Records |
Author |
Holman, I.P.; Brown, C.; Carter, T.R.; Harrison, P.A.; Rounsevell, M. |
Title |
Improving the representation of adaptation in climate change impact models |
Type |
Journal Article |
Year |
2019 |
Publication |
Regional Environmental Change |
Abbreviated Journal |
Reg. Environ. Change |
Volume |
19 |
Issue |
3 |
Pages |
711-721 |
Keywords |
Adaptive capacity; Limits; Water; Land; Decision making; Integrated assessment; Land-Cover Change; Global Change; River-Basin; Integrated Assessment; Adaptive Capacity; Vulnerability; Variability; Precautionary; Agriculture; Management |
Abstract |
Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate. |
Address |
2019-04-27 |
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English |
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Edition |
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ISSN |
1436-3798 |
ISBN |
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Article |
Area |
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Notes |
TradeM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5220 |
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Author |
Bojar, W.; Knopik, L.; Żarski, J.; Kuśmierek-Tomaszewska, R. |
Title |
Integrated assessment of crop productivity based on the food supply forecasting |
Type |
Journal Article |
Year |
2016 |
Publication |
Agricultural Economics – Czech |
Abbreviated Journal |
Agricultural Economics – Czech |
Volume |
61 |
Issue |
11 |
Pages |
502-510 |
Keywords |
climate changes; decision-making tools; estimation of parameters; forecasted outputs; gamma distribution; predicting yields; climate-change; emissions scenarios; impacts; potato; yield; growth; policy; scale; water |
Abstract |
Climate change scenarios suggest that long periods without rainfall will occur in the future often causing instability of the agricultural products market. The aim of our research was to build a model describing the amount of precipitation and droughts for forecasting crop yields in the future. In this study, we analysed a non-standard mixture of gamma and one point distributions as the model of rainfall. On the basis of the rainfall data, one can estimate parameters of the distribution. Parameter estimators were constructed using a method of maximum likelihood. The obtained rainfall data allow confirming the hypothesis of the adequacy of the proposed rainfall models. Long series of droughts allow one to determine the probabilities of adverse phenomena in agriculture. Based on the model, yields of barley in the years 2030 and 2050 were forecasted which can be used for the assessment of other crops productivity. The results obtained with this approach can be used to predict decreases in agricultural production caused by prospective rainfall shortages. This will enable decision makers to shape effective agricultural policies in order to learn how to balance the food supplies and demands through an appropriate management of stored raw food materials and import/export policies. |
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English |
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Series Editor |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0139-570x |
ISBN |
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Article |
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Notes |
CropM, TradeM, ft_macsur |
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no |
Call Number |
MA @ admin @ |
Serial |
4644 |
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Author |
Constantin, J.; Raynal, H.; Casellas, E.; Hoffman, H.; Bindi, M.; Doro, L.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Klatt, S.; Kuhnert, M.; Lewan, E.; Maharjan, G.R.; Moriondo, M.; Nendel, C.; Roggero, P.P.; Specka, X.; Trombi, G.; Villa, A.; Wang, E.; Weihermueller, L.; Yeluripati, J.; Zhao, Z.; Ewert, F.; Bergez, J.-E. |
Title |
Management and spatial resolution effects on yield and water balance at regional scale in crop models |
Type |
Journal Article |
Year |
2019 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
Volume |
275 |
Issue |
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Pages |
184-195 |
Keywords |
Drainage; Evapotranspiration; Aggregation; Decision rules; Scaling; winter-wheat yield; data aggregation; sowing dates; area index; input; data; carbon; growth; irrigation; productivity; assimilation |
Abstract |
Due to the more frequent use of crop models at regional and national scale, the effects of spatial data input resolution have gained increased attention. However, little is known about the influence of variability in crop management on model outputs. A constant and uniform crop management is often considered over the simulated area and period. This study determines the influence of crop management adapted to climatic conditions and input data resolution on regional-scale outputs of crop models. For this purpose, winter wheat and maize were simulated over 30 years with spatially and temporally uniform management or adaptive management for North Rhine-Westphalia ((similar to)34 083 km(2)), Germany. Adaptive management to local climatic conditions was used for 1) sowing date, 2) N fertilization dates, 3) N amounts, and 4) crop cycle length. Therefore, the models were applied with four different management sets for each crop. Input data for climate, soil and management were selected at five resolutions, from 1 x 1 km to 100 x 100 km grid size. Overall, 11 crop models were used to predict regional mean crop yield, actual evapotranspiration, and drainage. Adaptive management had little effect (< 10% difference) on the 30-year mean of the three output variables for most models and did not depend on soil, climate, and management resolution. Nevertheless, the effect was substantial for certain models, up to 31% on yield, 27% on evapotranspiration, and 12% on drainage compared to the uniform management reference. In general, effects were stronger on yield than on evapotranspiration and drainage, which had little sensitivity to changes in management. Scaling effects were generally lower than management effects on yield and evapotranspiration as opposed to drainage. Despite this trend, sensitivity to management and scaling varied greatly among the models. At the annual scale, effects were stronger in certain years, particularly the management effect on yield. These results imply that depending on the model, the representation of management should be carefully chosen, particularly when simulating yields and for predictions on annual scale. |
Address |
2020-02-14 |
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English |
Summary Language |
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Original Title |
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Series Editor |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-1923 |
ISBN |
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Medium |
Article |
Area |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5225 |
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Author |
Graversgaard, M.; Hedelin, B.; Smith, L.; Gertz, F.; Höjberg, A.L.; Langford, J.; Martinez, G.; Mostert, E. |
Title |
Opportunities and Barriers for Water Co-Governance – A Critical Analysis of Seven Cases of Diffuse Water Pollution from Agriculture in Europe, Australia and North America |
Type |
Journal Article |
Year |
2018 |
Publication |
Sustainability |
Abbreviated Journal |
Sustainability |
Volume |
10 |
Issue |
5 |
Pages |
1634 |
Keywords |
collaborative governance; decentralized decision-making; non-point source pollution; nutrient management; water governance; management; policy; river; eutrophication; phosphorus; resources; nitrogen; hypoxia; quality; options |
Abstract |
Diffuse Water Pollution from Agriculture (DWPA) and its governance has received increased attention as a policy concern across the globe. Mitigation of DWPA is a complex problem that requires a mix of policy instruments and a multi-agency, broad societal response. In this paper, opportunities and barriers for developing co-governance, defined as collaborative societal involvement in the functions of government, and its suitability for mitigation of DWPA are reviewed using seven case studies in Europe (Poland, Denmark, Sweden, The Netherlands and UK), Australia (Murray-Darling Basin) and North America (State of Minnesota). An analytical framework for assessing opportunities and barriers of co-governance was developed and applied in this review. Results indicated that five key issues constitute both opportunities and barriers, and include: (i) pressure for change; (ii) connected governance structures and allocation of resources and funding; (iii) leadership and establishment of partnerships through capacity building; (iv) use and co-production of knowledge; and (v) time commitment to develop water co-governance. |
Address |
2018-07-12 |
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Thesis |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
2071-1050 |
ISBN |
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Medium |
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Area |
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Notes |
CropM, ft_macsur |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
5205 |
Permanent link to this record |
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Author |
Mansouri, M.; Destain, M.-F. |
Title |
Predicting biomass and grain protein content using Bayesian methods |
Type |
Journal Article |
Year |
2015 |
Publication |
Stochastic Environmental Research and Risk Assessment |
Abbreviated Journal |
Stoch. Environ. Res. Risk Assess. |
Volume |
29 |
Issue |
4 |
Pages |
1167-1177 |
Keywords |
crop model; particle filter; prediction; ensemble kalman filter; parameter-estimation; particle filters; decision-support; state estimation; model; nitrogen; navigation; tracking; systems |
Abstract |
This paper deals with the problem of predicting biomass and grain protein content using improved particle filtering (IPF) based on minimizing the Kullback-Leibler divergence. The performances of IPF are compared with those of the conventional particle filtering (PF) in two comparative studies. In the first one, we apply IPF and PF at a simple dynamic crop model with the aim to predict a single state variable, namely the winter wheat biomass, and to estimate several model parameters. In the second study, the proposed IPF and the PF are applied to a complex crop model (AZODYN) to predict a winter-wheat quality criterion, namely the grain protein content. The results of both comparative studies reveal that the IPF method provides a better estimation accuracy than the PF method. The benefit of the IPF method lies in its ability to provide accuracy related advantages over the PF method since, unlike the PF which depends on the choice of the sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of this sampling distribution, which also utilizes the observed data. The performance of the proposed method is evaluated in terms of estimation accuracy, root mean square error, mean absolute error and execution times. |
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English |
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ISSN |
1436-3240 1436-3259 |
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Notes |
CropM |
Approved |
no |
Call Number |
MA @ admin @ |
Serial |
4664 |
Permanent link to this record |