Estimation of Evapotranspiration using the Modified Hargreaves Equation by Genetic Algorithm

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

<p>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.</p><p>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.</p><p>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.</p><p>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.</p><p>It is very important to estimate the reference evapotranspiration amount in order to develop the water long-term plan.</p><p>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.</p><p>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.</p><p> </p><p>Acknowledgements</p><p> This research is supported by the Research Program (20200041-001) of Korea Institute of Civil Engineering & Building Technology </p>

scholarly journals Investigation into the Effects of Climate Change on Reference Evapotranspiration Using the HadCM3 and LARS-WG

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 666 ◽  
Author(s):  
Maryam Bayatvarkeshi ◽  
Binqiao Zhang ◽  
Rojin Fasihi ◽  
Rana Muhammad Adnan ◽  
Ozgur Kisi ◽  
...  
Keyword(s):  
Climate Change ◽  
Reference Evapotranspiration ◽  
Irrigation Scheduling ◽  
Weather Data ◽  
Base Period ◽  
Resources Management ◽  
Weather Information ◽  
Daily Weather Data ◽  
Weather Stations ◽  
A1b Scenario

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.

scholarly journals Influence of multi-decadal meteorological variability on the reference evpotranspirtion in hot and humid coastal town of Annamalainagar in Tamil Nadu state

MAUSAM ◽  
2021 ◽  
Vol 71 (1) ◽  
pp. 45-56
Author(s):  
MURUGAPPAN A ◽  
MANIKUMARI N ◽  
MOHAN S
Keyword(s):  
Tamil Nadu ◽  
Reference Evapotranspiration ◽  
Meteorological Parameter ◽  
Vapour Pressure Deficit ◽  
Weather Data ◽  
Net Radiation ◽  
Sunshine Hours ◽  
Daily Weather Data ◽  
Tamil Nadu State ◽  
Decadal Trend

Reference evapotranspiration (ETo) is a key pointer of atmospheric evaporation demand and has been extensively used to describe the hydrological change. In this study, the reference evapotranspiration over the hot and humid town, Annamalainagar, very near to the east coast in Tamilnadu State, India, have been estimated employing the FAO Penman-Monteith (PM) method and the observed daily weather data during 1977-2016. The objective of the present study is two-fold: (i) To identify the multi-decadal trend of the various measured meteorological parameters namely, mean air temperature (Tmean), vapour pressure deficit (VPD), actual sunshine hours (SSH), net radiation (Rn) and wind speed (WS) at the study location and (ii) To identify the main contributing meteorological parameter for the detected decreasing trend in ETo over the multi-decadal period.

Estimation of reference evapotranspiration using Aquacrop model for agro-climatic conditions of Madhya Pradesh

2017 ◽  
Vol 51 (06) ◽  
Author(s):  
Deepika Yadav ◽  
M. K. Awasthi ◽  
R. K. Nema
Keyword(s):  
Temporal Variability ◽  
Reference Evapotranspiration ◽  
Madhya Pradesh ◽  
Weather Data ◽  
Accurate Estimation ◽  
Spatial And Temporal Variability ◽  
Statistical Parameters ◽  
Climatic Zones ◽  
Aquacrop Model ◽  
Daily Weather Data

Accurate estimation of evapotranspiration is necessary step for better management and allocation of water resources. The United Nations Food and Agriculture Organization (FAO) adopted the Penman Moneith method as a global standard to estimate reference crop evapotranspiration (ETo). The study aimed to estimate FAO P-M reference evapotranspiration for different district of five agro climatic zones of Madhya Pradesh state by using Aquacrop model. Daily weather data including maximum and minimum temperature, precipitation, relative humidity, wind speed and solar radiation were collected for the period of 1979 to 2013 which were used as input data in Aquacrop. Several statistical parameters were used for characterizing the spatial and temporal variability of ETo. The average monthly ETo was found maximum in month of May (10.67 mm day-1) in all district of different agro climatic zones for the average period considered for the study and also for each years, whereas average minimum ETo was estimated in month of December (3.23 mm day-1) in Kymore Plateau and August (2.44 mm day-1) in Satpura Plateau. The mean daily reference evapotranspiration ranges from 4 mm day-1 to 10 mm day-1 for all districts. From the statistical analysis it was found that spatial variability of ETo lower than the temporal variability. It means the bigger differentiation of ETo in the years than in the space.

scholarly journals Distribution and incidence of viruses in Irish seed potato crops

2015 ◽  
Vol 54 (2) ◽  
pp. 98-106 ◽  
Author(s):  
F. Hutton ◽  
J.H. Spink ◽  
D. Griffin ◽  
S. Kildea ◽  
D. Bonner ◽  
...  
Keyword(s):  
Potato Virus ◽  
Significant Proportion ◽  
Potato Production ◽  
Weather Data ◽  
Management Approach ◽  
Potato Seed ◽  
Virus Diseases ◽  
Aphid Control ◽  
Daily Weather Data ◽  
Potato Crops

Abstract Virus diseases are of key importance in potato production and in particular for the production of disease-free potato seed. However, there is little known about the frequency and distribution of potato virus diseases in Ireland. Despite a large number of samples being tested each year, the data has never been collated either within or across years. Information from all known potato virus testing carried out in the years 2006–2012 by the Department of Agriculture Food and Marine was collated to give an indication of the distribution and incidence of potato virus in Ireland. It was found that there was significant variation between regions, varieties, years and seed classes. A definition of daily weather data suitable for aphid flight was developed, which accounted for a significant proportion of the variation in virus incidence between years. This use of weather data to predict virus risk could be developed to form the basis of an integrated pest management approach for aphid control in Irish potato crops.

scholarly journals A method for simulating risk profiles of wheat yield in data-sparse conditions

2021 ◽  
pp. 1-12
Author(s):  
G. Bracho-Mujica ◽  
P.T. Hayman ◽  
V.O. Sadras ◽  
B. Ostendorf
Keyword(s):  
Reference Site ◽  
Climate Impacts ◽  
Weather Data ◽  
Climate Data ◽  
High Quality ◽  
Risk Profiles ◽  
Record Length ◽  
Daily Weather Data ◽  
Study Sites

Abstract Process-based crop models are a robust approach to assess climate impacts on crop productivity and long-term viability of cropping systems. However, these models require high-quality climate data that cannot always be met. To overcome this issue, the current research tested a simple method for scaling daily data and extrapolating long-term risk profiles of modelled crop yields. An extreme situation was tested, in which high-quality weather data was only available at one single location (reference site: Snowtown, South Australia, 33.78°S, 138.21°E), and limited weather data was available for 49 study sites within the Australian grain belt (spanning from 26.67 to 38.02°S of latitude, and 115.44 to 151.85°E of longitude). Daily weather data were perturbed with a delta factor calculated as the difference between averaged climate data from the reference site and the study sites. Risk profiles were built using a step-wise combination of adjustments from the most simple (adjusted series of precipitation only) to the most detailed (adjusted series of precipitation, temperatures and solar radiation), and a variable record length (from 10 to 100 years). The simplest adjustment and shortest record length produced bias of modelled yield grain risk profiles between −10 and 10% in 41% of the sites, which increased to 86% of the study sites with the most detailed adjustment and longest record (100 years). Results indicate that the quality of the extrapolation of risk profiles was more sensitive to the number of adjustments applied rather than the record length per se.

scholarly journals Impact of Extreme Weather on Healthcare Utilization by People with HIV in Metropolitan Miami

2021 ◽  
Vol 18 (5) ◽  
pp. 2442
Author(s):  
Daniel Samano ◽  
Shubhayu Saha ◽  
Taylor Corbin Kot ◽  
JoNell E. Potter ◽  
Lunthita M. Duthely
Keyword(s):  
Relative Risk ◽  
The United States ◽  
Extreme Weather ◽  
South Florida ◽  
Heat Index ◽  
Extreme Weather Events ◽  
Weather Data ◽  
Steady Increase ◽  
Daily Weather Data ◽  
The Impact

Extreme weather events (EWE) are expected to increase as climate change intensifies, leaving coastal regions exposed to higher risks. South Florida has the highest HIV infection rate in the United States, and disruptions in clinic utilization due to extreme weather conditions could affect adherence to treatment and increase community transmission. The objective of this study was to identify the association between EWE and HIV-clinic attendance rates at a large academic medical system serving the Miami-Dade communities. The following methods were utilized: (1) Extreme heat index (EHI) and extreme precipitation (EP) were identified using daily observations from 1990–2019 that were collected at the Miami International Airport weather station located 3.6 miles from the studied HIV clinics. Data on hurricanes, coastal storms and flooding were collected from the National Oceanic and Atmospheric Administration Storms Database (NOAA) for Miami-Dade County. (2) An all-HIV clinic registry identified scheduled daily visits during the study period (hurricane seasons from 2017–2019). (3) Daily weather data were linked to the all-HIV clinic registry, where patients’ ‘no-show’ status was the variable of interest. (4) A time-stratified, case crossover model was used to estimate the relative risk of no-show on days with a high heat index, precipitation, and/or an extreme natural event. A total of 26,444 scheduled visits were analyzed during the 383-day study period. A steady increase in the relative risk of ‘no-show’ was observed in successive categories, with a 14% increase observed on days when the heat index was extreme compared to days with a relatively low EHI, 13% on days with EP compared to days with no EP, and 10% higher on days with a reported extreme weather event compared to days without such incident. This study represents a novel approach to improving local understanding of the impacts of EWE on the HIV-population’s utilization of healthcare, particularly when the frequency and intensity of EWE is expected to increase and disproportionately affect vulnerable populations. More studies are needed to understand the impact of EWE on routine outpatient settings.

scholarly journals A dataset of future daily weather data for crop modelling over Europe derived from climate change scenarios

2015 ◽  
Vol 127 (3-4) ◽  
pp. 573-585 ◽  
Author(s):  
G. Duveiller ◽  
M. Donatelli ◽  
D. Fumagalli ◽  
A. Zucchini ◽  
R. Nelson ◽  
...  
Keyword(s):  
Climate Change ◽  
Weather Data ◽  
Climate Change Scenarios ◽  
Crop Modelling ◽  
Daily Weather ◽  
Daily Weather Data

Estimation of Track Irregularity Based on Genetic Algorithm and Unscented Kalman Filtering

2012 ◽  
Author(s):  
Hongmei Shi ◽  
Zujun Yu
Keyword(s):  
Genetic Algorithm ◽  
Kalman Filtering ◽  
High Speed ◽  
Measurement Data ◽  
Estimation Method ◽  
Coupling Model ◽  
Dynamic Responses ◽  
The Real ◽  
True Value ◽  
Track Irregularity

Track irregularity is the main excitation source of wheel-track interaction. Due to the difference of speed, axle load and suspension parameters between track inspection train and the operating trains, the data acquired from the inspection car cannot completely reflect the real status of track irregularity when the operating trains go through the rail. In this paper, an estimation method of track irregularity is proposed using genetic algorithm and Unscented Kalman Filtering. Firstly, a vehicle-track vertical coupling model is established, in which the high-speed vehicle is assumed as a rigid body with two layers of spring and damping system and the track is viewed as an elastic system with three layers. Then, the static track irregularity is estimated by genetic algorithm using the vibration data of vehicle and dynamic track irregularity which are acquired from the inspection car. And the dynamic responses of vehicle and track can be solved if the static track irregularity is known. So combining with vehicle track coupling model of different operating train, the potential dynamic track irregularity is solved by simulation, which the operating train could goes through. To get a better estimation result, Unscented Kalman Filtering (UKF) algorithm is employed to optimize the dynamic responses of rail using measurement data of vehicle vibration. The simulation results show that the estimated static track irregularity and the vibration responses of vehicle track system can go well with the true value. It can be realized to estimate the real rail status when different trains go through the rail by this method.

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