Quantification of Leached Pollutants into the Groundwater Caused by Agricultural Land Use — Model-Based Scenario Studies as a Method for Quantitative Risk Assessment of Groundwater Pollution

Author(s):  
Christoph Merz ◽  
Kurt Christian Kersebaum ◽  
Angelika Wurbs
2004 ◽  
Vol 26 (4) ◽  
pp. 537-542
Author(s):  
Yeung-Nan Shieh

One of the very important components in the urban and agricultural land use model is the so-called bid-rent curve. Regional and urban economists, city planners, and economic geographers have used this curve extensively as an analytical device. It is generally accepted that the explicit bid-rent function was first applied to the equilibrium of land use patterns in agricultural production by August Losch (1954) in Germany and Edgar S. Dunn (1954) in America, and was later extended by William Alonso (1964).


2013 ◽  
Vol 6 (4) ◽  
pp. 6975-7046 ◽  
Author(s):  
F. Souty ◽  
B. Dorin ◽  
T. Brunelle ◽  
P. Dumas ◽  
P. Ciais

Abstract. The central role of land-use change in the Earth System and its implications for food security, biodiversity and climate has spurred the development of global models that combine economical and agro-ecological drivers and constraints. With such a development of integrated approaches, evaluating the performance of global models of land-use against observed historical changes recorded by agricultural data becomes increasingly challenging. The Nexus Land-Use model is an example of land-use model integrating both biophysical and economical processes and constraints. This paper is an attempt to evaluate its ability to simulate historical agricultural land-use changes over 12 large but economically coherent regions of the world since 1961. The evaluation focuses on the intensification vs. extensification response of crop and livestock production in response to changes of socio-economic drivers over time, such as fertiliser price, population and diet. We examine how well the Nexus model can reproduce annual observation-based estimates of cropland vs. pasture areas from 1961 to 2006. Food trade, consumption of fertilisers and food price are also evaluated against historical data. Over the 12 regions considered, the total relative error on simulated cropland area is 2% yr−1 over 1980–2006. During the period 1961–2006, the error is larger (4% yr−1) due to an overestimation of the cropland area in China and Former Soviet Union over 1961–1980. Food prices tend to be underestimated while the performances of the trade module vary widely among regions (net imports are underestimated in Western countries at the expense of Brazil and Asia). Finally, a sensitivity analysis over a sample of input datasets provides some insights on the robustness of this evaluation.


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