Changes in Terrestrial Evaporation across Poland over the Past Four Decades Dominated by Increases in Summer Months

Given the importance of terrestrial evaporation (ET) for the water cycle, a fundamental understanding of the water quantity involved in this process is required. As recent observations reveal a widespread ET intensification across the world, it is important to evaluate regional ET variability. The specific objectives of this study are the following: (1) to assess annual and monthly ET trends across Poland, and (2) to reveal seasons and regions with significant ET changes. This study uses the ET estimates acquired from the Global Land Evaporation Amsterdam Model (GLEAM) dataset allowing for multi-year analysis (1980–2020). The Mann–Kendall test and the Sen’s slope were applied to estimate the significance and magnitude of the trends. The results show that a rising temperature, along with small precipitation increase, led to the accelerated ET of 1.36 mm/y. This was revealed by increased transpiration and interception loss not compensated by a decrease in bare soil evaporation and sublimation. The wide-spread higher water consumption especially occurred during the summer months of June, July, and August. Comparing the two subperiods of 1980–2020, it was found that in 2007–2020, the annual ET increased by 7% compared to the reference period of 1980–2006. These results can serve as an important reference for formulating a water resources management strategy in Poland.

Influence of calibration period length on predictions of evaporation

<p>Bare soil evaporation is a key component of the soil water balance. Accurate estimation of evaporation is thus critical for sustainable water resources management, especially in arid and semi-arid regions. Numerical models are widely used for estimating bare soil evaporation. Although models allow exploring evaporation dynamics under different hydrological and climatic conditions, their robustness is linked to the reliability of the imposed parameters. These parameters are typically obtained through model calibration. Even if a perfect match between observed and simulated variables is obtained, the predictions are not necessarily reliable. This can be related to model structural errors, or because the inverse problem is ill-posed. While this is conceptually very well known, it remains unclear how the temporal resolution and length of the employed observations for the calibration influence the reliability of the parameters and the predictions.</p><p>We used data from a lysimeter experiment in the Guanzhong Basin, China to systematically explore the influence of the calibration period length on the calibrated parameters and uncertainty of evaporation predictions. Soil water content dynamics and water level were monitored every 5 minutes. We set up twelve models using the fully coupled, physically-based HydroGeoSphere model with different calibration period lengths (one month, three months, six months, fourteen months). The estimated evaporation rates by the models for the calibration period and validation period were compared with the measured evaporation rates. Also, we predict cumulative, one-year evaporation rates. The uncertainty of the predictive evaporation by these models from different calibration lengths is quantified. Several key conclusions can be drawn as follows: (1) The extinction depth is a very important parameter for the soil water content dynamics in the vadose zone but is poorly informed unless the calibration includes significantly different depths to groundwater. (2) Using the longer calibration period length (six months or fourteen months) did not necessarily result in more reliable predictions of evaporation rates. (3) Preliminary results indicate that the uncertainty can be reduced if the calibration period includes both climatic forcing similar to the prediction, but additionally also feature similar water table conditions during calibration and prediction. Our results have implications for reducing uncertainty using unsaturated-saturated models to predict evaporation.</p>

Observations and modeling of evapotranspiration and dewfall during the 2018 meteorological drought in southern England

A meteorological drought in 2018 led to senescence of the C3 grass at Cardington, Bedfordshire, UK. Observations of near-surface atmospheric variables and soil moisture are compared to simulations by the JULES land surface model (LSM) as used for Met Office forecasts. In years without drought, JULES provides better standalone simulations of evapotranspiration (ET) and soil moisture when the canopy height and rooting depth are reduced to match local conditions. During drought with the adjusted configuration, JULES correctly estimates total ET, but the components are in the wrong proportions. Several factors affect the estimation of ET including modeled skin temperatures, dewfall and bare-soil evaporation. A diurnal range of skin temperatures close to observed is produced via the adjusted configuration and doubling the optical extinction coefficient. Although modeled ET during drought matches observed ET, this includes simulation of transpiration but in reality the grass was senescent. Excluding transpiration, the modeled bare-soil evaporation underestimates the observed midday latent heat flux. Part of the missing latent heat may relate to inappropriate parameterization of hydraulic properties of dry soils and part may be due to insufficient evaporation of dew. Dew meters indicate dewfall of up to 20 W m−2 during drought when the surface is cooling radiatively and turbulence is minimal. These data demonstrate that eddy-covariance techniques fail to reliably record the times, intensity and variations in negative latent heat flux. Furthermore, the parameterization of atmospheric turbulence as used in LSMs fails to represent accurately dewfall during calm conditions when the surface is radiatively cooled.

Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites

Plant activity in semi-arid ecosystems is largely controlled by pulses of precipitation, making them particularly vulnerable to increased aridity that is expected with climate change. Simple bucket-model hydrology schemes in land surface models (LSMs) have had limited ability in accurately capturing semi-arid water stores and fluxes. Recent, more complex, LSM hydrology models have not been widely evaluated against semi-arid ecosystem in situ data. We hypothesize that the failure of older LSM versions to represent evapotranspiration, ET, in arid lands is because simple bucket models do not capture realistic fluctuations in upper-layer soil moisture. We therefore predict that including a discretized soil hydrology scheme based on a mechanistic description of moisture diffusion will result in an improvement in model ET when compared to data because the temporal variability of upper-layer soil moisture content better corresponds to that of precipitation inputs. To test this prediction, we compared ORCHIDEE LSM simulations from (1) a simple conceptual 2-layer bucket scheme with fixed hydraulic parameters and (2) an 11-layer discretized mechanistic scheme of moisture diffusion in unsaturated soil based on Richards equations, against daily and monthly soil moisture and ET observations, together with data-derived estimates of transpiration / evapotranspiration, T∕ET, ratios, from six semi-arid grass, shrub, and forest sites in the south-western USA. The 11-layer scheme also has modified calculations of surface runoff, water limitation, and resistance to bare soil evaporation, E, to be compatible with the more complex hydrology configuration. To diagnose remaining discrepancies in the 11-layer model, we tested two further configurations: (i) the addition of a term that captures bare soil evaporation resistance to dry soil; and (ii) reduced bare soil fractional vegetation cover. We found that the more mechanistic 11-layer model results in a better representation of the daily and monthly ET observations. We show that, as predicted, this is because of improved simulation of soil moisture in the upper layers of soil (top ∼ 10 cm). Some discrepancies between observed and modelled soil moisture and ET may allow us to prioritize future model development and the collection of additional data. Biases in winter and spring soil moisture at the forest sites could be explained by inaccurate soil moisture data during periods of soil freezing and/or underestimated snow forcing data. Although ET is generally well captured by the 11-layer model, modelled T∕ET ratios were generally lower than estimated values across all sites, particularly during the monsoon season. Adding a soil resistance term generally decreased simulated bare soil evaporation, E, and increased soil moisture content, thus increasing transpiration, T, and reducing the negative bias between modelled and estimated monsoon T∕ET ratios. This negative bias could also be accounted for at the low-elevation sites by decreasing the model bare soil fraction, thus increasing the amount of transpiring leaf area. However, adding the bare soil resistance term and decreasing the bare soil fraction both degraded the model fit to ET observations. Furthermore, remaining discrepancies in the timing of the transition from minimum T∕ET ratios during the hot, dry May–June period to high values at the start of the monsoon in July–August may also point towards incorrect modelling of leaf phenology and vegetation growth in response to monsoon rains. We conclude that a discretized soil hydrology scheme and associated developments improve estimates of ET by allowing the modelled upper-layer soil moisture to more closely match the pulse precipitation dynamics of these semi-arid ecosystems; however, the partitioning of T from E is not solved by this modification alone.

A bench-scale assessment of the effect of soil temperature on bare soil evaporation in winter

To quantitatively evaluate in the laboratory the effect of soil temperature on bare soil evaporation, this study uses two indoor soil columns and homogenized sand as an example to carry out the experimental study of soil temperature on bare soil evaporation in winter. The results show that the soil temperature directly affects the change in bare soil evaporation and that the effect decreases as the soil temperature decreases. Because of the influence of soil temperature, the soil water movement accelerates, and the soil water content increases. At a depth of 50 cm, the average difference in soil water content between groups A and B was 7.61%. The soil evaporation when considering the soil temperature was obviously greater than that without considering the soil temperature. This shows that in a laboratory environment where the soil temperature is higher than the room temperature in winter, the effect of the soil temperature on bare soil evaporation is significant. Soil temperature directly affects soil water movement and distribution, which is one of the important influencing factors affecting bare soil evaporation.

Improving the Processes in the Land Surface Scheme TERRA: Bare Soil Evaporation and Skin Temperature

Newly improved formulations of the bare soil evaporation and the surface temperature are presented, using the multilayer land surface scheme TERRA of the Consortium for Small-scale Modeling (COSMO) atmospheric model. The simulations were carried out in offline mode with atmospheric forcing data from the Meteorological Observatory Lindenberg–Richard-Aßmann-Observatory of the German Meteorological Service. The results show that the bare soil evaporation simulated by the reference version of TERRA is substantially overestimated under wet conditions, and underestimated under dry conditions. Furthermore, the amplitude of the diurnal cycle of the surface temperature is systematically underestimated. In contrast, the diurnal cycles of the temperatures in the soil are overestimated instead. The new description of the bare soil evaporation in TERRA is based on a resistance formulation analogue to Ohm’s law, while the surface temperature is now based on the skin temperature formulation by Viterbo and Beljaars. The new formulation improves the simulated bare soil evaporation substantially. In particular, the overestimation under wet conditions is reduced, also acting against an extensive drying of the soil during the annual cycle. Additionally, the underestimation under dry conditions is reduced as well. Furthermore, the simulated amplitude of the diurnal cycle of the surface temperature is substantially increased. In particular, a nocturnal warm bias is systematically reduced. In addition to this, the new formulations were also applied in coupled mode in the COSMO model, resulting in improved diurnal cycles of near-surface temperature and dew point.

Evaporation over saturated bare soil: the role of soil texture

<p>Calculating actual bare soil evaporation (ET<sub>a</sub>) on the basis of potential bare soil evaporation (PE) is a widely followed approach in many disciplines including hydrogeology, hydrology and agricultural sciences. This approach considers that PE is independent from soil properties, and only ET<sub>a</sub> is affected by soil properties. In this work, in a unique experiment, seasonal and diurnal cycles of PE over saturated bare soil were assessed for lysimeters installed in the Guanzhong Basin, China. The assessment was made for different soil textures including gravel (PE<sub>g</sub><sub>ravel</sub>), coarse sand (PE<sub>c</sub><sub>oarse</sub>) and fine sand (PE<sub>f</sub><sub>ine</sub>) and also open water (PE<sub>w</sub><sub>ater</sub>). Meteorological variables, ground heat flux and soil temperature were captured at a high temporal resolution (5 min.) for more than 15 consecutive months. The daily evaporation rates over saturated bare soil (PE<sub>s</sub><sub>oil</sub>) showed clear differences between gravel, coarse sand and fine sand, with higher PE for fine sand, smaller PE for coarse sand and smallest PE for gravel, during spring and summer. In addition, PE<sub>w</sub><sub>ater</sub> was smaller than PE for the saturated bare soil lysimeters. In autumn and winter, the measured PE rates over different surfaces showed only minor differences. The measurement data also revealed that during spring and summer night-time PE was considerable with ~1.0 mm ET per night. These results can be quantitatively explained with detailed calculations of the energy balance, considering the different porosities for gravel, coarse sand and fine sand, as well as the thermal conductivities of the phases which constitute the porous media. </p>