Assessment of Climate Change Impacts on Reference Evapotranspiration and Simulation of Daily Weather Data Using
            SIMETAW

This study evaluates the effect of climate change on reference evapotranspiration (ET0), which is one of the most important variables in water resources management and irrigation scheduling. For this purpose, daily weather data of 30 Iranian weather stations from 1981 and 2010 were used. The HadCM3 statistical model was applied to report the output subscale of LARS-WG and to predict the weather information by A1B, A2, and B1 scenarios in three periods: 2011–2045, 2046–2079, and 2080–2113. The ET0 values were estimated by the Ref-ET software. The results indicated that the ET0 will rise from 2011 to 2113 approximately in all stations under three scenarios. The ET0 changes percentages in the A1B scenario during three periods from 2011 to 2113 were found to be 0.98%, 5.18%, and 12.17% compared to base period, respectively, while for the B1 scenario, they were calculated as 0.67%, 4.07%, and 6.61% and for the A2 scenario, they were observed as 0.59%, 5.35%, and 9.38%, respectively. Thus, the highest increase of the ET0 will happen from 2080 to 2113 under the A1B scenario; however, the lowest will occur between 2046 and 2079 under the B1 scenario. Furthermore, the assessment of uncertainty in the ET0 calculated by the different scenarios showed that the ET0 predicted under the A2 scenario was more reliable than the others. The spatial distribution of the ET0 showed that the highest ET0 amount in all scenarios belonged to the southeast and the west of the studied area. The most noticeable point of the results was that the ET0 differs from one scenario to another and from a period to another.

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Impact of climate change on harvest security and biomass yield of two timothy ley harvesting systems in Norway

The Journal of Agricultural Science ◽

10.1017/s0021859612001013 ◽

2013 ◽

Vol 152 (2) ◽

pp. 205-216 ◽

Cited By ~ 12

Author(s):

T. PERSSON ◽

M. HÖGLIND

Keyword(s):

Climate Change ◽

Biomass Yield ◽

Phleum Pratense ◽

Future Climate ◽

Weather Data ◽

Future Climate Change ◽

Daily Weather ◽

Daily Weather Data ◽

Dry Spell ◽

Harvesting Regime

SUMMARYPredicted future climate changes in northern Europe include increased air temperature and altered precipitation patterns. There is a lack of knowledge about potential climate change effects on the biomass yield and security of agricultural crops. The present study determined the potential impact of future climate change on the yield and harvest security of timothy (Phleum pratense L.). Harvest security was assessed using data on accumulated precipitation and the length of dry spell period within the 7 days after cutting. Timothy production as a function of weather, soil and management practices was simulated using the LINGRA model for the periods 1961–90, 2046–65 and 2080–99, and the locations Apelsvoll, Ås, Sola, Tromsø and Værnes in Norway and harvest systems with 600 and 800 °C days between cuts. One hundred years of daily weather data were generated with the LARS-WG tool, using future daily weather data sets based on 12 Global Climate Models. Total seasonal biomass yield varied between 690 g dry matter (DM)/m2 for the 800 °C days harvesting regime in the period 1961–90 at Tromsø and 1548 g DM/m2 for the same harvesting regime in the period 2046–65 at Sola. In general, the biomass was higher in the two future periods than in 1961–90 across locations and harvesting regimes, mainly owing to more cuts per season. Accumulated precipitation after cutting varied between 12·2 mm after the first cut for the 600 °C days harvesting regime in the period 1961–90 at Værnes and 42·5 mm after the fourth cut in the 800 °C days harvesting regime in the period 2080–99 at Sola. The longest duration of dry spell 7 days after pre-planned harvest varied between 1·8 days after the fourth cut at Sola in the 600 °C days harvesting regime for the period 2080–99, and 3·9 days after the first cut at Ås in the 800 °C days harvesting regime for the period 2046–65. Potential consequences of these results are discussed.

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Generation of Synthetic Daily Weather for Climate Change Scenarios and Extreme Storm Intensification

Environment and Natural Resources Research ◽

10.5539/enrr.v9n2p1 ◽

2019 ◽

Vol 9 (2) ◽

pp. 1

Author(s):

Jurgen Garbrecht ◽

X. C. Zhang ◽

David Brown ◽

Phillip Busteed

Keyword(s):

Climate Change ◽

Weather Data ◽

Climate Projections ◽

Climate Change Scenarios ◽

Generation Model ◽

Traditional Role ◽

Climate Conditions ◽

Daily Weather ◽

Daily Weather Data

Long-term simulations in watershed hydrology, soil and nutrient transport, and sustainability of agricultural production systems require long-term weather records that are often not available at the location of interest. Generation of synthetic daily weather data is a common approach to augment limited weather observations. Here a synthetic daily weather generation model (called SYNTOR) is described. SYNTOR fulfills the traditional role of generating alternative weather realizations that have statistical properties similar to those of the parent historical weather it is intended to simulate. In addition, it has the capability to simulate daily weather records for climate change scenarios and storm intensification due to climate change. The various model components are briefly summarized and an application is presented for semi-arid climate conditions in west-central Oklahoma. SYNTOR generated daily weather compared well with observed weather values. Climate change is simulated by adjusting weather generation parameters to reflect the changed mean monthly weather values of climate projections. Storm intensification is approximated by increasing the top 10 percentile of storm distribution by a predefined amount based on previous studies of trends in United States precipitation. Further evaluation of published storm intensification values and associated uncertainties and spatial variability is recommended.

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Integrated assessment of impact of water resources of important river basins in Eastern India under projected climate conditions

Global NEST Journal ◽

10.30955/gnj.001658 ◽

2015 ◽

Vol 17 (3) ◽

pp. 594-606 ◽

Cited By ~ 5

Keyword(s):

Climate Change ◽

Water Resources ◽

Catchment Area ◽

River Basins ◽

Weather Data ◽

Distributed Hydrological Model ◽

Eastern India ◽

Impact Of Climate Change ◽

Daily Weather Data ◽

The Impact

<div> The impact of climate change on water resources through increased evaporation combined with regional changes in precipitation characteristics has the potential to affect mean runoff, frequency and intensity of floods and droughts, soil moisture and water supply for irrigation and hydroelectric power generation. The Ganga-Brahmaputra-Meghna (GBM) system is the largest in India with a catchment area of about 110Mha, which is more than 43% of the cumulative catchment area of all the major rivers in the country. The river Damodar is an important sub catchment of GBM basin and its three tributaries- the Bokaro, the Konar and the Barakar form one important tributary of the Bhagirathi-Hughli (a tributary of Ganga) in its lower reaches. The present study is an attempt to assess the impacts of climate change on water resources of the four important Eastern River Basins namely Damodar, Subarnarekha, Mahanadi and Ajoy, which have immense importance in industrial and agricultural scenarios in eastern India. A distributed hydrological model (HEC-HMS) has been used on the four river basins using HadRM2 daily weather data for the period from 2041 to 2060 to predict the impact of climate change on water resources of these river systems.  </div>

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A simulation model operating with daily weather data to explore silage and haymaking opportunities in climatically different areas of Scotland

Agricultural Systems ◽

10.1016/0308-521x(94)00019-n ◽

1995 ◽

Vol 48 (3) ◽

pp. 315-343 ◽

Cited By ~ 7

Author(s):

M.B. McGechan ◽

G. Cooper

Keyword(s):

Simulation Model ◽

Weather Data ◽

Daily Weather ◽

Daily Weather Data

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Long-Term (2001–2020) Nutrient Transport from a Small Boreal Agricultural Watershed: Hydrological Control and Potential of Retention Ponds

Water ◽

10.3390/w12102731 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2731

Author(s):

Sari Uusheimo ◽

Tiina Tulonen ◽

Jussi Huotari ◽

Lauri Arvola

Keyword(s):

Climate Change ◽

Total Nitrogen ◽

Total Phosphorus ◽

Nutrient Loading ◽

Nitrogen Loading ◽

Agricultural Watershed ◽

Weather Data ◽

Pond System ◽

Daily Weather Data

Agriculture contributes significantly to phosphorus and nitrogen loading in southern Finland. Climate change with higher winter air temperatures and precipitation may also promote loading increase further. We analyzed long-term nutrient trends (2001–2020) based on year-round weekly water sampling and daily weather data from a boreal small agricultural watershed. In addition, nutrient retention was studied in a constructed sedimentation pond system for two years. We did not find any statistically significant trends in weather conditions (temperature, precipitation, discharge, snow depth) except for an increase in discharge in March. Increasing trends in annual concentrations were found for nitrate, phosphate, and total phosphorus and total nitrogen. In fact, phosphate concentration increased in every season and nitrate concentration in other seasons except in autumn. Total phosphorus and total nitrogen concentrations increased in winter as well and total phosphorus also in summer. Increasing annual loading trend was found for total phosphorus, phosphate, and nitrate. Increasing winter loading was found for nitrate and total nitrogen, but phosphate loading increased in winter, spring, and summer. In the pond system, annual retention of total nitrogen was 1.9–4.8% and that of phosphorus 4.3–6.9%. In addition, 25–40% of suspended solids was sedimented in the ponds. Our results suggest that even small ponds can be utilized to decrease nutrient and material transport, but their retention efficiency varies between years. We conclude that nutrient loading from small boreal agricultural catchments, especially in wintertime, has already increased and is likely to increase even further in the future due to climate change. Thus, the need for new management tools to reduce loading from boreal agricultural lands becomes even more acute.

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Climate change impact on energy balance of net-zero energy buildings in typical climate regions of China

E3S Web of Conferences ◽

10.1051/e3sconf/201911104004 ◽

2019 ◽

Vol 111 ◽

pp. 04004

Author(s):

Jiale Chai ◽

Pei Huang ◽

Yongjun Sun

Keyword(s):

Climate Change ◽

Energy Balance ◽

Climate Change Impacts ◽

Weather Data ◽

Zero Energy ◽

Zero Energy Building ◽

Net Zero Energy ◽

Net Zero Energy Building ◽

Net Zero ◽

Study Results

Net-zero energy building (NZEB) is widely considered as a promising solution to the current energy and environmental problems. The existing NZEBs are designed using the historical weather data (e.g. typical meteorological year-TMY). Nevertheless, due to climate change, the actual weather data during a NZEB’s lifecycle may differ considerably from the historical weather data. Consequently, the designed NZEBs using the historical weather data may not achieve the desired performance in their lifecycles. Therefore, this study investigates the climate change impacts on NZEB’s energy balance in different climate regions, and also evaluates different measures’ effectiveness in mitigating the associated impacts of climate change. In the study, the multi-year future weather data in different climate regions are firstly generated using the morphing method. Then, using the generated future weather data, the energy balance of the NZEBs, designed using the TMY data, are assessed. Next, to mitigate the climate change impacts, different measures are adopted and their effectiveness is evaluated. The study results can improve the understanding of climate change impacts on NZEB’s energy balance in different climate regions. They can also help select proper measures to mitigate the climate change impacts in the associated climate regions.

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Assessing the impact of climate change on crop management in winter wheat – a case study for Eastern Austria

The Journal of Agricultural Science ◽

10.1017/s0021859616000083 ◽

2016 ◽

Vol 154 (7) ◽

pp. 1153-1170 ◽

Cited By ~ 3

Author(s):

E. EBRAHIMI ◽

A. M. MANSCHADI ◽

R. W. NEUGSCHWANDTNER ◽

J EITZINGER ◽

S. THALER ◽

...

Keyword(s):

Climate Change ◽

Management Practices ◽

Crop Management ◽

Weather Data ◽

Climate Change Scenarios ◽

Management Scenarios ◽

Global Circulation Models ◽

Daily Weather Data ◽

Eastern Austria ◽

The Impact

SUMMARYClimate change is expected to affect optimum agricultural management practices for autumn-sown wheat, especially those related to sowing date and nitrogen (N) fertilization. To assess the direction and quantity of these changes for an important production region in eastern Austria, the agricultural production systems simulator was parameterized, evaluated and subsequently used to predict yield production and grain protein content under current and future conditions. Besides a baseline climate (BL, 1981–2010), climate change scenarios for the period 2035–65 were derived from three Global Circulation Models (GCMs), namely CGMR, IPCM4 and MPEH5, with two emission scenarios, A1B and B1. Crop management scenarios included a combination of three sowing dates (20 September, 20 October, 20 November) with four N fertilizer application rates (60, 120, 160, 200 kg/ha). Each management scenario was run for 100 years of stochastically generated daily weather data. The model satisfactorily simulated productivity as well as water and N use of autumn- and spring-sown wheat crops grown under different N supply levels in the 2010/11 and 2011/12 experimental seasons. Simulated wheat yields under climate change scenarios varied substantially among the three GCMs. While wheat yields for the CGMR model increased slightly above the BL scenario, under IPCM4 projections they were reduced by 29 and 32% with low or high emissions, respectively. Wheat protein appears to increase with highest increments in the climate scenarios causing the largest reductions in grain yield (IPCM4 and MPEH-A1B). Under future climatic conditions, maximum wheat yields were predicted for early sowing (September 20) with 160 kg N/ha applied at earlier dates than the current practice.

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Estimation of Evapotranspiration using the Modified Hargreaves Equation by Genetic Algorithm

10.5194/egusphere-egu2020-8421 ◽

2020 ◽

Author(s):

Deokhwan Kim

Keyword(s):

Genetic Algorithm ◽

Developing Countries ◽

Correction Factor ◽

Historical Data ◽

Reference Evapotranspiration ◽

Weather Data ◽

Correction Coefficient ◽

Test Bed ◽

True Value ◽

Daily Weather Data

In this study, the Hargreaves monthly correction factor is presented to estimate the reference evapotranspiration. For the analysis, I used daily weather data from 1989 to 2018, at 67 meteorological stations located throughout the Korean peninsula.A large number of more or less empirical methods have been developed over the last 50 years by numerous scientists and specialists worldwide to estimate evapotranspiration from different climatic variables. The FAO Penman-Monteith method is recommended as the sole ETo method for determining reference evapotranspiration. However, the Penman-Monteith method has the disadvantage of inputting a lot of weather data. In addition, there is a lack of meteorological data when using old historical data or as a test bed for developing countries.In the case of the Hargreaves method, the reference evapotranspiration can be estimated only if the latitude, maximum and minimum temperatures of the meteorological station are known. However, the accuracy of the results is not as good as that of the Penman-monteith method. Thus, using the genetic algorithm method suggested the monthly correction factor of the Hargreaves method each station. The reference evapotranspiration amount calculated by Penman-Monteith was set as the true value, and the learning period of genetic algorithm was set from 1989 to 2013, and the validation period was set from 2014 to 2018.In order to verify the model efficiency, the root mean square error decreased and the correlation coefficient increased when the monthly correction coefficient was applied to the reference evapotranspiration calculated by the Hargreaves method.It is very important to estimate the reference evapotranspiration amount in order to develop the water long-term plan.With the development of measuring equipment and technological capabilities, it is now possible to simulate the state of nature as if it were real, but many problems arise when using historical data or analyzing developing countries.If the monthly correction coefficient suggested in this study is applied, it is possible to estimate the standard evaporation amount with a more approximate value.&#160;Acknowledgements&#160;This research is supported by the Research Program (20200041-001) of Korea Institute of Civil Engineering & Building Technology&#160;

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