Location: Water Management and Systems ResearchTitle: Advances in the science and technology of simulating water, nutrient, soil and plant interactions and dynamics in space and time
|KIPKA, HOLM - Colorado State University|
|DAVID, OLAF - Colorado State University|
|Erskine, Robert - Rob|
|VALIYA-VEETTIL, ANOOP - Colorado State University|
|ARABI, MAZDAK - Colorado State University|
Submitted to: Environmental Modelling & Software
Publication Type: Abstract Only
Publication Acceptance Date: 5/24/2020
Publication Date: N/A
Interpretive Summary: The Agricultural Ecosystems Services (AgES) model simulates topographically based process interactions between physical hydrology, plant growth and development, and nitrogen processes at multiple scales in agricultural and mixed land-use watersheds. Advances in both the science and technology will be presented in 10 areas: (1) plant uptake of water and nitrogen, (2) layered soil hydrology affecting infiltration, percolation and capillary rise, (3) lateral flow through soils, tile drainage and groundwater, (4) crop seedling emergence and developmental stages; (5) code development for the Object Modeling System, (6) AgES deployment in the Cloud Services Innovation Platform; (7) on-line Catchment areas delineation with Cadel, (8) Landuse and Agricultural Management Practices web-Service with LAMPS, (9) cloud computing for broadly parallel uncertainty analysis and model calibration (in progress), and (11) input file pre-checking to improve the user experience and hopefully reduce frustration in the initial learning curve. These features will be demonstrated using case studies in Colorado and Iowa. Future work will allow for user-specified sub-daily simulation of hydrology and transport, testing effects of atmospheric carbon dioxide on plant-water interactions, and improved plant modeling with sub-daily meteorology at fine spatial resolutions.
Technical Abstract: The Agricultural Ecosystems Services (AgES) distributed watershed model is being developed as a component-based model for continuous daily simulation. Current case studies use AgES to simulate space-time patterns of soil moisture and infrequent runoff events in a dryland field-scale watershed in northern Colorado, contributions of irrigated agriculture to a mixed-landuse watershed near metropolitan Denver, and tile drainage contributing to high nitrate loads in Iowa, USA. These watersheds (56 ha to 581 km2) provide comparative studies to address model complexity across various scales with different types and amounts of data. Key advances include enhanced process simulation (1) coupling plant uptake of water and nitrogen, including partitioning transpiration and canopy/soil evaporation, (2) coupled soil layer conductance and storage controls on infiltration, percolation and capillary rise, (3) interactions between lateral interflow, tile drainage and groundwater, (4) crop seedling emergence and phenological stages; model framework (5) Object Modeling System compliant code, (6) leveraging the Cloud Services Innovation Platform for deployment; integrated tools (7) online Catchment areas delineation, Cadel, (8) Landuse and Agricultural Management Practices web-Service, LAMPS, and cloud computing for broadly parallel (9) parameter sampling and uncertainty analysis, and (10) model calibration (in progress). Each AgES run employs limited parallelization on a single computer, depending upon the watershed topology, while sampling and calibration have potential indefinite parallel computing over multiple (virtual) machines. Finally, (11) AgES includes input data checking with user-assisted adjustments and corrections to improve the user experience. These features will be demonstrated using the aforementioned case studies in Colorado and Iowa. Future work will allow for user-specified sub-daily simulation of hydrology and transport, testing of atmospheric CO2 effects on plant-water interactions, and new and/or improved plant modeling with sub-daily meteorology at fine spatial resolutions. Keywords: Multiscale modelling; agricultural watersheds; process interactions; user-friendly tools; cloud computing.