Model and Growth Stage Based Variability of the Irrigation Demand of Onion Crops with Predicted Climate Change

The variation characteristics of growth stages of winter wheat (Triticum aestivum L.) with the climate change were measured by designing its stability and prediction model. Results showed the trend of stability of growth stage of winter wheat in Jiangsu province of China was an S-shaped curve indicating the growth of winter wheat was more stable in late stage. The lengths of early and late stages of growth were in inverse proportion. Specifically, when the early stage was prolonged, the late stage was shortened, which ensured the relative stability of the length of growth stage. The length of growth stage was correlated with the meteorological conditions. Thus, favorable meteorological conditions contributed to the stability of growth stages of winter wheat. Along with the climate change, the basic statistical characteristics of growth stage remained stable. Each stage drifted moderately under the variation of meteorological conditions, typically during the stage of vegetative growth. The growth process can be regulated by means of variety improvement, adjustment of sowing time and density, reasonable fertilization, and the use of growth regulators. These measures are able to counteract the influences of climate change on winter wheat production and ensure the production security. Bangladesh J. Bot. 50(3): 737-746, 2021 (September) Special

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Growth stage-dependent responses of carbon fixation process of alpine grasslands to climate change over the Tibetan Plateau, China

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2020.108085 ◽

2020 ◽

Vol 291 ◽

pp. 108085 ◽

Cited By ~ 2

Author(s):

Yongfa You ◽

Siyuan Wang ◽

Naiqing Pan ◽

Yuanxu Ma ◽

Weihua Liu

Keyword(s):

Climate Change ◽

Tibetan Plateau ◽

Growth Stage ◽

Carbon Fixation ◽

The Tibetan Plateau ◽

Alpine Grasslands

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Effect of irrigation efficiency enhancement on water demand of date palms in a Tunisian oasis under climate change

Journal of Water and Climate Change ◽

10.2166/wcc.2020.099 ◽

2020 ◽

Author(s):

Zied Haj-Amor ◽

Tapos Kumar Acharjee

Keyword(s):

Climate Change ◽

Field Measurements ◽

Irrigation Efficiency ◽

Water Salinity ◽

Climate Change Scenarios ◽

Efficiency Enhancement ◽

Surface Irrigation ◽

Date Palms ◽

Irrigation Demand ◽

The Impact

Abstract Consideration of future change in water salinity is important for estimating irrigation demand in salinity-prone arid regions. Further, it is important to evaluate the contribution of irrigation efficiency enhancement to climate change resilience. Based on field measurements in 2019, a simulation approach from 2019 to 2050 was carried out in this study to investigate the impact of climate change and its consequences (i.e., change in water salinity) on the future gross irrigation demand of date palms and possible applied dose of water in a Tunisian oasis considering different irrigation efficiency enhancements. The estimation was done under very high (RCP 8.5), medium (RCP 6.0), and low (RCP 4.5) emission scenarios using the CROPWAT model. Results first showed an increase in gross irrigation requirement under inefficient surface irrigation (37% efficiency) from 3,340 mm year−1 in 2019 to 3,588–3,642 mm year−1 in 2050 for different climate change scenarios. This significant increase is mainly attributed to a significant change in climate variables and a high increase in water salinity. Second, considerable water savings (up to 1,980 mm) can be achieved if surface irrigation efficiency increases from the current value of 37–70%. Finally, much water can be saved only by reducing the overdose amount of water.

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Analysing the risk of climate change using an irrigation demand model

Climate Research ◽

10.3354/cr014089 ◽

2000 ◽

Vol 14 ◽

pp. 89-100 ◽

Cited By ~ 58

Author(s):

RN Jones

Keyword(s):

Climate Change ◽

Demand Model ◽

Irrigation Demand

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Assessing the Spatial Pattern of Irrigation Demand under Climate Change in Arid Area

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9090506 ◽

2020 ◽

Vol 9 (9) ◽

pp. 506

Author(s):

Liping Wang ◽

Shufang Wang ◽

Liudong Zhang ◽

Mohamed Khaled Salahou ◽

Xiyun Jiao ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

Spatial Pattern ◽

General Circulation ◽

General Circulation Models ◽

Northwest China ◽

Arid Areas ◽

Irrigation Demand ◽

Balance System ◽

Rcp 8.5

Studying the pattern of agricultural water demand under climate change has great significance for the regional water resources management, especially in arid areas. In this study, the future pattern of the irrigation demand in Hotan Oasis in Xinjiang Uygur Autonomous Region in Northwest China, including Hotan City, Hotan County, Moyu County and Luopu County, was assessed based on the general circulation models (GCMs) and the Surface Energy Balance System model (SEBS). Six different scenarios were used based on the GCMs of BCC_CSM1.1, HadGEM2-ES and MIROC-ESM-CHEM under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5. The results showed that the method integrating the GCMs and SEBS to predict the spatial pattern was useful. The irrigation demand of Hotan Oasis will increase in 2021–2040. The annual irrigation demand of Hotan City is higher, with 923.2 and 936.2 mm/a in 2021–2030 and 2031–2040, respectively. The other three regions (Hotan County, Moyu County and Luopu County) are lower in the six scenarios. The annual irrigation demand showed a spatial pattern of high in the middle, low in the northwest and southeast under the six scenarios in 2021–2040. The study can provide useful suggestions on the water resources allocation in different regions to protect water resources security in arid areas.

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Impact of climate change and carbon dioxide fertilization effect on irrigation water demand and yield of soybean in Serbia

The Journal of Agricultural Science ◽

10.1017/s0021859615000179 ◽

2015 ◽

Vol 153 (8) ◽

pp. 1365-1379 ◽

Cited By ~ 2

Author(s):

M. JANCIC ◽

B. LALIC ◽

D. T. MIHAILOVIC ◽

G. JACIMOVIC

Keyword(s):

Climate Change ◽

Carbon Dioxide ◽

Water Productivity ◽

Climate Change Impacts ◽

Weather Data ◽

Soybean Yield ◽

Change Models ◽

Irrigation Demand ◽

Carbon Dioxide Fertilization ◽

Weather Stations

SUMMARYThe Decision Support System for Agrotechnology Transfer (DSSAT) v. 4·2 crop model was used to estimate climate change impacts on soybean yield in Serbia in simulations for 2030 and 2050 integration periods using three global climate change models (GCMs): the European Centre Hamburg Model (ECHAM), The Hadley Centre Coupled Model (HadCM) and the National Center for Atmospheric Research Parallel Climate Model (NCAR-PCM) under two scenarios from the IPCC Special Report on Emissions Scenarios (IPCC 2001): A1B SRES and A2 SRES. Input data included weather data from a 1971–2000 baseline period from ten weather stations assimilated from the Republic Hydrometeorological Service of Serbia. Output results from the three GCMs under the two scenarios for 2030 and 2050 were statistically downscaled with the ‘Met & Roll’ weather generator for predicted climate conditions. Mechanical and chemical soil properties were collected in the vicinity of weather stations and analysed by the Agency for Environmental Safety in Belgrade. Genetic coefficients, for the soybean maturity group II variety, were slightly modified using the DSSAT-SOYGRO model ones. The results showed a considerable benefit of carbon dioxide fertilization on soybean yield and yield increases at all locations. The greatest estimated yield increases obtained using outputs the HadCM model for 2030 both scenarios; in 2050, however, the A2 scenario resulted in smaller increase in yield at some locations. The highest increase in yield was in the central and eastern parts of Serbia. Analyses of the climate change impacts on irrigation demand showed a great increase in the irrigation demand amount per growing season. The average irrigation demand reached the highest values in the southern and eastern parts of Serbia. Water productivity reached highest values in eastern and central locations, while the minimum is expected in the most southern and northern location. According to all results it can be concluded that soybean will benefit greatly under climate change conditions and that soybean cropping, currently most concentrated in the Vojvodina region in northern Serbia, expanding in the central part and one location in eastern Serbia.

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A GIS-Based Approach to Estimate Electricity Requirements for Small-Scale Groundwater Irrigation

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10110780 ◽

2021 ◽

Vol 10 (11) ◽

pp. 780

Author(s):

Anna Nilsson ◽

Dimitrios Mentis ◽

Alexandros Korkovelos ◽

Joel Otwani

Keyword(s):

Climate Change ◽

Energy Demand ◽

Average Energy ◽

Sub Saharan Africa ◽

Small Scale ◽

Reference Scenario ◽

Energy Services ◽

Irrigation Demand ◽

Groundwater Irrigation ◽

Effective Manner

Access to modern energy services is a precondition to improving livelihoods and building resilience against climate change. Still, electricity reaches only about half of the population in Sub-Saharan Africa (SSA), while about 40% live under the poverty line. Heavily reliant on the agriculture sector and increasingly affected by prolonged droughts, small-scale irrigation could be instrumental for development and climate change adaptation in SSA countries. A bottom-up understanding of the demand for irrigation and associated energy services is essential for designing viable energy supply options in an effective manner. Using Uganda as a case study, the study introduces a GIS-based methodology for the estimation of groundwater irrigation requirements through which energy demand is derived. Results are generated for two scenarios: (a) a reference scenario and (b) a drought scenario. The most critical need is observed in the northern and southern regions of the country. The total annual irrigation demand is estimated to be ca. 90 thousand m3, with the highest demand observed in the months of December through February, with an average irrigation demand of 445 mm per month. The highest energy demand is observed in the northern part of the study area in January, reaching 48 kWh/ha. The average energy demand increases by 67% in the drought scenario. The study contributes to current gaps in the existing literature by providing a replicable methodological framework and data aimed at facilitating energy system planning through the consideration of location-specific characteristics at the nexus of energy–water–agriculture.

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