Global comparison of 20 reference evapotranspiration equations in a semi-arid region of Iran

Abstract Accurate estimation of reference evapotranspiration (ETo) is a major task in hydrology, water resources management, irrigation scheduling and determining crop water requirement. There are many empirical equations suggested by numerous references in literature for calculating ETo using meteorological data. Some such equations have been developed for specific climatic conditions while some have been applied universally. The potential for usage of these equations depends on the availability of necessary meteorological parameters for calculating ETo in different climate conditions. The focus of the present study was a global cross-comparison of 20 ETo estimation equations using daily meteorological records of 10 weather stations (covering a period of 12 years) in a semi-arid region of Iran. Two data management scenarios, namely local and cross-station scenarios, were adopted for calibrating the applied equations against the standard FAO56-PM model. The obtained results revealed that the cross-station calibration might be a good alternative for local calibration of the ETo models when proper similar stations are used for feeding the calibration matrix.

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Usefulness of class A Pan coefficient models for computation of reference evapotranspiration for a semi-arid region

MAUSAM ◽

10.54302/mausam.v65i4.1186 ◽

2021 ◽

Vol 65 (4) ◽

pp. 521-528

Author(s):

PK SINGH ◽

SK PATEL ◽

P JAYSWAL ◽

SS CHINCHORKAR

Keyword(s):

Arid Region ◽

Reference Evapotranspiration ◽

Accurate Determination ◽

Climatic Conditions ◽

Gujarat State ◽

Semi Arid Region ◽

Semi Arid ◽

Statistical Criteria ◽

Agricultural Organization

The reliability of estimates of reference evapotranspiration (ET0) using pan evaporation (Epan) depends on the accurate determination of pan coefficients (Kpan). Six ET0 models were evaluated for their usefulness using 33-year climatological dataset of a semi-arid region of the Gujarat state of India. The equations compared include Cuenca (1989), Allen and Pruitt (1991), Snyder (1992), Modified Snyder (Grismer et al., 2002), Orang (1998), and Pereira et al. (1995). The ET0 data, calculated using daily Kpan values from these equations, were compared to the Food and Agricultural Organization (FAO)-Penman-Monteith (FAO56-PM) method as a reference. Based on the visual comparison as well as from the statistical criteria, ET0 values computed using Modified Snyder and Orang model have very close agreement with the FAO56-PM method for daily, monthly, and annual estimates as compared to other approaches. The sequential performances of the explored models was found as: Modified Snyder (Eqn. 5) > Orang (Eqn. 6) > Cuenca Eqn. (2) > Allen & Pruitt (Eqn. 3) > Snyder (Eqn. 4) > Pereira et al. (Eqn. 7) model. Therefore, the Modified Snyder model (Grismer et al., 2002) could be recommended as the best model for ET0 computations under these prevailing climatic conditions for a semi arid region.

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Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

Atmosphere ◽

10.3390/atmos12070927 ◽

2021 ◽

Vol 12 (7) ◽

pp. 927

Author(s):

Jamshad Hussain ◽

Tasneem Khaliq ◽

Muhammad Habib ur Rahman ◽

Asmat Ullah ◽

Ishfaq Ahmed ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Arid Region ◽

Field Experiments ◽

Climatic Conditions ◽

Seasonal Temperature ◽

Sowing Dates ◽

Rcp 8.5 ◽

Semi Arid Region ◽

Semi Arid

Rising temperature from climate change is the most threatening factor worldwide for crop production. Sustainable wheat production is a challenge due to climate change and variability, which is ultimately a serious threat to food security in Pakistan. A series of field experiments were conducted during seasons 2013–2014 and 2014–2015 in the semi-arid (Faisalabad) and arid (Layyah) regions of Punjab-Pakistan. Three spring wheat genotypes were evaluated under eleven sowing dates from 16 October to 16 March, with an interval of 14–16 days in the two regions. Data for the model calibration and evaluation were collected from field experiments following the standard procedures and protocols. The grain yield under future climate scenarios was simulated by using a well-calibrated CERES-wheat model included in DSSAT v4.7. Future (2051–2100) and baseline (1980–2015) climatic data were simulated using 29 global circulation models (GCMs) under representative concentration pathway (RCP) 8.5. These GCMs were distributed among five quadrants of climatic conditions (Hot/Wet, Hot/Dry, Cool/Dry, Cool/Wet, and Middle) by a stretched distribution approach based on temperature and rainfall change. A maximum of ten GCMs predicted the chances of Middle climatic conditions during the second half of the century (2051–2100). The average temperature during the wheat season in a semi-arid region and arid region would increase by 3.52 °C and 3.84 °C, respectively, under Middle climatic conditions using the RCP 8.5 scenario during the second half-century. The simulated grain yield was reduced by 23.5% in the semi-arid region and 35.45% in the arid region under Middle climatic conditions (scenario). Mean seasonal temperature (MST) of sowing dates ranged from 16 to 27.3 °C, while the mean temperature from the heading to maturity (MTHM) stage was varying between 12.9 to 30.4 °C. Coefficients of determination (R2) between wheat morphology parameters and temperature were highly significant, with a range of 0.84–0.96. Impacts of temperature on wheat sown on 15 March were found to be as severe as to exterminate the crop before heading. The spikes and spikelets were not formed under a mean seasonal temperature higher than 25.5 °C. In a nutshell, elevated temperature (3–4 °C) till the end-century can reduce grain yield by about 30% in semi-arid and arid regions of Pakistan. These findings are crucial for growers and especially for policymakers to decide on sustainable wheat production for food security in the region.

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Coupling a Bat Algorithm with XGBoost to Estimate Reference Evapotranspiration in the Arid and Semiarid Regions of China

Advances in Meteorology ◽

10.1155/2019/9575782 ◽

2019 ◽

Vol 2019 ◽

pp. 1-16 ◽

Cited By ~ 3

Author(s):

Yixiu Han ◽

Jianping Wu ◽

Bingnian Zhai ◽

Yanxin Pan ◽

Guomin Huang ◽

...

Keyword(s):

Air Temperature ◽

Reference Evapotranspiration ◽

Meteorological Data ◽

Bat Algorithm ◽

Irrigation Scheduling ◽

Multivariate Adaptive Regression Splines ◽

Accurate Estimation ◽

Agricultural Irrigation ◽

Semiarid Regions ◽

Arid And Semiarid

Accurate estimation of reference evapotranspiration (ETo) is key to agricultural irrigation scheduling and water resources management in arid and semiarid areas. This study evaluates the capability of coupling a Bat algorithm with the XGBoost method (i.e., the BAXGB model) for estimating monthly ETo in the arid and semiarid regions of China. Meteorological data from three stations (Datong, Yinchuan, and Taiyuan) during 1991–2015 were used to build the BAXGB model, the multivariate adaptive regression splines (MARS), and the gaussian process regression (GPR) model. Six input combinations with different sets of meteorological parameters were applied for model training and testing, which included mean air temperature (Tmean), maximum air temperature (Tmax), minimum air temperature (Tmin), wind speed (U), relative humidity (RH), and solar radiation (Rs) or extraterrestrial radiation (Ra, MJ m−2·d−1). The results indicated that BAXGB models (RMSE = 0.114–0.412 mm·d−1, MAE = 0.087–0.302 mm·d−1, and R2 = 0.937–0.996) were more accurate than either MARS (RMSE = 0.146–0.512 mm·d−1, MAE = 0.112–0.37 mm·d−1, and R2 = 0.935–0.994) or GPR (RMSE = 0.289–0.714 mm·d−1, MAE = 0.197–0.564 mm·d−1, and R2 = 0.817–0.980) model for estimating ETo. Findings of this study would be helpful for agricultural irrigation scheduling in the arid and semiarid regions and may be used as reference in other regions where accurate models for improving local water management are needed.

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Organic fertilizers as mitigating effects of water salinity on Passiflora cincinnata seedlings

Acta Agronómica ◽

10.15446/acag.v67n4.69475 ◽

2018 ◽

Vol 67 (4) ◽

pp. 501-511

Author(s):

José Sebastião de Melo Filho ◽

Mário Leno Martins Véras ◽

Toshik Larley Da Silva ◽

Lunara De Sousa Alves ◽

Thiago Jardelino Dias

Keyword(s):

Irrigation Water ◽

Arid Region ◽

Climatic Conditions ◽

Organic Fertilizers ◽

State University ◽

Electrical Conductivities ◽

Randomized Experimental Design ◽

Semi Arid Region ◽

Semi Arid

Maracujá-do-mato (Passiflora cincinnata) is a species adapted to the climatic conditions of the Brazilian semi-arid region and widely used as rootstock, however, studies related to the production of seedlings and their resistance to abiotic stresses are scarce in literature. The objective was to study the production of maracujá-do-mato seedlings under the effect of the electrical conductivity on the irrigation water as a function of the application of organic fertilizers. The experiment was developed at the State University of Paraíba, Catolé do Rocha-PB, in a completely randomized experimental design, in a 5 x 3 factorial scheme, with 6 replicates. The factors evaluated were five electrical conductivities of irrigation water (ECw: 1; 2; 3; 4 and 5 dS m-1) and application of three organic fertilizers (bovine urine, bovine biofertilizer and liquid earthworm humus). It was verified that the increase of ECw affected the morphology and the quality of the seedlings negatively, while the bovine biofertilizer presented better efficiency in comparison to the others. It is inferred that the use of organic fertilizers as mitigating effects of salinity may be a strategy for production of maracujá-do-mato seedlings in saline conditions.

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Are smallholder farmers’ perceptions of climate variability supported by climatological evidence? Case study of a semi-arid region in South Africa

International Journal of Climate Change Strategies and Management ◽

10.1108/ijccsm-01-2020-0007 ◽

2020 ◽

Vol 12 (5) ◽

pp. 571-585 ◽

Cited By ~ 1

Author(s):

Maropene Tebello Rapholo ◽

Lawrence Diko Makia

Keyword(s):

South Africa ◽

Climate Variability ◽

Arid Region ◽

Smallholder Farmers ◽

Linear Trend ◽

Meteorological Data ◽

Sub Saharan Africa ◽

Content Type ◽

Semi Arid Region ◽

Semi Arid

Purpose Literature contends that not much is known about smallholder farmers’ perceptions of climate variability and the impacts thereof on agricultural practices in Sub-Saharan Africa and South Africa in particular. The purpose of this study is to examine the perceptions of smallholder farmers from Botlokwa (a semi-arid region in South Africa) on climate variability in relation to climatological evidence. Design/methodology/approach The study area is in proximity to a meteorological station and comprises mainly rural farmers, involved in rain-fed subsistence agriculture. Focus group discussions and closed-ended questionnaires covering demographics and perceptions were administered to 125 purposely sampled farmers. To assess farmers’ perceptions of climate variability, their responses were compared with linear trend and variability of historical temperature and rainfall data (1985-2015). Descriptive statistics were used to provide insights into respondents’ perceptions. Findings About 64% of the farmers perceived climate variability that was consistent with the meteorological data, whereas 36% either held contrary observations or were unable to discern. Age, level of education, farming experience and accessibility to information influenced the likelihood of farmers to correctly perceive climate variability. No significant differences in perception based on gender were observed. This study concludes that coping and adaption strategies of over one-third of the farmers could be negatively impacted by wrong perceptions of climate variability. Originality/value This study highlights discrepancies in perceptions among farmers with similar demographic characteristics. To guarantee sustainability of the sector, intervention by government and other key stakeholders to address underlying factors responsible for observed discrepancies is recommended.

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