Improving SWAT for simulating water and carbon fluxes of forest ecosystems

Yang, Qichun; Zhang, Xuesong

doi:10.1016/j.scitotenv.2016.06.238

Cited by 72 publications

(37 citation statements)

References 71 publications

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“…It is worthwhile to note that phenological changes in vegetation affect the biophysical and hydrological processes in the basin and thus play a key role in integrated hydrologic and ecosystem modelling (Jolly and Running, 2004;Kiniry and MacDonald, 2008;Shen et al, 2013;Strauch and Volk, 2013;Yang and Zhang, 2016;Yu et al, 2016). The leaf area index (LAI) -the area of green leaves per unit area of land -is a vegetation attribute commonly used in ecohydrological modelling, as it strongly correlates with the vegetation phe-nological development.…”

Section: Introductionmentioning

confidence: 99%

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

Alemayehu

Griensven

Woldegiorgis

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. The Soil and Water Assessment Tool (SWAT) is a globally applied river basin ecohydrological model used in a wide spectrum of studies, ranging from land use change and climate change impacts studies to research for the development of the best water management practices. However, SWAT has limitations in simulating the seasonal growth cycles for trees and perennial vegetation in the tropics, where rainfall rather than temperature is the dominant plant growth controlling factor. Our goal is to improve the vegetation growth module of SWAT for simulating the vegetation variables -such as the leaf area index (LAI) -for tropical ecosystems. Therefore, we present a modified SWAT version for the tropics (SWAT-T) that uses a straightforward but robust soil moisture index (SMI) -a quotient of rainfall (P ) and reference evapotranspiration (ET r ) -to dynamically initiate a new growth cycle within a predefined period. Our results for the Mara Basin (Kenya/Tanzania) show that the SWAT-Tsimulated LAI corresponds well with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI for evergreen forest, savanna grassland and shrubland. This indicates that the SMI is reliable for triggering a new annual growth cycle. The water balance components (evapotranspiration and streamflow) simulated by the SWAT-T exhibit a good agreement with remote-sensing-based evapotranspiration (ET-RS) and observed streamflow. The SWAT-T model, with the proposed vegetation growth module for tropical ecosystems, can be a robust tool for simulating the vegetation growth dynamics in hydrologic models in tropical regions.

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Section: Introductionmentioning

confidence: 99%

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

Alemayehu

Griensven

Woldegiorgis

et al. 2017

Hydrol. Earth Syst. Sci.

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“…Although we selected four climate models to account for uncertainties in climate projections, using more climate projections in the future will help further constrain uncertainties associated with climate change. Fourth, current algorithms in the SWAT forest module may have introduced uncertainties in simulating forest growth responses to climate change (Y. Wu & Liu, ; Yang & Zhang, ). Adding more mechanistic features to the SWAT plant module will help better simulate forest ecosystem dynamics in response to climate change and associated impacts on water and nutrient cycling.…”

Section: Discussionmentioning

confidence: 99%

“…We adjusted T-Base from 0°C to 8°C to better simulate timing of plant growth and associated carbon and water fluxes in cold seasons (Yang & Zhang, 2016). The default value of 0.3 for the leaf to biomass fraction (BIO_LEAF) in SWAT is much higher than field observations (Yang & Zhang, 2016). We decreased this parameter to 0.08 for deciduous and evergreen forests in the study area on the basis of observational data (Yang et al, 2018).…”

Section: The Swat Forest Module Improvementmentioning

confidence: 99%

“…Most previous investigations adopted default parameterization of the SWAT forest module and did not perform a detailed evaluation of SWAT performances in simulating forest ecosystems. Recent investigations improved SWAT simulation of forest ecosystems (Yang et al, 2018;Yang & Zhang, 2016). In Yang and Zhang (2016), we identified limitations in default SWAT in simulating forest carbon cycling and improved SWAT forest parameterization through model data intercomparison.…”

Section: Introductionmentioning

confidence: 99%

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Improving the SWAT forest module for enhancing water resource projections: A case study in the St. Croix River basin

Yang

Almendinger

Huang

et al. 2019

Hydrological Processes

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Insufficiently calibrated forest parameters of the Soil & Water Assessment Tool (SWAT) may introduce uncertainties to water resource projections in forested watersheds. In this study, we improved SWAT forest parameterization and phosphorus cycling representations to better simulate forest ecosystems in the St. Croix River basin, and we further examined how those improvements affected model projections of streamflow, sediment, and nitrogen export under future climate conditions. Simulations with improved forest parameters substantially reduced model estimates of water, sediment, and nitrogen fluxes relative to those based on default parameters. Differences between improved and default projections can be attributed to the enhanced representation of forest water consumption, nutrient uptake, and protection of soil from erosion. Better representation of forest ecosystems in SWAT contributes to constraining uncertainties in water resource projections. Results of this study highlight the importance of improving SWAT forest ecosystem representations in projecting delivery of water, sediment, and nutrients from land to rivers in response to climate change, particularly for watersheds with large areas of forests. Improved forest parameters and the phosphorus weathering algorithms developed in this study are expected to help enhance future applications of SWAT to investigate hydrological and biogeochemical consequences of climate change.

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“…While model simulation experiments are useful in disentangling the complex interactions among different environmental factors and ecological processes (Yang et al. , Yang and Zhang ), process‐based algorithms have been developed and applied to quantify contributions of multiple processes and factors to N 2 O emissions, as well as to project N 2 O emissions under alternative climate and management scenarios (Del Grosso et al. , Abdalla et al.…”

Section: Introductionmentioning

confidence: 99%

Enhancing the soil and water assessment tool model for simulating N ₂ O emissions of three agricultural systems

Yang

Abraha

Grosso

et al. 2017

Ecosyst Health Sustain

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Nitrous oxide (N 2 O) is a potent greenhouse gas (GHG) contributing to global warming, with the agriculture sector as the major source of anthropogenic N 2 O emissions due to excessive fertilizer use. There is an urgent need to enhance regional-/watershed-scale models, such as Soil and Water Assessment Tool (SWAT), to credibly simulate N 2 O emissions to improve assessment of environmental impacts of cropping practices. Here, we integrated the DayCent model's N 2 O emission algorithms with the existing widely tested crop growth, hydrology, and nitrogen cycling algorithms in SWAT and evaluated this new tool for simulating N 2 O emissions in three agricultural systems (i.e., a continuous corn site, a switchgrass site, and a smooth brome grass site which was used as a reference site) located at the Great Lakes Bioenergy Research Center (GLBRC) scale-up fields in southwestern Michigan. These three systems represent different levels of management intensity, with corn, switchgrass, and smooth brome grass (reference site) receiving high, medium, and zero fertilizer application, respectively. Results indicate that the enhanced SWAT model with default parameterization reproduced well the relative magnitudes of N 2 O emissions across the three sites, indicating the usefulness of the new tool (SWAT-N 2 O) to estimate long-term N 2 O emissions of diverse cropping systems. Notably, parameter calibration can significantly improve model simulations of seasonality of N 2 O fluxes, and explained up to 22.5%-49.7% of the variability in field observations. Further sensitivity analysis indicates that climate change (e.g., changes in precipitation and temperature) influences N 2 O emissions, highlighting the importance of optimizing crop management under a changing climate in order to achieve agricultural sustainability goals.Citation: Yang, Q., X. Zhang, M. Abraha, S. Del Grosso, G. P. Robertson, and J. Chen. 2017. Enhancing the soil and water assessment tool model for simulating N 2 O emissions of three agricultural systems. Ecosystem Health and Sustainability 3(2):e01259.

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Improving SWAT for simulating water and carbon fluxes of forest ecosystems

Cited by 72 publications

References 71 publications

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

Improving the SWAT forest module for enhancing water resource projections: A case study in the St. Croix River basin

Enhancing the soil and water assessment tool model for simulating N ₂ O emissions of three agricultural systems

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