| |
Records |
Links |
|
Author |
Reidsma, P.; Wolf, J.; Kanellopoulos, A.; Schaap, B.F.; Mandryk, M.; Verhagen, J.; van Ittersum, M.K. |
|
| |
Title |
Climate change impact and adaptation research requires integrated assessment and farming systems analysis: a case study in the Netherlands |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
|
| |
Volume |
10 |
Issue |
4 |
Pages |
045004 |
|
| |
Keywords |
climate change adaptation; scenario; farm diversity; crop simulation; bio-economic farm modelling; european-union; crop yields; agriculture; responses; models; wheat; variability; improvement; strategies; scenarios |
|
| |
Abstract |
Rather than on crop modelling only, climate change impact assessments in agriculture need to be based on integrated assessment and farming systems analysis, and account for adaptation at different levels. With a case study for Flevoland, the Netherlands, we illustrate that (1) crop models cannot account for all relevant climate change impacts and adaptation options, and (2) changes in technology, policy and prices have had and are likely to have larger impacts on farms than climate change. While crop modelling indicates positive impacts of climate change on yields of major crops in 2050, a semiquantitative and participatory method assessing impacts of extreme events shows that there are nevertheless several climate risks. A range of adaptation measures are, however, available to reduce possible negative effects at crop level. In addition, at farm level farmers can change cropping patterns, and adjust inputs and outputs. Also farm structural change will influence impacts and adaptation. While the 5th IPCC report is more negative regarding impacts of climate change on agriculture compared to the previous report, also for temperate regions, our results show that when putting climate change in context of other drivers, and when explicitly accounting for adaptation at crop and farm level, impacts may be less negative in some regions and opportunities are revealed. These results refer to a temperate region, but an integrated assessment may also change perspectives on climate change for other parts of the world. |
|
| |
Address |
2016-10-31 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1748-9326 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes  |
CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4800 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Dietrich, J.P.; Schmitz, C.; Lotze-Campen, H.; Popp, A.; Muller, C. |
|
| |
Title |
Forecasting technological change in agriculture-An endogenous implementation in a global, and use model |
Type |
Journal Article |
| |
Year |
2014 |
Publication |
Technological Forecasting and Social Change |
Abbreviated Journal |
Technological Forecasting and Social Change |
|
| |
Volume |
81 |
Issue |
|
Pages |
236-249 |
|
| |
Keywords |
Technological change; Land use; Agricultural productivity; Land use; intensity; Research and development; land-use; research expenditures; productivity growth; impact; deforestation; forest; yield; Business & Economics; Public Administration |
|
| |
Abstract |
Technological change in agriculture plays a decisive role for meeting future demands for agricultural goods. However, up to now, agricultural sector models and models on land use change have used technological change as an exogenous input due to various information and data deficiencies. This paper provides a first attempt towards an endogenous implementation based on a measure of agricultural land use intensity. We relate this measure to empirical data on investments in technological change. Our estimated yield elasticity with respect to research investments is 029 and production costs per area increase linearly with an increasing yield level. Implemented in the global land use model MAgPIE (”Model of Agricultural Production and its Impact on the Environment”) this approach provides estimates of future yield growth. Highest future yield increases are required in Sub-Saharan Africa, the Middle East and South Asia. Our validation with FAO data for the period 1995-2005 indicates that the model behavior is in line with observations. By comparing two scenarios on forest conservation we show that protecting sensitive forest areas in the future is possible but requires substantial investments into technological change. (C) 2013 Elsevier Inc. All rights reserved. |
|
| |
Address |
2016-10-31 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0040-1625 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4789 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Castañeda-Vera, A.; Leffelaar, P.A.; Álvaro-Fuentes, J.; Cantero-Martínez, C.; Mínguez, M.I. |
|
| |
Title |
Selecting crop models for decision making in wheat insurance |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
|
| |
Volume |
68 |
Issue |
|
Pages |
97-116 |
|
| |
Keywords |
aquacrop; ceres-wheat; cropsyst; wofost; model choice; rainfed semi-arid areas; radiation use efficiency; water deficit; use efficiency; management-practices; farming systems; field-capacity; soil; yield; evaporation; photosynthesis; transpiration; irrigation |
|
| |
Abstract |
In crop insurance, the accuracy with which the insurer quantifies the actual risk is highly dependent on the availability on actual yield data. Crop models might be valuable tools to generate data on expected yields for risk assessment when no historical records are available. However, selecting a crop model for a specific objective, location and implementation scale is a difficult task. A look inside the different crop and soil modules to understand how outputs are obtained might facilitate model choice. The objectives of this paper were (i) to assess the usefulness of crop models to be used within a crop insurance analysis and design and (ii) to select the most suitable crop model for drought risk assessment in semi-arid regions in Spain. For that purpose first, a pre-selection of crop models simulating wheat yield under rainfed growing conditions at the field scale was made, and second, four selected models (Aquacrop, CERES-Wheat, CropSyst and WOFOST) were compared in terms of modelling approaches, process descriptions and model outputs. Outputs of the four models for the simulation of winter wheat growth are comparable when water is not limiting, but differences are larger when simulating yields under rainfed conditions. These differences in rainfed yields are mainly related to the dissimilar simulated soil water availability and the assumed linkages with dry matter formation. We concluded that for the simulation of winter wheat growth at field scale in such semi-arid conditions, CERES-Wheat and CropSyst are preferred. WOFOST is a satisfactory compromise between data availability and complexity when detail data on soil is limited. Aquacrop integrates physiological processes in some representative parameters, thus diminishing the number of input parameters, what is seen as an advantage when observed data is scarce. However, the high sensitivity of this model to low water availability limits its use in the region considered. Contrary to the use of ensembles of crop models, we endorse that efforts be concentrated on selecting or rebuilding a model that includes approaches that better describe the agronomic conditions of the regions in which they will be applied. The use of such complex methodologies as crop models is associated with numerous sources of uncertainty, although these models are the best tools available to get insight in these complex agronomic systems. (C) 2015 Elsevier B.V. All rights reserved. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
1161-0301 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4710 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Wolf, J.; Ouattara, K.; Supit, I. |
|
| |
Title |
Sowing rules for estimating rainfed yield potential of sorghum and maize in Burkina Faso |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
|
| |
Volume |
214-215 |
Issue |
|
Pages |
208-218 |
|
| |
Keywords |
crop modelling; maize; sorghum; sowing; WOFOST; yield potential; semiarid west-africa; pearl-millet cultivation; soil organic-matter; climate-change; planting dates; crop model; variability; water; adaptation; tillage |
|
| |
Abstract |
To reduce the dependence on local expert knowledge, which is important for large-scale crop modelling studies, we analyzed sowing dates and rules for maize (Zea mays L.) and sorghum (Sorghum bicolor (L)) at three locations in Burkina Faso with strongly decreasing rainfall amounts from south to north. We tested in total 22 methods to derive optimal sowing dates that result in highest water-limited yields and lowest yield variation in a reproducible and objective way. The WOFOST crop growth simulation model was used. We found that sowing dates that are based on local expert knowledge, may work quite well for Burkina Faso and for West Africa in general. However, when no a priori information is available, maize should be sown between Julian days 160 and 200, with application of the following criteria: (a) cumulative rainfall in the sowing window is >= 3 cm or available soil moisture content is >2 cm in the moderately dry central part of Burkina Faso, (b) cumulative rainfall in this period is >= 2 cm or available soil moisture content is >1 cm in the more humid regions in the southern part of Burkina Faso. Sorghum should also be sown between Julian days 160 and 200 with application of the following criteria: (a) in the dry northern part of Burkina Faso the long duration sorghum variety should be sown when cumulative rainfall is >2 cm in the sowing window, and the short duration sorghum variety should be sown later when cumulative rainfall is >= 3 cm, (b) in central Burkina Faso sowing should start when cumulative rainfall in this period is >= 2 cm or when available soil moisture content is >1 cm. Sowing date rules are shown to be generally crop and location specific and are not generic for West Africa. However, the required precision of the sowing rules appears to rapidly decrease with increasing duration and intensity of the rainy season. Sowing delay as a result of, for example, labour constraints, has a disastrous effect on rainfed maize and sorghum yields, particularly in the northern part of West Africa with low rainfall. Optimization of sowing dates can also be done by simulating crop yields in a time window of two months around a predefined sowing date. Using these optimized dates appears to result in a good estimate of the maximal mean rainfed yield level. (C) 2015 Elsevier B.V. All rights reserved. |
|
| |
Address |
2015-10-12 |
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0168-1923 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4702 |
|
| Permanent link to this record |
| |
|
| |
|
Author |
Dumont, B.; Basso, B.; Leemans, V.; Bodson, B.; Destain, J.-P.; Destain, M.-F. |
|
| |
Title |
A comparison of within-season yield prediction algorithms based on crop model behaviour analysis |
Type |
Journal Article |
| |
Year |
2015 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
|
| |
Volume |
204 |
Issue |
|
Pages |
10-21 |
|
| |
Keywords |
stics crop model; climate variability; lars-wg; yield prediction; log-normal distribution; convergence in law theorem; central limit theorem; weather generator; nitrogen balances; generic model; wheat; simulation; climate; stics; variability; skewness; efficiency |
|
| |
Abstract |
The development of methodologies for predicting crop yield, in real-time and in response to different agro-climatic conditions, could help to improve the farm management decision process by providing an analysis of expected yields in relation to the costs of investment in particular practices. Based on the use of crop models, this paper compares the ability of two methodologies to predict wheat yield (Triticum aestivum L.), one based on stochastically generated climatic data and the other on mean climate data. It was shown that the numerical experimental yield distribution could be considered as a log-normal distribution. This function is representative of the overall model behaviour. The lack of statistical differences between the numerical realisations and the logistic curve showed in turn that the Generalised Central Limit Theorem (GCLT) was applicable to our case study. In addition, the predictions obtained using both climatic inputs were found to be similar at the inter and intra-annual time-steps, with the root mean square and normalised deviation values below an acceptable level of 10% in 90% of the climatic situations. The predictive observed lead-times were also similar for both approaches. Given (i) the mathematical formulation of crop models, (ii) the applicability of the CLT and GLTC to the climatic inputs and model outputs, respectively, and (iii) the equivalence of the predictive abilities, it could be concluded that the two methodologies were equally valid in terms of yield prediction. These observations indicated that the Convergence in Law Theorem was applicable in this case study. For purely predictive purposes, the findings favoured an algorithm based on a mean climate approach, which needed far less time (by 300-fold) to run and converge on same predictive lead time than the stochastic approach. (C) 2015 Elsevier B.V. All rights reserved. |
|
| |
Address |
|
|
| |
Corporate Author |
|
Thesis |
|
|
| |
Publisher |
|
Place of Publication |
|
Editor |
|
|
| |
Language |
English |
Summary Language |
|
Original Title |
|
|
| |
Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
|
| |
Series Volume |
|
Series Issue |
|
Edition |
|
|
| |
ISSN |
0168-1923 |
ISBN |
|
Medium |
Article |
|
| |
Area |
|
Expedition |
|
Conference |
|
|
| |
Notes |
CropM |
Approved |
no |
|
| |
Call Number |
MA @ admin @ |
Serial |
4647 |
|
| Permanent link to this record |
