Model Library

Exploration of Long-tErM Nutrient Trajectories for Nitrogen (ELEMeNT-N)

Model name: Exploration of Long-tErM Nutrient Trajectories for Nitrogen (ELEMeNT-N)

Developed by: Van Meter et al (2017) (Last update: 2017)

Model type: Dynamic, parsimonious, process-based, biogeochemical and hydrological, watershed model

History: ELEMeNT-N is the modified version of ELEMeNT model.

Computational requirements: Windows/Linux, MATLAB or Python programming environments. The model does not demand high-performance computing resources.

Software requirements: GIS: optional.

Link to download model: Contact Dr. Van Meter (vanmeterkvm@psu.edu)

Capabilities and Limitations:

Capabilities

  • It focuses on nitrogen processes;
  • It has the capability to clearly differentiate between biogeochemical and hydrological legacy impacts;
  • ELEMeNT-N employs a parsimonious modeling approach to estimate the amount of biogeochemical legacy mass stored in the source zone and the amount being leached from it at any given time;
  • It can predict long-term nitrogen trends in streams, soil, and groundwater using minimal parameters and input data (Van Meter et al., 2017, 2018; Basu et al., 2022).

Limitations

  • Not open-source;
  • ELEMeNT-N is limited in its ability to address long-term legacy N dynamics as it ignores temporal changes in soil organic N (SON) mineralization rates (Zhou et al., 2023).
  • Limited by the model structure and data availability, N aged >10 years consisted of two components: N inputs from more than 10 years ago and the natural background N pool (Zhou et al., 2023).
  • ELEMeNT-N simulates N only.

Model Inputs and Outputs:

Inputs

Geometry data, LULC data, Soil data, Hydrological data, N mass balance data, N-related data, Management data

Outputs

N-related parameters’ simulation (N loadings, Soil organic N, Riverine N, N surplus, NO₃-N)

Examples:

References

Van Meter, K. J., Byrnes, D. K., & Basu, N. B. (2023). 
Memory and management: Competing controls on long-term nitrate trajectories in U.S. rivers. Global Biogeochemical Cycles, 37, e2022GB007651. 
https://doi.org/10.1029/2022GB007651

Chang, S. Y., Zhang, Q., Byrnes, D. K., Basu, N. B., & Van Meter, K. J. (2021). Chesapeake legacies: The importance of legacy nitrogen to improving Chesapeake Bay water quality. Environmental Research Letters, 16(8), 085002. https://doi.org/10.1088/1748-9326/ac0d7b

Objectives

This study aimed to answer these questions: (1) What changes have occurred in watershed-scale N surplus magnitudes over the last four decades (1970–2017)? (2) How are riverine N concentrations changing in response to changing N inputs? (3) What are the controls on relationships between watershed N inputs and riverine N export?

This study aimed to answer these questions: (1) What is the relationship between N inputs and N load across the Chesapeake region, and how does this relationship vary, both spatially and temporally across the study watersheds? (2) How do changing relationships between surplus N and N load relate to accumulation and depletion trajectories for legacy N? (3) To what extent do N legacies contribute to time lags in achieving water quality goals? (4) How long will it take to achieve desired reductions in N loading?