Analysis of potential evapotranspiration using 11 modified temperature-based models

Valipour, Mohammad; Eslamian, Saeid

doi:10.1504/ijhst.2014.067733

Cited by 119 publications

(50 citation statements)

References 42 publications

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“…This might be attributed to improved water uptake, root growth, and leaf erectness by application of Si (Gong et al 2003;Hattori et al 2005) and reduced the evapotranspiration which maintain water status of plant (Valipour and Eslamian 2014;Valipour 2014) and improved higher photosynthesis. Previously, Gong et al (2003) reported that addition of Si in soil increased photosynthetic rate drought conditions.…”

Section: Discussionmentioning

confidence: 99%

Physiological response of late sown wheat to exogenous application of silicon

Sattar¹,

Cheema

Abbas³

et al. 2017

Cereal Research Communications

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Late planting of wheat in rice-wheat cropping system is perhaps one of the major factors responsible for low crop yield. The main cause of reduction in yield is due to supra-optimal conditions during the reproductive growth. High temperature during reproductive phase induces changes in water relations, decreases photosynthetic rate, and transpiration rate, stomatal conductance and antioxidative defence system. Silicon (Si), being a beneficial nutrient not only provides significant benefits to plants growth and development but may also mitigate the adversities of high temperature. A field study was conducted at Agronomic Research Area of University of Agriculture; Faisalabad, Pakistan to assess the performance of late sown wheat with the soil applied Si. Experiment was comprised of three sowing dates; 10 th Nov (normal), 10 th Dec (late), 10 th Jan (very late) with two wheat varieties (Sehar-2006 and Faisalabad-2008), and an optimized dose of Si (100 mg per kg soil), applied at different growth stages (control, crown root, booting and heading). Results indicated that 100 mg Si per kg soil at heading stage offset the negative impact of high temperature and induced heat tolerance in late sown wheat. Silicon application improved 34% relative water contents (RWC), 30% water potential, 26% osmotic potential, 23% turgor potential and 21% photosynthetic rate, and 32% transpiration rate and 20% stomatal conductance in wheat flag leaf than control treatment. Further it was observed that Si application preventing the oxidative membrane damage due to enhanced activity of antioxidant enzymes, i.e. 35% superoxide dismutase (SOD) and 38% catalase (CAT). In conclusion results of this field study demonstrated that soil applied Si (100 mg per kg soil) at heading stage enhanced all physiological attributes of wheat flag leaf. Which in turn ameliorated the adverse effects of high temperature in late sown wheat. Study depicted that Si can be used as a potential nutrient in order to mitigate the losses induced by high temperature stress.

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Section: Discussionmentioning

confidence: 99%

Physiological response of late sown wheat to exogenous application of silicon

Sattar¹,

Cheema

Abbas³

et al. 2017

Cereal Research Communications

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“…This feedback has been verified by many observational and numerical studies in the transition zones between dry and wet climatic regions, where the high coupling between the land surface and the planetary boundary layer (PBL) could significantly influence the mesoscale convective systems (MCSs) [10,11]. In climate scales, positive effects of soil moisture on atmosphere in this closed feedback loop are suggested as the following: soil moisture partitions available net radiation into latent heat for evapotranspiration and sensible heat for temperature increase [12][13][14][15][16]. Therefore, soil moisture controls, to some extent, the thermodynamic conditions of the overlying lower atmosphere, which alters the PBL depth and moist static energy (MSE), and thus ultimately modulates the convective activities of the upper rainstorm.…”

Section: Introductionmentioning

confidence: 90%

Impacts of Soil Moisture on Typical Frontal Rainstorm in Yangtze River Basin

2016

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By using a coupled land surface-atmosphere model with initial conditions of varying resolution and ensembles of systematically changed soil moisture, convective-scale simulations of a typical frontal rainstorm in the Yangtze River Basin are collected to investigate: (1) effects of different datasets on the simulated frontal mesoscale convective systems (MCSs); (2) possible linkages between soil moisture, planetary boundary layer (PBL), MCSs and precipitation in this modeled rainstorm. Firstly, initial soil moisture differences can affect the PBL, MCSs and precipitation of this frontal rainstorm. Specially, for a 90 mm precipitation forecast, the Threat score (TS) can increase 6.61% by using the Global Land Data Assimilation System (GLDAS) soil moisture. Secondly, sensitivity experiment results show that the near-surface thermodynamic conditions are more sensitive to dry soil than wet due to the initial moist surface; atmosphere conditions have suppressed the relations between soil and atmosphere; and decreased precipitation can be found over both wet and dry surfaces. Generally, a positive feedback between soil moisture and the near-surface thermodynamic conditions is identified, while the relations between soil moisture and precipitation are quite complicated. This relationship shows a daytime mixing of warm surface soil over dry surfaces and a daytime evaporation of adequate moisture over wet surfaces. The large-scale forcing can affect these relations and finally cause decreased precipitation over both wet and dry surfaces.

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“…Regression coefficients are used to reflect the proportional relationship between driving factors and carbon emissions [30][31][32][33]. In order to further investigate the driving factors, a few more factors have been introduced to explain changes in carbon emissions.…”

Section: Lni a Blnp Clna Dlnt Lnementioning

confidence: 99%

Factors Driving Energy-Related Carbon Emissions in Xinjiang: Applying the Extended STIRPAT Model

Wang¹,

Wen²,

Wang³

et al. 2017

Pol. J. Environ. Stud.

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To achieve emission reduction targets in China, it is necessary to analyze the factors driving energyrelated carbon emissions from a regional perspective. We used extended STIRPAT model (stochastic impacts by regression on population, affluence, and technology) based on the classical IPAT identity (where I = impact representing carbon emissions, P = population, A = affluence, and T = emission intensity) to determine the main factors driving energy-related carbon emissions in Xinjiang from 1952 to 2014, an important Chinese energy base in northwestern China. Total carbon emissions in Xinjiang were found to increase from 28.51 × 10 4 t in 1952 to 9,446.61 × 10 4 t in 2014, representing a 331.34-fold increase over a period of 63 years. Results show that the impacts and influences of various factors on carbon emissions varied among three stages of development: "Before Reform and Opening up" , "After Reform and Opening up" , and "Western Development" (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). In the first stage, emission intensity and population size were the dominant contributors to increments in carbon emissions, while the energy consumption structure played an important role in curbing carbon emissions. In the second stage, economic growth and population size were the dominant contributors to increments in carbon emissions, while emission intensity had a significant negative effect on carbon emissions. In the third stage, fixed asset investment and economic growth were the dominant contributors to increments in carbon emissions, while emission intensity had a significant negative effect on carbon emissions.

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Analysis of potential evapotranspiration using 11 modified temperature-based models

Cited by 119 publications

References 42 publications

Physiological response of late sown wheat to exogenous application of silicon

Physiological response of late sown wheat to exogenous application of silicon

Impacts of Soil Moisture on Typical Frontal Rainstorm in Yangtze River Basin

Factors Driving Energy-Related Carbon Emissions in Xinjiang: Applying the Extended STIRPAT Model

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