Editorial : Observing, Modeling and Understanding Processes in Natural and Managed Peatlands

Non peer reviewe

Assimilation of backscatter observations into a hydrological model: a case study in Belgium using ASCAT data

We investigated the possibilities of improving hydrological simulations by assimilating radar backscatter observations from the advanced scatterometer (ASCAT) in the hydrological model SCHEME using a calibrated water cloud model (WCM) as an observation operator. The WCM simulates backscatter based on soil moisture and vegetation data and can therefore be used to generate observation predictions for data assimilation. The study was conducted over two Belgian catchments with different hydrological regimes: the Demer and the Ourthe catchment. The main differences between the two catchments can be summarized in precipitation and streamflow levels, which are higher in the Ourthe. The data assimilation method adopted here was the ensemble Kalman filter (EnKF), whereby the uncertainty of the state estimate was described via the ensemble statistics. The focus was on the optimization of the EnKF, and possible solutions to address biases introduced by ensemble perturbations were investigated. The latter issue contributes to the fact that backscatter data assimilation only marginally improves the overall scores of the discharge simulations over the deterministic reference run, and only for the Ourthe catchment. These performances, however, considerably depend on the period considered within the 5 years of analysis. Future lines of research on bias correction, the data assimilation of soil moisture and backscatter data are also outlined

Drought and Waterlogging Stress Regimes in Northern Peatlands Detected Through Satellite Retrieved Solar-Induced Chlorophyll Fluorescence

The water table depth (WTD) in peatlands determines the soil carbon decomposition rate and influences vegetation growth, hence the above-ground carbon assimilation. Here, we used satellite-observed Solar-Induced chlorophyll Fluorescence (SIF) as a proxy of Gross Primary Production (GPP) to investigate water-related vegetation stress over northern peatlands. A linear model with interaction effects was used to relate short- and long-term anomalies in SIF with WTD anomalies and the absolute WTD. Most locations showed the occurrence of drought and waterlogging stress though regions with exclusively waterlogging or drought stress were also detected. As a spatial median, minimal water-related vegetation stress was found for a WTD of -0.22 m (short-term) and -0.20 m (long-term) (+/- 0.01 m, 95% confidence interval of statistical uncertainty). The stress response observed with SIF is supported by an analysis of in situ GPP data. Our findings provide insight into how changes in WTD of northern peatlands could affect GPP under climate change.Water table depth is an important variable influencing the carbon cycle and vegetation growth in northern peatlands. In this paper, the impact of changing wetness conditions on vegetation growth over peatlands was studied through satellite measurements of solar-induced fluorescence (SIF), which is a radiation signal emitted by vegetation during photosynthesis. Previous studies over ecosystems on mineral soil, that is, not over peatland, suggested a response of SIF to drought conditions. In our study, it was shown that peatland vegetation experiences moisture-related growth stress under both very wet and very dry conditions, which might reduce the photosynthesis efficiency and the ability to capture and store CO2. Stress due to drought conditions was detected for peatlands in the south of the Western Siberian Lowlands and the Boreal Plains. Stress due to prolonged wet conditions occurred for example, in the north of the Western Siberian Lowlands and the north of the Hudson Bay Lowlands.Spaceborne Solar-Induced Fluorescence (SIF) data was used to analyze soil moisture-related vegetation stress regimes in northern peatlandsFor most locations, waterlogging as well as drought stress regimes occurred and alternated depending on peatland water level dynamicsThe SIF-based stress response observations are supported by in situ data of Gross Primary Productio

Global Soil Moisture Estimation from L-Band Satellite Data: The Impact of Radiative Transfer Modeling in Assimilation and Retrieval Systems

The SMOS and SMAP missions have collected a wealth of global L-band Brightness temperature (Tb) observations. The retrieval of surface Soil moisture estimates, and the estimation of other geophysical Variables, such as root-zone soil moisture and temperature, via data Assimilation into land surface models largely depends on accurate Radiative transfer modeling (RTM). This presentation will focus on various configuration aspects of the RTM (i) for the inversion of SMOS Tb to surface soil moisture, and (ii) for the forward modeling as part of a SMOS Tb data assimilation System to estimate a consistent set of geophysical land surface Variables, using the GEOS-5 Catchment Land Surface Model

Advancing global & regional reanalyses

This report outlines the structure of and summarizes the recommendations made at the 5th International Conference on Reanalysis (ICR5), attended by 259 participants from 37 countries, in Rome (Italy), on 13-17 November 2017. It first summarizes the conference structure. Then, the key recommendations of ICR5 are given for the five main conference topics: production; observations (data rescue and preparation); data assimilation methods; quality assurance of reanalysis; and applications in science, services, and policymaking. Lastly, five high-level recommendations are proposed to managing agencies on how best to advance the field of reanalyses, which serves tens of thousands of users, via enhanced research, development, and operations

Infiltration from the pedon to global grid scales: an overview and outlook for land surface modelling

Infiltration in soils is a key process that partitions precipitation at the land surface in surface runoff and water that enters the soil profile. We reviewed the basic principles of water infiltration in soils and we analyzed approaches commonly used in Land Surface Models (LSMs) to quantify infiltration as well as its numerical implementation and sensitivity to model parameters. We reviewed methods to upscale infiltration from the point to the field, hill slope, and grid cell scale of LSMs. Despite the progress that has been made, upscaling of local scale infiltration processes to the grid scale used in LSMs is still far from being treated rigorously. We still lack a consistent theoretical framework to predict effective fluxes and parameters that control infiltration in LSMs. Our analysis shows, that there is a large variety in approaches used to estimate soil hydraulic properties. Novel, highly resolved soil information at higher resolutions than the grid scale of LSMs may help in better quantifying subgrid variability of key infiltration parameters. Currently, only a few land surface models consider the impact of soil structure on soil hydraulic properties. Finally, we identified several processes not yet considered in LSMs that are known to strongly influence infiltration. Especially, the impact of soil structure on infiltration requires further research. In order to tackle the above challenges and integrate current knowledge on soil processes affecting infiltration processes on land surface models, we advocate a stronger exchange and scientific interaction between the soil and the land surface modelling communities

Expansion of Agriculture in Northern Cold-Climate Regions: A Cross-Sectoral Perspective on Opportunities and Challenges

Agriculture in the boreal and Arctic regions is perceived as marginal, low intensity and inadequate to satisfy the needs of local communities, but another perspective is that northern agriculture has untapped potential to increase the local supply of food and even contribute to the global food system. Policies across northern jurisdictions target the expansion and intensification of agriculture, contextualized for the diverse social settings and market foci in the north. However, the rapid pace of climate change means that traditional methods of adapting cropping systems and developing infrastructure and regulations for this region cannot keep up with climate change impacts. Moreover, the anticipated conversion of northern cold-climate natural lands to agriculture risks a loss of up to 76% of the carbon stored in vegetation and soils, leading to further environmental impacts. The sustainable development of northern agriculture requires local solutions supported by locally relevant policies. There is an obvious need for the rapid development of a transdisciplinary, cross-jurisdictional, long-term knowledge development, and dissemination program to best serve food needs and an agricultural economy in the boreal and Arctic regions while minimizing the risks to global climate, northern ecosystems and communities

Perspective on satellite-based land data assimilation to estimate water cycle components in an era of advanced data availability and model sophistication

The beginning of the 21st century is marked by a rapid growth of land surface satellite data and model sophistication. This offers new opportunities to estimate multiple components of the water cycle via satellite-based land data assimilation (DA) across multiple scales. By resolving more processes in land surface models and by coupling the land, the atmosphere, and other Earth system compartments, the observed information can be propagated to constrain additional unobserved variables. Furthermore, access to more satellite observations enables the direct constraint of more and more components of the water cycle that are of interest to end users. However, the finer level of detail in models and data is also often accompanied by an increase in dimensions, with more state variables, parameters, or boundary conditions to estimate, and more observations to assimilate. This requires advanced DA methods and efficient solutions. One solution is to target specific observations for assimilation based on a sensitivity study or coupling strength analysis, because not all observations are equally effective in improving subsequent forecasts of hydrological variables, weather, agricultural production, or hazards through DA. This paper offers a perspective on current and future land DA development, and suggestions to optimally exploit advances in observing and modeling systems

Structural and Functional Loss in Restored Wetland Ecosystems

In restored wetland ecosystems with apparently natural hydrology and biological structure, biogeochemical function may remain degraded, even a century after restoration efforts