Helmholtz Centre for Environmental Research - UFZ

About: Helmholtz Centre for Environmental Research - UFZ is a facility organization based out in Leipzig, Germany. It is known for research contribution in the topics: Population & Species richness. The organization has 3230 authors who have published 9880 publications receiving 394385 citations.

Reply on RC2

Abstract: Abstract. Temperate forest ecosystems play a crucial role in governing global carbon and water cycles. However, unprecedented global warming presents fundamental alterations to the ecological functions (e.g., carbon uptake) and biophysical variables (e.g., leaf area index) of forests. The quantification of forest carbon uptake, gross primary productivity (GPP), as the largest carbon flux has a direct consequence on carbon budget estimations. Part of this assimilated carbon stored in leaf biomass is related to the leaf area index (LAI), which is closely linked to and is of critical significance in the water cycle. There already exist a number of models to simulate dynamics of LAI and GPP; however, the level of complexity, demanding data, and poorly known parameters often prohibit the model applicability over data-sparse and large domains. In addition, the complex mechanisms associated with coupling the terrestrial carbon and water cycles poses a major challenge for integrated assessments of interlinked processes (e.g., accounting for the temporal dynamics of LAI for improving water balance estimations and soil moisture availability for enhancing carbon balance estimations). In this study, we propose a parsimonious forest canopy model (PCM) to predict the daily dynamics of LAI and GPP with few required inputs, which would also be suitable for integration into state-of-the-art hydrologic models. The light use efficiency (LUE) concept, coupled with a phenology submodel, is central to PCM (v1.0). PCM estimates total assimilated carbon based on the efficiency of the conversion of absorbed photosynthetically active radiation into biomass. Equipped with the coupled phenology submodel, the total assimilated carbon partly converts to leaf biomass, from which prognostic and temperature-driven LAI is simulated. The model combines modules for the estimation of soil hydraulic parameters based on pedotransfer functions and vertically weighted soil moisture, considering the underground root distribution, when soil moisture data are available. We test the model on deciduous broad-leaved forest sites in Europe and North America, as selected from the FLUXNET network. We analyze the model's parameter sensitivity on the resulting GPP and LAI and identified, on average, 10 common sensitive parameters at each study site (e.g., LUE and SLA). The model's performance is evaluated in a validation period, using in situ measurements of GPP and LAI (when available) at eddy covariance flux towers. The model adequately captures the daily dynamics of observed GPP and LAI at each study site (Kling–Gupta efficiency, KGE, varies between 0.79 and 0.92). Finally, we investigate the cross-location transferability of model parameters and derive a compromise parameter set to be used across different sites. The model also showed robustness with the compromise single set of parameters, applicable to different sites, with an acceptable loss in model skill (on average ±8 %). Overall, in addition to the satisfactory performance of the PCM as a stand-alone canopy model, the parsimonious and modular structure of the developed PCM allows for a smooth incorporation of carbon modules to existing hydrologic models, thereby facilitating the seamless representation of coupled water and carbon cycle components, i.e., prognostic simulated vegetation leaf area index (LAI) would improve the representation of the water cycle components (i.e., evapotranspiration), while GPP predictions would benefit from the simulated soil water storage from a hydrologic model.

Reply on RC1

Abstract: Soil structure in terms of the spatial arrangement of pores and solid is highly relevant for most physical, biochemical processes in soil. While this is known for long a scientific approach to quantify soil structural characteristics was also missing for long. This was due to its buried nature but also due to the three-dimensional complexity. During the last two decades, tools to acquire full 3D images of undisturbed soil became more and more available and a number of powerful software tools were developed to reduce the complexity to a set of meaningful numbers. However, the standardization of soil structure analysis for a better comparability of the results is not well developed and the accessibility of required computing facilities and software is still limited. At this stage we introduce an open access Soil Structure Library (https://structurelib.ufz.de/) which offers well-defined soil structure analyses for X-ray CT data sets uploaded by interested scientists. At the same time, the aim of this library is to serve as an open data source for real pore structures as developed in a wide spectrum of different soil types under different site conditions all over the globe. By combining pore structure metrics with essential soil information requested during upload (e.g. bulk density, texture, organic carbon content\ldots), this Soil Structure Library can be harnessed towards data mining and development of soil structure based pedotransfer functions. In this paper we describe the architecture of the Soil Structure Library and the provided metrics. This is complemented by an example how the data base can be used to address new research questions.

Utilizing Cosmic Ray data as input for neutron-based soil moisture measurement

Abstract: <p>Neutrons on Earth interact with the soil and are substantially moderated by hydrogen atoms. Since the reflected neutron flux is a function of the soil water content, cosmic-ray neutron measurements above the ground can be used to estimate the average field soil moisture. Thus, if the local incoming neutron flux and the abundance of nearby hydrogen pools are known, the reflected neutron flux could be modeled and compared to observed detector count rates. However, the incoming neutrons are secondaries produced by interacting energetic Galactic Cosmic Rays (GCRs) in the atmosphere. The total neutron flux on the ground depends on the solar modulation-dependent GCR flux, the geomagnetic position, and the altitude within the atmosphere. So far, measurements of either the Jungfraujoch neutron monitor (NM) or a NM of similar cutoff rigidity have been used and altered to estimate the neutron flux at the position of each neutron detector. In this contribution we present a new method based on the Dorman function to directly compute the local neutron flux using remote neutron monitor data.</p><p>We received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 870405</p>

Water management assessment with text mining

Abstract: Water allocation during droughts is a challenge for policymakers, often addressed through participatory approaches. The implications of this governance mode are understudied as long-term records of the decision-making processes are often unavailable. We use natural language processing (NLP) and network analysis to extract information on water allocation decisions and climate-related issues from meeting minutes of river basin stakeholders. To test this approach, we considered the minutes of 1100 meetings held between 1997 and 2021 in the twelve basin committees of Ceará, Brazil. This region has a long history of droughts, which have strongly influenced water policies and politics. The river basin committee is currently composed of representatives of governmental and non-governmental institutions and deliberates on the water management process. To identify conflicts and relevant issues discussed during the meetings, we created a topic modeling approach consisting of: (1) sentence embedding using SBERT, (2) dimensionality reduction using UMAP, and (3) sentence clustering using K-means. Based on this, we calculated the topic frequency in each committee over time and normalized it by the number of documents registered each year. We also detected the topics mentioned in the same document to build network graphs of co-occurring topics. By using named entity recognition and dependency parsing, we identified the main actors involved during these meetings. Findings indicate that the most common topics were related to 'organic farming', 'fish mortality in reservoirs' and 'structural problems in water infrastructure'. The enhancement of water use monitoring - to identify potential water right violations - seems to be the preferred strategy to cope with droughts. During droughts, stakeholders appear to be more concerned about urban water supply than agriculture demand. We use historical data on water permit granting and water use charging to validate this finding. We also see an increase in climate-informed decisions over time, which became more frequent as new droughts affected the region. In summary, the proposed approach allows exploiting existing text data in order to identify the spatio-temporal patterns of topics related to water allocation. These data are often underexplored due to difficulties in analysing large amounts of text using conventional tools. Hence, text analysis offer exciting new opportunities for research in the field of water management.