scholarly journals Impact of climate change on the blue water footprint of agriculture on a regional scale

2018 ◽  
Vol 19 (1) ◽  
pp. 52-59 ◽  
Author(s):  
Huiping Huang ◽  
Yuping Han ◽  
Dongdong Jia
Keyword(s):  
Climate Change ◽  
Temporal Change ◽  
Water Footprint ◽  
Regional Scale ◽  
Maximum Temperature ◽  
Agricultural Water ◽  
Climate Change Projections ◽  
Change Models ◽  
Average Value

Abstract In the case study of Tangshan city, Hebei Province, China, this paper analyzes the temporal change of the blue agricultural water footprint (WF) during 1991–2016 and discusses the applicability of different climate change models during 2017–2050. Results show effective rainfall, wind speed and maximum temperature are leading factors influencing the blue agricultural WF. Relative error analysis indicates that the HadGEM2-ES model is the most applicable for climate change projections in the period of 2017–2050. Agricultural blue WF is about 1.8 billion m3 in RCP2.6, RCP4.5 and RCP8.5 emission scenarios, which is almost equal to the average value during 1991–2016.

scholarly journals Impact of Climate Change on Production and Productivity: A Case Study of Maize Research and Development In Nepal

2010 ◽  
Vol 11 ◽  
pp. 59-69 ◽  
Author(s):  
Janak Lal Nayava ◽  
Dil Bahadur Gurung
Keyword(s):  
Climate Change ◽  
Maize Yield ◽  
Maximum Temperature ◽  
Rainfall Distribution ◽  
Maize Production ◽  
Growing Seasons ◽  
Agriculture And Environment ◽  
Present Rate ◽  
Annual Maximum Temperature

The relation between climate and maize production in Nepal was studied for the period 1970/71-2007/08. Due to the topographical differences within north-south span of the country, Nepal has wide variety of climatic condition. About 70 to 90% of the rainfall occurs during summer monsoon (June to September) and the rest of the months are almost dry. Maize is cultivated from March to May depending on the rainfall distribution. Due to the availability of improved seeds, the maize yield has been steadily increasing after 1987/1988. The national area and yield of maize is estimated to be 870,166ha and 2159kg/ha respectively in 2007/08. The present rate of annual increase of temperature is 0.04°C in Nepal. Trends of temperature rise are not uniform throughout Nepal. An increase of annual temperature at Rampur during 1968-2008 was only 0.039°C. However, at Rampur during the maize growing seasons, March/April - May, the trend of annual maximum temperature had not been changed, but during the month of June and July, the trend of increase of maximum temperature was 0.03°C to 0.04°C /year.Key words: Climate-change; Global-warming; Hill; Mountain; Nepal; TaraiThe Journal of AGRICULTURE AND ENVIRONMENT Vol. 11, 2010Page: 59-69Uploaded Date: 15 September, 2010

scholarly journals Equitable Allocation of Blue and Green Water Footprints Based on Land-Use Types: A Case Study of the Yangtze River Economic Belt

2018 ◽  
Vol 10 (10) ◽  
pp. 3556 ◽  
Author(s):  
Gang Liu ◽  
Lu Shi ◽  
Kevin Li
Keyword(s):  
Land Use ◽  
Water Resources ◽  
Agricultural Land ◽  
Optimal Allocation ◽  
Water Footprint ◽  
Agricultural Water ◽  
Land Area ◽  
Lexicographic Optimization ◽  
The Impact

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.

Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies

2015 ◽  
Vol 95 (1) ◽  
pp. 49-61 ◽  
Author(s):  
Ted Huffman ◽  
Budong Qian ◽  
Reinder De Jong ◽  
Jiangui Liu ◽  
Hong Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Spring Wheat ◽  
Input Data ◽  
Crop Yields ◽  
Regional Scale ◽  
Climate Change Impacts ◽  
Crop Productivity ◽  
Canadian Prairies ◽  
Crop Models

Huffman, T., Qian, B., De Jong, R., Liu, J., Wang, H., McConkey, B., Brierley, T. and Yang, J. 2015. Upscaling modelled crop yields to regional scale: A case study using DSSAT for spring wheat on the Canadian prairies. Can. J. Soil Sci. 95: 49–61. Dynamic crop models are often operated at the plot or field scale. Upscaling is necessary when the process-based crop models are used for regional applications, such as forecasting regional crop yields and assessing climate change impacts on regional crop productivity. Dynamic crop models often require detailed input data for climate, soil and crop management; thus, their reliability may decrease at the regional scale as the uncertainty of simulation results might increase due to uncertainties in the input data. In this study, we modelled spring wheat yields at the level of numerous individual soils using the CERES–Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) and then aggregated the simulated yields from individual soils to regions where crop yields were reported. A comparison between the aggregated and the reported yields was performed to examine the potential of using dynamic crop models with individual soils in a region for the simulation of regional crop yields. The regionally aggregated simulated yields demonstrated reasonable agreement with the reported data, with a correlation coefficient of 0.71 and a root-mean-square error of 266 kg ha−1 (i.e., 15% of the average yield) over 40 regions on the Canadian prairies. Our conclusion is that aggregating simulated crop yields on individual soils with a crop model can be reliable for the estimation of regional crop yields. This demonstrated its potential as a useful approach for using crop models to assess climate change impacts on regional crop productivity.

scholarly journals Assessment of impacts of climate change on water resources – a case study of the Great Lakes of North America

2006 ◽  
Vol 3 (5) ◽  
pp. 3183-3209 ◽  
Author(s):  
E. McBean ◽  
H. Motiee
Keyword(s):  
Climate Change ◽  
Great Lakes ◽  
Historical Data ◽  
Global Climate ◽  
Lake Superior ◽  
Great Lakes Basin ◽  
Historical Trends ◽  
Change Models ◽  
Impacts Of Climate Change

Abstract. Historical trends in precipitation, temperature, and streamflows in the Great Lakes are examined using regression analysis and Mann-Kendall statistics, with the result that many of these variables demonstrate statistically significant increases ongoing for a six decade period. Future precipitation rates as predicted using fitted regression lines are compared with scenarios from Global Climate Change Models (GCMs) and demonstrate similar forecast predictions for Lake Superior. Trend projections from historical data are, however, higher than GCM predictions for Michigan/Huron. Significant variability in predictions, as developed from alternative GCMs, is noted. Given the general agreement as derived from very different procedures, predictions extrapolated from historical trends and from GCMs, there is evidence that hydrologic changes in the Great Lakes Basin are likely the result of climate change.

Detection and attribution of climate change at regional scale: case study of Karkheh river basin in the west of Iran

2016 ◽  
Vol 130 (3-4) ◽  
pp. 1007-1020 ◽  
Author(s):  
Narges Zohrabi ◽  
Elahe Goodarzi ◽  
Alireza Massah Bavani ◽  
Husain Najafi
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Regional Scale ◽  
The West ◽  
Detection And Attribution ◽  
Karkheh River Basin
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