Ecovoltaic solar energy development effects to microclimate, temperature, and soil moisture in panel array interspaces in a warm desert.

天山北坡积雪消融对不同冻融阶段土壤温湿度的影响

It is of great significance to clarify the influence of soil temperature and moisture on soil respiration rate and its characteristics in ecologically fragile regions under the background of climate change for the accurate assessment and prediction of carbon budgets in this region. The average CO2 concentration and soil temperature and moisture at different soil depths (10, 50, and 100 cm) were measured using a CO2 analyzer and temperature and moisture sensors. The soil respiration rate was calculated using Fick's first diffusion coefficient method. The dynamic characteristics of soil temperature, soil moisture, and soil respiration rate in different soil depths were explored, and the response of soil respiration rate to soil temperature and moisture were further analyzed. The results showed that the diurnal variation in soil respiration rate decreased significantly with the increase in soil depth (P<0.05), and the peak time lagged behind. Soil respiration rate in adjacent soil depths (10, 50, and 100 cm) lagged 1 h from top to bottom. The monthly variation in soil respiration rate was a multi-peak curve, in which the maximum soil respiration rates of 10, 50, and 100 cm soil depths were on July 25th, August 6th, and August 10th, reaching 13.96, 2.96, and 1.47 μmol·(m2·s)-1, respectively. The effect of soil temperature on soil respiration rate decreased with the increase in soil depth. Soil temperature at 50 cm and below had no significant effect on soil respiration rate (P>0.05). The fitting index of 10 cm soil depth was the best (R2=0.96), but the fitting indexes of 50 cm and 100 cm soil depths were poor (R2=0.00 and R2=0.01, respectively). The temperature sensitivity coefficient Q10 decreased with the increase in soil depth. Soil moisture in different soil depths had significant effects on soil respiration rate (P<0.05), and the quadratic fitting indicated that 50 cm (R2=0.35)>10 cm (R2=0.22)>100 cm (R2=0.31). The combined effects of soil temperature and moisture in different soil depths could explain 96%, 6%-50%, and 22%-24% of soil respiration rate, respectively. In summary, the effects of soil temperature and moisture at different soil depths of the Caragana korshinskii plantation in the loess-hilly region on soil respiration rate differed. The soil respiration rate of the 10 cm soil depth was affected by the comprehensive effect of soil temperature and moisture; however, the relative contribution of soil temperature was higher, and soil moisture at and below a soil depth of 50 cm was the key factor. These results could help improve predictions on the impact of future climate change on the carbon cycle of terrestrial ecosystems in the region and provide a theoretical basis for greenhouse gas regulation in the future.

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.

Soil moisture is not only an essential component of the water cycle in terrestrial ecosystems but also a major influencing factor of regional climate. In the soil hydrothermal process, soil moisture has a significant regulating effect on surface temperature; it can drive surface temperature change by influencing the soil’s physical properties and the partitioning of the available surface energy. However, limited soil temperature and moisture observations restrict the previous studies of soil hydrothermal processes, and few models focus on estimating the impact of soil moisture on soil temperature. Therefore, based on the experiments conducted in Wuchuan County in 2020, this study proposes a soil water and heat coupling model that includes radiation, evaporation, soil water transport, soil heat conduction and ground temperature coupling modules to simulate the soil temperature and moisture and subsequently estimate the effects of soil moisture. The results show that the model performs well. The Nash–Sutcliffe coefficient (NSE) and the concordance index (C) of the simulated and measured values under each treatment are higher than 0.26 and 0.7, respectively. The RMSE of the simulation results is between 0.0067–0.017 kg kg−1 (soil moisture) and 0.43–1.06 °C (soil temperature), respectively. The simulated values matched well with the actual values. The soil moisture had a noticeable regulatory effect on the soil temperature change, the soil surface temperature would increase by 0.08–0.43 °C for every 1% decrease in soil moisture, and with the increase in soil moisture, the variation of the soil temperature decreased. Due to the changes in the solar radiation, the sensitivity of the soil temperature to the decline in soil moisture was the greatest during June–July and the least in September. Moreover, the contributions of soil moisture changes to temperature increase under various initial conditions are inconsistent, the increase in sunshine hours, initial daily average temperature and decrease in leaf area index (LAI), soil density and soil heat capacity can increase the soil surface temperature. The results are expected to provide insights for exploring the impact mechanism of regional climate change and optimizing the structure of agricultural production.

Simulations of pre- and post-harvest soil temperature, soil moisture, and snowpack for jack pine: comparison with field observations

番茄、玉米套种膜下滴灌条件下农田地温变化特征试验研究

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.

Respiration rate of moss-dominated biocrusts and their relationships with temperature and moisture in a semiarid ecosystem

Forest ecosystems in northeastern China play an important role in both local and national carbon budgets because of their large area extent and huge amount of carbon storage. The spatial and temporal changes in soil surface CO_2 flux (R_S), the major CO_2 source to the atmosphere from terrestrial ecosystems, directly influence the local and regional carbon budgets. However, few data on R_S were available for this region. In this study, we used an infrared gas exchange analyzer (LI_COR 6400) to measure the R_S and related biophysical factors, and examined soil temperature and moisture effects on soil respiration for six secondary temperate forest ecosystem types: Mongolian oak (dominated by Quercus mongolica), poplar_birch (dominated by Populus davidiana and Betula platyphylla), mixed_wood (no dominant tree species), hard_wood forests (dominated by Fraxinus mandshurica, Juglans mandshurica and Phellodendron amurense), Korean pine (Pinus koraiensis) and Dahurian larch (Larix gmelinii) plantations. Our specific objectives were to: 1) compare the soil temperature, soil moisture, R_S, and Q_ 10 (temperature coefficient) of the six forest types; 2) quantify the seasonality of R_S and related environmental factors; and 3) determine the environmental factors affecting the R_S, and construct models of R_S against the related environmental factors. Soil temperature, soil moisture and their interactions significantly (p 0.01) influenced the R_S, but their effects depended on forest type and soil depth. These factors could explain 67.5%-90.6% of the variations in the R_S data. During the growing season, the soil temperature at 10 cm depth in the different forest types did not differ significantly but soil moisture did. The R_S for the oak, pine, larch, hardwood, mixed_wood, and poplar_birch stands varied from 1.89-5.23, 1.09-4.66, 0.95-3.52, 1.13-5.97, 1.05-6.58, and 1.11-5.76 μmol CO_2·m~ -2 ·s~ -1 , respectively; the Q_ 10 values for those stands were 2.32, 2.76, 2.57, 2.94, 3.55 and 3.54, correspondingly. The seasonality of R_S was driven mainly by soil temperature and moisture, and was roughly consistent with that of soil temperature. The broad_leaved forests had a higher soil respiration rate than those of coniferous forests probably because of a more suitable soil thermal and moisture regimes and other biological factors. The temperature sensitivity coefficient of soil respiration (Q_ 10 ) showed a convex_type curve along a soil moisture gradient. The Q_ 10 tended to increase when soil moisture increased from 30.19 to 40.7, and then declined probably because the extremely high soil moisture content in the hardwood forest may impede activities of soil microbes and plant roots, and thus decrease decomposition rates and soil CO_2 emission. Our study strongly recommended that estimation of soil surface CO_2 flux from forest ecosystems should consider the comprehensive effects of both soil temperature and moisture on soil respiration so as to reduce uncertainties of ecosystem carbon budget studies in this region.

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 &lt; 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 &lt; 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.

Soil temperature and moisture are important initial conditions in weather and climate models. Owing to the sparsity of observations, surface and subsurface soil temperature and moisture are usually generated using land-surface models (LSMs). Hence, it is important to test the performance of LSMs in predicting these parameters. In the present study, the simulation skill of the three-dimensional Noah LSM is evaluated with respect to soil temperature and moisture at two sites in India, Kharagpur and Ranchi. The model-simulated soil temperature and soil moisture are compared with site observations for a period of 2 years, 2009–2010, at both sites. Soil moisture is reasonably well simulated by the model at all depths and at all time scales in both these sites, showing a dry bias in the monsoon and a wet bias in spring and winter. Soil temperature is usually over-predicted by the model except in the monsoon. It appears that the model has a slower infiltration rate and higher evaporation rate than the actual values.

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.

The comprehensive evaluation of model- and satellite-based surface soil temperature (ST) products is a prerequisite for applications of these datasets in hydrology, ecology, and climate change, as well as in passive microwave soil moisture retrieval algorithms. Distinguished from existing regional validations, this study used ground soil temperature observations of approximately 800 stations from 5 sparse and 15 dense networks worldwide to fully assess six model- and satellite-based surface ST products from April 2015 to December 2017. The products consist of five model-based ST from the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Goddard Earth Observing System Model version 5 Forward Processing (GEOS-5 FP), the Global Land Data Assimilation System (GLDAS) Noah, the ERA-Interim and the newly released ERA5 produced by the European Centre for Medium Range Weather Forecasts (ECMWF), and one satellite-based ST retrieved from the Advanced Microwave Scanning Radiometer 2 (AMSR2) by using the Land Parameter Retrieval Model (LPRM). The accuracy of these products was comprehensively assessed per availability of ground networks, soil temperature interval, soil moisture interval, land cover, climate zone, and elevation. The results show that the GEOS-5 exhibits the smallest averaged unbiased root mean square difference (ubRMSD) of 1.84 K among all the surface ST products. All model-based products show a high skill in capturing the temporal trend of ground observations with an averaged correlation coefficient larger than 0.97. The ERA5 surface ST obtains visible improvements compared to its predecessor ERA-Interim by showing smaller ubRMSD and absolute bias values. All model-based surface ST products generally show lower values than ground ST, while their bias tends to be warmer as soil temperature and soil moisture increase except for the highest temperature and moisture conditions. Moreover, unstable performance of most model-based products in shrubland and grassland, tropical, arid and cold climate, and high elevation regions is also demonstrated by larger ubRMSD values. The averaged ubRMSD of the satellite-based LPRM ST is 3.04 K, and more attentions should be paid to the impacts of elevations and underlying surfaces on improving this product. These new findings will be valuable for future refinement of ST datasets, algorithms used to estimate soil moisture from satellite data, and applications in various disciplines.

The rate of carbon (C) cycling in soils is controlled by an array of processes and conditions. It has been widely accepted that an increase in temperature would accelerate microbial decomposition of soil organic matter (SOM) and provide a positive feedback to global warming, other factors being equal. However, soil moisture has received little attention in C cycle studies. In this project, we developed a technique for sampling soil‐respired CO2 for isotopic measurements and a model that relates the radiocarbon (14C) content of soil respired CO2 to the rate of C cycling in soils. We measured soil CO2 flux, carbon isotopic content (both 13C and 14C) of soil‐respired CO2, soil temperature, and soil moisture on a monthly basis along an elevation transect in the Sierra Nevada in an attempt to determine the relationship between the rate of soil C cycling and soil environmental conditions. Both soil CO2 flux and its 14C content displayed significant variations (spatially and temporally), which reflect natural variations in the rate of SOM decomposition and in the relative amount of SOM‐derived CO2 versus root‐respired CO2 caused by seasonal changes in soil temperature, moisture, and plant activity. The relative contribution of SOM decomposition to total soil CO2 production changed throughout the year from ∼20–50% at the peak of the growing season to close to 100% in the nongrowing season. The apparent decay rate of SOM determined from the 14C content of soil‐respired CO2 varied from ∼0.2 yr−1 in the spring to ∼0.01 yr−1 in the fall at the lowest‐elevation site and from 0.1 yr−1 in the summer to ∼0.01 yr−1 in the late fall at the highest‐elevation site. It appears that the apparent decay rate of SOM increased with increasing temperature when soil moisture was adequate but decreased with increasing temperature when soil moisture became limited. The apparent decay rate of SOM also varied with soil moisture. Higher soil moisture content accelerated decomposition of SOM until it reached an optimal level of ∼14–25 wt % water content and then inhibited decomposition when more pores in soils became saturated with water and perhaps oxygen availability (for microbes) became limited. Although the rate of SOM decomposition varied throughout the year in response to fluctuations in soil temperature and moisture, the maximum apparent decay rate was higher at the low‐elevation site (i.e., maximum apparent decay rate = 0.22 yr−1) than at the high‐elevation sites (i.e., maximum apparent decay rate = 0.10 yr−1). Litter decomposition simulated by measuring changes in mass of litter in litter bags placed in the field also showed a similar decomposition pattern with decreasing decomposition rate with elevation. Multivariable regression analyses including various terms of soil temperature, moisture, and site variability suggest that soil moisture was a major factor, but not the only factor, controlling the rate of SOM decomposition and soil CO2 flux in the Sierra Nevada soils. Both decay rate and total soil CO2 flux are related significantly to soil moisture, temperature, and site effects.

Core Ideas Tillage practices on surface soil temperature in the winter months were tested. No‐till soil responses slowly to changes of air temperature than tilled soil. Soil temperatures in winter were significantly greater in no‐till than tilled soils. Soil temperature affects soil microbial activity and hence impacts soil greenhouse gas (CO 2 , N 2 O, CH 4 ) emissions and plant nutrient recycling. However, there is a lack of information on the effects of tillage practices on soil temperature in the surface soil layers in the winter months. Soil temperature and moisture in no‐tillage (NT) and fall moldboard plow (MP) of a Brookston clay loam in southwestern Ontario were measured on an hourly basis over the winter months (December to April) at soil depths (25, 75, and 150 mm) during 2012 to 2013, 2013 to 2014 and 2014 to 2015, respectively. Both soil temperature and moisture significantly varied with tillage practices over the winter months. The tillage and depth interaction occurred for soil moisture, but not soil temperature. Soil temperatures in December and January were significantly greater (+0.7°C) in NT than MP soil with a maximum divergence of 2 to 4°C in the 25‐mm depth for 4 to 5 d in January. In March and April, the soil temperature was about 0.7°C cooler for the NT than the MP soil. The soils were generally wetter in the NT than the MP plots and the difference was statistically significant from December to February. In general, the soil was warmer and wetter under NT than MP management in winter months for this clay loam soil whereas soils were cooler and wetter under no‐tillage in the spring.