Session programme

The importance of linking the soil and climate modeling is gaining importance as evidenced by the recent IPCC special report on Climate Change and Land (SRCCL - 2019).

The climate and soil/critical zone communities have been engaged in various activities to improve integration of soil and subsurface processes in current land surface models (for example via the GEWEX-SoilWat initiative, ISMC activities and other avenues). We want to build on these efforts; hence, this session seeks contributions in the general area of soil process representation (water- and heat dynamics, as well as biogeochemical processes) in land-surface models, including studies focusing on bridging scales between traditional soil profiles and processes at scales relevant to climate modeling. Contributions on new ways to improve soil information inputs (e.g. more realistic soil maps, novel pedotransfer functions, machine learning) to Earth system models including systematic evaluation of model performance with revised parameters are of particular interest. Links to ground water processes, vegetation processes (e.g. plant water stress and root water uptake) and dynamics, and observational or remote sensing studies of soil processes and energy- and water balance fluxes at large scales are also welcomed.

The processes that shape and alter the critical zone include the processes that develop soil and its properties. The horizons that are the vehicle for describing soil formation and soil state also result from these processes. For this reason, modelling soil formation and modelling the development of the critical zone are strongly connected, though both modelling communities rarely interact.

This session focuses on studies applying soil or soil-landscape models that mimic, reconstruct and predict critical zone development or soil development. Such models may include weathering and new formation of minerals, water/solute/colloid and gas transport, various forms of turbation, conversion of elements between pools, erosion, sedimentation and hillslope processes. A central theme is to assess what are essential processes that should be included in these models as function of their utilization domain, how far models have advanced today in this respect, and what should be future priorities.

This session calls for contributions that focus on modelling approaches that balance processes in soil and plant towards a system’s view on plant nutrition, growth and development and related environmental issues, such as pollution, over-use of resources and depletion in ecosystem functions and services. Especially rhizosphere process modelling that engages with bridging of micro-meter processes to meter-scale ecosystem functioning are welcomed, but also modelling approaches that connect global-scale available soil information and data products to mechanistic, one-dimensional simulation models of soil processes and plant physiology.

Human society during the past several centuries has created a large number of chemical substances that often find their way into the environment. Since many of these chemicals represent a significant health risk when they enter the food chain, contamination of both surface and subsurface water supplies has become a major issue. Modern agriculture uses an unprecedented number of chemicals, both in plant and animal production. A broad range of fertilizers, pesticides, and fumigants are now routinely applied to agricultural lands, thus making agriculture one of the most important sources for non-point source pollution. Agriculture also increasingly uses a variety of pharmaceuticals and hormones in animal production many of which, along with pathogenic microorganisms, are being released to the environment through animal waste. Meanwhile, modern industrial and mining activities are releasing varieties of pollutants to surrounding environment. Environmental behaviors of these chemicals from industrial contamination sites are complicate and their risk are hard to regulate.

Mathematical models are critical components of any effort to optimally understand and quantify site-specific subsurface water flow and solute transport processes. Models can be helpful tools for designing, testing, and implementing soil, water, and crop management practices that minimize soil and water pollution. Models are equally needed for designing or remediating industrial contamination sites, waste disposal sites and landfills, or for long-term risk management of nuclear waste repositories, mining areas and groundwater polluted by industrial activities. A large number of specialized numerical models now exist to simulate the different processes at various levels of approximation and for different applications.

This session welcomes contributions on recent advances in numerical modeling of the physicochemical (hydrogeological, geochemical, and microbiological) processes affecting the fate and transport of subsurface pollutants (ranging from organic pollutants, heavy metals, and radionuclides to pathogens and nanoparticles). Investigations of emerging contaminants are especially welcome. We encourage broad participation bridging traditional research areas, including groundwater, vadose zone, groundwater-surface water interactions, biology, chemistry, and soil physics.

Understanding and predicting the dynamics of soil biogeochemistry is critical for agriculture and climate. There is a central scaling issue that models are well poised to address. Many of the mechanisms governing soil dynamics occurs on the micro-scale(for example: microbial metabolism, mineral-organic interactions, extracellular enzyme kinetics, aggregate dynamics, and multi-phasic flow. Environmental drivers occur on a larger plot scale (including precipitation regimes, temperature variation, rooting zone, litter fall, and agricultural land management). And finally fluxes of interest are generally regional scales (including questions about farm or regional land management, and global scale carbon cycling).

This session will focus on studies designed to address questions of scale in soil biogeochemistry, especially how to connect knowledges from different scales and integrate them in models.

Erosion can cause serious agricultural and environmental damages by impairing landscape, producing soil and land loss, reducing agricultural productivity, inducing water pollution, and threatening waterways and hydraulic structures. It also plays a significant role in the biogeochemical cycles of carbon, nitrogen, and phosphorus by redistributing significant amounts of nutrients over the Earth’s surface. The multi-scale and non-linear nature of the processes involved in runoff generation and in soil erosion and the high spatial and temporal resolution of the required input data create a challenging modeling environment. Improving our basic understanding and modeling capabilities on water erosion are required to assess its impact on the soil and water resources and to evaluate the efficiency and the cost of the measures for resolving the problems.

Aiming at advancing our ability of modeling soil erosion across spatial scales, this session focuses on recent studies supporting surface runoff and soil erosion modeling on natural or disturbed landscapes, as well as their environmental effects. We invite submissions concerning surface runoff and/or water erosion processes, at the plot, hillslope, watershed, regional, or global scales. Studies may include analyses of monitoring or experimental data applying recent technologies, or modeling investigations using physics based, conceptual, data driven, or other types of novel approaches, to improve the assessment of the multi-scale, multidisciplinary processes, and their coupling with biogeochemical cycles as well as soil functioning.

Heterogeneity in the landscape, such as soil types, dynamic soil properties, temporal evolution of the vegetation cover and root growth, among others, generates heterogeneous water fluxes entering and traveling through the soil. Interactions between vegetation, soil properties, water and gas fluxes pose challenges and often calls for a lot of creativity when measuring and modelling the –often interlinked - processes. Machine learning approaches will help recognize correlations between the occurring processes, but to increase our understanding of the confusing blueprint of landscape heterogeneity, we will need to combine it with modelling and measurement approaches. This session aims to bring together modelling approaches to better characterise landscape heterogeneity and understand its role. It is combined with a focus on the scope of different measurement methodologies that are being used in soil science, and the extent to which these play a role in the perceived heterogeneity of landscapes.

Soil functions play an important role in ecosystems services. They are themselves determined by interactions of the ensemble of soil processes. Examples for soil functions are biomass production, water storage and filtering, and carbon sequestration.

Evaluating the state of these functions and evaluating the impact of management decisions on these functions is essential for sustainable soil and land management. In this session, we want to discuss related modelling approaches and evaluation tools. We also welcome modelling approaches that aim at predicting the impact of management options on these functions. This session wants to bring together experts on soil functions working at very different scales. This may reach from the local evaluation at a soil profile or a farmer's field all the way to global decision support systems.

At present large uncertainty exists in predicting carbon climate feedbacks, as current models do not agree whether the land surface will remain as a sink or become a source of atmospheric carbon under changing climate and land use. Current ecosystem and earth system models need appropriate representation of soil carbon dynamics and their environmental controllers in order to reduce the existing uncertainty in predicting carbon climate feedbacks. In this session, we invite contributions from an ecosystem to earth system scales that incorporate field observations, remote sensing, and laboratory experiments into geospatial and process-based models to represent unique soil carbon processes that operate at large spatial scales. We encourage submissions that demonstrate: 1) emergent environmental controllers of soil carbon storage and dynamics, and 2) data-model integration to address critical uncertainties that exists in the carbon dynamics of mineral and organic soils.

Soil modeling are witnessing an unprecedented increase in data volume, opening up new opportunities to advance physical understanding, improve earth system modeling, and increase the predictive ability of climate and earth surface processes at a range of scales. Mining the data for new knowledge presents also new challenges and opportunities to the soil science community instigating the development or adaptation of tools from mathematics, statistics, and computer science for the problems at hand. This session provides a forum for scientists to exchange ideas on the topic such as, but not limited to the following (1) innovative data analytics approach in soil modeling, (2) using machine learning and other innovative approaches in predicting soil hydraulic properties, soil transport parameters, thermal parameters, biogeochemical parameters, etc., (3) machine learning coupled with field data and numerical data, (4) advances in theoretical and applied studies in soil modeling along with their predictability and uncertainty, and (5) development of soil related data and its application in soil modeling. Scientists working in soil modeling sciences related to the above topics are encouraged to participate.