for any water resources planning and management problems, this paper focuses on exploring the benefits of such an approach within the domain of groundwater monitoring design. Systematic procedures and guidelines for designing a SIGA are presented, along with proposed strategies for improving the performance of SIGA. The SIGA approach is also compared with a noninteractive genetic algorithm strategy for a real-world application, and the advantages and limitations of the interactive strategy are examined. DOI: 10.1061/(ASCE)0733-9496(2008)134:6(538) CE Database subject headings: Water resources: Groundwater management; Monitoring; Interactive systems; Optimization; Decision making; Computation.