Extrapolation of the LTE data for regional prediction of crop production and agro-environmental impacts in the Czech Republic with the EPIC-based modelling system

Křížová, K., Skalský, R. ORCID: https://orcid.org/0000-0002-0983-6897, Madaras, M., & Balkovič, J. ORCID: https://orcid.org/0000-0003-2955-4931 (2022). Extrapolation of the LTE data for regional prediction of crop production and agro-environmental impacts in the Czech Republic with the EPIC-based modelling system. In: EGU General Assembly 2022, 23-27 May 2022, Vienna.

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Abstract

The long-term crop trials (LTE) provide valuable insights into functioning of the crop systems under variety of crop management strategies. In particular, those field operations which in long run affect the soil organic carbon balance might be of an importance for the climate change impacts oriented research. Bonded strongly to the local site conditions, LTEs provide spatially limited information, not fully reflecting the needs of the large-scale inventories covering countries or big regions. Representing LTEs with a process-based model via locally calibrated model parameters and data, and subsequent upscaling of the model with regional data on climate, terrain, soil, and land use, provides a possible way for LTEs extrapolation to wider geographical domains. As a follow-up to the earlier work on formalising LTE records from several sites in Czechia with the EPIC model, the simulation infrastructure (EPIC-IIASA (CZ)) has been created for regional predictions of crop production and its agro-environmental impacts over the whole territory of Czech Republic (CZ). Conceptually, the EPIC-IIASA (CZ) has been designed based on the EPIC-IIASA global gridded crop modelling system. A set of 977 spatial simulation units (or typical fields, > 1 ha each), which represent a unique combination of an administrative unit (level LAU1), climate region, and soil region, has been compiled using CZ national data. Each simulation unit has been used for linking spatially explicit input data on i) climate, ii) site, iii) soil properties, and iv) crop management to the process-based model EPIC. As an output, various agro-environmental variables may be acquired and visualized geographically. Initially, the spatial infrastructure worked with fixed sowing and harvesting dates across all CZ regions. In order to get the full potential of the EPIC-IIASA (CZ), a calibration with regional planting scenarios was done. Agronomically relevant planting-harvesting windows scenarios were assessed based on the published data (MOCA report), this specifically for traditional production areas in CZ (CZ_R01: Maize growing; CZ_R02: Potato growing; CZ_R03: Cereal growing; CZ_R04: Forage growing; CZ_R05: Sugar beet growing). Since there was not any yield data available for the LAU1 level administrative regions, published LAU1 estimates of the potential yields were used for validation of the EPIC-IIASA (CZ) simulated rainfed and nutrient-unlimited yields. Both absolute simulated yields and the percentage of reported potential yields were displayed geographically and spatial pattern of the simulated values evaluated. Furthermore, longterm average and inter-annual variability of simulated yields were compared to the available statistical data at the NUTS3 administrative level. To date, calibration and validation of two crops, spring barley and winter wheat were successfully performed. Other crops will be calibrated in the next step, so that representative crop rotations could be constructed and used in EPIC-IIASA (CZ) setup to properly approximate the prevailing regional cropping systems in the simulations. Such a completely calibrated and validated crop modelling system could serve as a powerful tool for extrapolating impacts of different crop management strategies, well explored with LTEs, over the larger areas, and hence, provide valuable evidence-based inputs for decision-making support at regional and national levels in CZ.

Item Type:	Conference or Workshop Item (Paper)
Research Programs:	Biodiversity and Natural Resources (BNR) Biodiversity and Natural Resources (BNR) > Agriculture, Forestry, and Ecosystem Services (AFE)
Depositing User:	Luke Kirwan
Date Deposited:	18 May 2022 14:13
Last Modified:	18 May 2022 14:13
URI:	https://pure.iiasa.ac.at/18014

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