Projections of future soil temperature in the western part of the Southeastern Anatolia Project region, Türkiye

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.

Studying the effect of environmental factors on the variation of soil microbial respiration and its temperature sensitivity (Q10) at different time scales under field conditions is of great significance for accurately understanding the region's climate warming potential. From March 2008 to November 2013, in situ soil microbial respiration rates were determined using an automated CO2 flux system (Li~8100) in long-term bare fallow soil at the Changwu State Key Agro-Ecosystem Experimental Station, Shaanxi, China, for studying the effect of environmental factors on the variation of soil microbial respiration and Q10 at different time scales. At diurnal time scales, the daily variation of soil microbial respiration rates showed a single-peak curve, which was closely related to soil temperature (P<0.05); whereas the daily mean soil microbial respiration rate and Q10 varied with soil moisture, with both showing the order of moderate soil moisture conditions > higher soil moisture conditions > lower soil moisture conditions[daily mean soil microbial respiration rate:1.20 μmol·(m2·s)-1 vs. 0.95 μmol·(m2·s)-1 vs. 0.79 μmol·(m2·s)-1; Q10:2.12 vs. 1.93 vs. 1.59]. At seasonal time scales, both the seasonal mean soil microbial respiration rate and Q10 showed the order of rainy season > non-rainy season[seasonal mean soil microbial respiration rate:1.11 μmol·(m2·s)-1vs. 0.90 μmol·(m2·s)-1; Q10:1.96 vs. 1.59], which was consistent with the trend of soil temperature and moisture (soil temperature:20.39 vs. 14.50℃; soil moisture:49.2% vs. 38.6%). The bivariate model of soil temperature and soil moisture could explain the greater seasonal variability of the soil microbial respiration rate than did the univariate model of soil temperature or soil moisture (R2:0.45-0.82 vs. 0.32-0.67 vs. 0.35-0.86; the fitting coefficient between the simulated and measured soil microbial respiration rates:0.76 vs. 0.64 vs. 0.58). At annual time scales, the annual cumulative soil microbial respiration ranged from 226 to 298 g·(m2·a)-1, with an average of 253 g·(m2·a)-1, and the annual Q10 ranged from 1.48 to 1.94, with an average of 1.70. The annual cumulative soil microbial respiration and Q10 showed a negative quadratic correlation with annual mean soil moisture (P<0.05), with the annual mean soil moisture explaining 39% and 54% of the annual variability of annual cumulative soil microbial respiration and Q10, respectively. In the bare soil treatment, the soil organic carbon decreased from 6.5 g·kg-1 at the beginning of the experiment to 5.5 g·kg-1 at present; whereas, the annual cumulative soil microbial respiration was up to 255 g·(m2·a)-1 and the loss of annual cumulative soil microbial respiration was 20 times larger than the loss of soil organic carbon in the Loess Plateau region, China.

Projections of future soil temperature in northeast Iran

This study aimed to explore soil respiration in response to soil moisture and soil temperature subjected to different ridge/furrow ratios under various planting patterns. Traditional flat planting and three different ridge-furrow plantings with altering ridge/furrow ratios, i. e. 20:40 cm (P40); 30:30 cm (P30); 40:20 cm (P20), were performed in the present study. Soil respirations among different planting patterns were compared. Their relationships with soil moisture and soil temperature were also analyzed. The results showed that soil respiration flux of four planting patterns reached its minimum value during the wintering stage, started to rise during the returning green stage until it reached a peak value at the flowering stage, and decreased gradually when reaching the maturity stage. The magnitude of soil respiration flux in three ridge-furrow planting patterns followed this order: P40 > P30 > P20, which implied that increasing ridge width could improve soil respiration by 1.2%-18.4%. In addition, soil respiration fluxes of three ridge-furrow plantings patterns were significantly higher than those under conditional patterns during the seedling stage (P<0.05). The soil temperature of ridge-furrow planting patterns was higher than that of the conditional flat pattern from the seeding stage to the wintering stage, but was converse from the jointing stage to the maturity stage. Moreover, three ridge-furrow planting patterns have shown significant effect on preserving soil water storage in comparison with the conditional flat pattern. In general, increasing the width of the ridge increased soil water storage due to less rainfall from the seedling stage to the jointing stage. The correlation analysis indicated a positive and significant correlation coefficient between soil respiration and soil temperature (P<0.01). Correlation coefficients in case of P40 and P30 were higher than those in P20 and the conditional flat pattern. The quadratic model of two-factor soil moisture and soil temperature could explain 61.7%-74.1% of variations in soil respiration. The single factor of the soil temperature model could explain 50.3%-68.2% of variations in soil respiration. Those results could provide a theory basis for further evaluation of ecological effect on the ridge-furrow planting patterns.

Dynamics of soil respiration in Horqin semi-fixed dune and meadow wetland as a function of precipitation, temperature, and drought

Revealing the characteristics of soil moisture and temperature under typical sloping land uses in the loess hilly region is of great significance for the efficient and sustainable use of sloping land resources. In this study, the soil moisture content in the 0–160 cm soil layer and the soil temperature in the 0–100 cm soil layer under soybean sloping field, maize terraced field, jujube orchard, and grassland were continuously observed during the 2014 and 2015 growing seasons (May to October). Traditional statistical analysis and wavelet fractal dimension method were used to study the characteristics and complexity of soil moisture and temperature changes under different sloping land uses. The main findings are as follows: (1) Maize terraced field obtained high soil moisture content in the 0–160 cm soil layer, showing the outstanding effect of soil moisture conservation, especially in the drought growing season. Maize terraced field minimized the changing amplitude (Ka), variation degree (Cv), and active layer of soil moisture in the 0–160 cm soil layer and the Ka and Cv of soil temperature in the 0−100 cm soil layer. The maize terraced field had the minimum fractal dimensions of soil moisture and temperature both in normal precipitation and drought growing seasons, indicating that the maize terraced field minimized the complexity of soil moisture and temperature changes. (2) The jujube orchard obtained the minimum soil moisture content in the 0−160 cm soil layer, and greatly increased the Ka, Cv, and active layer of soil moisture both in normal precipitation and drought growing seasons. The jujube orchard obtained the maximum soil temperature in the 0–100 cm soil layer, and greatly increased the Ka and Cv of soil temperature. The jujube orchard also had the maximum fractal dimensions of soil moisture and temperature, indicating that soil moisture and temperature changes in jujube orchard were the most complex. (3) Compared to jujube orchard, soybean sloping field and grassland increased soil moisture content, reduced the Ka and Cv of soil moisture and temperature, and weakened the complexity of soil moisture and temperature changes. (4) The analysis results of the complexity of soil moisture and temperature changes under the experimental sloping land uses based on the wavelet fractal dimension method were consistent with the traditional statistical analysis results, indicating that it is feasible to evaluate the complexity of soil moisture and temperature changes under the typical sloping land uses in the loess hilly region by using wavelet fractal dimension method. In summary, terraced fields were conducive to improving soil moisture content and maintaining the stability of soil moisture and temperature. It is recommended that the project of changing sloping fields into terraced fields should be popularized in the loess hilly region to effectively utilize limited natural precipitation. In order to prevent the jujube orchard from degenerating and dying due to long-term drought and water shortage, effective water management measures need to be taken to achieve the sustainable development of dry farming jujube orchard.

NO fluxes from soils of a periodically flooded tropical savanna in southern Africa were investigated and modeled. In the laboratory, NO production rates, NO consumption rate constants, NO mixing ratios, relationships between NO emissions and soil temperature and moisture were determined for nutrient‐poor, nutrient‐rich savanna soils and a floodplain soil. The NO production rate and consumption rate constants of the floodplain soil (1.96 ng N s−1 per kilogram of soil and 2.04×10−5 m3 s−1 per kilogram of soil, respectively) were significantly higher than those of the savanna soils (average of 1.28 ng N s−1 per kilogram of soil and 1.47×10−5 m3 s−1 per kilogram of soil, respectively), but there were no significant difference between the nutrient‐rich and nutrient‐poor soils. NO flux rates increased exponentially with soil temperature. NO flux rates increased with soil moisture reaching a maximum near the field capacity (7.5–10% and 31.2% gravimetric water content for savanna and floodplain soils, respectively), after which the NO flux rate declined. These laboratory data were used in a model to estimate field NO flux rates, which were compared with actual field NO emission measurements. The NO model was modified to incorporate NO “pulsing” after the first rains of the season. Correlation between the modeled and field NO fluxes from the nutrient‐poor savanna, nutrient‐rich savanna, and the floodplain soils showed r2 values of 0.91, 0.82, and 0.74, respectively. The NO model was linked with a soil moisture and temperature model to predict annual NO emission estimates from savannas. Annual NO flux from the nutrient‐poor and nutrient‐rich savannas was estimated to be 0.16×10−3 and 0.14×10−3 kg N m−2 yr−1, respectively, which agree well with estimates from other savanna studies.

Parameterization, calibration and validation of the DNDC model for carbon dioxide, nitrous oxide and maize crop performance estimation in East Africa

Conversion of tropical forests to agricultural land uses is known to alter soil nitrogen (N) transformation processes and microbial biomass carbon (MB-C ), which affect productivity and stability of the derived land uses. Information about how conversion of moist evergreen forest to agricultural land uses affects soil nitrogen (N) transformation processes and MB-C in hot humid tropics is meager. The present study explores the following questions: (1) how does conversion of native moist evergreen forest to agricultural production systems (grassland, home garden and silvopasture) affect net soil N mineralization rates, pools of mineral nitrogen (NH4+- N and NO3-- N) and MB-C in the hot humid tropical climate of South Andaman, India and (2) are changes in soil N transformations and MB-C related to differences in soil moisture and temperature induced with forest conversion? Variations in net soil N mineralization, NH4+- N and NO3−- N pools, MB-C and soil temperature and moisture were measured across wet, post-wet and dry seasons at ten sites of each derived agricultural land use and native forest. In addition, inputs of carbon (C ) and N to the soils and outputs of C and N from the land use systems through harvests were also measured. We measured the N mineralization rate by the buried bag technique using 2 M KCl as an extractant. The NO3−- N and NH4+- N were measured at the beginning and end of incubation. The MB-C was measured by a chloroform fumigation-extraction method. We found that forest conversion resulted in a decline in carbon input, but caused rise in soil temperature (from 0.4 to 9.8% across the seasons) in derived agricultural land uses compared to native forest. The soil temperature increase was the highest in the grassland and lowest in the home garden. Across the three seasons, net soil N mineralization rates increased 27 to 55 % in the derived agricultural land uses compared to the native forest, with the increase highest in the grassland and lowest in the home garden. Soil organic C (SOC), MB-C, and NO3- declined in the derived agricultural land uses relative to native forest, with the greatest effect again seen in the grassland. These observations suggest that native forest conversion to agricultural uses results in lower soil organic C content over time, due to increased mineralization rates stimulated by a rise in soil temperature, and that these soil changes may be most pronounced in grasslands. Therefore, tree based land uses offer good options for soil carbon build up and protection against N loss in the hot humid tropics.

BackgroundBiochar is widely recognized for its capacity to capture and store carbon in soil attributed to its stable structure. However, in most field studies examining the effects of biochar application on soil respiration, the impact of rainfall events on the experimental outcomes has not been taken into account. To address the existing gap in this research field, we conducted a one-year study on soil respiration in an urban camphor forest and collected the data of soil respiration, soil temperature, soil moisture, and the rainfall events closest to the soil respiration monitoring time. We specifically examined how different stages of rainfall events influenced soil respiration in relation to biochar application.ResultsThis study found that the annual average soil respiration rate increased with the doses of biochar application, and the soil respiration rate under the biochar application at the dose of 45 t/ha showed a significant rise. The stages of rainfall events, rainfall amount, and the interaction effect of the two, and biochar doses significantly affected soil respiration. The parameters in the regression model for soil respiration, soil temperature and moisture varied with the different stages of rainfall events and the doses of biochar application. The biochar application eliminated the significant effect of soil moisture on soil respiration during one day after rainfall events. The significant correlation between soil moisture and the temperature sensitivity of soil respiration (Q10) was eliminated by biochar application, both during one day after rainfall events and more than eight days after rainfall events.ConclusionsOur findings indicated that the rice straw biochar application has a short-term positive effect on soil respiration in urban camphor forests. The rainfall events affect the field soil respiration monitored in the biochar applications, possibly by affecting the soil respiration response to soil temperature and moisture under different doses of biochar application. The impact of rainfall events on soil respiration in biochar application experiments should be considered in future forest monitoring management and practice.

Soil mulching and irrigation are critical practices for alleviating water scarcity and enhancing crop yields in arid and semi-arid regions by regulating soil moisture and soil temperature. Clarifying the effects of various irrigation depths on soil moisture and temperature under mulched condition is essential for optimizing irrigation strategies. This study investigated the effects of four irrigation depths based on crop evapotranspiration (ETc): 60, 80, 100, and 120% (W0.6, W0.8, W1.0, and W1.2, respectively) on the soil moisture content (SMC), soil temperature and seed cotton yield in mulched cotton fields. Results revealed that when the irrigation depth increased from 60%ETc to 120%ETc, seed cotton yield increased by 12.04% in 2018 and 17.00% in 2019 at the cost of irrigation water use efficiency (IWUE), which decreased from 2.53 kg m−3 to 1.54 kg m−3 in 2018 and 2.60 kg m−3 to 1.58 kg m−3 in 2019. Soil temperature exhibited a temporal trend of initial increase followed by decline, and it was positively affected by soil mulching. Notably, W0.6 treatment maintained significantly higher soil temperature than other treatments. Soil moisture content was positively affected by irrigation depth, while soil water storage first decreased and then increased over time, reaching the minimum at the flowering and boll setting stages during the two growing seasons. Higher irrigation amount reduced the total spatial variability (C0 + C) of soil but did not significantly alter the distribution characteristics of soil moisture, as indicated by stable coefficients of variation (CVs) and stratification ratios (SRs). The variability of soil moisture diminished with soil depth with the lowest CV obtained at a 60 cm soil layer across the growth stages. Correlation analysis results showed that the seed cotton yield was mainly affected by irrigation depth and soil water storage. Soil temperature at the flowering and boll setting stage negatively affected seed cotton yield and was inversely correlated with soil water storage. The structural equation model (SEM) further indicated that both soil water storage and soil temperature primarily influenced seed cotton yield boll weight rather than boll number. Furthermore, 100%ETc (W1.0) can be considered as the recommended irrigation depth based on the soil moisture and temperature, seed cotton yield and water use efficiency in this region.

A coupled force‐restore model of surface soil temperature and moisture (FRMEP) is formulated by incorporating the maximum entropy production model of surface heat fluxes and including the gravitational drainage term. The FRMEP model driven by surface net radiation and precipitation are independent of near‐surface atmospheric variables with reduced sensitivity to the uncertainties of model input and parameters compared to the classical force‐restore models (FRM). The FRMEP model was evaluated using observations from two field experiments with contrasting soil moisture conditions. The modeling errors of the FRMEP predicted surface temperature and soil moisture are lower than those of the classical FRMs forced by observed or bulk formula based surface heat fluxes (bias 1 ~ 2°C versus ~4°C, 0.02 m3 m−3 versus 0.05 m3 m−3). The diurnal variations of surface temperature, soil moisture, and surface heat fluxes are well captured by the FRMEP model measured by the high correlations between the model predictions and observations (r ≥ 0.84). Our analysis suggests that the drainage term cannot be neglected under wet soil condition. A 1 year simulation indicates that the FRMEP model captures the seasonal variation of surface temperature and soil moisture with bias less than 2°C and 0.01 m3 m−3 and correlation coefficients of 0.93 and 0.9 with observations, respectively.

A simulation model of soil moisture and heat flux, FroST (frozen soil temperatures) was developed and applied to field data for the BOREAS northern and southern study areas (NSA, SSA). FroST is a modification of another soil physics model (“Residue”) [Bidlake et al., 1982] to which simple representations of snow dynamics and transpiration, canopy, and litter properties were added. Simulations were run for the old jack pine and black spruce sites at the SSA and NSA. Predicted results showed good fit to measured data for snow depth and soil temperature at various depths at the old jack pine sites for which measured data were available for 1994. The presence of ice through the soil profile was also predicted, indicating a longer and deeper frozen period in the NSA and the development of permafrost at the NSA black spruce site. The model was sensitive to initial conditions of soil moisture and temperature and soil profile characteristics. With the availability of these data, estimates of temperature and moisture flux in soils over time can be predicted. Because the model relies on soil characterization data and yet represents fundamental physical processes, it can be readily extended to new conditions or a wider range of sites.

Soil enthalpy represents the land surface thermal states by combining soil moisture (sum of soil ice and liquid water) and soil temperature into a single variable. This study applied soil moisture and soil temperature outputs from off-line CLM4.0 model to calculate soil enthalpy from 1948 through 2010 and analyzed the contributions of the soil water and temperature to the trends of winter soil enthalpy in Eastern Northern Hemisphere. The results show that an increasing trend of winter soil enthalpy occurred during the period 1979-2010, especially in Eastern Europe (EE), Eastern Mongolia (EM), the India River Plain (IP) and Central Africa (CA). Overall, increases in soil enthalpy are primarily controlled by decreased soil ice over EE and EM and by increased soil temperature over IP, while the increased soil enthalpy over CA is mainly attributed to increases in soil liquid water and soil temperature, whose contributions are roughly equivalent. The roles of soil moisture and soil temperature in soil enthalpy changes exhibit evident regional differences and are generally latitude-dependent, with soil ice and soil temperature the dominant contributors at mid-high latitudes and mid-low latitudes, respectively. More importantly, when under the condition of soil water phase transition soil enthalpy may be served as a better metric to monitor the long-term trend of land surface thermal states than by using soil moisture or soil temperature alone. Therefore, our findings have important implications for soil enthalpy in climate change research (e.g., the impacts of land thermal anomalies on regional and even global climate).

Preventive control of desert locusts is based on monitoring recession areas to detect outbreaks. Remote sensing has been increasingly used in the preventive control strategy. Soil moisture is a major ecological driver of desert locust populations but is still missing in the current imagery toolkit for preventive management. By means of statistical analyses, combining field observations of locust presence/absence and soil moisture estimates at 1 km resolution from a disaggregation algorithm, we assess the potential of soil moisture to help preventive management of desert locust. We observe that a soil moisture dynamics increase of above 0.09 cm3/cm3 for 20 days followed by a decrease of soil moisture may increase the chance to observe locusts 70 days later. We estimate the gains in early warning timing compared to using imagery from vegetation to be 3 weeks. We demonstrate that forecasting errors may be reduced by the combination of several types of indicators such as soil moisture and vegetation index in a common statistical model forecasting locust presence. Policy implications. Soil moisture estimates at 1 km resolution should be used to plan desert locust surveys in preventive management. When soil moisture increases in a dry area of potential habitat for the desert locust, field surveys should be conducted two months later to evaluate the need of further preventive actions. Remote sensing estimates of soil moisture could also be used for other applications of integrated pest management.