Soil climate in classification systems: advantages and disadvantages

The dataset presented in this article is related to the work “Evaluation and Analysis of SMAP, AMSR2, and MEaSUREs Freeze/Thaw Products in China [1]”. Soil moisture and temperature are important variables of land-atmosphere energy exchange, monitoring vegetation growth, predicting drought disasters and climate and hydrological modelling [2–6]. This work provides detailed information on in situ soil moisture and temperature data network established in the Genhe watershed and Saihanba area in China, respectively. The Genhe watershed represents the complex surface heterogeneity in Northeast China. Therefore, data from 22 in situ sites were established in the Genhe watershed since March 2016 to improve the dynamic analysis and modeling of remotely sensed information for complex land surfaces. Saihanba is currently China's largest manmade forest and has a unique alpine wetland and a complete aquatic ecosystem. There are 29 in situ sites deployed in Saihanba since August 2018 for studying the cold temperate continental monsoon climate and estimating forest carbon storage capacity and carbon emissions from manmade forests. Soil temperature and permittivity data in the network were measured using ECH2O EC-5TM probes (Decagon Devices, Inc., Washington, USA, https://www.metergroup.com/) and XingShiTu (XST) probes (BEIJING XST Co., Ltd., www.xingshitu.com) every 30 min at depths of 3, 5, and 10 cm for the Genhe watershed continuous automatic observation network, and depths of 5 and 10 cm for the Saihanba continuous automatic observation network. In the Genhe watershed, soil moisture and soil temperature data in the network were automatically collected using the EM50 data collection system. The Saihanba area has the XST data collection system to record soil temperature and permittivity. The permittivity data collected with the XST data collector were transformed to soil moisture data (volumetric water content) based on the formula developed by [7]. The datasets of the Genhe watershed and Saihanba area consist of raw data acquired by the data collector and processed data of soil moisture and temperature. The Saihanba dataset also includes the calibration data based on soil texture. The result of temporal variations analysis in observed data in the Genhe Watershed and the processing in observed data in the saihanba area show that the long-term in situ soil moisture and temperature datasets can be used for the validation/calibration and improvement of the soil moisture and soil freeze/thaw algorithm.

The temperature, moisture, and salt content of soil in alpine regions are sensitive to changes in climatic factors and are important indicators of ecosystem functions. In this study, we collected soil moisture, temperature and electrical conductivity data at different depths at a sampling site on Bird Island in Qinghai Lake during winter using a continuous soil temperature, moisture and salt content monitoring system and analyzed their variations and influential factors. The variation in soil moisture showed an obvious ‘V-shaped’ pattern from 00:00 to 23:00 and an upward trend with soil layer depth. From 00:00 to 23:00, the overall soil temperature data fitted a ‘unimodal’ curve and showed a clear and continuous upward trend with soil layer depth at a rate of 0.684 (p < 0.001). Soil electrical conductivity data also exhibited a distinct ‘V-shaped’ pattern from 00:00 to 23:00 and a continuous increase with increasing soil depth. The correlation between soil temperature, moisture, and conductivity and the spatial distribution of five climate factors indicated that climate factors accounted for 53.6% of the changes in soil temperature, moisture, and salinity. Climate factors showed a significant positive correlation with soil temperature, moisture, and conductivity (p < 0.001), and air temperature was the most important factor influencing soil temperature and soil moisture changes, whereas wind direction was the most important factor influencing soil conductivity. (Wind direction and wind speed affect soil evapotranspiration, and then affect soil moisture and solute transport process). The results of this preliminary study reveal the characteristics associated with soil temperature, moisture, and salinity changes in winter within the wetlands of Bird Island on Qinghai Lake in the context of climate change, and they can be used as valuable reference data in further studies investigating associated changes in ecosystem functions.

PDF HTML阅读 XML下载 导出引用 引用提醒 天山北坡积雪消融对不同冻融阶段土壤温湿度的影响 DOI: 10.5846/stxb201901040044 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 自治区重点实验室课题(2018D04024);国家自然科学基金项目(U1603342,41961002) The influence of snowmelt on soil temperature and moisture in different freezing-thawing stages on the north slope of Tianshan mountain Author: Affiliation: Fund Project: The National Natural Science Foundation of China (General Program, Key Program, Major Research Plan) 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:积雪作为一种特殊的覆被,直接影响着土壤温度、土壤水分分布及其冻结深度、冻结速率等,影响当地的生态水文过程。利用2017年11月1日至2018年3月31日天山北坡伊犁阿热都拜流域的土壤含水率资料,划分土壤不同冻融阶段,结合积雪不同阶段,进而分析积雪消融对季节性冻土温湿度的影响。结果表明:在整个土壤冻融期间,土壤温湿度的变化取决于积雪深度、大气温度和雪面温度的高低,且与其稳定性有关。土壤冻结阶段,土壤温湿度持续下降,表层土壤温湿度受气温影响较大,且波动明显,而深层土壤的温湿度变化平缓;土壤完全冻结时,有稳定积雪覆盖,由于积雪的高反射性、低导热性,影响着地气之间的热量传递,因此土壤的温湿度变化较为平稳,积雪有一定的保温作用;冻土消融阶段,气温回升,积雪消融,地表出露,各层土壤温度随气温变化而变化,且越靠近地表,土壤温度越高,变幅越大,与冻结期完全相反。由于融雪水的下渗,土壤湿度快速增加。进一步分析积雪与土壤温湿度的相关性得出,积雪对土壤温湿度的影响分不同时期,对土壤温度的影响主要在积雪覆盖时,对土壤湿度的影响主要是在积雪消融时期,这对于研究该地生态水文循环及后续融雪性洪水的模拟与预报具有一定的参考价值。 Abstract:As a special cover, snow cover directly affects soil temperature, soil moisture distribution, freezing depth and freezing rate, and affects the local eco-hydrological processes. The existence of snow can affect the frozen soil, the interaction of surface-atmosphere, and change the energy exchange and temperature transfer between the soil and the atmosphere. The freezing-thawing process of soil has an important impact on soil water content. It is of great significance for the effective utilization of frozen soil resources, the guidance of irrigation water, the study of soil evaporation, groundwater recharge and local eco-hydrological cycle. In this paper, meteorological data, soil temperature and moisture data and snow cover data were used to analyze the characteristics of seasonal frozen soil temperature and moisture changes in the study area. Based on the data of soil water content from November 1, 2017 to March 31, 2018 in the Alatobe Basin, Ili, on the northern slope of Tianshan Mountains, the different freezing-thawing stages of soil were divided, and the effects of snow melting on the temperature and moisture of seasonal frozen soil were analyzed. The results show that snow melting has a great influence on the temperature and moisture of seasonal frozen soil. The soil was frozen beginning in November in Alatobe Basin, and the soil freezing time lagged with the increase of soil depth. The soil freezing process is one-way, starting from the surface, while the melting process is two-way, starting from both the surface and the bottom. During the whole freezing-thawing period, the change of soil temperature and moisture depends on the depth of snow cover, atmospheric temperature and snow surface temperature. And it mainly affects the surface soil temperature. The deeper the soil depth is, the more slightly the change of soil temperature and moisture is. During the soil freezing stage, the soil temperature and moisture continued to decline, the surface soil temperature and moisture were greatly affected by temperature, and the fluctuation was obvious, while the deep soil temperature and moisture changed slightly. When the soil was completely frozen, there was stable snow cover. Because the high reflectivity and low thermal conductivity of snow affected the heat transfer of surface-atmosphere, the change of soil temperature and moisture was relatively stable, and the snow cover had a certain degree. During the thawing stage, the temperature rises, the snow melts and the surface exposes. The soil temperature varies with the change of temperature. The closer to the surface, the higher the soil temperature, the larger the change range, which is completely contrary to the freezing period. Soil moisture increases rapidly due to the infiltration of snowmelt water. Further analysis of the correlation between snow cover and soil temperature and moisture shows that the influence of snow cover on soil temperature and moisture can be divided into different periods. The influence on soil temperature is mainly in snow cover, and the influence on soil moisture is mainly in snow melting period, which has a certain reference value for the study of the eco-hydrology cycle and the simulation and prediction of subsequent snowmelt flood in this area. 参考文献 相似文献 引证文献

Physico‐biochemical processes occurring in soil are difficult to predict because the knowledge of local soil properties such as soil moisture and temperature is often limited. Therefore, soil moisture and temperature regime classes are necessary for US soil taxonomy and other classification systems. The goal of this study is to develop a modeling tool to predict soil moisture and temperature at multiple soil horizons and to code the Keys to Soil Taxonomy in a Soil Moisture and Temperature Regime Classification (SMTRC) module for automatic identification of soil moisture and temperature regimes. The Environmental Policy Integrated Climate (EPIC) model was extended as the EPIC–SMTRC tool for this purpose. Field data from the Soil Climate Analysis Network (SCAN) sites and the Wye farm site in Maryland for validation of soil moisture and temperature predictions. Results indicate that predicted daily soil temperatures are in close agreement with observed values with R2 values ranging from 0.73 to 0.98 and Nash–Sutcliffe efficiency (NSE) from 0.50 to 0.96. Predicted soil moisture by EPIC–SMTRC captured observed trends reasonably well. Testing results at the Wye farm indicate that the predicted daily values of water content are satisfactory, with R2 values ranges from 0.66 to 0.88 and NSE from 0.51 to 0.84. The EPIC–SMTRC tool demonstrated the ability to automate the identification of the soil moisture and temperature regimes as currently defined in the US soil taxonomy and can be used to classify soils and to be utilized for other sites.

Soil temperature and moisture are important factors affecting vegetation growth and drought in desert steppe environments. These factors also strongly influence grassland ecosystems. This study interpreted long-term (2009–2019) ground observation data on soil temperature, soil moisture, and meteorological factors from a study area in Inner Mongolia. The monitoring station collected soil moisture, soil temperature, and precipitation data. Covarying relationships indicated how soil properties influence each other throughout the year. Soil temperature was clearly affected by atmospheric changes, solar radiation, and freeze/thaw processes. The surface soil layers showed the greatest degree of variation, while middle and lower layers showed less seasonal variation and smaller differences between daily highs and lows. Surface soil moisture correlates strongly with the vertical temperature decline in soil. Time series revealed major variation in soil moisture throughout the year with lower soil layers showing obvious hysteresis effects. Multi-year soil moisture data allowed for subdivision of the year into seven intervals based maximum and minimum values. Soil temperature showed unique patterns of covariation with soil moisture during different time periods. Differences in soil moisture cause more rapid changes in temperature during soil thawing relative the moisture-induced temperature changes observed 1 month after soil freezing. When soil temperature was greater than 0 °C (32 ℉), soil temperature and soil moisture showed inverse correlation. A dependency of evapotranspiration on soil temperature can explain its effect on soil moisture. When soil temperature fell below 0 °C(32 ℉), soil temperature and soil moisture showed a positive correlation. During an interval defined as the summer fluctuation (SF), precipitation and soil moisture showed a significant positive correlation. During other periods, soil moisture did not clearly covary with precipitation.

Soil moisture and temperature conditions play an important role in plant growth. Modeling soil moisture and temperature is useful for predicting crop yields and risks. In this study, the Soil Temperature and Moisture Model (STM2) was used to predict soil moisture and temperature at several depths: 15, 30, 45, and 60 cm for soil moisture and 10, 25, and 50 cm for soil temperature. The objective of this study was to assess the prediction efficiency of STM2 according to soil depth and phenology. The STM2 uses soil texture data along with average daily weather data (maximum and minimum air temperature and precipitation) as inputs. During the 2008 and 2010 growing seasons, soil moisture and temperature data were measured using monitoring stations located in four agricultural fields in southern Quebec. These fields represent the range of soil texture diversity found in this agricultural area: gravelly, sandy, loamy, and clayey soils. The measurements were used to validate STM2 predictions. The overall performance of soil temperature prediction was better than that for soil moisture. Estimation quality decreased with increasing depth and was higher during the first and third phenological periods for soil moisture. Good performances were observed for the sandy and loamy soils, moderate for the clayey soil, and mostly weak for the gravelly soil. A sensitivity analysis was performed on STM2 data inputs. For soil moisture, bulk density, saturated hydraulic conductivity, and weather data have a great impact while for soil temperature, only weather data have an impact on model estimates. This study showed that STM2 can be used in combination with soil and climatic data sets to reliably predict surface soil moisture and temperature variations in southern Quebec.

Summary In Nordic regions water infiltration into soil is controlled by soil moisture content and frozen soil conditions, which are regulated by soil temperature. For long‐term model predictions of the effects of climate change, models need to be tested with long‐term data to assess model sensitivity to parameter uncertainties under both typical and exceptional conditions. Ten‐year (2002–2011) daily soil moisture and temperature data at different depths in glacial till soils in central Finland were used to assess the sensitivity of a coupled heat and water transfer model, COUP, to model parameters. The model was most sensitive to the parameters controlling snow accumulation and melt, the thermal conductivity of frozen soil and soil water retention characteristics. Observed time series for soil temperature and moisture at different depths were matched reasonably well by model simulations, although the model performance with respect to moisture dynamics in the topsoil was relatively poor. The model was not able to simulate accurately exceptional winter conditions, such as mid‐winter snowmelt events. This study showed that the main characteristics of long‐term variation in soil temperature for till‐derived soil in a cold climate can be resolved by a coupled water and heat transport model. Better characterization of infiltration in cold climates would require measurement of water fluxes, and soil frost occurrence and penetration. Highlights Ten‐year soil temperature and moisture observations are predicted with coupled heat and water model. Snow processes and soil thermal and water retention properties proved critical in our simulations. Exceptional winter conditions pose a challenge in parameterization of the model. Studies measuring water fluxes and soil frost occurrence are needed for advances in modelling.

Soil moisture and temperature are key factors of land production and hydrological dynamics. Estimating soil temperature and moisture content is essential to learning land surface-atmosphere interactions and is an essential component of the water-energy cycle. This study examines the correlation between soil moisture and soil temperature across two land uses (bare and vegetation) at different depths (0–5 cm, 5–15 cm, 15–30 cm, and 30–45 cm) during the dry period (September). Statistical analysis, including mean, standard deviation (SD), and coefficient of variation (CV), was performed to assess the variability of soil moisture. The results show that the coefficient of variation (CV) was lower in bare soil compared to vegetative soil and decreased with depth in both land use, suggesting that upper layers have more spatial and temporal variability than lower. Soil moisture was lower in the higher layers and increased with depth, with vegetative soil continuously holding greater moisture than bare ground at all depths. In contrast, soil temperature exhibited an inverse correlation with soil moisture. A regression study was conducted to forecast soil moisture with soil temperature data, illustrating the efficacy of temperature-based models for moisture estimates. These findings highlight soil-water interactions across various land covers, which are crucial for sustainable land and water management.

Soil temperature and soil moisture data from sixty-six monitoring sites located in forest ecosystems of western Montana and northern Idaho were summarized. These data were analyzed in comparison to the criteria for soil temperature and soil moisture regimes (U.S.D.A.- Soil Taxonomy, Soils Staff, 1975). The hypothesis that climax forest communities (habitat types) occupy sites with characteristic soil temperature and moisture conditions was tested. The soil temperature and soil moisture status throughout the growing season for fifty-two monitoring sites was analyzed in respect to their climax forest series and habitat type class. The results of the analysis demonstrate that some forest habitat types of northern Idaho and western Montana occupy sites with a narrow range of soil temperature and soil moisture conditions; where as other habitat types have variable soil temperature and soil moisture conditions. The monitored soil temperature and soil moisture data were displayed for nineteen forest habitat types. Several relationships between climax forest vegetation, soil temperature regimes and soil moisture regimes were identified, for western Montana and northern Idaho. The Abies Iasiocarpa climax forest series monitoring sites classify primarily in the cryic soil temperature regime. The Thuja plicata, Abies grandis, and Pseudotsuga menziesii climax forest series monitoring sites classify primarily in the frigid soil temperature regime. In western Montana all the Abies lasiocarpa, Thuja plicata, and Abies grandis climax forest series monitoring sites classify in the udic soil moisture regime. The Pseudotsuga menziesii climax forest series monitoring sites classify in either a udic or a xeric soil moisture regime. It was concluded that a field soil scientist in western Montana or northern Idaho could estimate the soil temperature regime by knowing the climax forest series and elevation of a site. Discriminant analysis was applied to thirty-four monitoring sites representing six habitat types. The probability of the membership in a habitat type being correctly predicted by the site characteristics alone (i.e. average soil temperature, average soil moisture tension, and elevation) was eighty-six percent.

Abstract. Permafrost has great influences on the climatic, hydrological, and ecological systems on the Qinghai–Tibet Plateau (QTP). The changing permafrost and its impact have been attracting great attention worldwide like never before. More observational and modeling approaches are needed to promote an understanding of permafrost thermal state and climatic conditions on the QTP. However, limited data on the permafrost thermal state and climate background have been sporadically reported in different pieces of literature due to the difficulties of accessing and working in this region where the weather is severe, environmental conditions are harsh, and the topographic and morphological features are complex. From the 1990s, we began to establish a permafrost monitoring network on the QTP. Meteorological variables were measured by automatic meteorological systems. The soil temperature and moisture data were collected from an integrated observation system in the active layer. Deep ground temperature (GT) was observed from boreholes. In this study, a comprehensive dataset consisting of long-term meteorological, GT, soil moisture, and soil temperature data was compiled after quality control from an integrated, distributed, and multiscale observation network in the permafrost regions of QTP. The dataset is helpful for scientists with multiple study fields (i.e., climate, cryospheric, ecology and hydrology, meteorology science), which will significantly promote the verification, development, and improvement of hydrological models, land surface process models, and climate models on the QTP. The datasets are available from the National Tibetan Plateau/Third Pole Environment Data Center (https://data.tpdc.ac.cn/en/disallow/789e838e-16ac-4539-bb7e-906217305a1d/, last access: 24 August 2021, https://doi.org/10.11888/Geocry.tpdc.271107, Lin et al., 2021).

Historically, the NSM has been used to aid U.S. Soil Survey research by providing categorical output for soil moisture and temperature regimes. Terminology for soil moisture regimes includes categories such as Udic, Aridic, Ustic, Xeric, and Aquic, which indicate varying levels of seasonal or annual moisture conditions (Soil Survey Staff, 1999). In order to provide classifications for particular soils the NSM populates a calendar of soil moisture and temperature status for the calendar days of a year or set of years of interest. The NSM can provide monthly and annual summaries of soil climate status, modeled at the depth of the taxonomic soil moisture control section of U.S. Soil1 INTRODUCTIONThe Newhall Simulation Model (NSM) has been used by the U.S. Soil Survey and in international soil mapping efforts for more than 50 years (Smith, 1982; Newhall and Berdanier, 1996; Waltman et al., 2012). NSM provides categorical output useful in U.S. Soil Taxonomy, is simple and flexible and does not require extensive model inputs. For inputs it uses monthly air temperature and precipitation values, elevation, a programmable offset between annual air temperature and annual soil temperature, and available water holding capacity of soils. The purpose of the NSM is to classify soils according to their dominant soil moisture and temperature properties based on rudimentary estimates of evapotranspiration, drainage, and the effects of air temperature and precipitation on soil moisture and soil temperature characteristics. While the modelTaxonomy, including soil climate variables such as cumulative days in a year the soil is dry, or partly moist and partly dry, or moist, or dry and above 5°C, or partly moist partly dry and above 5°C, or moist and above 5°C; the consecutive days in a year that the soil is moist, or above 8°C and moist; and finally the consecutive days in the summer that a soil is dry or the consecutive days in the winter that the soil is moist. These outputs are needed in order to classify soils in the U.S. Soil Taxonomic system (Soil Survey Staff, 1999).

Soil temperature and moisture influence soil respiration at a range of temporal and spatial scales. Although soil temperature and moisture may be seasonally correlated, intra and inter-annual variations in soil moisture do occur. There are few direct observations of the influence of local variation in species composition or other stand/site characteristics on seasonal and annual variations in soil moisture, and on cumulative annual soil carbon release. Soil climate and soil respiration from twelve sites in five different forest types were monitored over a 2-year period (1998–1999). Also measured were stand age, species composition, basal area, litter inputs, total above-ground wood production, leaf area index, forest floor mass, coarse and fine root mass, forest floor carbon and nitrogen concentration, root carbon and nitrogen concentration, soil carbon and nitrogen concentration, coarse fraction mass and volume, and soil texture. General soil respiration models were developed using soil temperature, daily soil moisture, and various site/soil characteristics. Of the site/soil characteristics, above-ground production, soil texture, roots + forest floor mass, roots + forest floor carbon:nitrogen, and soil carbon:nitrogen were significant predictors of soil respiration when used alone in respiration models; all of these site variables were weakly to moderately correlated with mean site soil moisture. Daily soil climate data were used to estimate the annual release of carbon (C) from soil respiration for the period 1998–1999. Mean annual soil temperature did not differ between the 2 years but mean annual soil moisture was approximately 9% lower in 1998 due to a summer drought. Soil C respired during 1998 ranged from 8.57 to 11.43 Mg C ha−1 yr−1 while the same sites released 10.13 and 13.57 Mg C ha−1 yr−1 in 1999; inter-annual differences of 15.41 and 15.73%, respectively. Among the 12 sites studied, we calculated that the depression of soil respiration linked to the drought caused annual differences of soil respiration from 11.00 to 15.78%. Annual estimates of respired soil C decreased with increasing site mean soil moisture. Similarly, the difference of respired carbon between the drought and the non-drought years generally decreased with increasing site mean soil moisture.

We examined the spatial and seasonal variation of Q10 as an indicator of the temperature sensitivity of soil respiration based on field measurements at a young ponderosa pine plantation in the Sierra Nevada Mountains in California. We measured soil CO2 efflux and soil temperature and moisture in two 20 m × 20 m plots from June 1998 to August 1999. The Q10 values calculated from soil temperature at 10‐cm depth ranged spatially from 1.21 to 2.63 among 18 chamber locations in the plots. Seasonally, the Q10 values calculated on the basis of the average soil CO2 efflux and temperature (10 cm) across the sites could vary from 1.05 to 2.3. Q10 and soil temperature are negatively correlated through a simple linear relationship with R2 values of 0.45, 0.40, and 0.54 for soil temperature at 5−, 10−, and 20−cm depth, respectively. However, Q10 and soil moisture are positively correlated with R2 values of 0.81, 0.86, and 0.51 for soil temperature at 5−, 10−, and 20−cm depth, respectively. Q10 values derived from temperatures at different soil depths also showed considerable variation along the vertical dimension. Q10 had a large seasonal variation with the annual minimum occurring in midsummer and the annual maximum occurring in winter. Seasonal values of Q10 depended closely on both soil temperature and moisture. Soil temperature and moisture explained 93% of the seasonal variation in Q10. The spatial variation of Q10 had significant influences on the estimation of soil CO2 efflux of the ecosystem. These variations tended to affect the seasonality of the soil CO2 efflux more than the annual average. The variations of Q10 and its dependence on soil moisture and temperature have important implications for regional and global ecosystem carbon modeling, in particular for predicting the responses of terrestrial ecosystems to future global warming.

In this study we attempted to determine if vine maple priority gaps show similar trends in temperature and moisture status to those reported in the literature for treefall gaps and whether temperature and moisture status differed between microtopographic positions (pits and mounds). Biweekly measurements of mid-day soil and air temperature, moisture contents at 30-, 50- and 80-cm depths, and depths to the groundwater table were made in pit and mound locations within six vine maple priority gaps paired with six conifer canopy sites. Trends did not follow those found in treefall gaps: vine maple gaps had similar mid-day temperature and moisture status to the surrounding conifer forest. Larger gaps had higher mid-day air temperatures in the summer, higher mid-day soil temperatures in the spring and summer, and greater amounts of throughfall in the spring and summer than smaller gaps. Trends in mid-day soil temperature and moisture status for pit and mound microtopography followed those reported in the literature. Pits were significantly cooler in summer and warmer in winter than mounds and pits were wetter than mounds in all seasons. This study suggests that soil microtopography has an effect on soil climate that overwhelms the influence of vine maple gaps. Key words: Vine maple, canopy gap, soil moisture, soil temperature, microtopography, pits and mounds

In this study, we analyzed the potential of distributed soil temperature and soil moisture observations for identifying the spatiotemporal variability of near‐surface water and energy fluxes. We studied the soil energy balance using soil moisture and temperature data collected during the Second Microwave Water and Energy Balance Experiment (MicroWEX‐2) in Florida. We found that heat transfer in the shallow subsurface could not be explained by conduction. Sinks and sources of energy in each soil layer were quantified using an inversion approach to the heat diffusion equation. We investigated the extent to which the sinks and sources could be explained by advection and phase change. From our analysis, it seems that, for dry days, advection is a comparatively minor contributor to heat transfer and that phase change plays a more significant role. Yet vapor diffusion rates, required for sustaining phase changes and thus evaporation in the soil large enough to explain the sinks and sources, were beyond the plausible range. We concluded that soil moisture and temperature observations can yield quantitative information on the surface energy balance and heat partitioning. There is a lack of understanding of heat transfer in the shallow subsurface, however, that hampers the translation of soil temperature and moisture observations to water and energy fluxes.