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Yin, X.; Olesen, J.E.; Wang, M.; Kersebaum, K.-C.; Chen, H.; Baby, S.; Öztürk, I.; Chen, F. |
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Title  |
Adapting maize production to drought in the Northeast Farming Region of China |
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Journal Article |
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Year |
2016 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
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Volume |
77 |
Issue |
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Pages |
47-58 |
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Keywords |
Drought; Maize production; Adaptation strategies; Household characteristics; Policy support; The Northeast Farming Region of China; climate change; Jilin province; water-stress; sowing date; yield; risk; tolerance; impacts; corn; agriculture |
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Abstract |
Maize (Zea mays L.) is the most prominent crop in the Northeast Farming Region of China (NFR), and drought has been the largest limitation for maize production in this area during recent decades. The question of how to adapt maize production to drought has received great attention from policy makers, researchers and farmers. In order to evaluate the effects of adaptation strategies against drought and examine the influences of policy supports and farmer households’ characteristics on adopting decisions, a large scale household survey was conducted in five representative maize production counties across NFR. Our survey results indicated that using variety diversification, drought resistant varieties and dibbling irrigation are the three major adaptation strategies against drought in spring, and farmers also adopted changes in sowing time, conservation tillage and mulching to cope with drought in spring. About 20% and 18% of households enhanced irrigation against drought in summer and autumn, respectively. Deep loosening tillage and organic fertilizer are also options for farmers to resist drought in summer. Maize yield was highly dependent on soil qualities, with yields on land of high soil quality approximately 1050 kg/ha and 2400 kg/ha higher than for normal and poor soil conditions, respectively. Using variety diversification and drought resistant varieties can respectively increase maize yield by approximately 150 and 220 kg/ha under drought. Conservation tillage increased maize yield by 438–459 kg/ha in drought years. Irrigation improved maize yield by 419–435 kg/ha and 444–463 kg/ha against drought in summer and autumn, respectively. Offering information service, financial and technical support can greatly increase the use of adaptation strategies for farmers to cope with drought. However, only 46% of households received information service, 43% of households received financial support, and 26% of households received technical support against drought from the local government. The maize acreage and the irrigation access are the major factors that influenced farmers’ decisions to apply adaptation strategies to cope with drought in each season, but only 25% of households have access to irrigation. This indicates the need for enhanced public support for farmers to better cope with drought in maize production, particularly through improving access to irrigation. |
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2016-10-31 |
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ISSN |
1161-0301 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
Serial |
4825 |
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Author |
Luo, K.; Tao, F.; Moiwo, J.P.; Xiao, D. |
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Title |
Attribution of hydrological change in Heihe River Basin to climate and land use change in the past three decades |
Type |
Journal Article |
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Year |
2016 |
Publication |
Scientific Reports |
Abbreviated Journal |
Scientific Reports |
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Volume |
6 |
Issue |
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Pages |
33704 |
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Keywords |
water-resources; groundwater recharge; stream-flow; surface-energy; china; runoff; impact; evapotranspiration; cover; availability; Science & Technology – Other Topics |
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Abstract |
The contributions of climate and land use change (LUCC) to hydrological change in Heihe River Basin (HRB), Northwest China were quantified using detailed climatic, land use and hydrological data, along with the process-based SWAT (Soil and Water Assessment Tool) hydrological model. The results showed that for the 1980s, the changes in the basin hydrological change were due more to LUCC (74.5%) than to climate change (21.3%). While LUCC accounted for 60.7% of the changes in the basin hydrological change in the 1990s, climate change explained 57.3% of that change. For the 2000s, climate change contributed 57.7% to hydrological change in the HRB and LUCC contributed to the remaining 42.0%. Spatially, climate had the largest effect on the hydrology in the upstream region of HRB, contributing 55.8%, 61.0% and 92.7% in the 1980s, 1990s and 2000s, respectively. LUCC had the largest effect on the hydrology in the middle-stream region of HRB, contributing 92.3%, 79.4% and 92.8% in the 1980s, 1990s and 2000s, respectively. Interestingly, the contribution of LUCC to hydrological change in the upstream, middle-stream and downstream regions and the entire HRB declined continually over the past 30 years. This was the complete reverse (a sharp increase) of the contribution of climate change to hydrological change in HRB. |
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2016-10-18 |
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2045-2322 |
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CropM, ft_macsur |
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Call Number |
MA @ admin @ |
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4668 |
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Author |
Zhang, W.; Liu, C.; Zheng, X.; Zhou, Z.; Cui, F.; Zhu, B.; Haas, E.; Klatt, S.; Butterbach-Bahl, K.; Kiese, R. |
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Title |
Comparison of the DNDC, LandscapeDNDC and IAP-N-GAS models for simulating nitrous oxide and nitric oxide emissions from the winter wheat–summer maize rotation system |
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Journal Article |
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2015 |
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Agricultural Systems |
Abbreviated Journal |
Agricultural Systems |
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140 |
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1-10 |
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Keywords |
Model ensemble; Straw incorporation; Irrigation; Fertilization; Calcareous soil; North China Plain; process-oriented model; soil organic-matter; biogeochemical model; cropping system; N2O emissions; forest soils; microbial-growth; rainfall events; calcareous soil |
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The DNDC, LandscapeDNDC and IAP-N-GAS models have been designed to simulate the carbon and nitrogen processes of terrestrial ecosystems. Until now, a comparison of these models using simultaneous observations has not been reported, although such a comparison is essential for further model development and application. This study aimed to evaluate the performance of the models, delineate the strengths and limitations of each model for simulating soil nitrous oxide (N2O) and nitric oxide (NO) emissions, and explore short-comings of these models that may require reconsideration. We conducted comparisons among the models using simultaneous observations of both gases and relevant variables from the winter wheat-summer maize rotation system at three field sites with calcareous soils. Simulations of N2O and NO emissions by the three models agreed well with annual observations, but not with daily observations. All models failed to correctly simulate soil moisture, which could explain some of the incorrect daily fluxes of N2O and NO, especially for intensive fluxes during the growing season. Multi-model ensembles are promising approaches to better simulate daily gas emissions. IAP-N-GAS underestimated the priming effect of straw incorporation on N2O and NO emissions, but better results were obtained with DNDC95 and LandscapeDNDC. LandscapeDNDC and IAP-N-GAS need to improve the simulation of irrigation water allocation and residue decomposition processes, respectively, and together to distinguish different irrigation methods as DNDC95 does. All three models overestimated the emissions of the nitrogenous gases for high nitrogen fertilizer (>430 kg N ha(-1) yr(-1)) addition treatments, and therefore, future research should focus more on the simulation of the limitation of soil dissolvable organic carbon on denitrification in calcareous soils. |
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0308-521x |
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CropM, ft_macsur |
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MA @ admin @ |
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4685 |
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Author |
Conradt, T.; Gornott, C.; Wechsung, F. |
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Extending and improving regionalized winter wheat and silage maize yield regression models for Germany: Enhancing the predictive skill by panel definition through cluster analysis |
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Journal Article |
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Year |
2016 |
Publication |
Agricultural and Forest Meteorology |
Abbreviated Journal |
Agricultural and Forest Meteorology |
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216 |
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68-81 |
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Keywords |
cluster analysis; crop yield estimation; germany; multivariate regression; silage maize; winter wheat; climate-change; canadian prairies; crop yield; temperature; responses; environments; variability; cultivar; china |
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Abstract |
Regional agricultural yield assessments allowing for weather effect quantifications are a valuable basis for deriving scenarios of climate change effects and developing adaptation strategies. Assessing weather effects by statistical methods is a classical approach, but for obtaining robust results many details deserve attention and require individual decisions as is demonstrated in this paper. We evaluated regression models for annual yield changes of winter wheat and silage maize in more than 300 German counties and revised them to increase their predictive power. A major effort of this study was, however, aggregating separately estimated time series models (STSM) into panel data models (PDM) based on cluster analyses. The cluster analyses were based on the per-county estimates of STSM parameters. The original STSM formulations (adopted from a parallel study) contained also the non-meteorological input variables acreage and fertilizer price. The models were revised to use only weather variables as estimation basis. These consisted of time aggregates of radiation, precipitation, temperature, and potential evapotranspiration. Altering the input variables generally increased the predictive power of the models as did their clustering into PDM. For each crop, five alternative clusterings were produced by three different methods, and similarities between their spatial structures seem to confirm the existence of objective clusters about common model parameters. Observed smooth transitions of STSM parameter values in space suggest, however, spatial autocorrelation effects that could also be modeled explicitly. Both clustering and autocorrelation approaches can effectively reduce the noise in parameter estimation through targeted aggregation of input data. (C) 2015 Elsevier B.V. All rights reserved. |
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0168-1923 |
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MA @ admin @ |
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4709 |
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Zhen, L.; Deng, X.; Wei, Y.; Jiang, Q.; Lin, Y.; Helming, K.; Wang, C.; König, H.J.; Hu, J. |
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Title |
Future land use and food security scenarios for the Guyuan district of remote western China |
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Journal Article |
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2014 |
Publication |
iForest |
Abbreviated Journal |
iForest |
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7 |
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6 |
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372-384 |
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land-use patterns; scenario analysis; dynamics of land systems modeling; food security; guyuan district; north-central china; cultivated land; dynamics; conversion; policy |
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Government policy is a major human factor that causes changes in land use. Decisions on land management and land-use planning, as well as the analysis and quantification of policy consequences, may greatly benefit from the simulation of the dynamics of land-use systems. In the present study, we predicted land-use changes and their potential impacts on food security in the environmentally fragile Guyuan District, Ningxia Hui Autonomous Region (north-central China), under the influence of a program to convert sloping agricultural land to conservation uses. Baseline and conservation policy scenarios (2005 to 2020) were developed based on input from local stakeholders and expert knowledge. For the baseline and conservation policies, we formulated high-, moderate-, and low-growth scenarios, analyzed the driving mechanisms responsible for the land-use dynamics, and then applied a previously developed “dynamics of land systems” model to simulate changes in land uses based on the driving mechanisms. We found that spatially explicit policies can promote the conversion of land to more sustainable uses; however, decreasing the amount of agricultural and urban land and increasing grassland and forest cover will increase the risk of grain shortages, and the effect will be more severe under the conservation and high- growth scenarios than under the baseline and low-growth scenarios. The Guyuan case study suggests that, during the next decade, important trade-offs between environmental conservation and food security will inevitably occur. Future land-use decisions should carefully consider the balance between land resource conservation, agricultural production, and urban expansion. |
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1971-7458 |
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MA @ admin @ |
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4547 |
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