A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future

Wanniarachchi, Susantha; Sarukkalige, Ranjan

doi:10.3390/hydrology9070123

Cited by 75 publications

(26 citation statements)

References 83 publications

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“…An objective of the SALUS model was to predict water use at field‐resolution as opposed to over the entire LEMA region. While previous research has compared different approaches of estimating crop water demand and irrigation scheduling (e.g., Gu et al 2020; Wanniarachchi and Sarukkalige 2022), or remotely‐sensed methods of agricultural water use (e.g., Massari et al 2021), these methods compare within model types (e.g., crop demand; remotely‐sensed). Our results provide a comparison between different model types, and the similar estimates between types demonstrate that, if adequately constrained, they all provide a method of reasonably estimating groundwater extraction.…”

Section: Methodsmentioning

confidence: 99%

Estimating Groundwater Pumping for Irrigation: A Method Comparison

et al. 2023

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Effective groundwater management is critical to future environmental, ecological, and social sustainability and requires accurate estimates of groundwater withdrawals. Unfortunately, these estimates are not readily available in most areas due to physical, regulatory, and social challenges. Here, we compare four different approaches for estimating groundwater withdrawals for agricultural irrigation. We apply these methods in a groundwater‐irrigated region in the state of Kansas, USA, where high‐quality groundwater withdrawal data are available for evaluation. The four methods represent a broad spectrum of approaches: (1) the hydrologically‐based Water Table Fluctuation method (WTFM); (2) the demand‐based SALUS crop model; (3) estimates based on satellite‐derived evapotranspiration (ET) data from OpenET; and (4) a landscape hydrology model which integrates hydrologic‐ and demand‐based approaches. The applicability of each approach varies based on data availability, spatial and temporal resolution, and accuracy of predictions. In general, our results indicate that all approaches reasonably estimate groundwater withdrawals in our region, however, the type and amount of data required for accurate estimates and the computational requirements vary among approaches. For example, WTFM requires accurate groundwater levels, specific yield, and recharge data, whereas the SALUS crop model requires adequate information about crop type, land use, and weather. This variability highlights the difficulty in identifying what data, and how much, are necessary for a reasonable groundwater withdrawal estimate, and suggests that data availability should drive the choice of approach. Overall, our findings will help practitioners evaluate the strengths and weaknesses of different approaches and select the appropriate approach for their application.

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Section: Methodsmentioning

confidence: 99%

Estimating Groundwater Pumping for Irrigation: A Method Comparison

et al. 2023

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“…A thorough understanding of the factors controlling the energy balance of cropped soil enables making accurate estimates or predictions of evapotranspiration and irrigation water requirements [54]. While contributing to the surface energy balance, ET quantifies the water requirement for efficient water management [55][56][57], especially in sub-humid and humid climates [54]. According to the energy budget concept, when the surface is wet or heavily vegetated, net energy is mainly consumed by the evaporation and evapotranspiration of water in soil and vegetation [20].…”

Section: Variations Of Precipitation and Evapotranspiration On The Sebmentioning

confidence: 99%

“…In essence, if there is adequate water in the soil, the incoming solar radiation will be used for convective activities [52]. Moreover, an increase in soil moisture gives rise to increased evaporation from the soil surface, and a substantial part of net radiation goes into evaporation, which also gives rise to the observed low temperature [41], and increasing evapotranspiration can decrease the surface temperature of tree canopy [57,58]. Atmospheric temperature is projected to increase with climate change, and it provides more energy to cause more evaporation [57].…”

Section: Variations Of Precipitation and Evapotranspiration On The Sebmentioning

confidence: 99%

“…Moreover, an increase in soil moisture gives rise to increased evaporation from the soil surface, and a substantial part of net radiation goes into evaporation, which also gives rise to the observed low temperature [41], and increasing evapotranspiration can decrease the surface temperature of tree canopy [57,58]. Atmospheric temperature is projected to increase with climate change, and it provides more energy to cause more evaporation [57]. Salman et al [59] used simple waterbalance equations and identified that when the temperature increases, it contributes to an increment in evapotranspiration, which leads to a large increase in crop water demand and a decrease in climatic water availability.…”

Section: Variations Of Precipitation and Evapotranspiration On The Sebmentioning

confidence: 99%

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Seasonal variation of surface energy balance over Mubi northeastern Nigeria during 2000-2020

Umar¹,

Usman²

2023

fuen

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Several studies have been undertaken on surface energy balance (SEB) at various places in the world, but none have been undertaken for Mubi, Northeastern Nigeria. In the effort of consideration, this study aims to evaluate the seasonal variation of SEB in Mubi, with emphasis on the observational data from 2000 to 2020. Evaluation of seasonal variations was executed using time series analysis to find out the impact of precipitation, evapotranspiration, soil, and air temperature changes on SEB components. It was found that the SEB components variations of sensible heat (H) had a maximum value of 1035.13 Wm−2 in the dry season, in the month of December, while a minimum value of -104.13 Wm−2 during the rainy season, in the month of July; latent heat (LH), had a peak value of 5243.46 Wm-2 in the dry season in the month of April, while in the rainy season, the lower value was found to be 2460.6 Wm-2, in the month of August; soil heat (G) had minimum and maximum values of 886.43 Wm-2 in March and 275.25 Wm-2 in August respectively; and net radiative (Rn) varies roughly between the highest month in March with 2809.35 Wm−2 (rainy season months) and lowest month in August with 6879.69 Wm−2 (dry season months). It was also found that precipitation, evapotranspiration, soil, and air temperature follow the same trend with some SEB results, affirming their dependency on each other. Therefore, it is expected that this study will help to understand the amount of energy received or emitted in the Mubi region. Along with the main work, some recommendations were made by researchers on some applications of SEB to the community.

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“…These activities are related to modern and precise agricultural applications (Malik et al 2022). In large agricultural lands, including irrigation systems, actual evapotranspiration (ET) data are used to estimate and evaluate the water needs of different crops for managing and planning the optimal allocation of available water resources (Wanniarachchi and Sarukkalige 2022). There are different methods to measure ET, such as the local measurement method (Kandra et al 2023).…”

Section: Introductionmentioning

confidence: 99%

Can hybrid models predict actual evapotranspiration instead of weighting lysimeters?

Sharafi

Rezaverdinejad

Behmanesh

2023

Preprint

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Actual daily evapotranspiration (ET) can be considered as one of the most important meteorological parameters. One of the main ways to measure ET is using lysimeters, which are expensive tools, and the data obtained from them are not available in most parts of the world. Therefore, the purpose of this research is to provide an intelligent model that can predict ET using data obtained from cheap and available tools. To do this, data from two NE and SE lysimeters located in Potter County, Texas between 1996-1999 were used as input for SVR and SVR-FFA models in 13 scenarios. The results of this study showed that the SVR-FFA model with an error value of 1.22 mm/day for 1996, 1.14 mm/day for 1997, 1.56 mm/day for 1998, and 1.54 mm/day for 1999 has the highest accuracy for all combinations. Among the standalone SVR models, the SVR-13 model has performed better than other SVR combinations for all years with a Willmott's index of agreement above 0.87. The comparison between the inputs used for the models showed that the Rn and PAR parameters had the greatest impact on the accuracy of the SVR and SVR-FFA models, so they increased the accuracy of the models in every four years. One of the limitations of this study is the lack of access to some parameters such as minimum and maximum temperature in the study area. Therefore, it is suggested to measure these parameters and consider them as other inputs to measure the performance of the models.

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A Review on Evapotranspiration Estimation in Agricultural Water Management: Past, Present, and Future

Cited by 75 publications

References 83 publications

Estimating Groundwater Pumping for Irrigation: A Method Comparison

Estimating Groundwater Pumping for Irrigation: A Method Comparison

Seasonal variation of surface energy balance over Mubi northeastern Nigeria during 2000-2020

Can hybrid models predict actual evapotranspiration instead of weighting lysimeters?

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