Climate Change Impact on Wheat Production in the Southern Great Plains of the US Using Downscaled Climate Data

Abstract. Potential evapotranspiration PET is the water that would be lost by plants through evaporation and transpiration if water was not limited in the soil, and it is commonly used in conceptual hydrological modelling in the calculation of runoff production and hence river discharge. Future changes of PET are likely to be as important as changes in precipitation patterns in determining changes in river flows. However PET is not calculated routinely by climate models so it must be derived independently when the impact of climate change on river flow is to be assessed. This paper compares PET estimates from twelve equations of different complexity, driven by the Hadley Centre's HadRM3-Q0 model outputs representative of 1961–1990, with MORECS PET, a product used as reference PET in Great Britain. The results show that the FAO56 version of the Penman-Monteith equations reproduce best the spatial and seasonal variability of MORECS PET across GB when driven by HadRM3-Q0 estimates of relative humidity, total cloud, wind speed and linearly bias-corrected mean surface temperature. This suggests that potential biases in HadRM3-Q0 climate do not result in significant biases when the physically-based FAO56 equations are used. Percentage changes in PET between the 1961–1990 and 2041–2070 time slices were also calculated for each of the twelve PET equations. Results show a large variation in the magnitude (and sometimes direction) of changes estimated from different PET equations, with Turc, Jensen-Hense and calibrated Blaney-Criddle methods systematically projecting the largest increases across GB for all months and Priestley-Taylor, Makkink and Thornthwaite showing the smallest changes. We recommend the use of the FAO56 equation as when driven by HadRM3-Q0 climate data this best reproduces the reference MORECS PET across Great Britain for the reference period of 1961–1990. Further, the future changes of PET estimated by FAO56 are within the range of uncertainty defined by the ensemble of twelve PET equations. The changes show a clear northwest-southeast gradient of PET increase with largest (smallest) changes in the northwest in January (July and October) respectively. However, the range in magnitude of PET changes due to the choice of PET method shown in this study for Great Britain suggests that PET uncetainty is perhaps one of the greatest challenges facing the assessment of climate change impact on hydrology.

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Reliability and input-data induced uncertainty of the EPIC model to estimate climate change impact on sorghum yields in the U.S. Great Plains

Agriculture Ecosystems & Environment ◽

10.1016/j.agee.2008.09.012 ◽

2009 ◽

Vol 129 (1-3) ◽

pp. 268-276 ◽

Cited By ~ 51

Author(s):

Xianzeng Niu ◽

William Easterling ◽

Cynthia J. Hays ◽

Allyson Jacobs ◽

Linda Mearns

Keyword(s):

Climate Change ◽

Great Plains ◽

Climate Change Impact ◽

Input Data ◽

Epic Model ◽

Change Impact ◽

The U.S

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Derivation of RCM-driven potential evapotranspiration for hydrological climate change impact analysis in Great Britain: a comparison of methods and associated uncertainty in future projections

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1365-2013 ◽

2013 ◽

Vol 17 (4) ◽

pp. 1365-1377 ◽

Cited By ~ 33

Author(s):

C. Prudhomme ◽

J. Williamson

Keyword(s):

Climate Change ◽

Great Britain ◽

Climate Change Impact ◽

Impact Analysis ◽

Climate Models ◽

River Flow ◽

Potential Evapotranspiration ◽

Climate Data ◽

Change Impact ◽

The Impact

Abstract. Potential evapotranspiration (PET) is the water that would be lost by plants through evaporation and transpiration if water was not limited in the soil, and it is commonly used in conceptual hydrological modelling in the calculation of runoff production and hence river discharge. Future changes of PET are likely to be as important as changes in precipitation patterns in determining changes in river flows. However PET is not calculated routinely by climate models so it must be derived independently when the impact of climate change on river flow is to be assessed. This paper compares PET estimates from 12 equations of different complexity, driven by the Hadley Centre's HadRM3-Q0 model outputs representative of 1961–1990, with MORECS PET, a product used as reference PET in Great Britain. The results show that the FAO56 version of the Penman–Monteith equations reproduces best the spatial and seasonal variability of MORECS PET across GB when driven by HadRM3-Q0 estimates of relative humidity, total cloud, wind speed and linearly bias-corrected mean surface temperature. This suggests that potential biases in HadRM3-Q0 climate do not result in significant biases when the physically based FAO56 equations are used. Percentage changes in PET between the 1961–1990 and 2041–2070 time slices were also calculated for each of the 12 PET equations from HadRM3-Q0. Results show a large variation in the magnitude (and sometimes direction) of changes estimated from different PET equations, with Turc, Jensen–Haise and calibrated Blaney–Criddle methods systematically projecting the largest increases across GB for all months and Priestley–Taylor, Makkink, and Thornthwaite showing the smallest changes. We recommend the use of the FAO56 equation as, when driven by HadRM3-Q0 climate data, this best reproduces the reference MORECS PET across Great Britain for the reference period of 1961–1990. Further, the future changes of PET estimated by FAO56 are within the range of uncertainty defined by the ensemble of 12 PET equations. The changes show a clear northwest–southeast gradient of PET increase with largest (smallest) changes in the northwest in January (July and October) respectively. However, the range in magnitude of PET changes due to the choice of PET method shown in this study for Great Britain suggests that PET uncertainty is a challenge facing the assessment of climate change impact on hydrology mostly ignored up to now.

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Climate change impact on Mexico wheat production

Agricultural and Forest Meteorology ◽

10.1016/j.agrformet.2018.09.008 ◽

2018 ◽

Vol 263 ◽

pp. 373-387 ◽

Cited By ~ 24

Author(s):

Ixchel M. Hernandez-Ochoa ◽

Senthold Asseng ◽

Belay T. Kassie ◽

Wei Xiong ◽

Ricky Robertson ◽

...

Keyword(s):

Climate Change ◽

Climate Change Impact ◽

Wheat Production ◽

Change Impact

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Numerical assessment of climate change impact on the hydrological regime of a small Mediterranean river, Lesvos Island, Greece

Acta Horticulturae et Regiotecturae ◽

10.2478/ahr-2021-0022 ◽

2021 ◽

Vol 24 (1) ◽

pp. 28-48

Author(s):

Eleni Ioanna Koutsovili ◽

Ourania Tzoraki ◽

Nicolaos Theodossiou ◽

Petros Gaganis

Keyword(s):

Climate Change ◽

Climate Change Impact ◽

Future Climate Change ◽

Research Station ◽

Hydrologic Regime ◽

Climate Change Scenarios ◽

Climate Data ◽

Mediterranean River ◽

Basin Scale ◽

Change Impact

Abstract Frequency of flash floods and droughts in the Mediterranean climate zone is expected to rise in the coming years due to change of its climate. The assessment of the climate change impact at a basin scale is essential for developing mitigation and adaptation plans. This study analyses the variation of the hydrologic regime of a small Mediterranean river (the Kalloni river in Lesvos Island, Greece) by the examination of possible future climate change scenarios. The hydrologic response of the basin was simulated based on Hydrologic Modeling System developed by the Hydrologic Engineering Center (HEC-HMS). Weather Generator version 6 from the Long Ashton Research Station (LARS-WG 6.0) was utilized to forecast climate data from 2021 to 2080. These forecasted climate data were then assigned as weather inputs to HEC-HMS to downscale the climate predictions of five large-scale general circulation models (GCMs) for three possible emission scenarios (such as RCP 2.6, RCP 4.5, and RCP 8.5). The alteration of the Kalloni hydrologic regime is evaluated by comparing GCMs based estimates of future streamflow and evapotranspiration with business as usual (BaU) scenario. Variation was noted in seasonal and in annual scale forecasting of long-term average discharges, which show increasing trend in autumn and decreasing in summer and there is observed a general upward trend of actual evapotranspiration losses.

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