Variability Of Soil Water Content Research Articles

Assessing soil water content variability through active heat distributed fiber optic temperature sensing

Soil spatial variability is a key point for the sustainable water management in agriculture. Fractal techniques provide proper tools to analyze soil spatial variability searching for statistical self-similarity patterns among different scales. Although they have been extensively applied to study the soil properties variability, its applicability for the soil water content (SWC) distribution is complicated because requires many data difficult to obtain with the typical point soil water sensors. Recently, a fiber optic distributed temperature sensor has been used to measure soil thermal properties which relate to SWC. These sensors provide large amount of data with high spatial and temporal resolution, thus filling the gap of point soil water sensors. In the present work, soil temperature was measured with a Distributed Temperature Sensing (DTS) and SWC was estimated by different fitting functions which have been studied with focus on spatial variability.Temperature was measured in a 133 m fiber optic cable laid in a sandy soil field plot. A The Active Heat Fiber Optic (AHFO) method was used, with 12 cm sampling resolution, and heat pulses (19,4 W/m during 2 min) were applied. The temperature data were correlated to SWC, considering the integration of temperature during the heat pulse Tcum, and then the datasets Tcum-SWC were fitted to the best fit statistical function (exponential, potential and polynomial). The results showed that the Tcum distribution presented a non-Gaussian pattern. Additionally, highly anti-persistent patterns have been detected for the larger spatial scaling lags. The function`s performance was different thus, the exponential function reproduced better the absolute moments of the temperature profile but it failed reproducing the non-Gaussian behavior.

Shallow groundwater effects on evaporation and soil temperature in two windblown sands (Eutric Cambisol and Chromic Luvisol) in South Africa

The aim of this study was to investigate the effect of shallow groundwater tables on soil surface evaporation and its effect on temperature distribution on two aeolian soils in South Africa, Clovelly (Eutric Cambisol) and Hutton (Chromic Luvisol) soil forms. The study was conducted at a lysimeter under semi-arid climatic conditions. A constant groundwater tables were created at different depths (0 mm, 500 mm, 1000 mm, 1500 mm and a No WT (no water table treatment as a control) and each of the lysimeters were equipped with a 1200 mm long DFM soil moisture probe to measure the profile water content and soil temperature at 6 depths along the profile (every 200 mm depth). The research site was also equipped with a movable shelter to prevent rain water dilution during rainfall events. Finally, evaporation is calculated by the water balance approach. The ANOVA showed that there was a highly significant difference (P < .01) in rate of evaporation from the water table depths and soil types. The minimum and maximum evaporation were recorded in the deepest and shallowest water table depths. The diurnal soil water content shows that the maximum water content in the two soil profiles was recorded in the early morning times (6:00) and the minimum was in the late afternoon times (between 16:00–17:00). The diurnal variation of soil water content also increased with decreasing water table depth. Regarding the soil temperature, the ANOVA showed that the soil temperature was influenced by the interaction between water table and measurement depths. Hence, the top five minimum soil temperatures were recorded in the shallower (≤500 mm) water tables and the top 5 maximums were recorded in the deeper water table depths (1000, 1500 and No WT). Generally, as the groundwater table depth increased from the surface down the profile, the rate of evaporation decreased resulting an increase in the variation of temperature with in the diurnal cycle.

A Novel Dielectric Tomography System for In-Situ Tracking Three-Dimensional Soil Water Dynamics.

In this study, we developed a novel dielectric tomography system for in-situ tracking three-dimensional (3D) soil water dynamics. The system was designed to control a single dielectric tube sensor that automatically lowered in a PVC tube array installed in-situ to determine the water content of a soil profile, which eliminated probe-to-probe uncertainties and labor costs. Two tests for evaluating the novel system were conducted (i) to analyze and correct the positional error of the probe due to out-of-step errors of stepper motors, and (ii) to track and visualize 3D soil water temporal variations in a soil tank with heterogenetic bulk densities and initial water contents under drip irrigation. The results show that the positioning correcting algorithm combined with starting point alignment can minimize the positioning error of the probe during the 3D tomography. The single drip emitter test illustrated spatial and temporal variations of soil water content due to heterogeneous soil properties in vertical and horizontal directions around the access tube array. Based on these data, 3D distributions of soil water dynamics were visualized. The developed tomography system has potential application to be extended to the local scale in a greenhouse or the large scale in an agricultural field. Future research should explore the performance for agricultural crop irrigation or for modeling and validating soil water flow or hydrological process under either steady state or non-steady state condition.

Soil aggregate stability improves greatly in response to soil water dynamics under natural rains in long-term organic fertilization

Soil structure in highly-weathered soils is adjusted by soil water content (SWC) under natural precipitation, and is also driven by the soil chemical properties. Such a relationship may be further dependent on types of fertilization. The objectives of this study were to investigate the effects of long-term fertilization (NPK, NPK + straw, manure, and control) after 17 continuous years on the SWC, temperature, aggregate stability, and the associated chemical properties (oxides, organic matter, and zeta potential), and to elucidate the relationship between SWC and aggregate. The aggregate stability (MWD), consecutive SWC, temperature, and chemical properties from 0 to 10 and 10 to 25 cm were measured during one year. Our results showed that the manure and NPK + straw treatments significantly improved the soil aggregate stability (P < 0.05) (e.g., average MWD 1.13 vs. 0.74 mm for manure vs. control at 0–10 cm) due to increase in the fraction of macroaggregate (>2 mm). The SWC values and degree of variation at the same time were also improved more in manure and NPK + straw treatments than others. Soil aggregate MWD was significantly negatively correlated the SWC at the moment of soil sampling (WC0) for all treatments. But the aggregates under two organic treatments was not significantly correlated with the antecedent SWC before half day and 4 days (WC0.5 and WC4), which indicated that the aggregates under manure and NPK + straw treatments were relatively stable when SWC changed before 0.5 and 4 days. The high stability of aggregates in the two organic-treated soils was also confirmed by very low relative slaking index values. The fertilization positive effect on soil aggregation to resist slaking was also attributed to the decline in soil clay zeta potential and improvement in soil OM and amorphous Fe oxides compared to control. The results suggest that long-term manure and NPK + straw application can improve aggregate stability and resistance to slaking under SWC variation whereas application of NPK only did not show such an effect.

Stratification response of soil water content during rainfall events under different rainfall patterns

AbstractMany researchers have studied the influence of rainfall patterns on soil water movement processes using rainfall simulation experiments. However, less attention has been paid to the influence under natural condition. In this paper, rainfall, soil water content (SWC), and soil temperature at 10‐, 20‐, 30‐, 40‐, and 50‐cm depths were simultaneously monitored at 1‐min intervals to measure the variation in SWC (SWCv) in response to rainfall under different rainfall patterns. First, we classified rainfall events into four patterns. During the study period, the main pattern was the advanced rainfall pattern (38% of all rainfall events), whereas the delayed, central, and uniform rainfall patterns had similar frequencies of about 20%. During natural rainfall, rainwater rapidly passed through the top soil layers (10–40 cm) and was accumulated in the bottom layer (50 cm). When a high rainfall pulse occurred, the water storage balance was disturbed, resulting in the drainage of initial soil water from the top layers into the deeper layers. Therefore, the critical function of the top layers and the bottom layers was infiltration and storage, respectively. The source of water stored in the bottom layer was not only rainfall but also the initial soil water in the upper soil layers. Changes in soil temperature at each soil depth were comonitored with SWCv to determine the movement characteristics of soil water under different rainfall patterns. Under the delayed rainfall pattern, preferential flows preferred to occur. Under the other rainfall patterns, matrix flow was the main form of soil water movement. Rainfall amount was a better indicator than rainfall intensity for SWCv in the bottom layer under the delayed rainfall pattern. These results provide insights into the responses of SWCv under different rainfall patterns in northern China.

Spatial and temporal variability of 0‐ to 5‐m soil–water storage at the watershed scale

AbstractDynamic relationships among rainfall patterns, soil water distribution, and plant growth are crucial for sustainable conservation of soil and water resources in water‐limited ecosystems. Spatial and temporal variation in deep soil water content at a watershed scale have not yet been characterized adequately due to the lack of deep soil water data. Deep soil–water storage (SWS) up to a depth of 5 m (n = 73) was measured at 19 sampling occasions at the LaoYeManQu watershed on the Chinese Loess Plateau (CLP). At a depth of 0–1.5 m, the annual mean SWS was highly correlated with rain intensity, and the correlation decreased with depth, but within the layers at 1.5–5.0 m, the changes in SWS indicated a lag between precipitation and the replenishment of soil water. Geostatistical parameters of SWS were also highly dependent on depth, and the mean SWS presented similar spatial structures in two adjacent layers. Temporal stability of SWS as indicated by mean relative difference, standard deviation of the relative difference (SDRD), and mean absolute bias error (MABE) was significantly weaker at the shallow than at deeper layers. Soil separates and organic carbon content controlled the spatial pattern of SWS at the watershed scale. One representative location (Site 57) was identified to estimate the mean SWS in the 1‐ to 5‐m layer of the watershed. Semivariograms of the SDRD and MABE were best fitted by an isotropic spherical model, and their spatial distributions were depth‐dependent. Both temporal stability and spatial variability of SWS increased over depth. This study is helpful for deep SWS estimation and sustainable management of soil and water on the CLP, and for other similar regions around the world.

High-resolution modelling of the grass swale response to runoff inflows with Mike SHE

The feasibility of simulating the hydrological response of a grass swale to runoff inflows was examined using the hydrological model Mike SHE and the available input data from 12 irrigation events mimicking runoff from block rainfalls. The test swale channel had a trapezoidal cross-section, bottom slope of 1.5%, length of 30 m, and was built in loamy fine sand. The irrigation events consisted in releasing two equal constant inflows to the swale: a concentrated longitudinal flow at the upstream end and a distributed lateral inflow along the swale side slope adjacent to the contributing drainage area. The total inflows approximated runoff from two events with return periods of 2 months and 3 years, respectively, for durations of 30 min. Irrigation experiments were done for two states of the initial soil moisture, dry or wet antecedent moisture conditions (AMC). Mike SHE has been extensively used on catchments of various sizes, but rarely for small stormwater management facilities and their detailed topography investigated in this study. The latter application required high spatial and temporal resolutions, with computational cells of 0.2 × 0.2 m and time steps as short as 0.6 s to avoid computational instabilities. For dominant hydrological processes, the following computational options in Mike SHE were chosen: Soil infiltration – the van Genuchten equation, unsaturated zone flow – the one-dimensional Richards equation, and overland flow – the diffusive wave approximation of the St. Venant equations. For study purposes, the model was calibrated for single events representing one of four combinations of low and high inflows, and dry and wet AMC, and then applied to the remaining 11 events. This was complemented by calibration for two events, representing high inflow on wet AMC and low inflow in dry AMC. The goodness of fit was statistically assessed for observed and simulated peak flows, hydrograph volumes, Nash-Sutcliffe model efficiencies (NSE), and soil water content (SWC) in swale soil layers. The best fit (NSE > 0.8) was obtained for high inflows and wet AMC (i.e., when the primary swale function is flow conveyance); the least fit was noted for low inflows and dry AMC, when the primary swale function is flow attenuation. Furthermore, this observation indicates the overall importance of correct modelling of the soil infiltration. The effects of spatial variation of SWC on the swale discharge hydrograph could not be confirmed from simulation results, but high topographical accuracy was beneficial for reproducing well the locations of the observed water ponding. No significant increases in simulated SWC at 0.3 m or greater depths were noted, which agreed with field observations. Overall, the results indicated that Mike SHE was effective in process-oriented small-scale modelling of grass swale flow hydrographs.

Characterizing Spatial Variability in Soil Water Content for Precision Irrigation Management

Among one of the many challenges in implementing precision irrigation is to obtain an accurate characterization of the soil water content (SWC) across spatially variable fields along the crop growing season. The accuracy of characterizing SWC has been tested primarily on a small-scale and has received little attention from the scientific community at the field scale. Hence, the objective of this study was to assess the characterization of the spatial distribution of soil water content at the field scale by the apparent electrical conductivity (ECa). In evaluating the current aim, ECa survey was compared against repeated measurements of SWC at five depths using neutron probe. Results showed that mean SWC was different across ECa derived management zones, which indicates that on a macro-scale, soil ECa could effectively characterize the mean differences in SWC across management zones. Results also showed that deep ECa (0–150 cm) survey outperformed shallow survey (0–75 cm). Considering other soil properties, such as organic matter content and salt content, further improved the relationship between SWC and ECa.

Seasonal variation and implications of soil water content in the cultivation of olive trees

Seasonal variation and implications of soil water content in the cultivation of olive trees

Comparison of actual evapotranspiration of irrigated maize in a sub-humid region using four different canopy resistance based approaches

The single layer Penman-Monteith (PM) method is widely used method for the estimation of crop evapotranspiration (ETc). The accuracy of ETc estimate relies upon the quality of input weather data and capacity to approach adequately canopy (rc) and aerodynamic resistance (ra). In this study, the PM method was used to estimate daily crop evapotranspiration of irrigated maize for the years 2013 and 2014 in a sub-humid region. Four different approaches (Monteith, Katerji-Perrier, Todorovic, and Jarvis) were used to estimate canopy resistance and, then after, crop evapotranspiration by PM equation were evaluated. The comparison was made to daily crop evapotranspiration obtained from the soil water balance (SWB) and soil water content variation measured by time domain reflectometry (TDR). The cumulative crop evapotranspiration of SWB, Monteith, Katerji-Perrier, Todorovic and Jarvis approach was respectively, 260.4, 266.8, 252.8, 263.4, 256 mm for the year 2013, and 250.5, 257.7, 240.6, 251.8, 247.6 mm for the year 2014. The comparison of results and the statistical analysis confirmed that Todorovic and Jarvis approach gave reliable values, while the Katerji-Perrier approach could be used as an alternative method.

Spatial Variation of Soil CO2, CH4 and N2O Fluxes Across Topographical Positions in Tropical Forests of the Guiana Shield

The spatial variation of soil greenhouse gas fluxes (GHG; carbon dioxide—CO2, methane—CH4 and nitrous oxide—N2O) remains poorly understood in highly complex ecosystems such as tropical forests. We used 240 individual flux measurements of these three GHGs from different soil types, at three topographical positions and in two extreme hydric conditions in the tropical forests of the Guiana Shield (French Guiana, South America) to (1) test the effect of topographical positions on GHG fluxes and (2) identify the soil characteristics driving flux variation in these nutrient-poor tropical soils. Surprisingly, none of the three GHG flux rates differed with topographical position. CO2 effluxes covaried with soil pH, soil water content (SWC), available nitrogen and total phosphorus. The CH4 fluxes were best explained by variation in SWC, with soils acting as a sink under drier conditions and as a source under wetter conditions. Unexpectedly, our study areas were generally sinks for N2O and N2O fluxes were partly explained by total phosphorus and available nitrogen concentrations. This first study describing the spatial variation of soil fluxes of the three main GHGs measured simultaneously in forests of the Guiana Shield lays the foundation for specific studies of the processes underlying the observed patterns.

Application of EMI and FDR Sensors to Assess the Fraction of Transpirable Soil Water over an Olive Grove

Accurate soil water status measurements across spatial and temporal scales are still a challenging task, specifically at intermediate spatial (0.1–10 ha) and temporal (minutes to days) scales. Consequently, a gap in knowledge limits our understanding of the reliability of the spatial measurements and its practical applicability in agricultural water management. This paper compares the cumulative EM38 (Geonics Ltd., Mississauga, ON, Canada) response collected by placing the sensor above ground with the corresponding soil water content obtained by integrating the values measured with an FDR (frequency domain reflectometry) sensor. In two field areas, characterized by different soil clay content, two Diviner 2000 access tubes (1.2 m) were installed and used to quantify the dimensionless fraction of transpirable soil water (FTSW). After the calibration, the work proposes the combined use of the FDR and electromagnetic induction (EMI) sensors to measure and map FTSW. A strong correlation (R2 = 0.86) between FTSW and EM38 bulk electrical conductivity was found. As a result, field changes of FTSW are due to the variability of soil water content and soil texture. As with the data acquired in the field, more structured patterns occurred after a wetting event, indicating the presence of subsurface flow or root water uptake paths. After assessing the relationship between the soil and crop water status, the FTSW domain includes a critical value, estimated around 0.38, below which a strong reduction of relative transpiration can be recognized.

Spatio-temporal variations of soil water content and salinity around individual Tamarix ramosissima in a semi-arid saline region of the upper Yellow River, Northwest China

Ecological restoration by Tamarix plants on semi-arid saline lands affects the accumulation, distribution patterns and related mechanisms of soil water content and salinity. In this study, spatio-temporal variations of soil water content and salinity around natural individual Tamarix ramosissima Ledeb. were invetigated in a semi-arid saline region of the upper Yellow River, Northwest China. Specifically, soil water content, electrical conductivity (ECe), sodium adsorption ratio (SARe), and salt ions (including Na+, K+, Ca2+, Mg2+ and SO42–) were measured at different soil depths and at different distances from the trunk of T. ramosissima in May, July, and September 2016. The soil water content at the 20–80 cm depth was significantly lower in July and September than in May, indicating that T. ramosissima plants absorb a large amount of water through the roots during the growing period, leading to the decreasing of soil water content in the deep soil layer. At the 0–20 cm depth, there was a salt island effect around individual T. ramosissima, and the ECe differed significantly inside and outside the canopy of T. ramosissima in May and July. Salt bioaccumulation and stemflow were two major contributing factors to this difference. The SARe at the 0–20 cm depth was significantly different inside and outside the canopy of T. ramosissima in the three sampling months. The values of SARe at the 60–80 cm depth in May and July were significantly higher than those at the 0–60 cm depth and higher than that at the corresponding depth in September. The distribution of Na+ in the soil was similar to that of the SARe, while the concentrations of K+, Ca2+, and Mg2+ showed significant differences among the sampling months and soil depths. Both season and soil depth had highly significant effects on soil water content, ECe and SARe, whereas distance from the trunk of T. ramosissima only significantly affected ECe. Based on these results, we recommend co-planting of shallow-rooted salt-tolerant species near the Tamarix plants and avoiding planting herbaceous plants inside the canopy of T. ramosissima for afforestation in this semi-arid saline region. The results of this study may provide a reference for appropriate restoration in the semi-arid saline regions of the upper Yellow River.

Numerical investigation of water evaporation from Fontainebleau sand in an environmental chamber

The global warming and climate change have aroused increasing attention to the effect of intensive soil water evaporation on earth constructions. When investigating the hydro-mechanical behavior of soil during evaporation, it is of paramount importance to consider the coupled transport of heat and water in soil. In this study, four different evaporation tests of Fontainebleau sand conducted in an environmental chamber are investigated. A numerical approach combing a coupled hydro-thermal model and a soil-atmosphere interaction model is adopted, enabling the numerical estimation of soil temperature and soil water content variations. Comparison between the measurements and the simulation results shows the relevance of the proposed approach with consideration of suitable thermal and hydraulic boundary conditions and soil parameters. Further inspection on the variations of soil water content and soil temperature suggests the significant influence of water and heat flux boundary conditions at the soil-atmosphere interface. In this study, it is proposed to estimate the mode of soil temperature variations directly based on the observed actual evaporation curve. Moreover, the simulation results also reveal the necessity of accounting for the dry layer formed in sand during evaporation.

Characterization of Grain‐Size Distribution, Thermal Conductivity, and Gas Diffusivity in Variably Saturated Binary Sand Mixtures

Core Ideas Parameterized models are relevant to applications where different porous media mixtures are used. Models include a grain‐size distribution function to describe bimodal behavior for binary mixtures. Improved model describes observed thermal conductivity–saturation relations for binary mixtures. Combined Buckingham–Penman model used to describe observed gas diffusivity–air content relations. This work is relevant for proper simulation of mixed porous media. Characterization of differently textured porous materials, as well as different volumetric porous media mixtures, in relation to mass and heat transport is vital for many engineering and research applications. Functional relations describing physical (e.g., grain‐size distribution, total porosity), thermal, and gas diffusion properties of porous media and mixtures are necessary to optimize the design of porous systems that involve heat and gas transport processes. However, only a limited number of studies provide characterization of soil physical, thermal, and gas diffusion properties and the functional relationships of these properties under varying soil water contents, especially for soil mixtures, complicating optimization efforts. To better understand how mixing controls the physical, thermal, and gas diffusion properties of porous media, a set of laboratory experiments was performed using five volumetric mixtures of coarse‐ and fine‐grained sand particles. For each mixture, the grain‐size distribution (GSD), thermal conductivity, and gas diffusivity were obtained and parameterized using existing and suggested parametric models. Results show that the extended, two‐region Rosin–Rammler particle‐size distribution model proposed in this study could successfully describe the bimodal behavior of the GSD of binary mixtures. Further, the modified Côté and Konrad thermal conductivity model adequately described the thermal conductivity–water saturation relations observed in different mixtures. The proposed simple soil‐gas diffusivity descriptive model parameterized the upper limit, average, and lower limit behavior in gas diffusivity–air content relations in apparently texture‐invariant gas diffusivity data. Results further show a close analogy between gas diffusivity and thermal conductivity and their variation with saturation across different binary mixtures. Overall, the results of the study provide useful numerical insight into the physical, thermal, and gas transport characteristics of binary mixtures, with wide implications for future engineering and research applications that involve multicomponent porous systems.

Factors that Influence the Vertical Distribution of Soil Water Content in the Critical Zone on the Loess Plateau, China

Core Ideas Soil water distributions in deep profiles were described and analyzed. Soil water storage distributions were evaluated. Bulk density significantly affected soil water distribution of deep profiles. In arid and semiarid regions, determining the vertical distribution of the soil water content (SWC) in the Earth's Critical Zone is important for understanding hydrological processes and for evaluating soil water storage (SWS) levels. However, the vertical distribution of SWC and its storage in deeper layers are unclear due to the difficulties associated with soil sampling. In this study, we investigated the vertical distribution of the SWC and SWS, and analyzed the relationship between SWC and related soil properties, including bulk density (BD), sand, silt, clay, and soil organic C (SOC), from the top of the soil profile to the bedrock at five sampling sites on the Loess Plateau in China (Yangling, Changwu, Fuxian, An'sai, and Shenmu) by soil core drilling. The results showed that the SWC variations at the five sampling sites tended to become weak as the depth increased. The mean SWC of all sampling sites exhibited a decreasing trend from south to north, with a significant difference (P &lt; 0.01). Stepwise multiple regression analysis and state‐space modeling showed that the BD was an important factor that affected the variations in the SWC in the deep soil layer. The trend of vertical distribution of the SWS was similar to that of the SWC. The results of this study deepen our understanding of the water conditions in deep soil layers, as well as the evaluation of SWS on the Loess Plateau in China.

祁连山西段草地土壤温度、水分变化特征

祁连山西段草地土壤温度、水分变化特征

Measurement and Simulation of Soil Water Contents in an Experimental Field in Delta Plain

Variation in soil water content in the delta plain has its own particularity and is significant for agricultural improvement, the utilization of water resources and flood risk mitigation. In this study, experimental data collected from a plot of farmland located in the Taihu Basin were used to investigate the temporal and vertical variation of soil water content, as well as the effects of individual rainfall on soil water and shallow groundwater and their interaction. The results showed that the variation of soil water content is dependent on the comprehensive influence of soil hydraulic properties, meteorological factors and shallow groundwater and the correlation to the groundwater table is the strongest due to the significant capillary action in the delta plain. A saturated-unsaturated three-dimensional soil water numerical model was developed for the study area in response to rainfall and evapotranspiration. Scenario simulations were performed with different soil depths for soil water content and the error source was analyzed to improve the model. The average RMSE, RE and R2 values of the soil water content at the five depths between the measured and simulated results were 0.0192 cm3·cm−3, 2.09% and 0.8119, respectively. The results indicated that the developed model could estimate vertical soil water content and its dynamics over time at the study site at an acceptable level. Moreover, further research and application to other sites in delta plains are necessary to verify and improve the model.

A Field‐Scale Sensor Network Data Set for Monitoring and Modeling the Spatial and Temporal Variation of Soil Water Content in a Dryland Agricultural Field

AbstractWe describe a soil water content monitoring data set and auxiliary data collected at a 37 ha experimental no‐till farm in the Northwestern United States. Water content measurements have been compiled hourly since 2007 by ECH2O‐TE and 5TE sensors installed at 42 locations and five depths (0.3, 0.6, 0.9, 1.2, and 1.5 m, 210 sensors total) across the R.J. Cook Agronomy Farm, a Long‐Term Agro‐Ecosystem Research Site stationed on complex terrain in a Mediterranean climate. In addition to soil water content readings, the data set includes hourly and daily soil temperature readings, annual crop histories, a digital elevation model, Bt horizon maps, seasonal apparent electrical conductivity, soil texture, and soil bulk density. Meteorological records are also available for this location. We discuss the unique challenges of maintaining the network on an operating farm and demonstrate the nature and complexity of the soil water content data. This data set is accessible online through the National Agriculture Library, has been assigned a DOI, and will be maintained for the long term.

Mathematical Modelling of Arctic Polygonal Tundra with Ecosys: 2. Microtopography Determines How CO2 and CH4 Exchange Responds to Changes in Temperature and Precipitation

AbstractDifferences of surface elevation in arctic polygonal landforms cause spatial variation in soil water contents (θ), active layer depths (ALD), and thereby in CO2 and CH4 exchange. Here we test hypotheses in ecosys for topographic controls on CO2 and CH4 exchange in trough, rim, and center features of low‐ and flat‐centered polygons (LCP and FCP) against chamber and eddy covariance (EC) measurements during 2013 at Barrow, Alaska. Larger CO2 influxes and CH4 effluxes were measured with chambers and modeled with ecosys in LCPs than in FCPs and in lower features (troughs) than in higher (rims) within LCPs and FCPs. Spatially aggregated CO2 and CH4 fluxes from ecosys were significantly correlated with EC flux measurements. Lower features were modeled as C sinks (52–56 g C m−2 yr−1) and CH4 sources (4–6 g C m−2 yr−1), and higher features as near C neutral (−2–15 g C m−2 yr−1) and CH4 neutral (0.0–0.1 g C m−2 yr−1). Much of the spatial and temporal variations in CO2 and CH4 fluxes were modeled from topographic effects on water and snow movement and thereby on θ, ALD, and soil O2 concentrations. Model results forced with meteorological data from 1981 to 2015 indicated increasing net primary productivity in higher features and CH4 emissions in some lower and higher features since 2008, attributed mostly to recent rises in precipitation. Small‐scale variation in surface elevation causes large spatial variation of greenhouse gas (GHG) exchanges and therefore should be considered in estimates of GHG exchange in polygonal landscapes.