A comprehensive dataset of vegetation states, fluxes of matter and energy, weather, agricultural management, and soil properties from intensively monitored crop sites in western Germany

Abstract

Abstract. The development and validation of hydroecological land-surface models to simulate agricultural areas require extensive data on weather, soil properties, agricultural management, and vegetation states and fluxes. However, these comprehensive data are rarely available since measurement, quality control, documentation, and compilation of the different data types are costly in terms of time and money. Here, we present a comprehensive dataset, which was collected at four agricultural sites within the Rur catchment in western Germany in the framework of the Transregional Collaborative Research Centre 32 (TR32) “Patterns in Soil–Vegetation–Atmosphere Systems: Monitoring, Modeling and Data Assimilation”. Vegetation-related data comprise fresh and dry biomass (green and brown, predominantly per organ), plant height, green and brown leaf area index, phenological development state, nitrogen and carbon content (overall > 17 000 entries), and masses of harvest residues and regrowth of vegetation after harvest or before planting of the main crop (> 250 entries). Vegetation data including LAI were collected in frequencies of 1 to 3 weeks in the years 2015 until 2017, mostly during overflights of the Sentinel 1 and Radarsat 2 satellites. In addition, fluxes of carbon, energy, and water (> 180 000 half-hourly records) measured using the eddy covariance technique are included. Three flux time series have simultaneous data from two different heights. Data on agricultural management include sowing and harvest dates as well as information on cultivation, fertilization, and agrochemicals (27 management periods). The dataset also includes gap-filled weather data (> 200 000 hourly records) and soil parameters (particle size distributions, carbon and nitrogen content; > 800 records). These data can also be useful for development and validation of remote-sensing products. The dataset is hosted at the TR32 database (https://www.tr32db.uni-koeln.de/data.php?dataID=1889, last access: 29 September 2020) and has the DOI https://doi.org/10.5880/TR32DB.39 (Reichenau et al., 2020).

Plant phenotyping relevance

植物のバイオマス、草丈、LAI、フェノロジーなどの再利用可能な形質データを含む包括的データセットを構築し、リモートセンシング手法の開発・検証にも利用できるため、植物フェノタイピングデータセットとして中心的です。

Code and data availability

This is a data description paper whose core contribution is a public plant-phenotyping dataset (vegetation states, biomass, LAI, phenology, fluxes, weather, management, soil) hosted at the TR32 database with a DOI. The dataset is directly downloadable via the authors' public URLs; no code or models are described.