| Records |
| Author |
Schmitz, C.; Lotze-Campen, H.; Gerten, D.; Dietrich, J.P.; Bodirsky, B.; Biewald, A.; Popp, A. |
| Title |
Blue water scarcity and the economic impacts of future agricultural trade and demand |
Type |
Journal Article |
| Year |
2013 |
Publication |
Water Resource Research |
Abbreviated Journal |
Water Resource Research |
| Volume |
49 |
Issue |
6 |
Pages |
3601-3617 |
| Keywords |
water scarcity; land use model; irrigation efficiency; trade liberalization; livestock consumption; modeling; land cover change; water budgets |
| Abstract |
An increasing demand for agricultural goods affects the pressure on global water resources over the coming decades. In order to quantify these effects, we have developed a new agroeconomic water scarcity indicator, considering explicitly economic processes in the agricultural system. The indicator is based on the water shadow price generated by an economic land use model linked to a global vegetation-hydrology model. Irrigation efficiency is implemented as a dynamic input depending on the level of economic development. We are able to simulate the heterogeneous distribution of water supply and agricultural water demand for irrigation through the spatially explicit representation of agricultural production. This allows in identifying regional hot spots of blue water scarcity and explicit shadow prices for water. We generate scenarios based on moderate policies regarding future trade liberalization and the control of livestock-based consumption, dependent on different population and gross domestic product (GDP) projections. Results indicate increased water scarcity in the future, especially in South Asia, the Middle East, and north Africa. In general, water shadow prices decrease with increasing liberalization, foremost in South Asia, Southeast Asia, and the Middle East. Policies to reduce livestock consumption in developed countries not only lower the domestic pressure on water but also alleviate water scarcity to a large extent in developing countries. It is shown that one of the two policy options would be insufficient for most regions to retain water scarcity in 2045 on levels comparable to 2005. |
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English |
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Edition |
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| ISSN |
0043-1397 |
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Article |
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TradeM |
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no |
| Call Number |
MA @ admin @ |
Serial |
4502 |
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| Author |
Dono, G.; Cortignani, R.; Doro, L.; Giraldo, L.; Ledda, L.; Pasqui, M.; Roggero, P.P. |
| Title |
An integrated assessment of the impacts of changing climate variability on agricultural productivity and profitability in an irrigated Mediterranean catchment |
Type |
Journal Article |
| Year |
2013 |
Publication |
Water Resource Management |
Abbreviated Journal |
Water Resource Manage. |
| Volume |
27 |
Issue |
10 |
Pages |
3607-3622 |
| Keywords |
discrete stochastic programming; climate change variability; adaptation to climate change; net evapotranspiration and irrigation requirements; water availability; epic crops model; economic impact of climate change; precipitation; uncertainty; region; series; yield; model; scale; wheat; gis |
| Abstract |
Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ETN), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ETN may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy. |
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English |
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Series Issue |
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Edition |
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| ISSN |
0920-4741 |
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Article |
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TradeM |
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no |
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MA @ admin @ |
Serial |
4487 |
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| Author |
König, H.J.; Uthes, S.; Schuler, J.; Zhen, L.; Purushothaman, S.; Suarma, U.; Sghaier, M.; Makokha, S.; Helming, K.; Sieber, S.; Chen, L.; Brouwer, F.; Morris, J.; Wiggering, H. |
| Title |
Regional impact assessment of land use scenarios in developing countries using the FoPIA approach: findings from five case studies |
Type |
Journal Article |
| Year |
2013 |
Publication |
Journal of Environmental Management |
Abbreviated Journal |
J. Environ. Manage. |
| Volume |
127 Suppl |
Issue |
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Pages |
S56-S64 |
| Keywords |
Conservation of Natural Resources; Developing Countries; Environmental Monitoring/*methods; (Ex-ante) impact assessment; Indicators; Land use change; Scenario study; Stakeholder participation; Sustainable development |
| Abstract |
The impact of land use changes on sustainable development is of increasing interest in many regions of the world. This study aimed to test the transferability of the Framework for Participatory Impact Assessment (FoPIA), which was originally developed in the European context, to developing countries, in which lack of data often prevents the use of data-driven impact assessment methods. The core aspect of FoPIA is the stakeholder-based assessment of alternative land use scenarios. Scenario impacts on regional sustainability are assessed by using a set of nine regional land use functions (LUFs), which equally cover the economic, social and environmental dimensions of sustainability. The cases analysed in this study include (1) the alternative spatial planning policies around the Merapi volcano and surrounding areas of Yogyakarta City, Indonesia; (2) the large-scale afforestation of agricultural areas to reduce soil erosion in Guyuan, China; (3) the expansion of soil and water conservation measures in the Oum Zessar watershed, Tunisia; (4) the agricultural intensification and the potential for organic agriculture in Bijapur, India; and (5) the land degradation and land conflicts resulting from land division and privatisation in Narok, Kenya. All five regions are characterised by population growth, partially combined with considerable economic development, environmental degradation problems and social conflicts. Implications of the regional scenario impacts as well as methodological aspects are discussed. Overall, FoPIA proved to be a useful tool for diagnosing regional human-environment interactions and for supporting the communication and social learning process among different stakeholder groups. |
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English |
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Edition |
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| ISSN |
0301-4797 |
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Article |
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TradeM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4474 |
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| Author |
Below, T.B.; Mutabazi, K.D.; Kirschke, D.; Franke, C.; Sieber, S.; Siebert, R.; Tscherning, K. |
| Title |
Can farmers’ adaptation to climate change be explained by socio-economic household-level variables |
Type |
Journal Article |
| Year |
2012 |
Publication |
Global Environmental Change |
Abbreviated Journal |
Glob. Environ. Change |
| Volume |
22 |
Issue |
1 |
Pages |
223-235 |
| Keywords |
Sub-Saharan Africa; Tanzania; Adaptive capacity; Index; Vulnerability; Adaptation; adaptive capacity; environmental-change; south-africa; vulnerability; variability; resilience; tanzania; framework; drought; policy |
| Abstract |
A better understanding of processes that shape farmers’ adaptation to climate change is critical to identify vulnerable entities and to develop well-targeted adaptation policies. However, it is currently poorly understood what determines farmers’ adaptation and how to measure it. In this study, we develop an activity-based adaptation index (AAI) and explore the relationship between socioeconomic variables and farmers’ adaptation behavior by means of an explanatory factor analysis and a multiple linear regression model using latent variables. The model was tested in six villages situated in two administrative wards in the Morogoro region of Tanzania. The Mlali ward represents a system of relatively high agricultural potential, whereas the Gairo ward represents a system of low agricultural potential. A household survey, a rapid rural appraisal and, a stakeholder workshop were used for data collection. The data were analyzed using factor analysis, multiple linear regression, descriptive statistical methods and qualitative content analysis. The empirical results are discussed in the context of theoretical concepts of adaptation and the sustainable livelihood approach. We found that public investment in rural infrastructure, in the availability and technically efficient use of inputs, in a good education system that provides equal chances for women, and in the strengthening of social capital, agricultural extension and, microcredit services are the best means of improving the adaptation of the farmers from the six villages in Gairo and Mlali. We conclude that the newly developed AAI is a simple but promising way to capture the complexity of adaptation processes that addresses a number of shortcomings of previous index studies. |
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English |
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Edition |
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| ISSN |
0959-3780 |
ISBN |
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Article |
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TradeM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4467 |
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| Author |
von Lampe, M.; Willenbockel, D.; Ahammad, H.; Blanc, E.; Cai, Y.; Calvin, K.; Fujimori, S.; Hasegawa, T.; Havlik, P.; Heyhoe, E.; Kyle, P.; Lotze-Campen, H.; Mason, d’C., Daniel; Nelson, G.C.; Sands, R.D.; Schmitz, C.; Tabeau, A.; Valin, H.; van der Mensbrugghe, D.; van Meijl, H. |
| Title |
Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison |
Type |
Journal Article |
| Year |
2014 |
Publication |
Agricultural Economics |
Abbreviated Journal |
Agric. Econ. |
| Volume |
45 |
Issue |
1 |
Pages |
3-3 |
| Keywords |
Computable general equilibrium; Partial equilibrium; Meta-analysis; Socioeconomic pathway; Climate change; Bioenergy; Land use; Model; intercomparison; land-use change; food demand; crop productivity; climate-change; future |
| Abstract |
Recent studies assessing plausible futures for agricultural markets and global food security have had contradictory outcomes. To advance our understanding of the sources of the differences, 10 global economic models that produce long-term scenarios were asked to compare a reference scenario with alternate socioeconomic, climate change, and bioenergy scenarios using a common set of key drivers. Several key conclusions emerge from this exercise: First, for a comparison of scenario results to be meaningful, a careful analysis of the interpretation of the relevant model variables is essential. For instance, the use of real world commodity prices differs widely across models, and comparing the prices without accounting for their different meanings can lead to misleading results. Second, results suggest that, once some key assumptions are harmonized, the variability in general trends across models declines but remains important. For example, given the common assumptions of the reference scenario, models show average annual rates of changes of real global producer prices for agricultural products on average ranging between -0.4% and +0.7% between the 2005 base year and 2050. This compares to an average decline of real agricultural prices of 4% p.a. between the 1960s and the 2000s. Several other common trends are shown, for example, relating to key global growth areas for agricultural production and consumption. Third, differences in basic model parameters such as income and price elasticities, sometimes hidden in the way market behavior is modeled, result in significant differences in the details. Fourth, the analysis shows that agro-economic modelers aiming to inform the agricultural and development policy debate require better data and analysis on both economic behavior and biophysical drivers. More interdisciplinary modeling efforts are required to cross-fertilize analyses at different scales. |
| Address |
2016-10-31 |
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English |
Summary Language |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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| ISSN |
0169-5150 |
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Article |
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| Notes |
TradeM, ft_macsur |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
4822 |
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