Estimate Soil Evaporation Research Articles

Prediction of the weighted-mean soil water diffusivity in supporting the falling rate stage of evaporation

Daily soil evaporation from drying soil can be described as isothermal linear diffusion process, resulting in a simple equation for estimating soil evaporation rate. However, determining soil water diffusivity and subsequently the crucial parameter of weighted-mean diffusivity, essential for estimating soil evaporation rate, is challenging and time-consuming. In this paper, the soil water diffusivity was re-evaluated by considering the effect of film flow, a phenomenon often overlooked but recently argued by Wang et al. (2019, https://doi.org/10.1029/2019WR025003) as the dominant process in the falling rate stage of evaporation. Theoretical derivation reveals a universal relationship between soil water diffusivity and matric potential, independent of soil types. Additionally, soil water diffusivity can be expressed in the form of an exponential function, a form commonly assumed empirically in the literature. Testing with various datasets suggests that the theoretically derived soil water diffusivity generally agrees closely with observations for matric potentials less than about −1 m, wherein the diffusivity accounting for capillary flow shows significant underestimation. Furthermore, a simple function is derived for estimating the weighted-mean diffusivity, enabling a direct estimation of soil evaporation rates in the falling rate stage. Testing with various data sets of different soil types and ambient conditions generally demonstrates close agreements between the estimated soil evaporation rates and observations, indicating that the developed method provides a robust estimation of the weighted-mean soil water diffusivity. When the initial matric potential of the linear diffusion process of drying is higher than about −1 m, which usually occurs under very high atmospheric demand conditions or for very coarse-textured soils, however, the effects of capillary flow were found to be important and need consideration. The effects of vapor diffusion were also discussed and found to have a negligible impact on the estimation of weighted-mean soil water diffusivity.

Improving the estimation of soil water evaporation based on days after wetting

AbstractSoil evaporation constitutes a major pathway of water loss in agriculture. Understanding its dynamics in the face of drying and soil cover is fundamental to improve both simulation models and the sustainability of production systems. Thus, the objective of this study was to estimate soil evaporation as a function of drying and percentage of soil cover. Three experiments were carried out in three different periods. In each of the periods, in parallel and in an adjacent area, an experiment was carried out to evaluate the influence of weighing micro‐lysimeter (ML) height on the estimation of direct soil evaporation. The experiments were installed with a completely randomized design. For the experiments that measured evaporation as a function of cover, the treatments consisted of six different percentages of cover of the internal area of the ML (0%, 10%, 25%, 50%, 75% and 100%), with four replicates, using artificial plants to cover the soil. The experiments that estimated evaporation as a function of ML height were conducted with eight repetitions and three different ML heights (100, 200 and 300 mm). It was observed that the accumulated evaporation up to 25 days after wetting was 52% and 53% lower in micro‐lysimeters with 100 mm height, compared to those with 200 and 300 mm height, respectively, for all experiments. The new model developed to calculate soil evaporation as a function of the days after wetting and percentage of soil cover showed excellent performance (NSE > 0.95).

A modified DSSAT‐CERES model for simulating summer maize growth under film mulching

AbstractPlastic film mulching is an effective agronomic measure for increasing crop yield, and the decision support system for agricultural technology transfer (DSSAT) model is an effective tool for simulating crop growth and water management. However, the DSSAT model does not have a specific soil evaporation module for plastic film mulching. In this paper, a method for estimating soil evaporation capacity under film mulching conditions based on the small hole effect was developed and embedded in the DSSAT model. Then, considering the compensation effect of soil temperature on air temperature under the condition of film mulching, the DSSAT model was modified accordingly. The results show that the average temperature compensation coefficient for 2 yr from sowing to emergence was 0.695 °C, and 0.305 °C from emergence to jointing. The improved DSSAT model can simulate the growth of summer maize (Zea mays L.) and changes in soil water content. Compared with the original model, the average relative RMSE of the simulated and observed soil water content of the modified DSSAT model improved by 2.26 and 1.63%, respectively. The modified model can improve the simulation accuracy, which shows that the method proposed in this paper can provide an effective way for the simulation of crop growth process under film mulching conditions.

A continental-scale soil evaporation dataset derived from Soil Moisture Active Passive satellite drying rates

This manuscript describes an observationally-based dataset of soil evaporation for the conterminous U.S. (CONUS), gridded to a 9 km resolution for the time-period of April 2015-March 2019. This product is termed E-SMAP (Evaporation-Soil Moisture Active Passive) in which soil evaporation is estimated from the surface layer, defined by the SMAP sensing depth of 50 mm, between SMAP overpass intervals that are screened on the basis of precipitation and SMAP quality control flags. Soil evaporation is estimated using a water balance of the surface soil that we show is largely dominated by SMAP-observed soil drying. E-SMAP soil evaporation is on average 0.72 mm day−1, which falls within the range of soil evaporation estimates (0.17–0.89 mm day−1) derived from operational land surface models and an alternative remote sensing product. E-SMAP is independent from existing soil evaporation estimates and therefore has the potential to improve understanding of evapotranspiration partitioning and model development.

Comparison of field methods for estimating evaporation from bare soil using lysimeters in a semi-arid area

Evaporation from bare soil is an important component of a catchment water balance. However, it is arguably one of the most challenging hydrological processes to estimate and measure accurately. Several approaches to estimate soil evaporation exist, but their performance for specific water table conditions remains unclear. This study investigated the performance of four commonly used approaches and several ways on how to implement them: the energy-balanced based FAO-56 method with the skin evaporation enhancement (FAO-56 skin), hydraulic methods based on groundwater level fluctuation (GLF), Darcy’s law, and the maximum entropy production (MEP) method based on non-equilibrium thermodynamics theory. Three lysimeters with different water table depths were used at a research site in the Guanzhong Basin of China. The lysimeters were equipped with soil moisture probes. Water table fluctuations were also measured. The data allow us to accurately estimate evaporation rates using a water balance approach and are used to assess the performance of the analysed methods. The results show that: (1) The MEP method performed best for all water table conditions, but tends to overestimate evaporation if the water table is below the extinction depth. The extinction depth is the depth of the water table were there the contribution of groundwater to bare-soil evaporation is zero. In our case, the extinction depth was 78 cm. (2) The FAO-56 skin method underestimated evaporation where the water table was above the extinction depth, and vice versa. (3) The groundwater level fluctuation method significantly overestimated the evaporation if the specific yield was estimated using hydraulic methods. The groundwater level fluctuation method should be combined with a soil water balance, independent of water table conditions. The method can only be applied if the water table is above the extinction depth. (4) Conceptually, Darcy’s law was suitable for estimating evaporation. However, the estimation of the required parameters is challenging. A good fit could only be obtained through calibration to measured evaporation rates.

Measuring soil evaporation from a cropped land in the semi-arid Makanya catchment, Northern Tanzania: Methods and challenges

Estimating soil water loss from cropped land is vital for sustainable management of water resources in semi-arid and hot regions. Soil evaporation (Es) is an important process in these regions but hard to quantify. The study aimed at quantifying Es in maize field under three treatments using micro-lysimeters (MLs). It also aims to identify sources of challenges in the method. The treatments were; flat cultivation with mulching (FCM), without mulches (FC) and double digging (DD, manual tillage practice), were replicated trice. In each plot, two micro-lysimeters were installed, one containing soil samples to measure soil evaporation and an empty one to measure throughfall (Ʈr) under the maize canopy. The 24-hr soil samples weight change and throughfall records were used to estimate soil evaporation for each plot. The estimated mean daily soil evaporation was 3.4 mm/day in FC, 2.1 mm/day in FCM and 3.0 mm/day for DD. There was a challenge in the method during the rainfall period which lead to both negative and high Es values during rainfall period. Less throughfall from empty MLs than in soil containing MLs caused the negative Es and the opposite was true for higher Es during rainy period. We urge the method to be improved by measuring throughfall simultaneously with soil weight changes immediately after rainfall events and minimize random errors by using many MLs. To have more results on reducing water losses while increasing available water for crop growth in this water scarce environment, we suggest FCM to be combined with DD treatment.

Measuring and Modelling Soil Evaporation in an Irrigated Olive Orchard to Improve Water Management

The aim of this study was to estimate soil evaporation (Es) in an intensive olive orchard. Measurements of Es were performed for 19 days using microlysimeters, during summers 2010, 2011 and 2012 in southeast Portugal. In order to relate each area type to radiation transmissivity, ground cover measurements were performed over the years. These data were used to calibrate and validate an empirical model for Es estimation. Measured daily average Es was 0.55 ± 0.14 mm; the model estimated 0.53 ± 0.18 mm for the same days, with a determination coefficient of 0.94. This corresponds to 9% of the reference evapotranspiration, representing well the overall values estimated for the summer, except for days after rain. Regarding the wet area, measured Es for the validation data set was 2.42 L/(m2 of wet area), the estimated was 2.49 L/(m2 of wet area). Measured average Es in dry area (validation data set) was 0.42 L/(m2 of dry area), estimated Es was 0.43 L/(m2 of dry area). The large exposed dry area had a significant contribution to evaporation. On average, estimated Es during a typical Mediterranean summer was 10% of reference evapotranspiration, representing 30% of transpiration and 23% of evapotranspiration.

Partitioning evapotranspiration and its long-term evolution in a dry pine forest using measurement-based estimates of soil evaporation

The future of forests and their productivity in dry environments will depend on both water availability through precipitation and ecosystem and plant water use characteristics. It is increasingly recognized that better understanding water use patterns and their response to change depends on our ability to partition evapotranspiration (ET). Here, we use chamber-based direct measurements of soil evaporation (Es) in a semi-arid Pinus halepensis forest to partition ET to Es and tree transpiration (Et), to assess the daily and seasonal changes and to compare annual-scale values with measurements carried out at the same site ten years earlier. The ecosystem is characterized by a high annual Es/ET ratio of 0.26, and an Et/ET of 0.63. Es diminished in the long dry season, but as much as 74 ± 5% of the residual flux was due to the re-evaporation of nighttime moisture adsorption, which may provide critical protection from soil drying. Over the 10 years observation period concurrent increase in the transpiration ratio (TR=Et/ET; +29%) and in leaf area index (LAI; +44%) were observed, with the ratio of TR/LAI remaining constant at ~0.31, and with persistently closed hydrological balance (ET/P of 0.94–1.07). The observed Et/ET values are similar to the estimated global mean values, but are attained at a much higher aridity index (5.5) than the mean one, demonstrating the potential for expanding forestation into dry regions.

ESTIMATION OF SOIL EVAPORATION BY SOIL HYDRAULIC FACTOR FROM BARE DUNE SAND MULCH

A method is presented that employs soil moisture measurements and lysimetric reference evapotranspiration data to estimate a soil hydraulic factor for estimating soil evaporation. Soil evaporation is a complicated process. The soil evaporation process has two main stages. In this study, soil hydraulic factor was used to estimate soil evaporation under dune sand mulch. The soil hydraulic factor was derived from small pan evaporation data and soil evaporation data from dune sand soil columns. Dune sand soil columns were saturated and gravitational water was drained. The dune sand soil columns were then covered by dry Tottori dune sand soil of 0 cm, 2 cm and 5 cm thickness. Soil evaporation from these columns was measured gravimetrically. Potential evaporation was determined from small evaporation pans placed alongside the dune sand soil columns. Water was applied to three weighing lysimeters (for measuring actual soil evaporation) in a glasshouse to the field capacity of the dune sand soil. The weighing lysimeters were also covered by the dune sand soil of 0 cm, 2 cm and 5 cm thickness and that was dried naturally. Cumulative soil evaporation from dune sand soil columns and cumulative potential evaporation from small evaporation pans was used to determine the soil hydraulic factor under the three dune sand mulch treatments. The soil hydraulic factor was then used to estimate soil evaporation under natural drying conditions in the glasshouse. Estimated cumulative soil evaporation was compared with measured cumulative soil evaporation. The soil hydraulic factor overestimated cumulative soil evaporation during the falling rate stage of soil evaporation under 0 cm and 2 cm sand mulch. Adjusting the estimation by subtracting the difference between the estimated and the measured cumulative soil evaporation at the point where the square root of cumulative potential evaporation was equal to the soil hydraulic factor from the estimates moved the values closer to the actual measured. The soil hydraulic factor overestimated cumulative soil evaporation during the whole drying period under 5 cm dune sand soil mulch. The adjustment of the estimates did not move the values as close to the actual measured as in the 2 cm mulch. Using the soil hydraulic factor gave better estimates of cumulative soil evaporation during the constant rate stage under 0 cm and 2 cm sand mulch than under 5 cm sand mulch.

A Modified Surface Energy Balance to Estimate Crop Transpiration and Soil Evaporation in Micro-Irrigated Orchards

A surface energy balance model was conceived to estimate crop transpiration and soil evaporation in orchards and vineyards where the floor is partially wetted by micro-irrigation systems. The proposed surface energy balance model for partial wetting (SEB-PW) builds upon previous multiple-layer modelling approaches to estimate the latent, sensible, and soil heat fluxes, while partitioning the total evapotranspiration ( E T ) into dry and wet soil evaporation ( λ E s o i l ) and crop transpiration ( T ). The model estimates the energy balance and flux resistances for the evaporation from dry and wet soil areas below the canopy, evaporation from dry and wet soil areas between plant rows, crop transpiration, and total crop E T . This article describes the model development, sensitivity analysis and a preliminary model evaluation. The evaluation shows that simulated hourly E T values have a good correlation with field measurements conducted with the surface renewal method and micro-lysimeter measurements in a micro-irrigated winegrape vineyard of Northern California for a range of fractional crop canopy cover conditions. Evaluation showed that hourly L E estimates had root mean square error ( R M S E ) of 58.6 W m−2, mean absolute error ( M A E ) of 35.6 W m−2, Nash-Sutcliffe coefficient ( C N S ) of 0.85, and index of agreement ( d a ) of 0.94. Daily soil evaporation ( E s ) estimations had R M S E of 0.30 mm d−1, M A E of 0.24 mm d−1, C N S of 0.87, and d a of 0.94. E s estimation had a coefficient of determination ( r 2 ) of 0.95, when compared with the micro-lysimeter measurements, which showed that E s can reach values from 28% to 46% of the total E T after an irrigation event. The proposed SEB-PW model can be used to estimate the effect and significance of soil evaporation from wet and dry soil areas on the total E T , and to inform water balance studies for optimizing irrigation management. Further evaluation is needed to test the model in other partially wetted orchards and to test the model performance during all growing seasons and for different environmental conditions.

Estimating soil evaporation in dry seeded rice and wheat crops after wetting events

Soil evaporation (Es) is quite challenging to measure directly, and researchers most commonly resort to using mini-lysimeter’s to measure Es from both bare soil and from soil beneath the crop canopy. However, this technique is unable to measure Es during and shortly after periods of irrigation or rain, and an approach to fill data gaps during these periods would be valuable. One possible approach is the use of the relationship between Es, pan evaporation (Ep) and gravimetric soil water content (θg). To this end, a mini-lysimeter field study was carried out during periods of low evaporative demand (Ep ≤ 3 mm) and high evaporative demand (Ep > 3 mm) to determine the relationship between Es, Ep and θg. There was a highly significant multi-linear relationship between Es, Ep, θg and time after wetting (R2 = 0.78; p < 0.001). Direct measurement using mini-lysimeters and gap-filling using Ep on days of irrigation or rainfall, and the multi-linear relationship for up to 6 d following wetting events, showed that significant amounts of water were lost as Es from both wheat (168 mm) and dry seeded rice (455 mm) crops. This study suggested that both θg and evaporative demand influence Es collectively and are not separate influences as has been implied by Ritchie’s two-stage evaporation model (Ritchie, 1972). The high significance and high R2 of the relationship between Es, θg, Ep and time suggests that θg can be used to calculate Es after irrigation or rainfall when empirical measurements of Es are unavailable. Further, the strong significance of regression between θg and Ep suggests that water content and energy potential are important components of Es during both stage 1 and stage 2 evaporation.

An optimized two source energy balance model based on complementary concept and canopy conductance

In this study, we revised a two source energy balance model (Gc-TSEB) that is based on canopy conductance and soil moisture in evapotranspiration (ET) estimation. We estimate soil evaporation (E) using the complementary concept and soil surface temperature, therefore, the revised Gc-TSEB requires no soil moisture as input. We tested Gc-TSEB at 10 flux sites under various land cover and climate conditions. The flux-calibrated Gc-TSEB performed well in ET predictions, with determinant coefficients (R2) larger than 0.9 at most of the sites. The modeled transpiration was highly correlated with the Gross Primary Production, indicating the usefulness of the model in ET partitioning. More importantly, Gc-TSEB can be calibrated against the land surface temperature (LST), which is operationally available using remote sensing technique. Overall, daily ET that was predicted by the LST-calibrated Gc-TSEB generally matched the trends of the ET measurements at most of the sites, and R2 range from 0.63 to 0.93, with a median of 0.80, at all sites. Transpiration estimation was highly consistent with the simulations from the flux-calibrated model. Moreover, in vegetated surfaces, soil evaporation was estimated reasonably well using the LST-calibrated Gc-TSEB. However, positive biases are prevalent when vegetated fraction is smaller than 0.2, especially in cold regions because of the dramatic differences in evaporation process between summer and winter. To improve model performances, calibrating Gc-TSEB model in separated periods and using prior knowledge as constraints proved to be useful.

Estimating Soil Evaporation Using Drying Rates Determined from Satellite-Based Soil Moisture Records

We describe an approach (ESMAP; Evaporation–Soil Moisture Active Passive) to estimate direct evaporation from soil, Esoil, by combining remotely-sensed soil drying rates with model calculations of the vertical fluxes in and out of the surface soil layer. Improved knowledge of Esoil can serve as a constraint in how total evapotranspiration is partitioned. The soil drying rates used here are based on SMAP data, but the method could be applied to data from other sensors. We present results corresponding to ten SMAP pixels in North America to evaluate the method. The ESMAP method was applied to intervals between successive SMAP overpasses with limited precipitation (&lt;2 mm) to avoid uncertainty associated with precipitation, infiltration, and runoff. We used the Hydrus 1-D model to calculate the flux of water across the bottom boundary of the 0 to 50 mm soil layer sensed by SMAP, qbot. During dry intervals, qbot typically transfers water upwards into the surface soil layer from below, usually &lt;0.5 mm day−1. Based on a standard formulation, transpiration from the surface soil layer, ET_s, is usually &lt; 0.1 mm day−1, and, thus, generally not an important flux. Soil drying rates (converted to equivalent water thickness) are typically between 0 and 1 mm day−1. Evaporation is almost always greater than soil drying rates because qbot is typically a source of water to the surface soil and ET_s is negligible. Evaporation is typically between 0 and 1.5 mm day−1, with the highest values following rainfall. Soil evaporation summed over SMAP overpass intervals with precipitation &lt;2 mm (60% of days) accounts for 15% of total precipitation. If evaporation rates are similar during overpasses with substantial precipitation, then the total evaporation flux would account for ~25% of precipitation. ESMAP could be used over spatially continuous domains to provide constraints on Esoil, but model-based Esoil would be required during intervals with substantial precipitation.

Testing three approaches to estimate soil evaporation through a dry soil layer in a semi-arid area

Bare soils and grasslands in arid and semi-arid conditions constitute a large portion of the earth surface. Evaporation, which is the main component of the water balance in these conditions, often takes place through a dry soil layer (DSL). There is no scientific agreement yet on the DSL effects on evaporation rates.The implementations of three conceptual models of DSL-evaporation were tested for the simulation of evaporation rates in a semi-arid study area in Central Spain: (i) the daily-average model, based on the assumption that the daily average vapour transport in a DSL can be represented in analogy to isothermal liquid flow; (ii) the numerical model solving the Richards equation, in this case HYDRUS1D was used; and (iii) the pore-scale model, based on soil column experiments in laboratory conditions. The evaporation rates estimated by the three conceptual models for semi-arid field conditions were compared with the evaporation rates measured by an eddy covariance tower in the same area.The results indicate that the daily-average conceptual model assumption, in which the DSL has no effects on evaporation, does not hold in very dry conditions. The numerical model solving the Richards equation was not able to simulate the effects of the DSL on evaporation rates. The evaporation estimates obtained by the pore-scale conceptual model were closest to the eddy covariance measurements during the dry season, however this model was applicable only to the relatively steady evaporation conditions during afternoons and only assuming spatially constant DSL thickness.

Sensitivity of Evapotranspiration Components in Remote Sensing-Based Models

Accurately estimating evapotranspiration (ET) at large spatial scales is essential to our understanding of land-atmosphere coupling and the surface balance of water and energy. Comparisons between remote sensing-based ET models are difficult due to diversity in model formulation, parametrization and data requirements. The constituent components of ET have been shown to deviate substantially among models as well as between models and field estimates. This study analyses the sensitivity of three global ET remote sensing models in an attempt to isolate the error associated with forcing uncertainty and reveal the underlying variables driving the model components. We examine the transpiration, soil evaporation, interception and total ET estimates of the Penman-Monteith model from the Moderate Resolution Imaging Spectroradiometer (PM-MOD), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL) and the Global Land Evaporation Amsterdam Model (GLEAM) at 42 sites where ET components have been measured using field techniques. We analyse the sensitivity of the models based on the uncertainty of the input variables and as a function of the raw value of the variables themselves. We find that, at 10% added uncertainty levels, the total ET estimates from PT-JPL, PM-MOD and GLEAM are most sensitive to Normalized Difference Vegetation Index (NDVI) (%RMSD = 100.0), relative humidity (%RMSD = 122.3) and net radiation (%RMSD = 7.49), respectively. Consistently, systemic bias introduced by forcing uncertainty in the component estimates is mitigated when components are aggregated to a total ET estimate. These results suggest that slight changes to forcing may result in outsized variation in ET partitioning and relatively smaller changes to the total ET estimates. Our results help to explain why model estimates of total ET perform relatively well despite large inter-model divergence in the individual ET component estimates.

Evaluation of TSEB turbulent fluxes using different methods for the retrieval of soil and canopy component temperatures from UAV thermal and multispectral imagery.

The thermal-based Two-Source Energy Balance (TSEB) model partitions the evapotranspiration (ET) and energy fluxes from vegetation and soil components providing the capability for estimating soil evaporation (E) and canopy transpiration (T). However, it is crucial for ET partitioning to retrieve reliable estimates of canopy and soil temperatures and net radiation, as the latter determines the available energy for water and heat exchange from soil and canopy sources. These two factors become especially relevant in row crops with wide spacing and strongly clumped vegetation such as vineyards and orchards. To better understand these effects, very high spatial resolution remote-sensing data from an unmanned aerial vehicle were collected over vineyards in California, as part of the Grape Remote sensing and Atmospheric Profile and Evapotranspiration eXperiment and used in four different TSEB approaches to estimate the component soil and canopy temperatures, and ET partitioning between soil and canopy. Two approaches rely on the use of composite T rad, and assume initially that the canopy transpires at the Priestley-Taylor potential rate. The other two algorithms are based on the contextual relationship between optical and thermal imagery partition T rad into soil and canopy component temperatures, which are then used to drive the TSEB without requiring a priori assumptions regarding initial canopy transpiration rate. The results showed that a simple contextual algorithm based on the inverse relationship of a vegetation index and T rad to derive soil and canopy temperatures yielded the closest agreement with flux tower measurements. The utility in very high-resolution remote-sensing data for estimating ET and E and T partitioning at the canopy level is also discussed.

Dynamics of crop coefficients for citrus orchards of central India using water balance and eddy covariance flux partition techniques

Accurate quantification of crop water demand and characterizing its temporal variability is essential in evaluating the role of water saving strategies for sustainable production. Representing evapotranspiration (ET) as a proxy to crop water needs is often misleading, particularly during the periods of high non-stomatal exchanges. This study is aimed at modeling crop water requirements for citrus orchards of central India using single and dual crop coefficient approaches. ET fluxes derived from eddy-covariance (EC) technique were used to develop single crop coefficient (Kc) curves at daily, weekly, and seasonal scales. Site-specific Kc values for initial, mid, and late season were found to be 0.43, 0.78, and 0.80 respectively. ET partitioning was done by estimating soil evaporation coefficient (Ke), and basal crop coefficient in the presence of water stress (Ks×Kcb) using soil-water balance (SIMDualKc) and EC flux partitioning (EC FP) methods. SIMDualKc model was calibrated against electrical resistivity tomography (ERT) derived soil water contents (R2 = 0.81, RMSE = 0.021 cm3 cm−3). Energy based flux partitioning was done by considering the correlation between high-frequency water vapour and carbon fluxes and applying flux variance similarity principles. Direct measurement of evaporation (E) and transpiration (T) at four citrus trees (using micro-lysimeters and sap flow meters) was used to assess the performance of two models. Three-stage basal crop coefficients from SIMDualKc and EC FP methods were found to be 0.18, 0.57, 0.63 and 0.26, 0.51, 0.59 respectively. Both methods were effectively partitioning the ET fluxes at daily scale (R2 > 0.5, RMSE < 0.6 mm, NSE > 0.3), however, variability in estimated fluxes between the two methods is high during the initial stage and gradually diminished with time.

Partitioning of evapotranspiration in remote sensing-based models

Satellite based retrievals of evapotranspiration (ET) are widely used for assessments of global and regional scale surface fluxes. However, the partitioning of the estimated ET between soil evaporation, transpiration, and canopy interception regularly shows strong divergence between models, and to date, remains largely unvalidated. To examine this problem, this paper considers three algorithms: the Penman-Monteith model from the Moderate Resolution Imaging Spectroradiometer (PM-MODIS), the Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), and the Global Land Evaporation Amsterdam Model (GLEAM). Surface flux estimates from these three models, obtained via the WACMOS-ET initiative, are compared against a comprehensive collection of field studies, spanning a wide range of climates and land cover types. Overall, we find errors between estimates of field and remote sensing-based soil evaporation (RMSD = 90–114%, r2 = 0.14–0.25, N = 35), interception (RMSD = 62–181%, r2 = 0.39–0.85, N = 13), and transpiration (RMSD = 54–114%, r2 = 0.33–0.55, N = 35) are relatively large compared to the combined estimates of total ET (RMSD = 35–49%, r2 = 0.61–0.75, N = 35). Errors in modeled ET components are compared between land cover types, field methods, and precipitation regimes. Modeled estimates of soil evaporation were found to have significant deviations from observed values across all three models, while the characterization of vegetation effects also influences errors in all three components. Improvements in these estimates, and other satellite based partitioning estimates are likely to lead to better understanding of the movement of water through the soil-plant-water continuum.

Estimation of bare soil evaporation for different depths of water table in the wind-blown sand area of the Ordos Basin, China

Soil surface evaporation is a significant component of the hydrological cycle, occurring at the interface between the atmosphere and vadose zone, but it is affected by factors such as groundwater level, soil properties, solar radiation and others. In order to understand the soil evaporation characteristics in arid regions, a field experiment was conducted in the Ordos Basin, central China, and high accuracy sensors of soil moisture, moisture potential and temperature were installed in three field soil profiles with water-table depths (WTDs) of about 0.4, 1.4 and 2.2 m. Soil-surface-evaporation values were estimated by observed data combined with Darcy’s law. Results showed that: (1) soil-surface-evaporation rate is linked to moisture content and it is also affected by air temperature. When there is sufficient moisture in the soil profile, soil evaporation increases with rising air temperature. For a WTD larger than the height of capillary rise, the soil evaporation is related to soil moisture content, and when air temperature is above 25 °C, the soil moisture content reduces quickly and the evaporation rate lowers; (2) phreatic water contributes to soil surface evaporation under conditions in which the WTD is within the capillary fringe. This indicates that phreatic water would not participate in soil evaporation for a WTD larger than the height of capillary rise. This finding developed further the understanding of phreatic evaporation, and this study provides valuable information on recognized soil evaporation processes in the arid environment.

Evaluation of variable rate irrigation using a remote-sensing-based model

Improvements in soil water balance modeling can be beneficial for optimizing irrigation management to account for spatial variability in soil properties and evapotranspiration (ET). A remote-sensing-based ET and water balance model was tested for irrigation management in an experiment at two University of Nebraska-Lincoln research sites located near Mead and Brule, Nebraska. Both fields included a center pivot equipped with variable rate irrigation (VRI). The study included maize in 2015 and 2016 and soybean in 2016 at Mead, and maize in 2016 at Brule, for a total of 210 plot-years. Four irrigation treatments were applied at Mead, including: VRI based on a remote sensing model (VRI-RS); VRI based on neutron probe soil water content measurement (VRI-NP); uniform irrigation based on neutron probe measurement; and rainfed. Only the VRI-RS and uniform treatments were applied at Brule. Landsat 7 and 8 imagery were used for model input. In 2015, the remote sensing model included reflectance-based crop coefficients for ET estimation in the water balance. In 2016, a hybrid component of the model was activated, which included energy-balance-modeled ET as an input. Both 2015 and 2016 had above-average precipitation at Mead; subsequently, irrigation amounts were relatively low. Seasonal irrigation was greatest for the VRI-RS treatment in all cases because of drift in the water balance model. This was likely caused by excessive soil evaporation estimates. Irrigation application for the VRI-NP at Mead was about 0 mm, 6 mm, and –12 mm less in separate analyses than for the uniform treatment. Irrigation for the VRI-RS was about 40 mm, 50 mm, and –98 mm greater in separate analyses than the uniform at Mead and about 18 mm greater at Brule. For maize at Mead, treatment effects were primarily limited to hydrologic responses (e.g., ET), with differences in yield generally attributed to random error. Rainfed soybean yields were greater than VRI-RS yields, which may have been related to yield loss from lodging, perhaps due to over-irrigation. Regarding the magnitude of spatial variability in the fields, soil available water capacity generally ranked above ET, precipitation, and yield. Future research should include increased cloud-free imagery frequency, incorporation of soil water content measurements into the model, and improved wet soil evaporation and drainage estimates.