Evapotranspiration Partitioning Research Articles

Estimating transpiration globally by integrating the Priestley-Taylor model with neural networks

Abstract Transpiration (T), the component of evapotranspiration (ET) controlled by the vegetation, dominates terrestrial ET in many ecosystems; however, estimating it accurately, especially at the global scale, remains a considerable challenge. Existing approaches mostly rely on the relationship between T and photosynthesis, but untangling this relationship is difficult and leads to diverging T estimates. Limited in-situ measurements and the inability to directly measure transpiration from space further complicate the reliable assessment of this crucial process in the terrestrial water cycle. Here, we developed a new hybrid Priestley-Taylor (PT) model combined with an Artificial Neural Network (ANN) using globally available remote sensing and reanalysis data of soil moisture, vapor pressure deficit and windspeed. We also take advantage of the newly released global sap flow measurement network SAPFLUXNET. In the proposed approach, we avoid the parameterization of stomatal conductance by training the ANN on the PT-Coefficient α, obtained by inverting the PT equation. The results showed that our model framework can estimate T in different forest ecosystems based on few predictors. By utilizing forcings from independent datasets, we eliminate the reliance on in-situ measurements for predicting T. Through upscaling actual observations to a larger scale, this model framework helps alleviate the scarcity of T products. Intercomparison of T with ET partitioning methods based on eddy covariance data, shows high performances (KGE of 0.69 in Europe and 0.60 in North America), slightly improving estimates compared to other models. Analysis of contribution of T to ET across 100 FLUXNET sites result in a global mean of 55.2%. We believe that modelling T independent from the carbon cycle can support our understanding of land-atmosphere feedbacks and climate extremes in future research.

Partitioning of Evapotranspiration and Its Response to Eco‐Environmental Factors Over an Alpine Grassland on the Qinghai–Tibetan Plateau Based on the SiB2 Model

ABSTRACTPartitioning evapotranspiration (ET) is challenging but essential for understanding the exchange of energy, water, and carbon between terrestrial ecosystems and the atmosphere. In this study, we applied the simple biosphere model (SiB2) to partition ET at a typical alpine grassland site on the Qinghai–Tibet Plateau (QTP). In addition, through process‐based model scenario experiments, we quantified the effects of four environmental factors on ET components and predicted their evolution under the two future carbon emission scenarios (ssp126 and ssp585). Our findings are summarized as follows: (1) The original version of SiB2, despite its simple structure, effectively simulates ET and its components. (2) The ratios of annual total transpiration (T), soil evaporation (Es), and canopy interception evaporation (Ei) to ET in the alpine grassland ecosystem were 51%, 43%, and 6%, respectively. (3) Each 100 mm increase in annual precipitation results in a significant increase in soil evaporation (2.77%). A 1°C increase in air temperature leads to a significant increase in vegetation transpiration (5.22%) and canopy interception evaporation (5.63%). Each 100 ppm increase in CO2 concentration causes a significant decrease in T (−5.43%) and ET (−2.97%). An increase in LAI (1 m2 m−2) has the largest effect on canopy interception evaporation (4.67%). (4) Under the high carbon emission scenario (ssp585), all ET components in this ecosystem show a significant growth trend, particularly vegetation transpiration and canopy interception evaporation. These findings will facilitate more precise predictions of the water cycle dynamics, reveal land‐atmosphere interaction mechanisms, and aid in the protection of the ecological environment of the QTP.

Effects of different mulching technologies on rainfed maize field energy exchange and evapotranspiration partitioning in northwest China

Artificial mulching, a prevalent water-saving tool in arid and semiarid agroecosystems, complicated energy exchange and water transport process between land surface and atmosphere. The field energy and evapotranspiration (ET) partitioning within a soil-mulch-plant-atmosphere continuum have not been comprehensively examined, which limited cognition of the underlying mechanisms that control hydrological processes and achieve yield improvement. Here, a four-season experiment in a rainfed summer maize field with four mulching treatments (NM: non-mulching, SM: straw mulching, RPBF: plastic-mulched ridge with bare furrow, and RPSF: plastic mulched ridge with straw-mulched furrow) was conducted to study the dynamics of surface energy and ET components and their regulation mechanisms. Results indicated that the effects of mulching on field energy partitioning were most evident at the maize initial stage, during which net radiation was significantly decreased under PM treatments (RPBF and RPSF), while soil heat flux was significantly reduced in SM treatments (p < 0.05). The average latent heat flux (LE) was 3.55 and 5.65 MJ·d−1 for NM maize at sowing and seedling stages, but decreased by 9.01 %, 27.04 %, 29.58 % at sowing, and 7.08 %, 9.56 % and 16.46 % at seedling stages for SM, RPBF and PRSF, respectively. The energy component differences among different treatments were minimal during the middle and late stages with high leaf coverage, and total LE and sensible heats were not significantly different. Mulch exerted a notable impact on soil evaporation (E) and crop transpiration (T), characterized by the average E of 0.96, 0.82, 0.57 and 0.46 mm·d−1 in NM, SM, RPBF and RPSF, while the value for T was 1.67, 1.88, 2.03 and 2.10 mm·d−1, respectively. PM conserved soil water by reducing E during the initial growing season and in dry periods, but also enhancing T and deepening the depth of soil water consumption under higher leaf cover. Energy exchange and ET partitioning were found to be more sensitive to soil water content (SWC) during periods characterized by lower leaf coverage, while the role of underlying canopy coverage characteristics overwhelmed soil properties in controlling energy and ET partitioning along with the leaf expansion. These findings contributed to a more comprehensive understanding of different mulching management on rainfed maize energy exchange and water use in Northwest China.

Comparative analysis of FAO dual Kc, Priestley‐Taylor and flux variance similarity methods in partitioning evapotranspiration from flood‐irrigated rice fields

AbstractAccurate quantification of evapotranspiration (ET) and its bifurcation into productive transpiration (T) and unproductive evaporation (E) are essential for the successful implementation of sustainable irrigation practices. This study compares the performances of three distinct methods for partitioning ET into E and T fluxes from flood‐irrigated rice fields. These methods include: i) the FAO dual Kc‐ETo model, which utilizes Penman–Monteith (PM) estimates of reference ET and crop‐specific scaling factors; ii) the Priestley‐Taylor (PT) method, which relies on radiation‐driven energy balance at the canopy surface; and iii) the flux variance similarity (FVS) method, which utilizes high‐frequency eddy covariance (EC) measurements of carbon and water vapour fluxes. Meteorological, phenological and hydrological parameters were monitored over two winter seasons in a paddy field, replicating site‐specific management strategies. The cumulative ETs obtained from the PM, PT and FVS methods were 445 mm, 300 mm and 356 mm, respectively, for season 1 and 428 mm, 321 mm and 375 mm, respectively, for season 2. The accuracy of the ET estimation and partition methods was assessed against independent measurements of ET and E using a lysimeter and a microlysimeter. The results demonstrated that the EC‐based FVS method offers superior accuracy in both quantifying (R2 = 0.67, RMSE = 0.70 mm) and partitioning (R2 = 0.51, RMSE = 0.76 mm) ET fluxes, followed by the PM‐based FAO dual Kc‐ETo and PT methods. Evaporation accounted for 29 ± 5% of consumptive water use, highlighting an opportunity for the implementation of water‐saving strategies, particularly during vegetative and transplantation stages. The findings of the path analysis indicate that vegetative and radiation factors influence ET variation, while meteorological and soil factors significantly impact T variation.

How does greening affect the surface water budget in the Loess Plateau?

Significant vegetation increase in the Loess Plateau (LP) of China could strongly affect the surface water budget. Through the WRF model with the Water Vapor Tracer (WVT) method tracking moisture within the LP, this study conducted three sets of experiments from 1999 to 2018 with GLASS Fractional Vegetation Cover (FVC) data. The results indicate that vegetation has a critical role in partitioning evapotranspiration (ET) into transpiration (Et), canopy evaporation (Ecan), and soil evaporation (Edir), thus regulating terrestrial internal convective precipitation (P). The local P response largely depends on external P (E_P), while the internal P (I_P) contribution remains minor. In summer, the total wet difference of I_P in the LP is about 0.03 mm/day, almost 5 times that of E_P. Greening also causes surface runoff reduction. Thus, in spring and summer, surface water storage (W) decreases due to the greater increase in ET than in P. In autumn, W increases by about 0.06 mm/day due to a large decrease in Ecan, implying confining the increased W to shallower soils, resulting in accelerated loss of deep soil moisture. The greening trend of 2000–2018 contributed to an increase in I_P, which could not offset increased ET and reduced E_P, leading to terrestrial water storage reduction.

Improving evapotranspiration partitioning by integrating satellite vegetation parameters into a land surface model

Land evapotranspiration (ET) primarily involves vegetation transpiration, canopy interception loss, and soil evaporation. Previous studies have made significant progress in total ET estimation; however, substantial challenges remain in partitioning ET on a regional scale, largely due to the intricate water and energy balance that is disrupted by vegetation cover changes. The accuracy of land surface models in representing ET components may be constrained by their inadequate consideration of vegetation dynamics. In this study, we integrate satellite leaf area index (LAI) and fraction of vegetation coverage (FVC) into the Variable Infiltration Capacity model (VIC) to improve ET partitioning ability in the Loess Plateau of China, a region that has experienced substantial vegetation dynamics. The results showed that satellite dynamic vegetation parameters in modeling are effective in improving the estimation of ET components compared with the default/static vegetation parameters. Considering LAI dynamics in the model enhances the representation of the inter- and intra-annual variations in vegetation transpiration and canopy interception loss. Dynamic FVC reasonably allocates transpiration to soil evaporation, capturing evaporation in forest gaps effectively. This effect is particularly relevant in arid and semi-arid regions. Among the ET components, transpiration was the most sensitive to the two dynamic vegetation parameters, followed by canopy interception loss and soil evaporation. Through the VIC model with dynamic vegetation parameters, our study revealed that soil evaporation was twice that of transpiration in the Loess Plateau, which is consistent with its semi-arid region and relatively sparse vegetation coverage. Our study offers valuable insights regarding the use of vegetation coverage for partitioning ET and highlights the advantage of integrating satellite vegetation products into land surface models.

Effects of Saline Irrigation Water Applications on Evapotranspiration Partitioning and Crop Coefficient of Tomato Grown in Mediterranean-Type Greenhouses

Effects of Saline Irrigation Water Applications on Evapotranspiration Partitioning and Crop Coefficient of Tomato Grown in Mediterranean-Type Greenhouses

Partition evapotranspiration into transpiration and evaporation in a natural boreal larch forest in China: A framework from concurrent eddy covariance systems

Partitioning forest ecosystem evapotranspiration (ET) into transpiration (T) and evaporation (E) has been widely discussed, as it is crucial for understanding hydrological processes and functions. However, quantifying the hydrological importance of the understory ecosystem is limited, particularly in China’s boreal forests. In this study, we first employed a framework with concurrent eddy covariance (EC) systems and the underlying water use efficiency (uWUE) method to partition ET in a natural boreal larch forest (Larix gmelinii) of China during the growing seasons of 2020 to 2022. The results showed that understory transpiration (Tu) and overstory transpiration (Tos) contributed 21.8 and 78.2% to T, respectively, while the contributions of understory evaporation (Eu) and overstory evaporation (Eos) to E were 41.2 and 58.8%, respectively. Understory evapotranspiration (ETu) contributed 32.6% to the total ET, suggesting the considerable importance of understory vegetation to water flux in the boreal larch forest. Interestingly, Tos and Eos had a similar contribution to ET. While the controlling mechanisms in Tu/T, Eu/E, and ETu/ET were more complex than those in Tu, Eu, and ETu, the leaf area index (LAI) of the overstory and solar radiation (SR) played greater roles in regulating each component and its respective ratios. Those results highlight the non-negligible role of understory vegetation in hydrological processes in boreal forests, which must be considered when managing or modelling forest-water relationships. Our study also demonstrates the effective utility of concurrent EC systems in partitioning ET in natural boreal forest ecosystems.

A Semi‐Mechanistic Model for Partitioning Evapotranspiration Reveals Transpiration Dominates the Water Flux in Drylands

AbstractPopular evapotranspiration (ET) partitioning methods make assumptions that might not be well‐suited to dryland ecosystems, such as high sensitivity of plant water‐use efficiency (WUE) to vapor pressure deficit (VPD). Our objectives were to (a) create an ET partitioning model that can produce fine‐scale estimates of transpiration (T) in drylands, and (b) use this approach to evaluate how climate controls T and WUE across ecosystem types and timescales along a dryland aridity gradient. We developed a novel, semi‐mechanistic ET partitioning method using a Bayesian approach that constrains abiotic evaporation using process‐based models, and loosely constrains time‐varying WUE within an autoregressive framework. We used this method to estimate daily T and weekly WUE across seven dryland ecosystem types and found that T dominates ET across the aridity gradient. Then, we applied cross‐wavelet coherence analysis to evaluate the temporal coherence between focal response variables (WUE and T/ET) and environmental variables. At yearly scales, we found that WUE at less arid, higher elevation sites was primarily limited by atmospheric moisture demand, and WUE at more arid, lower elevation sites was primarily limited by moisture supply. At sub‐yearly timescales, WUE and VPD were sporadically correlated. Hence, ecosystem‐scale dryland WUE is not always sensitive to changes in VPD at short timescales, despite this being a common assumption in many ET partitioning models. This new ET partitioning method can be used in dryland ecosystems to better understand how climate influences physically and biologically driven water fluxes.

Aspect Differences in Vegetation Type Drive Higher Evapotranspiration on a Pole‐Facing Slope in a California Oak Savanna

AbstractQuantifying evapotranspiration (ET) is critical to accurately predict vegetation health, groundwater recharge, and streamflow generation. Hillslope aspect, the direction a hillslope faces, results in variable incoming solar radiation and subsequent vegetation water use that drive ET. Previous work in watersheds with a single dominant vegetation type (e.g., trees) have shown that equator‐facing slopes (EFS) have higher ET compared to pole‐facing slopes (PFS) due to higher evaporative demand. However, it remains unclear how differences in vegetation type (i.e., grasses and trees) influence ET and water partitioning between hillslopes with opposing aspects. Here, we quantified ET and root‐zone water storage deficits between a PFS and EFS with contrasting vegetation types within central coastal California. Our results suggest that the cooler PFS with oak trees has higher ET than the warmer EFS with grasses, which is counter to previous work in landscapes with a singule dominant vegetation type. Our root‐zone water storage deficit calculations indicate that the PFS has a higher subsurface storage deficit and a larger seasonal dry down than the EFS. This aspect difference in subsurface water storage deficits may influence the subsequent replenishment of dynamic water storage, groundwater recharge and streamflow generation. In addition, larger subsurface water deficits on PFS may reduce their ability to serve as hydrologic refugia for oaks during multi‐year droughts. This research provides a novel integration of field‐based and remotely‐sensed estimates of ET required to properly quantify hillslope‐scale water balances. These findings emphasize the importance of resolving hillslope‐scale vegetation structure within Earth system models, especially in landscapes with diverse vegetation types.

Comparing Four Evapotranspiration Partitioning Methods from Eddy Covariance Considering Turbulent Mixing in a Poplar Plantation

Evapotranspiration is a key link in the water cycle of terrestrial ecosystems, and the partitioning of evapotranspiration is a prerequisite for diagnosing vegetation growth and water use strategies. In this study, we used double-layer eddy covariance (DLEC) measurements within and above the canopy of poplar plantations to divide evapotranspiration into transpiration and evaporation during the growing season. We diagnosed the coupling state of airflows in the canopy vertical layer and found that the daytime coupling state at the half-hourly scale can mask nighttime decoupling. Furthermore, we investigated the daytime and nighttime vertical layer airflow coupling states separately and quantified the effects of coupling states on the DLEC of resolved transpiration. The partitioning results of the DLEC method were taken as the standard after the airflow coupling test. Then, the performance and accuracy of evapotranspiration partitioning for the modified relaxed eddy accumulation (MREA), the conditional eddy covariance (CEC), and the flux variance similarity (FVS) with DLEC were compared. Transpiration calculated from MREA showed the best agreement with DLEC, and the other methods showed different degrees of underestimation (1:1 slope = 0.64–0.83). Evaporation calculated from FVS showed the best agreement with DLEC, while CEC and FVS made an overestimation of more than 26% (1:1 slope = 1.26–1.99), but MREA made an underestimation from 5% to 35% (1:1 slope = 0.65–0.95). The correlation coefficients between DLEC and MREA for transpiration were 0.95–0.97 with RMSEs of 15.52–17.04 W m−2, and those between DLEC and FVS for transpiration were 0.73–0.78 with RMSEs of 10–21.26 W m−2 at the daily half-hourly scale. A detailed comparison of the differences between DLEC and evapotranspiration partitioning methods from high-frequency eddy covariance data under the condition of canopy vertical layer airflow mixing provides knowledge about the consistency of results for evapotranspiration partitioning in poplar plantation forests.

Partitioning urban forest evapotranspiration based on integrating eddy covariance of water vapor and carbon dioxide fluxes

Partitioning of evapotranspiration (ET) in urban forest lands plays a vital role in mitigating ambient temperature and evaluating the effects of urbanization on the urban hydrological cycle. While ET partitioning has been extensively studied in diverse natural ecosystems, there remains a significant paucity of research on urban ecosystems. The flux variance similarity (FVS) theory is used to partition urban forest ET into soil evaporation (E) and vegetation transpiration (T). This involves measurements from eddy covariance of water vapor and carbon dioxide fluxes, along with an estimated leaf-level water use efficiency (WUE) algorithm. The study compares five WUE algorithms in partitioning the average transpiration fraction (T/ET) and validates the results using two years of oxygen isotope observations. Although all five FVS-based WUE algorithms effectively capture the dynamic changes in hourly scale T and E across the four seasons, the algorithm that assumes a constant ratio of intercellular CO2 concentration (ci) to ambient CO2 concentration (ca) provides the most accurate simulation results for the ratio of T/ET. The performance metrics for this specific algorithm include the RMSE of 0.06, R2 of 0.88, the bias of 0.02, and MAPE of 8.9 %, respectively. Comparing urban forests to natural forests, the T/ET in urban areas is approximately 2.4–25.3 % higher, possibly due to the elevated air temperature (Ta), greater leaf area index (LAI), and increased soil water availability. Correlation analysis reveals that the T/ET dynamic is primarily controlled by Ta, LAI, net radiation, ca, and soil water content at half-hourly, daily, and monthly scales. This research provides valuable insights into the performance and applicability of various WUE algorithms in urban forests, contributing significantly to understanding the impact of urbanization on energy, water, and carbon cycles within ecosystems.

Estimating and partitioning evapotranspiration in a film mulched cropland with shallow groundwater by the improved dual source model

Evapotranspiration (ET) is a key link in terrestrial water cycle and influenced by complex environmental factors in cropland. Accurate assessment of crop ET over heterogeneous underlying surfaces remains challenging. In this study, the dual source Shuttleworth-Wallace (SW) model was modified to estimate λET (latent heat corresponding to ET) through incorporating the effects of film mulching and shallow groundwater. λET and latent heat from transpiration (λT) were measured in a maize field in northwest China during 2017 and 2018 to assess the performance of the original (SW) and modified (SWM) models. Results indicate that the overestimation of latent heat from soil evaporation (λE) due to ignoring film mulching could be obviously mitigated by SWM. Besides, considering capillary rise from shallow groundwater in SWM improved not only λET estimates but also the accuracy of canopy resistance parameter. The SWM model outperformed the SW model that the slopes of fitting lines for λET and λT increased from 0.60 to 0.79 to 0.77–0.99 at daily scale and Nash-Sutcliffe Efficiency coefficient exceeded 0.86. Relative error and RMSE were decreased to below 0.15 and 19.88 W m−2, respectively. The estimations of λET and λT by SWM were also improved at hourly scale. Seasonal variation and partition of λET between two years were comparable and average T/ET for the entire growing season was about 78 %-84 %, which was largest at the heading stage. Path analysis on the responses of λET to the environmental factors recognized the greatest direct effect of crop height or leaf area index, and identified the significantly direct control of shallow groundwater on λT in this area. The study presented an improved dual source model to better quantify λET, which would benefit water resources management for film mulched croplands with shallow groundwater.

Partitioning evapotranspiration of Camellia oleifera during the growing season based on the Penman-Monteith model combined with the micro-lysimeter and stable isotope methods

Frequent seasonal droughts impact on crop growth and yield in the hilly areas of southern China. A good knowledge of its evapotranspiration partitioning of the main economic oil crop Camellia Oleifera is particularly important to increase water productivity and improve water resource management. The isotope-based method was applied to partition ET in the hilly Camellia Oleifera Forest of southern China. The isotopic composition of evapotranspiration vapor (δET), transpiration vapor (δT) and evaporation vapor (δE) were calculated by the Keeling plot method, the Craig-Gordon model (C-G model), and isotopic steady-state assumptions, respectively. The conventional Penman-Monteith model and the micro-lysimeter method (PM-L) were used to compare and assess the ET partitioning results (Ft). It showed that the Ft values calculated by the two methods were in good agreement. The isotopic composition of soil water at the evaporating front (δS) ahead and after DOY151 was sampled at 5 and 10 cm depth, respectively, where the correlation coefficients (R2) of the Ft values calculated by δ18O and δ2H were 0.84 and 0.66. Ft Calculated by δ18O was more accurate than δ2H because of the higher correlation coefficient of δ18O in the keeling plot regression and in the linear fit with PM-L. The isotopic composition of soil evaporation vapor（δE）calculated by dynamic εk (kinetic fractionation effects) values can be more accurate to quantify the ET partitioning results (with the R2 of 0.90). The mean values of Ft were 0.79 and 0.82 by the PM-L method and the isotope-based method respectively over the whole growing season, indicating the isotope method is robust in calculating ET partitioning for Camellia oleifera in the region. We also found that the seasonal variation of Ft is mainly controlled by temperature (T), soil water content (SWC), and leaf area index (LAI), all of which can be effectively expressed as power functions. The results provide potential assistance for water management in Camellia oleifera woodlands.

Revisiting the hydrological legacy of revegetation on China's Loess Plateau using Eagleson's ecohydrological perspective

Revegetation has resulted in a trend of increasing vegetation greenness on the Chinese Loess Plateau. However, it remains unclear whether the regional vegetation coverage exceeds hydroclimatic limitations in the context of revegetation, and the hydrological effects of greening are controversial. Eagleson's optimality hypothesis can explain some of the hydrological effects on the Loess Plateau. Here, building on previous research, the geospatial vegetation states were estimated for pre- and post-revegetation periods on the Loess Plateau from 1982 to 2015 using Eagleson's ecological optimality theory. Additionally, a drought composite analysis approach was utilized to investigate the hydrological effects related to drought (including sensitivity and partitioning) under various vegetation states. It was found that revegetation increased the proportion of catchments in the equilibrium state and decreased the proportion in the disturbed state, owing to a wetter climate compared with the pre-revegetation period. Root-zone soil drought, driven by precipitation (P) deficit, asymmetrically triggered hydrological effects for both the pre- and post-revegetation periods, with reduced runoff (Q) for both periods and a decrease in evapotranspiration (ET) during the pre-revegetation period but an increase in ET during the post-revegetation period. Moreover, catchments in an equilibrium state exhibited lower sensitivity between ET and P, and more stable partitioning of ET with regards to P, compared with those in a disturbed state. These results underscore the theoretical framework that an equilibrium state is crucial for maintaining ecosystem ET. Our results highlight the necessity of considering the hydrologic regulation of vegetation states when assessing the hydrological effects of vegetation change.

Evapotranspiration partitioning through water stable isotopic measurements in a subtropical coniferous forest

AbstractEvapotranspiration (ET) partitioning distinguishes the soil evaporation (E) and plant transpiration (T) components and is crucial for understanding the land‐atmosphere interactions and ecosystem water budget. However, the mechanism and controls of ET partitioning for subtropical forests in heterogeneous environments remain poorly understood. Here, we present δ18O and δ2H of about 1,527 isotope samples including atmospheric water, soil and plant water during different seasons in 2 years of 2020–2021 from a coniferous forest across Southeast China. We used the isotopic mass balance of ecosystem water pools, the Craig‐Gordon model and the Keeling‐Plot method to partition T from ET (T/ET) and quantify the controls on T/ET. Results indicated that the uncertainty in the T/ET was principally from the soil water evaporation (δE) value, about 20–30 cm was found to be a reasonable evaporating front depth for estimating δE in this coniferous forest. T/ET presented a “U” shape diurnal pattern and varied from 66.7% to 89.9%. Isotope‐based T/ET in autumn with high temperatures and little rain was higher than those in the summer and winter seasons. Relative humidity (or vapour pressure deficit) dominated the diurnal T/ET variations (relative contributions of &gt; 40%) in summer and autumn, while air temperature and soil water content were the main controls in winter. Our study also showed that δ18O‐derived T/ET was consistent with that of δ2H, although δ2H was found to be more stable in ET partitioning, the dual stable isotope approach should be employed in future studies for the uncertainties brought by samplings or measurements. The agreement between the isotope‐based T/ET and ET partitioning approach that uses eddy covariance and sap flux data was stronger at midday. These isotope‐inferred ET partitioning can inform land surface models and provide more insights into water management in subtropical forests.

Coupled DSSAT and HYDRUS-1D Simulation of the Farmland–Crop Water Cycling Process in the Dengkouyangshui Irrigation District

(1) Background: Effective water management in agricultural systems poses a significant challenge, particularly in the Dengkouyangshui irrigation district. Inefficiencies and insufficient detail in water usage across crop growth stages have resulted in suboptimal water cycling. Recent infrastructure improvements and technological interventions necessitate a reevaluation of water usage, especially concerning changes in irrigation and seepage dynamics. (2) Methods: This study addresses these concerns by employing an integrated modeling approach that combines the DSSAT with the HYDRUS-1D soil hydrology model to simulate complex interactions among soil, crop growth, and irrigation practices within the district. Observational data were used to calibrate and validate the integrated model, including soil moisture, LAI, and crop yields from the 2022 and 2023 agricultural seasons. (3) Results: The simulation results strongly align with the empirical data, highlighting the ability of the model to capture the intricate dynamics of soil–water–atmosphere–plant interactions. (4) Conclusions: The soil’s retention and moisture-holding characteristics exhibited resilience during periods without water supplementation, with measurable declines in soil moisture at various depths, indicating the soil’s capacity to support crops in water-limited conditions. This study delineates water consumption by maize crops throughout their growth cycle, providing insights into evapotranspiration partitioning and quantifying seepage losses. An in-depth analysis of water balances at different growth stages informs irrigation strategies, suggesting optimal volumes to enhance efficiency during critical crop development phases. This integrative modeling approach is valuable for providing actionable data to optimize the water cycling process and improve agricultural sustainability in the Dengkouyangshui irrigation district.

Using Median Point in Keeling Plot to Reduce the Uncertainty of the Isotopic Composition of Evapotranspiration

Abstract The isotopic composition of evapotranspiration δET is a crucial parameter in isotope-based evapotranspiration (ET) partitioning and moisture recycling studies. The Keeling plot method is the most prevalent method to calculate δET, though it contains large extrapolated uncertainties from the least squares regression. Traditional Keeling regression uses the mean point of individual measurements. Here, a modified Keeling plot framework was proposed using the median point of individual measurements. We tested the δET uncertainty using the mean point [σET (mean)] and median point [σET (median)]. Multiple resolutions of input and output data from six independent sites were used to test the performance of the two methods. The σET (mean) would be greater than σET (median) when the mean value of inverse vapor concentration () is greater than the median value of inverse vapor concentration []. When applying the filter of r2 &gt; 0.8, around 70% of σET (mean) was greater than σET (median). This phenomenon might be due to the normality of the vapor concentration Cυ producing the asymmetric distribution of 1/Cυ. The median method could perform significantly better than the mean method when inputting high-resolution measurements (e.g., 1 Hz) and when the water vapor concentration Cυ is relatively low. Compared to the mean method, applying the median method could on average reduce 6.88% of ET partitioning uncertainties and could on average reduce 9.00% of moisture recycling uncertainties. This study provided a new insight of the Keeling plot method and emphasized handling model output uncertainty from multiple perspectives instead of only from input parameters.

Environmental Controls on Evapotranspiration and Its Components in a Qinghai Spruce Forest in the Qilian Mountains.

Qinghai spruce forests, found in the Qilian mountains, are a typical type of water conservation forest and play an important role in regulating the regional water balance and quantifying the changes and controlling factors for evapotranspiration (ET) and its components, namely, transpiration (T), evaporation (Es) and canopy interceptions (Ei), of the Qinghai spruce, which may provide rich information for improving water resource management. In this study, we partitioned ET based on the assumption that total ET equals the sum of T, Es and Ei, and then we analyzed the environmental controls on ET, T and Es. The results show that, during the main growing seasons of the Qinghai spruce (from May to September) in the Qilian mountains, the total ET values were 353.7 and 325.1 mm in 2019 and 2020, respectively. The monthly dynamics in the daily variations in T/ET and Es/ET showed that T/ET increased until July and gradually decreased afterwards, while Es/ET showed opposite trends and was mainly controlled by the amount of precipitation. Among all the ET components, T always occupied the largest part, while the contribution of Es to ET was minimal. Meanwhile, Ei must be considered when partitioning ET, as it accounts for a certain percentage (greater than one-third) of the total ET values. Combining Pearson's correlation analysis and the boosted regression trees method, we concluded that net radiation (Rn), soil temperature (Ts) and soil water content (SWC) were the main controlling factors for ET. T was mainly determined by the radiation and soil hydrothermic factors (Rn, photosynthetic active radiation (PAR) and TS30), while Es was mostly controlled by the vapor pressure deficit (VPD), atmospheric precipitation (Pa), throughfall (Pt) and air temperature (Ta). Our study may provide further theoretical support to improve our understanding of the responses of ET and its components to surrounding environments.

Evapotranspiration partitioning by integrating eddy covariance, micro-lysimeter and unmanned aerial vehicle observations: A case study in the North China Plain

Partitioning of evapotranspiration (ET) into soil evaporation (E) and plant transpiration (T) poses a significant challenge. This study proposed a novel approach that combines eddy covariance, micro-lysimeter, and high-resolution unmanned aerial vehicle (UAV) images within the flux footprint to optimize the canopy and soil resistances of the Shuttleworth-Wallace model (S-W) using a multi-objective optimization scheme. A two-year experiment was conducted at the Yucheng and Luancheng sites to investigate the effectiveness of the proposed method for the summer maize-wheat winter system in the North China Plain. Our results showed that the S-W model with multi-objective optimization by using high-resolution UAV images within the flux footprint significantly improved the estimation accuracy of ET components compared with the traditional one- and two-objective optimization schemes. The estimation of ET, T, and E of our method had an average root mean square error of 0.67 mm day−1, 0.66 mm day−1, and 0.28 mm day−1, respectively. The optimized S-W model using high-resolution UAV data within the flux footprint produced better ET partitioning than that optimized using Moderate Resolution Imaging Spectroradiometer (MODIS) data. We then applied the proposed method to estimate ET and ET components in the North China Plain. This study highlighted the importance of utilizing multi-source data (especially high-resolution UAV images) and multi-objective optimization for accurate ET partitioning.