Dynamic coupling of soil structure and gas fluxes measured with distributed sensor systems: implications for carbon modeling

该研究的目标是开发两种原位传感器系统，用于测量不同尺度的地下气体浓度和应变/湿度/温度/吸力，以提供气体通量和土壤结构的动态数据。一种是基于分布式光纤传感器（DFOS）系统，可以提供米到公里尺度的测量，而另一种是基于低功耗传感器与地面网状无线传感器网络（WSN）系统耦合，以分布式方式在选定的局部点提供数据。这两项技术目前正在加州大学伯克利分校（UCB）进行原型设计。开发的传感器系统将首先在科罗拉多矿业学院（CSM）独特的风洞-土壤实验设施中进行试验。我们提出了一种实验方案，旨在通过平衡降水事件引起的地下水引入和由大气扰动（温度、风速和相对湿度）控制的蒸发和蒸散损失来操纵土壤水分波动，从而在气候变化条件下做出更明智的生物地球化学预测和土壤结构变化。在可控的环境下，我们将量化所开发的传感器系统的精度误差。开发的系统也将在洛桑研究所（RR）的领域实施，以审查其在实际领域条件下的可行性。最终目标是提高对大气碳负荷如何受土壤结构变化影响的预测性理解。拟议的传感器开发和实验研究将导致土壤碳模型（如RR开发的RothC模型）的实质性改进。模型中的每个隔室都由一个一阶过程分解，并具有自己的特征速率。IOM隔室是抗分解的。该模型通过改变分解过程中产生的CO2和（BIO+HUM）之间的分配来调整土壤质地及其变化，而不是使用速率修正因子，例如用于温度的速率修正因子。此外，CO2总通量在很大程度上受根呼吸和土壤有机质（包括根际有机碳）微生物呼吸的控制，这些过程对土壤结构高度敏感。因此，在本研究中，我们假设土壤结构变化与土壤气体生成密切相关。我们将开发和实施测量两者的传感器系统，这反过来将使我们能够量化这种联系。这些新模型将在未来预测土壤管理对碳动态的影响，从而了解不同土壤管理策略（例如耕作）对土壤可持续性的影响。该研究将补充由BBSRC在国家能力计划和ISP资金流中支持的RR正在进行的实地研究；尤其是在向植物输送养分方面。项目中研究的过程预计将导致改进的配方，包括RR正在开发的多尺度，多物理场：(1)更合理地表示地表-地下耦合过程，(2)包括植被流体动力学和碳和养分分配，以及(3)纳入土壤和基因组支持的地下反应运输模型，这些模型具有明确和动态的微生物表示。该项目将导致该领域空间分布传感系统的发展，该系统可以(1)感知土壤结构的变化，(2)将这些变化与N2O、CH4、CO2和O2进出土壤的通量联系起来。

The goal of the proposed research is to develop two in-situ sensor systems that measure in-ground gas concentrations and strain/moisture/temperature/suction at different scales in order to provide data on the dynamics of gas flux and soil structure. One is based on distributed fiber optic sensor (DFOS) system that can provide measurements at meters to kilometers-scale, whereas the other is based on low-power sensor coupled with in-ground mesh-network wireless sensor network (WSN) system that provides data at selected local points in distributed manner. Both technologies are currently being prototyped at UC Berkeley (UCB). The developed sensor systems will be trialed first in the unique wind tunnel-soil experimental facility available at the Colorado School of Mines (CSM). We propose an experimental plan designed to manipulate soil moisture fluctuations by balancing subsurface water introduction through precipitation events and losses to evaporation and evapotranspiration as controlled by atmospheric perturbations (temperature, wind speed, and relative humidity) so as to make more informed biogeochemical predictions and soil structure changes under changing climate conditions. Under the controlled environment, we will quantify the precision errors of the developed sensor systems. The developed systems will also be implemented in the fields of Rothamsted Research (RR) to examine its feasibility in the actual field conditions. The ultimate goal is to improve the predictive understanding of how atmospheric carbon loading is affected by soil structure changes. The proposed sensor development and experimental research will lead to a substantial improvement of soil carbon models such as the RothC model developed at RR]. Each compartment in the model decomposes by a first-order process with its own characteristic rate. The IOM compartment is resistant to decomposition. The model adjusts for soil texture and its changes by altering the partitioning between CO2 evolved and (BIO+HUM) formed during decomposition, rather than by using a rate modifying factor, such as that used for temperature. Moreover, total CO2 effluxes are largely controlled by root respiration, and microbial respiration of soil organic matter including rhizospheric organic carbon and all of these processes are highly sensitive to soil structure. In this proposed research, we therefore hypothesize that soil structure change is strongly linked to soil gas generation. We will develop and implement sensor systems that measure both, which in turn will allow us to quantify the link. These new models will in the future allow the effects of soil management on carbon dynamics to be predicted and hence give an understanding of the impact of different soil management strategies (e.g. tillage) on soil sustainability. The research will complement ongoing field research at RR supported by the BBSRC in the National Capability scheme and in ISP funding streams; especially on the delivery of nutrients to plants. The processes to be studied in the project are expected to lead to improved formulations to include multi-scale, multi-physics under development at RR by: (1) more rationally representing the coupled surface-subsurface processes, (2) including vegetation hydrodynamics and carbon and nutrient allocation, and (3) incorporating soil and genome-enabled subsurface reactive transport models that have explicit and dynamic microbial representation. The project will lead to the development of spatially-distributed sensing systems in the field that can (1) sense changes in soil stricture and (2) link these changes to fluxes of N2O, CH4, CO2 and O2 into and from soils.