Evaporation from a large lowland reservoir – (dis)agreement  between evaporation models from hourly to decadal timescales

Jansen, Femke A.; Teuling, Adriaan J.

doi:10.5194/hess-24-1055-2020

Cited by 20 publications

(15 citation statements)

References 44 publications

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“…The measured pan evaporation rates are generally 30 % higher than that of lake evaporation at the annual scale. The monthly pan coefficients can differ from the commonly used coefficient of 0.7 by more than 100 % (Kohler et al, 1955;Linsley et al, 1982;Ferguson et al, 1985). It is expected that the relationship between pan evaporation and lake evaporation should be a function of meteorological parameters through the modelled K pan .…”

Section: Introductionmentioning

confidence: 92%

Reservoir evaporation in a Mediterranean climate: comparing direct methods in Alqueva Reservoir, Portugal

Rodrigues

Moreira

Guimarães

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. Alqueva Reservoir is one of the largest artificial lakes in Europe and is a strategic water storage for public supply, irrigation, and energy generation. The reservoir is integrated within the Multipurpose Alqueva Project (MAP), which includes almost 70 reservoirs in a water-scarce region of Portugal. The MAP contributes to sustainability in southern Portugal and has an important impact on the entire country. Evaporation is the key component of water loss from the reservoirs included in the MAP. Evaporation from Alqueva Reservoir has been estimated by indirect methods or pan evaporation measurements; however, specific experimental parameters such as the pan coefficient were never evaluated. Eddy covariance measurements were performed at Alqueva Reservoir from June to September in 2014 as this time of the year provides the most representative evaporation volume losses in a Mediterranean climate. This period is also the most important period for irrigated agriculture and is, therefore, the most problematic period of the year in terms of managing the reservoir. The direct pan evaporation approach was first tested, and the results were compared to the eddy covariance evaporation measurements. The total eddy covariance (EC) evaporation measured from June to September 2014 was 450.1 mm. The mean daily EC evaporation in June, July, August, and September was 3.7, 4.0, 4.5, and 2.5 mm d−1, respectively. A pan coefficient, Kpan, multivariable function was established on a daily scale using the identified governing factors: air temperature, relative humidity, wind speed, and incoming solar radiation. The correlation between the modelled evaporation and the measured EC evaporation had an R2 value of 0.7. The estimated Kpan values were 0.59, 0.57, 0.57, and 0.64 in June, July, August, and September, respectively. Consequently, the daily mean reservoir evaporation (ERes) was 3.9, 4.2, 4.5, and 2.7 mm d−1 for this 4-month period and the total modelled ERes was 455.8 mm. The developed Kpan function was validated for the same period in 2017 and yielded an R2 value of 0.68. This study proposes an applicable method for calculating evaporation based on pan measurements in Alqueva Reservoir, and it can be used to support regional water management. Moreover, the methodology presented here could be applied to other reservoirs, and the developed equation could act as a first evaluation for the management of other Mediterranean reservoirs.

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Section: Introductionmentioning

confidence: 92%

Reservoir evaporation in a Mediterranean climate: comparing direct methods in Alqueva Reservoir, Portugal

Rodrigues

Moreira

Guimarães

et al. 2020

Hydrol. Earth Syst. Sci.

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“…The low annual evaporation in the early 1990s resulted from the small incoming solar radiation. The increasing trend of lake evaporation has also been reported in lakes with different climate background, including a small highland lake in the Tibetan Plateau [32], Lake Taihu in a subtropical region of China [73], Lake IJssel in the Netherlands [69] and a small reservoir in the Brazilian savannah [74]. The long-term trend of evaporation of Erhai Lake calculated by the modified JH method is opposite to the results obtained from evaporation pan E601 situated in the surrounding land site [75], in which pan evaporation showed an obvious decreasing trend since the 1980s with rising temperature.…”

Section: Estimation Of Long-term Lake Evaporationmentioning

confidence: 73%

“…The modified Mak method reduced the large negative deviation of default condition and overestimated evaporation during spring, consequently resulting in less negative annual bias ranged from −4.4% to 0.65% during 2015-2018 (Figure 5, V1). For the sake of simplicity and accuracy, the modified solar radiation-based methods have an advantage over the combination methods and were applied in estimating the long-term lake evaporation [32,69].…”

Section: Evaluation Of Solar Radiation-based Methodsmentioning

confidence: 99%

Evaluation of the Performance of Different Methods for Estimating Evaporation over a Highland Open Freshwater Lake in Mountainous Area

Meng

Liu

et al. 2020

Water

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Lake evaporation is an important link connecting the water cycle and the surface energy cycle and remains one of the most uncertain terms in the local catchment’s water balance. Quantifying lake evaporation and its variability is crucial to improve water resource management and understand the response of the lake system towards climate change. In this study, we evaluated the performances of nine evaporation methods at different timescales and calibrated them by using the continuous eddy covariance (EC) observation data during 2015–2018 over Erhai Lake, a highland open freshwater lake situated in the Dali valley, China. The nine evaporation methods could be classified into combination methods (Bowen-ratio energy budget, Penman, Priestley–Taylor, DeBruin–Keijman and Brutsaert–Stricker), solar radiation-based methods (Jensen–Haise and Makkink) and Dalton-based method (mass transfer and Ryan–Harleman) based on their parameterization schemes. The Dalton-based Ryan–Harleman method is most suitable for estimating evaporation at daily to weekly scales, while the combination methods and solar radiation-based method had good estimates at monthly timescale. After calibration, the biases of the Jensen–Haise and Ryan–Harleman method were slightly reduced, while the biases of the Makkink and mass transfer methods were reduced substantially. The calibrated Jensen–Haise method with small annual bias (−2.2~2.8%) and simple input variables was applied to estimate the long-term trend of evaporation during 1981–2018. The annual total evaporation showed an insignificant increasing trend of 0.30 mm year−1, mainly caused by the significant rising air temperature. This study showed the performance of evaporation methods over water bodies had large discrepancies on different time scales, which indicated the importance of the choice of evaporation methods and provided instruction for water resource management of this region under climate change.

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“…Makkink is a radiation-based model which finds its origin in Penman's equation through the Priestley-Taylor equation (explained in Sect.2.5) and has been developed to estimate evapotranspiration over well-watered grasslands at daily timescale. Although a correction factor is applied to account for the difference between terrestrial evaporation and E water , Makkink's equation is not able to capture the dynamics of E water as estimated with physicallybased lake models such as FLake (Jansen and Teuling, 2020). This calls for improving and implementing our understanding of the driving process of E water by building on previous studies about E water of Lake IJssel (Keijman and Koopmans, 1973;De Bruin and Keijman, 1979;Abdelrady et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Evaporation from a large lowland reservoir – observed dynamics during a warm summer

Jansen

Uijlenhoet

Jacobs

et al. 2021

Preprint

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Abstract. Evaporation forms a large loss term in the water balance of inland water bodies. During summer seasons, which are projected to become warmer with more severe and prolonged periods of drought, the combination of high evaporation rates and increasing demand on freshwater resources forms a challenge for water managers. Correct parameterisation of open water evaporation is crucial to include in operational hydrological models to make well supported predictions of the loss of water through evaporation. Here, we aim to study the controls on open water evaporation of a large lowland reservoir in the Netherlands. To this end, we analyse the dynamics of open water evaporation at two locations, i.e. Stavoren and Trintelhaven, at the border of Lake IJssel (1100 km2) where eddy covariance systems were installed during the summer seasons of 2019 and 2020. From these measurements we find that wind speed and the vertical vapour pressure gradient, but not available energy, can explain most of the variability of observed hourly open water evaporation. This is in agreement with Dalton's model which is a well-established model often used in oceanographic studies for calculating open water evaporation. At the daily timescale, we find that wind speed and water temperature are the main drivers in Stavoren. These observed driving variables of open water evaporation are used to develop simple data-driven models for both measurement locations. Validation of these models demonstrates that a simple model using only two variables, performs well both at the hourly timescale (R2 = 0.84 in Stavoren, and R2 = 0.67 in Trintelhaven), and at the daily timescale (R2 = 0.72 in Stavoren, and R2 = 0.51 in Trintelhaven). Using only routinely measured meteorological variables leads to well performing simple data-driven models at hourly (R2 = 0.78 in Stavoren, and R2 = 0.51 in Trintelhaven) and daily (R2 = 0.85 in Stavoren, and R2 = 0.43 in Trintelhaven) timescales. These results for the summer periods show that global radiation is not directly coupled to open water evaporation at the hourly or even daily timescale, but rather wind speed and vertical gradient of vapour pressure are variables that explain most of the variance of open water evaporation. However, when we extend the time series to a complete year, we find a distinct yearly cycle reflecting the yearly dynamics of global radiation. We find that the commonly used model of Penman (1948) produces results that resemble the yearly cycle of observed evaporation. However, at the diurnal scale estimated evaporation using Penman’s model disagrees with observed evaporation. Therefore, using the Penman equation to model open water evaporation for shorter periods of time is questioned. We would like to stress the importance of including the correct drivers in the parameterization of open water evaporation in hydrological models to adequately represent the role of evaporation in the surface-atmosphere interaction of inland water bodies.

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Evaporation from a large lowland reservoir – (dis)agreement between evaporation models from hourly to decadal timescales

Cited by 20 publications

References 44 publications

Reservoir evaporation in a Mediterranean climate: comparing direct methods in Alqueva Reservoir, Portugal

Reservoir evaporation in a Mediterranean climate: comparing direct methods in Alqueva Reservoir, Portugal

Evaluation of the Performance of Different Methods for Estimating Evaporation over a Highland Open Freshwater Lake in Mountainous Area

Evaporation from a large lowland reservoir – observed dynamics during a warm summer

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