Hydrological assessment and biogeochemical advancement of the Noah-MP land surface model
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Land surface models (LSMs) simulate the energy, momentum, water, and carbon balance of the soil-vegetation-atmosphere system. As a key component of weather and climate models, LSMs play an important role in weather prediction and climate projections. Rapid growth in LSM development has resulted in both the improvement of existing process representation and the addition of new processes and functionalities. However, it is a challenge to evaluate the accuracy of energy, water, and nutrient fluxes simulated by LSMs, due to the lack of observational data and the complexity of interactions and feedback among different processes. Additionally, climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading nutrient for causing eutrophication in water bodies. However, few LSMs include nitrogen dynamics and nitrogen leaching is usually not well parameterized; hence these LSMs are not feasible for applications-based modeling, particularly for land management and agricultural impacts. Therefore, this dissertation uses the Noah-MP LSM to study the following three questions. (1) How do recent developments in Noah-MP improve its performance in hydrological modeling, based on a case study for the Mississippi River Basin? (2) Compared to other similar LSMs, what are the advantages and disadvantages of Noah-MP in assessing the water balance over the conterminous U.S.? (3) After coupling the Fixation and Uptake of Nitrogen plant model and the Soil and Water Assessment Tool soil nitrogen dynamics into Noah-MP, can this coupled model characterize the major nitrogen fluxes and how the nitrogen dynamics affect the carbon and water simulations? The main scientific findings are as follows. (1) Noah-MP shows significant improvement in modeling the major hydrological variables such as runoff, groundwater, evapotranspiration, soil moisture, and terrestrial water storage (TWS), which is very likely due to the incorporation of some major improvements into Noah-MP, particularly an unconfined aquifer storage layer for groundwater dynamics and an interactive vegetation canopy for dynamic leaf phenology. (2) Compared to other three LSMs, Noah-MP provides the best performance in simulating soil moisture and is among the best in simulating TWS. (3) The new Noah-MP with nitrogen dynamics performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). (4) The addition of nitrogen dynamics in Noah-MP improves the modeling of the carbon and water cycles (e.g., net primary productivity and evapotranspiration).