Melannie D. Hartman

DAYCENT and its land surface submodel: description and testing

Abstract A land surface submodel was developed for the daily version of the CENTURY ecosystem model (DAYCENT). The goal of DAYCENT to simulate soil N 2 O, NO x , and CH 4 fluxes for terrestrial ecosystems determined the structure and processes represented in the land surface model. The land surface model was set up to simulate daily dynamics of soil water and temperature from a multi-layered soil system (0–1, 1–4, 4–15, 15–30 cm, etc.) and included surface runoff and above field capacity soil water dynamics during intense rainfall events and snowmelt into frozen soils. The comparison of the simulated soil water content (0–10 cm) with observed data from four sites was quite favorable (squared correlation coefficient— γ 2 =0.87, 0.65, 0.86 and 0.58) and the simulated results were comparable for the soil temperature model ( r 2 =0.92 and 0.95 for minimum and maximum 10 cm soil temperatures). Detailed soil water and temperature data during snowmelt time periods and following rainfall events are needed to fully evaluate the performance of the water flow model.

Implementation of a Two-Way Interactive Atmospheric and Ecological Model and Its Application to the Central United States

A coupled Regional Atmospheric Modeling System (RAMS) and ecosystem (CENTURY) modeling system has been developed to study regional-scale two-way interactions between the atmosphere and biosphere. Both atmospheric forcings and ecological parameters are prognostic variables in the linked system. The atmospheric and ecosystem models exchange information on a weekly time step. CENTURY receives as input air temperature, precipitation, radiation, wind speed, and relative humidity simulated by RAMS. From CENTURY-produced outputs, leaf area index, and vegetation transimissivity are computed and returned to RAMS. In this way, vegetation responses to weekly and seasonal atmospheric changes are simulated and fed back to the atmospheric‐ land surface hydrology model. The coupled model was used to simulate the two-way biosphere and atmosphere feedbacks from 1 January to 31 December 1989, focusing on the central United States. Validation was performed for the atmospheric portion of the model by comparing with U.S. summary-of-the-day meteorological station observational datasets, and for the ecological component by comparing with advanced very high-resolution radiometer remote-sensing Normalized Difference Vegetation Index datasets. The results show that seasonal vegetation phenological variation strongly influences regional climate patterns through its control over land surface water and energy exchange. The coupled model captures the key aspects of weekly, seasonal, and annual feedbacks between the atmospheric and ecological systems. In addition, it has demonstrated its usefulness as a research tool for studying complex interactions between the atmosphere, biosphere, and hydrosphere.

Simulations of snow distribution and hydrology in a mountain basin

We applied a version of the Regional Hydro-Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind-driven sublimation to Loch Vale Watershed (LVWS), an alpine-subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind-driven sublimation was necessary to predict moisture losses.

Evaluating litter decomposition in earth system models with long-term litterbag experiments: an example using the Community Land Model version 4 (CLM4)

Decomposition is a large term in the global carbon budget, but models of the earth system that simulate carbon cycle-climate feedbacks are largely untested with respect to litter decomposition. We tested the litter decomposition parameterization of the community land model version 4 (CLM4), the terrestrial component of the community earth system model, with data from the long-term intersite decomposition experiment team (LIDET). The LIDET dataset is a 10-year study of litter decomposition at multiple sites across North America and Central America. We performed 10-year litter decomposition simulations comparable with LIDET for 9 litter types and 20 sites in tundra, grassland, and boreal, conifer, deciduous, and tropical forest biomes using the LIDET-provided climatic decomposition index to constrain temperature and moisture effects on decomposition. We performed additional simulations with DAYCENT, a version of the CENTURY model, to ask how well an established ecosystem model matches the observations. The results show large discrepancy between the laboratory microcosm studies used to parameterize the CLM4 litter decomposition and the LIDET field study. Simulated carbon loss is more rapid than the observations across all sites, and nitrogen immobilization is biased high. Closer agreement with the observations requires much lower decomposition rates, obtained with the assumption that soil mineral nitrogen severely limits decomposition. DAYCENT better replicates the observations, for both carbon mass remaining and nitrogen, independent of nitrogen limitation. CLM4 has low soil carbon in global earth system simulations. These results suggest that this bias arises, in part, from too rapid litter decomposition. More broadly, the terrestrial biogeochemistry of earth system models must be critically tested with observations, and the consequences of particular model choices must be documented. Long-term litter decomposition experiments such as LIDET provide a real-world process-oriented benchmark to evaluate models.

Sensitivity of a high‐elevation rocky mountain watershed to altered climate and CO2

We explored the hydrologic and ecological responses of a headwater mountain catchment, Loch Vale watershed, to climate change and doubling of atmospheric CO2 scenarios using the Regional Hydro-Ecological Simulation System (RHESSys). A slight (2°C) cooling, comparable to conditions observed over the past 40 years, led to greater snowpack and slightly less runoff, evaporation, transpiration, and plant productivity. An increase of 2°C yielded the opposite response, but model output for an increase of 4°C showed dramatic changes in timing of hydrologic responses. The snowpack was reduced by 50%, and runoff and soil water increased and occurred 4–5 weeks earlier with 4°C warming. Alpine tundra photosynthetic rates responded more to warmer and wetter conditions than subalpine forest, but subalpine forest showed a greater response to doubling of atmospheric CO2 than tundra. Even though water use efficiency increased with the double CO2 scenario, this had little effect on basin-wide runoff because the catchment is largely unvegetated. Changes in winter and spring climate conditions were more important to hydrologic and vegetation dynamics than changes that occurred during summer.

EFFECTS OF LAND COVER, WATER REDISTRIBUTION, AND TEMPERATURE ON ECOSYSTEM PROCESSES IN THE SOUTH PLATTE BASIN

Over one-third of the land area in the South Platte Basin of Colorado, Nebraska, and Wyoming, has been converted to croplands. Irrigated cropland now comprises 8% of the basin, while dry croplands make up 31%. We used the RHESSys model to compare the changes in plant productivity and vegetation-related hydrological processes that occurred as a result of either land cover alteration or directional temperature changes (−2°C, +4°C). Land cover change exerted more control over annual plant productivity and water fluxes for converted grasslands, while the effect of temperature changes on productivity and water fluxes was stronger in the mountain vegetation. Throughout the basin, land cover change increased the annual loss of water to the atmosphere by 114 mm via evaporation and transpiration, an increase of 37%. Both irrigated and nonirrigated grains became active earlier in the year than shortgrass steppe, leading to a seasonal shift in water losses to the atmosphere. Basin-wide photosynthesis increased by 80...

Intra-annual and interannual variability of ecosystem processes in shortgrass steppe.

We used a daily time step ecosystem model (DAYCENT) to simulate ecosystem processes at a daily, biweekly, monthly, and annual time step. The model effectively represented variability of ecosystem processes at each of these timescales. Evolution of CO2 and N2O, NPP, and net N mineralization were more responsive to variation in precipitation than temperature, while a combined temperature-moisture decomposition factor (DEFAC) was a better predictor than either component alone. Having established the efficacy of CENTURY at representing ecosystem processes at multiple timescales, we used the model to explore interannual variability over the period 1949–1996 using actual daily climate data. Precipitation was more variable than temperature over this period, and our most variable responses were in CO2 flux and NEP. Net ecosystem production averaged 6 g C m−2 yr and varied by 100% over the simulation period. We found no reliable predictors of NEP when compared directly, but when we considered NEP to be lagged by 1 year, predictive power improved. It is clear from our study that NEP is highly variable and difficult to predict. The emerging availability of system-level C balance data from a network of flux towers will not only be an invaluable source of information for assessments of global carbon balance but also a rigorous test for ecosystem models.

Chapter 16 – Simulated effects of land use, soil texture, and precipitation on N gas emissions using DAYCENT

This chapter discusses simulated effects of land use; soil texture; and precipitation on N gas emissions using DAYCENT. The chapter describes the N gas flux submodel used in the DAYCENT ecosystem model and demonstrates the ability of DAYCENT to simulate the low N gas emissions observed from native soils, the intermediate emissions associated with dryland agriculture, and the high emissions observed for irrigated agricultural soils. DAYCENT has been used to compare N gas emissions from soils for native range grass, winter wheat conventional till and no till, winter wheat/corn/fallow no till, irrigated corn and irrigated silage cropping. NO x made up the majority of N gas fluxes in all cases followed by N 2 O and N 2 . Soil water inputs, tillage, timing of crop/fallow periods, and fertilizer application interact to control N gas emissions so generalizations regarding land use are difficult to make. Switching to no till without changing the winter wheat cropping schedule resulted in higher N 2 O emissions because the increased soil water content induced by no till supported higher denitrification rates. Finally, the soil water savings associated with no till also allows a reduction in the fallow period and the 3-year winter wheat rotations had lower N 2 O and NO x emissions than the 2-year winter wheat/fallow systems considered.

Improvement and validation of a daily soil temperature submodel for freezing/thawing periods.

The soil temperature submodel of the daily version of the CENTURY ecosystem model, DAYCENT, has been improved for freezing/thawing conditions in soils. The simulation of the soil heat propagation in the model is based on the Fourier heat flow equation and approximated by use of the explicit finite difference scheme. In our study, we propose a tipping bucket algorithm to incorporate the discontinuous freezing/thawing process in the model by means of a calculated fusion energy pool. Daily average, maximum and minimum soil temperatures for each soil layer are estimated. The soil thermal diffusivity for each soil layer is simulated by the method of De Vries using upper and lower limits as well as a correction factor. A correction factor was optimized for the tipping bucket approximation of the freezing/thawing process. The model was tested and validated at three different sites with different climates and soils and showed good agreement with measured soil temperatures during winter periods. The mean deviation for maximum soil temperatures at 10 cm depth during the winter period was less than 1 °C for all locations; for the minimum temperatures the mean deviation was slightly higher. At a depth of 20 cm, mean deviations were higher but can nevertheless be seen as showing good results for the given approximations.

Impact of historical land-use changes on greenhouse gas exchange in the U.S. Great Plains, 1883-2003.

European settlement of North America has involved monumental environmental change. From the late 19th century to the present, agricultural practices in the Great Plains of the United States have dramatically reduced soil organic carbon (C) levels and increased greenhouse gas (GHG) fluxes in this region. This paper details the development of an innovative method to assess these processes. Detailed land-use data sets that specify complete agricultural histories for 21 representative Great Plains counties reflect historical changes in agricultural practices and drive the biogeochemical model, DAYCENT, to simulate 120 years of cropping and related ecosystem consequences. Model outputs include yields of all major crops, soil and system C levels, soil trace-gas fluxes (N2O emissions and CH4 consumption), and soil nitrogen mineralization rates. Comparisons between simulated and observed yields allowed us to adjust and refine model inputs, and then to verify and validate the results. These verification and validation exercises produced measures of model fit that indicated the appropriateness of this approach for estimating historical changes in crop yield. Initial cultivation of native grass and continued farming produced a significant loss of soil C over decades, and declining soil fertility led to reduced crop yields. This process was accompanied by a large GHG release, which subsided as soil fertility decreased. Later, irrigation, nitrogen-fertilizer application, and reduced cultivation intensity restored soil fertility and increased crop yields, but led to increased N2O emissions that reversed the decline in net GHG release. By drawing on both historical evidence of land-use change and scientific models that estimate the environmental consequences of those changes, this paper offers an improved way to understand the short- and long-term ecosystem effects of 120 years of cropping in the Great Plains.