Guenther Fischer

Study on the Impacts of Climate Change on China's Agriculture

This paper measures the economic impacts of climate change on Chinas agriculture based on the Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture dominated counties, we find that under most climate change scenarios both higher temperature and more precipitation would have an overall positive impact on Chinas agriculture. However, the impacts vary seasonally and regionally. Autumn effect is the most positive, but spring effect is the most negative. Applying the model to five climate scenarios in the year 2050 shows that the East, the Central part, the South, the northern part of the Northeast, and the Plateau would benefit from climate change, but the Southwest, the Northwest and the southern part of the Northeast may be negatively affected. In the North, most scenarios show that they may benefit from climate change. In summary, all of China would benefit from climate change in most scenarios.

Discounting, catastrophic risks management and vulnerability modeling

Traditional discounting dramatically affects the outcome of catastrophic risk management and spatio-temporal vulnerability modeling. The misperception of discount rates produces inadequate evaluations of risk management strategies, which may provoke catastrophes and significantly contribute to the increasing vulnerability of our society. This paper analyses the implication of potential catastrophic events on the choice of discounting. In particular, it shows the necessity of using proposed equivalent undiscounted stopping time criterion and Monte Carlo based stochastic optimization procedures.

Extreme events, discounting and stochastic optimization

The paper analyzes the implications of extreme events on the proper choice of discounting. Any discounting with constant or declining rates can be linked to random “stopping time” events, which define the internal discount-related horizons of evaluations. Conversely, any stopping time induces a discounting, in particular, with the standard discount rates. The expected duration of the stopping time horizon for discount rates obtained from capital markets does not exceed a few decades and, as such, these rates may significantly underestimate the net benefits of long-term decisions. The alternative undiscounted stopping time criterion allows to induce social discounting focusing on arrival times of potential extreme events rather then horizons of market interests. Induced discount rates are conditional on the degree of social commitment to mitigate risk. In general, extreme events affect these rates, which alter the optimal mitigation efforts that, in turn, change events. The use of undiscounted stopping time criteria requires stochastic optimisation methods.

Agriculture under Climate Change in China: Mitigate the Risks by Grasping the Emerging Opportunities

ABSTRACT There have been increasing concerns on risks and uncertainty posed by climate change to Chinas future crop production. The existing assessments using popular process-based and site-specific crop growing models highlight the significant extent of climate-induced yield reduction, and thus suggest a scary downward risk for Chinas future food production. Surprisingly, much less attention has been paid to exploring the potential gains that may also be brought by climate change. To address this imbalance, we develop an integrated agro-climatic and ecological assessment tool that is capable of detecting the shifts of multicropping opportunities under different climate change scenarios. The application of this tool to the context of China reveals significant extension of multicropping opportunities brought in by climate change. We argue for an active adaptation to such emerging opportunities through both market and policy incentives, because the aggregate gain of such adaptation is sufficient to outweigh the loss as revealed by the existing assessments.

A cross-scale model coupling approach to simulate the risk-reduction effect of natural adaptation on soybean production under climate change

ABSTRACT This study establishes a procedure to couple Decision Support System for Agrotechnology Transfer (DSSAT) and China Agroecological Zone model (AEZ-China). This procedure enables us to quantify the effects of two natural adaptation measures on soybean production in China, concern on which has been growing owing to the rapidly rising demand for soybean and the foreseen global climate change. The parameters calibration and mode verification are based on the observation records of soybean growth at 13 agro-meteorological observation stations in Northeast China and Huang-Huai-Hai Plain over 1981–2011. The calibration of eco-physiological parameters is based on the algorithms of DSSAT that simulate the dynamic bio-physiological processes of crop growth in daily time-step. The effects of shifts in planting day and changes in the length of growth cycle (LGC) are evaluated by the speedy algorithms of AEZ. Results indicate that without adaptation, climate change from the baseline 1961–1990 to the climate of 2050s as specified in the Providing Regional Climate for Impacts Studies-A1B would decrease the potential yield of soybean. By contrast, simulations of DSSAT using AEZ-recommended cultivars with adaptive LGC and also the corresponding adaptive planting dates show that the risk of yield loss could be fully or partially mitigated across majority of grid cells in the major soybean-growing areas.

Modeling the impacts of climate change on China's agriculture

Tee impacts of climate change on China’s agriculture are measured based on Ricardian model. By using county-level cross-sectional data on agricultural net revenue, climate, and other economic and geographical data for 1275 agriculture-dominated counties in the period of 1985–1991, we find that both higher temperature and more precipitation will have overall positive impact on China’s agriculture. However, the impacts vary seasonally and regionally. Higher temperature in all seasons except spring increases agricultural net revenue while more precipitation is beneficial in winter but is harmful in summer. Applying the model to five climate scenarios in the 2020s and 2050s shows that the North, the Northeast, the Northwest, and the Qinghai-Tibet Plateau would always benefit from climate change while the South and the Southwest may be negatively affected. For the East and the Central China, most scenarios show that they may benefit from climate change. In conclusion, climate change would be beneficial to the whole China.

A continental-scale hydro-economic model for integrating water-energy-land nexus solutions

This study presents the development of a new bottom‐up large‐scale hydro‐economic model, Extended Continental‐scale Hydro‐economic Optimization (ECHO), that works at a sub‐basin scale over a continent. The strength of ECHO stems from the integration of a detailed representation of local hydrological and technological constraints with regional and global policies, while accounting for the feedbacks between water, energy and agricultural sectors. In this study, ECHO has been applied over Africa as a case study with the aim of demonstrating the benefits of this integrated hydro‐economic modeling framework. Results of this framework are overall consistent with previous findings evaluating the cost of water supply and adaptation to global changes in Africa. Moreover, results provide critical assessments of future investment needs in both supply and demand side water management options, economic implications of contrasting future socio‐economic and climate change scenarios, and the potential tradeoffs among economic and environmental objectives. Overall, this study demonstrates the capacity of ECHO to address challenging research questions examining the sustainability of water supply, and the impacts of water management on energy and food sectors and vice versa. As such, we propose ECHO as useful tool for water‐related scenario analysis and management options evaluation.

A Study of the Impact on Soybean Potential under Climate Change

Soybean is one of the important oil crops in China. However the supply and demand of soybean is at stake currently. The demand keeps increasing and the self-sufficient keeps decreasing. More seriously, climate change will bring obvious impact on the growth and development, planting pattern, planting area, potential production of soybean, etc. Therefore, assessment of the impact of soybean production under climate change is quite essential for improving the self-sufficient and guaranteeing the safety of oil crops. This study will extend and improve the parameters of soybean in agricultural ecology zone (AEZ) based on the 22 soybean observation stations in the major planting area from 1981-2011 to achieve China-AEZ. And then simulate the impact of climate change on soybean. The results show that: the simulation of China-AEZ has been improved a lot. In 2050s, the total soybean potential will increased by 7123 thousand tons. The total suitable planting area will increased by 3589 thousand hectare. But the average potential will decreased by 55 kg/ha. From the spatial scale, the soybean potential will increase in Northeast China and Northwest China. Soybean potential will decrease in the other area of China under climate change.