Improving the use of crop models for risk assessment and climate change adaptation

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Our analysis drew on the other papers in this special issue, and on our experience in the UK Climate Change Risk Assessment 2017 and the MACSUR, AgMIP and ISIMIP projects. The criteria were used to assess how improvements could be made to the framing of climate change risks, and to outline the good practice and new developments that are needed to improve risk assessment. Key areas of good practice include: i. the development, running and documentation of crop models, with attention given to issues of spatial scale and complexity; ii. the methods used to form crop-climate ensembles, which can be based on model skill and/or spread; iii. the methods used to assess adaptation, which need broadening to account for technological development and to reflect the full range options available. The analysis highlights the limitations of focussing only on projections of future impacts and adaptation options using pre-determined time slices. Whilst this long-standing approach may remain an essential component of risk assessments, we identify three further key components: 1. Working with stakeholders to identify the timing of risks. What are the key vulnerabilities of food systems and what does crop-climate modelling tell us about when those systems are at risk? 2. Use of multiple methods that critically assess the use of climate model output and avoid any presumption that analyses should begin and end with gridded output. 3. Increasing transparency and inter-comparability in risk assessments. Whilst studies frequently produce ranges that quantify uncertainty, the assumptions underlying these ranges are not always clear. We suggest that the contingency of results upon assumptions is made explicit via a common uncertainty reporting format; and/or that studies are assessed against a set of criteria, such as those presented in this paper

Climate change impact assessment for four key crops in the Flemish Region, Belgium

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Hoe goed boeren we nog in 2050?

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Crop Responses to Climate Change: Impact on Agricultural Production and the Soil Water Balance in the Flemish Region of Belgium

On a global scale, increasing atmospheric CO2 concentrations ([CO2]) and the associated process of global warming cause climatic changes. They include increased air temperatures, altered rainfall patterns and a higher occurrence of extreme weather episodes. In Belgium, expected climatic changes include higher temperatures year round, wetter winters and drier summers. Agricultural production and its available water resources are highly vulnerable to climatic changes. The magnitude and direction of the climate change impact on agricultural production and the soil water balance depend on location and environment. Generally, elevated [CO2] benefit crop production by stimulating photosynthesis and simultaneously reducing crop transpiration (through stomatal closure). Decreases in rainfall can lead to water stress for crops and drier soils. But also floods and changes in rainfall intensity can be harmful for agricultural fields. Temperature increases lead to a higher evaporative demand of the atmosphere. If temperatures rise to supra-optimal temperatures, crop production is at risk. In temperate regions at mid latitude however, moderate rises in air temperature extend the length of the suitable growing period and allow to grow late maturing cultivars with a higher production potential. In this research, the impact of combined changes in weather variables and [CO2] on four important crops in the Flemish Region of Belgium was assessed with process-based crop models, driven by future weather projections from climate models. First, scenarios of future local-scale weather were generated for the study area. Scenarios were constructed by downscaling climate signals from two ensembles of global (GCMs, from the Coupled Model Intercomparison Project (CMIP3)) and regional climate models (RCMs, from the EU-ENSEMBLES project (ENS)) by the stochastic weather generator LARS-WG. All models used in this research projected temperature increases but the CMIP3-based scenarios were generally more pronounced than the ENS-based scenarios. For precipitation, projected trends in change were less univocal. Next, the AquaCrop model was selected as impact model and prepared for the assessment study. AquaCrop is a functional, multi-crop model that is principally water-driven and simulates crop development and production. At the core of the model is the biomass production, which is simulated in exchange for water transpired by the developing crop canopy. The proportional factor between transpiration and biomass production is the water productivity parameter. To augment the understanding of and adapt the model for crop responses to elevated [CO2], a statistical meta-analysis of research results of free air CO2 enrichment (FACE) studies was performed. The most prominent analysis results were the positive correlation between [CO2] and biomass/yield production and the negative correlation between [CO2] and evapotranspiration. They lead to a substantial increase in water productivity for crops (for both C3 andC4type crops). Additionally, changes in root:shoot ratio and phenology were apparent. Based on the results of the meta-analysis, a correction factor was introduced in AquaCrop to correct transpiration downwards with increasing [CO2]. Additionally, a flexible response of the water productivity parameter to elevated [CO2] was introduced to capture the variation in crop responsiveness associated with crop sink strength. Limited sink strength of a crop in the field, e.g. as a result of sub-optimal nitrogen availability, can suppress the crop responsiveness to CO2. The research results suggest that considering crop sink strength and variation in responsiveness is equally relevant to considering climatic changes and elevated [CO2] when assessing future crop production. Indicative values for crop responsiveness (representing sink strength) were proposed for all crops currently available in the AquaCrop database. Subsequently, a global sensitivity analysis of the AquaCrop model output to changes in model parameters was performed, and the model was calibrated and validated for the temperate maritime climate of Belgium. The sensitivity analysis consisted of a Morris screening followed by an EFAST analysis. The analysis revealed important interaction effects between parameters and some irrelevant parameters, for which suggestions for model simplification were formulated. In general, the model s yield output sensitivity to important parameters depends strongly on environmental conditions but thematic categories of parameters that merit attention according to different local conditions can be distinguished. The calibration and validation of the AquaCrop model was performed based on field data collected on farmers fields. AquaCrop could be satisfactorily calibrated and validated for winter wheat (Triticum aestivum L.), maize (Zea mays L.), potato (Solanum tubersosum L.) and sugar beet (Beta vulgaris L.) in the actual temperate maritime climate of Belgium. Given the earlier successful validation of the model in warmer conditions, under more severe levels of water stress and at elevated [CO2], and given the model s physiological base, it was assumed that AquaCrop can be used under the future climate conditions. Winter cereals form an exception because particularities characteristic to these winter crops, including dormancy, cold hardening and vernalization, are summarized in AquaCrop. Yet, it turned out that without explicit consideration of these processes, simulated crop development responds too strongly to the projected future temperatures increase. Thus, the wheat model Sirius, which explicitly considers these processes, was selected to perform winter wheat simulations under future climate conditions. Finally, the impact assessment of climatic changes on the four major crops in the Flemish Region was performed by using the climate projections as input for the impact models AquaCrop and Sirius. Even though impacts vary among crops, environment and projected climatic changes, there are clear trendsvisible. Advantages of climate change dominate over negative effects for mean crop production in Belgium towards the middle of this century. Elevated [CO2] benefits production of winter wheat, potato and sugar beet and counteracts potential negative effects of supra-optimal temperatures and precipitation changes. Maize benefits less from elevated [CO2] than the C3 crops and can suffer from drought stress under the projected climatic changes. Adaption of cultivation management (including shifted sowing dates and late maturing cultivars) shows additionally potential to augment the mean production level of spring-sown crops. Yet, climatic changes and adapted management also have an impact on interannual yield stability, which decreases generally for spring-sown crops. Even though the projected climatic changes may lead to mean production gains in the Flemish Region of Belgium, the soil water balance can be negatively affected. Often, this increases the incidence of drought stress for crops, which increases the crop s vulnerability and affects the yield stability negatively. Only for winter wheat, changes in climate affect much less the soil water balance and interannual yield stability.This research does not pretend to represent the future reality. Instead, it provides probable future trends, which may be expected in agriculture in the coming decades under a changing climate. Uncertainty related to climate scenario generation propagates to the impact assessment. Although we can only speculate that RCM-based scenarios may be more advanced than GCM-based scenarios for agricultural impact assessments, the research results demonstrate definitely that the choice of one or another ensemble of climate models (with different resolution) adds to the overall uncertainty of climate change impact assessments in agriculture.Problem statement and research questions Chapter 1 Climate scenarios Chapter 2 Crop responses to CO2 Chapter 3 The AquaCrop model Chapter 4 Modelling the responses to CO2 with AquaCrop Chapter 5 Global sensitivity analysis of AquaCrop Chapter 6 Calibration of AquaCrop in the temperate maritime climate of Belgium Chapter 7 Impact on crop production and the soil water balance Conclusions and perspectivesnrpages: 188status: publishe

Understanding responses of nitrogen dynamics in plants and soils to elevated CO2 concentrations through multi-level meta-analytical insights

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Crop Yield in Drought-prone Areas: Projections for a Changed Climate with the AquaCrop Model

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Combined deficit irrigation and soil fertility management on different soil textures to improve wheat yield in drought-prone Bangladesh

© 2017 Elsevier B.V. Proper utilization of water resources is very important in agro-based and drought-prone Bangladesh. Sustainable use of water resources in agriculture requires irrigation schedules based on local environmental conditions, soil type and water availability. In this study, the water productivity model AquaCrop was used to simulate different water and fertilizer management strategies in a drought prone area of Bangladesh to obtain management recommendations. First, the Standardised Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) were determined to quantify the aggregated deficit between precipitation and the evaporative demand of the atmosphere, which confirm that meteorological drought is occurring frequently in the study area. Also, the AquaCrop model was successfully calibrated and validated for wheat in the area, which was confirmed by the several statistical indicators, and could be used to design water and fertilizer management strategies. Simulations identified stem elongation (jointing) to booting and flowering stage as the most water sensitive stages for wheat. Deficit irrigation during the most water sensitive stages could increase the interannual yield stability and the grain yield compared to rainfed conditions for different soil fertility levels on loamy and sandy soils by 21–136% and 11–71%, respectively, while it could increase water productivity compared to full irrigation strategies. Deficit irrigation resulted in grain yields almost equal to yields under full irrigation and could at the same time save 121–197 mm of water per growing season. Specifically, we suggest two irrigation applications: one at the stem elongation (jointing) to booting stage and another at the flowering stage for loamy soils; and one at the end of seedling development to the beginning of crown root initiation stage and another at the flowering stage for sandy soils. Given the water scarcity in the region, instead of optimal fertility levels, moderate fertility levels are recommended that result in 60% of the potential biomass production for loamy soils and in 50% for sandy soils in combination with the suggested deficit irrigation strategies.status: publishe

Responses to atmospheric CO2 concentrations in crop simulation models: a review of current simple and semicomplex representations and options for model development

Elevated atmospheric CO2 concentrations ([CO2]) cause direct changes in crop physiological processes (e.g., photosynthesis and stomatal conductance). To represent these CO2 responses, commonly used crop simulation models have been amended, using simple and semi-complex representations of the processes involved. Yet, there is no standard approach to, and often poor documentation of these developments. This study used a bottom-up approach (starting with the APSIM framework as case-study) to evaluate modelled responses in a consortium of commonly used crop models, and illuminate whether variation in responses reflects true uncertainty in our understanding compared to arbitrary choices of model developers. Diversity in simulated CO2 responses and limited validation was common among models, both within the APSIM framework and more generally. Whereas production responses show some consistency up to moderately high [CO2] (around 700 ppm), transpiration and stomatal responses vary more widely in nature and magnitude (e.g. a decrease in stomatal conductance varying between 35% and 90% among models was found for [CO2] doubling to 700 ppm). Most notably, nitrogen responses were found to be included in few crop models despite being commonly observed and critical for simulation of photosynthetic acclimation, crop nutritional quality and carbon allocation. We suggest harmonization and consideration of more mechanistic concepts in particular sub-routines, for example for the simulation of N dynamics, as a way to improve our predictive understanding of CO2 responses and capture secondary processes. Inter-comparison studies could assist in this aim, provided that they go beyond simple output comparison and explicitly identify the representations and assumptions that are causal for inter-model differences. Additionally, validation and proper documentation of the representation of CO2 responses within models should be prioritized.status: publishe

Regional and global climate projections increase mid-century yield variability and crop productivity in Belgium

The impact of mid-century climatic changes on crop productivity of winter wheat, maize, potato and sugar beet was assessed for a temperate maritime climate in the Flemish Region, Belgium. Climatic projections of multiple regional and global climate models (RCMs from the EU-ENSEMBLES project and GCMs from the Coupled Model Intercomparison Project phase 3) were stochastically downscaled by the LARS-WG weather generator for use in the crop models AquaCrop and Sirius. Primarily positive effects on mean yield were simulated. Crops benefitted from elevated CO2., and from more radiation interception if the cropping period was adapted in response to higher temperatures. However, increased productivity was linked with increased susceptibility to water stress and greater inter-annual yield variability, particularly with adapted management. Impacts differed among and within ensembles of climate models, and among crops and environments. Although RCMs may be more suitable for local impact assessments than GCMs, inter-ensemble differences and contingent wider ranges of impacts with GCM projections found in this study indicate that applying RCMs driven by a limited number of GCMs alone would not give the full range of possible impacts. Further, this study suggests that the simulated inter-model variation can be larger than spatial variation within the region. These findings advocate the use of both GCM and RCM ensembles in assessments where temperature and precipitation are central, such as for crop production.status: publishe

Waarom water broodnodig is

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