Global sensitivity analyses of key riparian nitrogen models. (December 2022)

• Record Type: Journal Article
• Authors: Buhr, Daniel X.; Lammers, Roderick W.; Bledsoe, Brian P.
• Is Part Of: Environmental modelling & software. Volume 158(2022)
• Publication Date: 2022-12
• Subjects: Riparian zone -- Nitrogen cycling -- REMM -- SWAT+ -- Sensitivity analysis -- Numerical modeling; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2022.105542
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Riparian zones can effectively reduce excess nitrogen loading to streams. Modeling nitrogen retention in riparian zones is useful, especially at larger scales. We evaluated select riparian nitrogen models for their robustness in representing hydrology, vegetation, soils, nutrients, and channel morphodynamics. We used global, time-varying sensitivity analyses of REMM (Riparian Ecosystem Management Model) and SWAT+ (Soil and Water Assessment Tool+) to identify the most influential parameters for calculating water table depth and nitrogen processes. Both REMM and SWAT+ were sensitive to topographic and soil parameters such as slope and soil layer thickness, although spatial and temporal scale and hydroclimatic conditions affected parameter sensitivity. Neither model was sensitive to stream channel depth, which is known to affect riparian hydrology and nitrogen cycling. It is necessary to incorporate stream morphodynamics like channel change into both riparian-scale and watershed-scale nitrogen models to provide useful management tools for addressing excessive nitrogen loading in stream networks. Highlights: Global sensitivity analyses identified influential parameters for nitrogen loading. Model controls varied among slope, soils, and reaction kinetics. Sensitivity changed depending on spatial and temporal scale and hydroclimatic condition. REMM and SWAT + missed the role of stream depth in hydrologic and nitrogen processes. Improved modeling of riparian-stream connections is needed for nitrogen management.