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Evaporation of water bodies is significantly controlled by the available energy (net radiation Rn minus heat storage G). Compared to deep lakes or lakes in the high‐latitude or high‐altitude regions, the heat storage effects of shallow lakes in subtropical regions are less well studied. In this paper, we tested the heat storage effect on the latent heat fluxes estimation using the Priestley‐Taylor (PT) equation and numerical water temperature simulations in an ephemeral and shallow lake, Poyang Lake, in China. Results showed that the estimation bias was significantly correlated with heat storage changes (r = 0.97). Overlooking the impacts of the heat storage changes will induce an increase in the RMSE (root‐mean‐square error) of the evaporation estimation from 10.1 to 54.4 W m−2. Evaporation was overestimated in June and underestimated in August because the daytime Rn tended to be stored in water in June, whereas the heat storage during daytime tended to be released as nighttime evaporation in August, when the vapor gradient between the saturated surface and the air was generally larger than in other months. Water temperature simulations showed that the diurnal changes in the heat storage in the layer that were less than 2 m deep govern G of the total water column. PT estimation of a shallow lake can be improved if the temperature of the top 2 m of water is known. Also, from the modeling perspective, because G was linearly correlated with Rn (r = 0.77), a simple equation (a*Rn + b) that approximates the available energy can improve the evaporation estimate. Key Points: We study the heat storage effect on the PT estimation in an ephemeral and shallow lake, Poyang LakeThe overlook of heat storage induced the RMSE of evaporation estimation increased over three timesThe conversion of heat storage in the water into nighttime LE was the key for evaporation estimation [ABSTRACT FROM AUTHOR]

Surface heat fluxes are crucial to the energy and water exchanges between surface and the atmosphere. Hysteresis effect poses a challenge in model simulation of evaporation (latent heat flux, LE) at hourly or intradaily scales. The hidden mechanisms behind the hysteresis remain unclear, given the diverse reports in various climates, geographical locations, and underlying surfaces. This study took advantage of eddy covariance flux observation over Poyang Lake of China, an ephemeral lake experiencing seasonal shifts from land to water. It depicted the hysteresis behavior of LE to environmental forces for the period from May to July in 2018, a hydrologic transition period from land to water surface. Our results showed obvious clockwise hysteresis loops between LE and water vapor pressure deficit (VPD), surface temperature (Ts), and air temperature (Ta). Counterclockwise loops exhibited between LE and surface net radiation (Rn), wind speed (WS), and temperature difference (Ts‐Ta). Rn, WS, and Ts‐Ta dominants control the hysteresis effects and regulate LE variations. The hysteresis loops changed in direction, shape, and area when the surface shifted from land to water. It was primarily related to the lengthened lag time between LE and other variables except for WS, which was attributable to enhanced impacts from WS and VPD, and weakened impacts from Rn and Ts‐Ta. The findings should help to improve our understanding of the complicated water‐atmosphere interactions at the intradaily scale. Key Points: Surface water fluxes altered their hysteresis behavior when surface shifted from land to waterMore significant controls on latent heat flux come from surface net radiation, wind speed, and temperature differenceSurface inertia to energy conversion strengthened from land to water surface [ABSTRACT FROM AUTHOR]

Accurate estimation of regional evapotranspiration (ET) or latent heat flux (latent energy, LE) remains a challenge. On the basis of a nonparametric approach, this study proposed an all-sky algorithm based on moderate-resolution imaging spectroradiometer (MODIS) products and datasets of China Meteorological Administration Land Data Assimilation System (CLDAS). Eddy covariance observations from three nonvegetated sites (desert, Gobi, and village) and three vegetated sites (orchard, vegetable, and wetland) over an arid/semiarid region were used as references to validate the new algorithm. Results showed that the spatial and temporal patterns of LE coincided with desert–oasis ecosystems. Comparison of the retrieved and reference values yielded the following results: R2 = 0.19–0.63, bias = −129–56 W/m2, relative error (RE) = 5%–29%, and root-mean-square error (RMSE) = 95–150 W/m2. Remote-sensing-retrieved LE (RSLE) exhibited relatively good accuracy and poor agreement with ground observations at the nonvegetated sites (RE: 5%–23%, R2: 0.19–0.40), whereas contradicting scenario occurred at the vegetated sites (RE: 24%–29%, R2: 0.46–0.63). In the arid nonvegetated region, the ET error might have been caused by net radiation, soil heat flux, land surface temperature, and air temperature. In the vegetated region, the errors of MODIS and CLDAS products were not the dominant error sources of RSLE. The validation supported the applicability of the proposed algorithm in the arid/semiarid region. [ABSTRACT FROM PUBLISHER]

Rice serves as the staple food for over 50% of the global population. Remotely-sensed based estimation of the gross primary production (GPP) and evapotranspiration (ET) of rice paddy fields is essential to assess global food security. In this study, we tested the application of a recently proposed remotely-sensed based water-carbon coupled model (PML-V2) in the lower reaches of the Poyang Lake plain, which is one of the nine production bases for crops in China. Evaluation using the eddy covariance measurements showed that, after parameter localization, the model reproduced the seasonal variations of GPP and ET for both the early rice and the late rice. The model performed reasonably well in the validation period because the key parameters (e.g., the quantum efficiency and the stomatal conductance coefficient) exhibited predictable seasonal variations. At the regional scale, the spatial distribution in multi-year GPP of rice (1365 ± 326 gCm−2year−1) can be explained by the vegetation cover fraction (R2 > 0.9); in comparison, the multi-year ET (1003 ± 65 mm/year) exhibits smaller spatial variations due to the high evaporation rate of the saturated soil surface of paddy fields. The water use efficiency of rice in this region varies around 1.35 gC/kgH2O with a standard deviation of 0.30. Our study shows that GPP and ET of rice can be estimated by remote sensing models without detailed crop management information, which is usually unavailable at regional scales. [ABSTRACT FROM AUTHOR]

• We use the P-T coefficient (α e) of wet environment to estimate transpiration (α c). • Similar function is identified between α c and α e in a given region at 8-day scales. • α c Converges to α e at an annual scale. Transpiration (T) from plant tissues is an important variable in ecological and agricultural studies. T is usually estimated using the Priestley-Taylor (PT) equation by an analog to the wet environment evaporation (ET w), because vegetation can use water from deep soils. However, the relation between the PT coefficients of T and ET w (α c and α e) was still unclear. In this paper, we tested whether α e can be used as a reasonable indicator of α c at intra-annual and annual scales. We obtained α e by inverting a complementary relationship model with measured evapotranspiration (ET) at the flux sites and obtained α c after ET was partitioned into evaporation (E) and T. We found that α c tends to converge to α e at annual scales, and a linear equation can adequately fit the α c = f(α e) functions at annual scales. With the α c = f(α e) functions determined, satisfactory accuracy (R2 = 0.89) was achieved in estimating T from ET following the "ET → α e → α c → T" calculating process at annual scales. In comparison, the α c ~ α e relationship at 8-day scales are modulated by leaf area index and vapor pressure deficit. However, similar α c = f(α e) functions are identified in the region with the same climate type at 8-day scales, indicating that a single α c = f(α e) function is applicable in the same region. The accuracy in T predictions at 8 day scales deteriorated compared to those at annual scales. However, R2 were still larger than 0.58 at most of the sites. Because great progress in ET estimation has been achieved with the help of thermal remote sensing technique in the last two decades, our results here can provide a new method to estimate T from remotely sensed ET. [ABSTRACT FROM AUTHOR]

The Priestley–Taylor equation (PTE) is widely used with its sole parameter (α) set as 1.26 for estimating the evapotranspiration (ET) of water bodies. However, variations in α may be large for ephemeral lakes. Poyang Lake, which is the largest freshwater lake in China, is water-covered and wetland-covered during its high-water and low-water periods, respectively, over a year. This paper examines the seasonal and diurnal variations in α using eddy covariance observation data for Poyang Lake. The results show that α = 1.26 is overall feasible for both periods at daily and subdaily scales. No obvious seasonal trend was observed, although the standard deviation in α for the wetland was larger than that for the water surface. The mean bias in evaporation estimations using the PTE was less than 5 W·m−2 during both periods, and the root mean square errors were much smaller than the average evaporation measurements at daily scale. U-shaped diurnal patterns of α were found during both periods, due partly to the negative correlation between α and the available energy (A). Compared to the vapor pressure deficit (VPD), wind speed (u) exerts a larger contribution to these variations. In addition, u is positively correlated with α during both periods, however, VPD was positively and negatively correlated with α during the high-water and low-water periods, respectively. Subdaily α exhibited contrasting clusters in the (u, VPD) plane under the same available energy ranges. Our study highlights the seasonal and diurnal course of α and suggests the careful use of PTE at subdaily scales. [ABSTRACT FROM AUTHOR]

The accuracy of a complementary relationship (CR) evapotranspiration (ET) model depends on how to parameterize the relationship between apparent potential ET and actual ET as the land surface changes from wet to dry. Yet, the validity of its inherent symmetric assumption of the original CR framework, i.e., the B value equal to one, is controversial. In this study, we conduct a comparative study between a linear, symmetric version (B = 1) and a nonlinear, asymmetric version (B is not necessarily equal to 1) of the advection-aridity (AA) CR model in a large ephemeral lake, which experiences dramatic changes in surface/atmosphere humidity. The results show that B was typically 1.1 ± 1.4 when ET ≤ ETPT ≤ ETPM, where ETPM and ETPT are estimated using the Penman (PM) and Priestley–Taylor (PT) equations, respectively; the AA model performed reasonably well in this case. However, the value of B can be negative and deviate from 1 significantly if the inequality ET ≤ ETPT ≤ ETPM is violated, which is quite common in humid environments. Because the actual ET can be negatively (B > 0) or positively (B < 0) related to the evaporative demand of the air, the nonlinear AA model generally performs better than the AA model if ET ≤ ETPM is satisfied. Although B is not significantly correlated with the atmospheric relative humidity (RH), both models, especially the nonlinear AA model, resulted in negative biases when ET > ETPM, which generally occur at high RH conditions. Both the linear and the nonlinear AA models performed better under higher water level conditions, however, our study highlights the need for higher-order (≥3) polynomial functions when CR models are applied in humid environments. [ABSTRACT FROM AUTHOR]

[Display omitted] • LVB experienced extensive conversion of forest and grass to agricultural land. • SWAT model presents good applicability in seasonal runoff modeling in LVB. • annual runoff generally increased with seasonal differences due to LULC changes. • hydrological drought aggravated over central western and eastern LVB with increased frequency and lengthened duration. Understanding the hydrological impacts of land use and land cover (LULC) changes is significant for sustainable water resources management and planning. The Lake Victoria basin (LVB) has experienced extensive forest and grass degradation and agricultural land expansion under rapid socio-economic development and population growth in recent decades. However, the hydrological impacts of LULC changes for the whole LVB is still poorly documented. This study first investigated the LULC changing effects of LVB, focusing on its impacts on the annual and seasonal runoff and the hydrological drought based on a distributed hydrological modeling of the Soil and Water Assessment Tool (SWAT). SWAT model showed comparatively good applicability in seasonal runoff simulation of LVB, with the percent bias (PBIAS) kept within ± 20 % and the coefficient of determination (R2) over 0.6 at ten hydrological stations available over the calibration and validation phases. Generally, the annual runoff obtained a monthly increase of 1.5 mm under collective LULC changes. Moreover, the LULC effects presented considerable seasonal dependence. A largest runoff increase of approximately 4 mm was detected in short rainy season attributed to the combined surface runoff and groundwater increase. Insignificant runoff increase was observed in long rainy and dry seasons under the complementary effects of surface runoff increase and groundwater decrease. Additionally, the hydrological drought was generally aggravated with increased drought frequency and lengthened duration, particularly for the central western and eastern regions with massive conversion of forest to agricultural land. The findings provide importance implication for rational water resources management and drought disaster response for the LVB. [ABSTRACT FROM AUTHOR]