Spatial Variability Of Soil Moisture Research Articles

Impact of spatially-variable soil thickness and texture on simulated hydrologic conditions in a semiarid watershed in northwest Mexico

Soil depth and texture exert strong controls on the spatial distribution of water and energy fluxes and states in semiarid watersheds. As a result, realistic representations of the spatial soil characteristics within watersheds are important for the improvement of process-based distributed hydrologic modeling applications. In this study, we evaluated the effects of combinations of soil thickness and soil texture products with varying spatial distributions to assess their effects on the simulated hydrologic response in the semiarid Sierra Los Locos watershed in Sonora, Mexico. The main findings of the hydrological simulations show that soil texture exerted a strong control on evapotranspiration and soil moisture patterns, while soil thickness was directly related with the magnitude and range of the simulated values. Furthermore, soil texture patterns were an important factor controlling the spatial and temporal persistence of soil moisture which is highly evident during the transition from dry to wet conditions in the North American monsoon region. Once vegetation cover increases in the watershed in response to seasonal rainfall, the influence of soil texture decreases for determining the spatial distribution of the simulated hydrologic response and soil thickness becomes more important. Spatially-variable soil thickness tends to create soil depressions that store and transmit subsurface water, leading to large spatial variations in soil moisture, evapotranspiration and runoff generation. The results of this study highlight the sensitivity of estimated water fluxes and states with respect to the spatial distribution of soil depth and texture as obtained in a distributed hydrologic model representative of modern approaches. Finally, this research work offers insight into the importance of field studies and remote sensing approaches to better characterize these watershed properties.

Factors affecting soil moisture spatial variability for a humid forest hillslope

AbstractSoil moisture is an important variable in explaining hydrological processes at hillslope scale. The distribution of soil moisture along a hillslope is related to the spatial distribution of the soil properties, the topography, the soil depth, and the vegetation. In order to investigate the factors affecting soil moisture, various environmental data were collected from a humid forest hillslope in this study. Several factors (the wetness index; the contributing area; the local slope; the soil depth; the composition of sand, silt, and clay; the scaling parameter; the hydraulic conductivity; the tree diameter at breast height; and the total weighted basal area) were evaluated for their effect on soil moisture and its distribution over the hillslope at depths of 10, 30, and 60 cm. Both linear correlation analysis and empirical orthogonal function analysis indicated that the soil texture was a dominant factor in soil moisture distribution. The impact of soil hydraulic conductivity was important for all soil moisture ranges at a depth of 30 cm, but those at 10 and 60 cm were limited to very wet and dry conditions, respectively. The relationships of the various factors with the spatial variability of soil moisture indicated the existence of a threshold soil moisture that is related to the composition of the soil and the factors related to the distribution of water in the study area.

Scale dependency of spatial variability of soil moisture in gravel-mulched field

Knowledge of the scale dependency of the spatial variability of soil moisture is of paramount importance in the study of soil–atmosphere interactions and hydrological processes. We present a case study of the effects of sampling area and spacing on the spatial variability of soil moisture in a 32 × 32 m gravel-mulched field in an arid area of northwestern China. The coefficient of variation, correlation length and Moran’s index, which are commonly used in spatial analysis, were applied to each scenario to characterise the degree of spatial variability of soil moisture. The spatial variability was weak at all sampling scales. All indices increased to various degrees with an increase in sampling area. The correlation length decreased with increasing sampling spacing, and neither the coefficient of variation nor Moran’s index were significantly correlated with sampling spacing, indicating that sampling spacing had little effect on soil-moisture variability. The spatial distributions of soil moisture were irregular, with peaks and valleys at different sampling spacings but tending to gradually stabilise as sampling spacing increased. A sampling spacing of 8 m was reasonable, because it best-characterised the spatial distribution of soil moisture. This study also provides a theoretical reference for the establishment of optimal sampling schemes, which allow a considerable savings in both time and cost, and provides theoretical support for ecological agricultural production in gravel-mulched fields.

Soil moisture prediction of bare soil profiles using diffuse spectral reflectance information and vadose zone flow modeling

Soil hydraulic property information of the vadose zone is key to quantifying the temporal and spatial variability of soil moisture, and for modeling water flow and contaminant transport processes in the near surface. This study deals with exploring the feasibility of using diffuse soil spectral information in the visible, near-infrared and shortwave infrared range (350–2500 nm) to estimate coarse-scale soil hydraulic parameters and predict soil moisture profiles using a topography-based aggregation scheme in conjunction with a 1D mechanistic water flow model. Three different types of parametric transfer functions (so-called spectrotransfer functions, STFs; pedotransfer functions, PTFs; and spectral pedotransfer functions, SPTFs) were aggregated from the point scale to 1 km2 pixel size. to provide coarse scale estimates of van Genuchten-Mualem (VGM) hydraulic parameters. The coarse scale hydraulic parameters were evaluated by simulating soil water dynamics of the 1 km2 pixels across the Zanjanrood River sub-watershed (ZRS) in northwest Iran. Resultant soil water states were compared with ground-truth measurements and advanced synthetic aperture radar (ASAR) estimates of soil water content. The topography-based aggregation scheme was found to provide effective values of the VGM hydraulic parameters across the ZRS study site. The coarse scale STFs performed best in terms of simulating surface, near-surface and subsurface soil water dynamics, followed by the coarse scale SPTFs and PTFs, which performed similarly. The average simulated soil water contents of the surface layer closely correlated with ASAR estimates during relatively wet periods. Simulated subsurface soil water dynamics matched well with the ground-truth measurements. These findings indicate the feasibility of using spectral data to predict VGM hydraulic parameters and, ultimately, to predict soil water dynamics at the larger scales.

Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

Abstract. Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson's correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were present, while SEBS model estimates displayed a disconnect from the soil moisture distribution in summers with long dry spells. Importantly, no single evaporation model matched the statistical distribution of the measured soil moisture for the entire period, highlighting the challenges in effectively capturing evaporative flux response within changing landscapes. One of the outcomes of this work is that the analysis points to the feasibility of using intermediate-scale soil moisture measurements to evaluate gridded estimates of evaporation, exploiting the independent, yet physically linked nature of these hydrological variables.

노지 작물의 적정 관개계획을 위한 토양수분의 공간변이성 분석

노지 작물의 적정 관개계획을 위한 토양수분의 공간변이성 분석

Regional scale spatial and temporal variability of soil moisture in a prairie region

AbstractUnderstanding the dynamics of spatial and temporal variability of soil moisture at the regional scale and daily interval, respectively, has important implications for remote sensing calibration and validation missions as well as environmental modelling applications. The spatial and temporal variability of soil moisture was investigated in an agriculturally dominated region using an in‐situ soil moisture network located in central Saskatchewan, Canada. The study site evaluated three depths (5, 20, 50 cm) through 139 days producing a high spatial and temporal resolution data set, which were analysed using statistical and geostatistical means. Processes affecting standard deviation at the 5‐cm depth were different from the 20‐cm and 50‐cm depths. Deeper soil measurements were well correlated through the field season. Further analysis demonstrated that lag time to maximum correlation between soil depths increased through the field season. Temporal autocorrelation was approximately twice as long at depth compared to surface soil moisture as measured by the e‐folding frequency. Spatial correlation was highest under wet conditions caused by uniform rainfall events with low coefficient of variation. Overall soil moisture spatial and temporal variability was explained well by rainfall events and antecedent soil moisture conditions throughout the Kenaston soil moisture network. It is expected that the results of this study will support future remote sensing calibration and validation missions, data assimilation, as well as hydrologic model parameterization for use in agricultural regions. Copyright © 2016 John Wiley & Sons, Ltd.

Analysis of soil moisture dynamics beneath olive trees

AbstractOlive cultivation is a widespread land use in Mediterranean climates. The proper implementation of soil and water conservation practices in groves requires detailed knowledge of the governing hydrological processes. In this work topsoil moisture dynamics under wet and dry conditions and across a small catchment was investigated in the inter row (IR) and directly under the olive tree canopies (UC). We do this using a sensor network (11 stations) and a simple bucket model which was calibrated (June, 2011–2012) and validated (June, 2012–2013). During most of the year the normalized soil moisture contents (s) were greater in the IR than under UC, with an average normalized soil moisture difference of 0.12. The difference between UC and IR normalized soil moisture followed a seasonal pattern, reaching a maximum near 0.30 during spring. An analysis of the normalized soil moisture probability density functions (pdfs) was bimodal, showing characteristic dominant wet and dry soil moisture states, with the highest probability densities for the dry state. Overall the spatial variability of soil moisture was lower UC than in the IR. This was a result of the soil moisture buffering capacity of the canopy with respect to rainfall and evaporation, in addition to observed differences in soil properties. Hourly soil moisture data were successfully modelled (R2 > 0.85), both UC and in the IR, yet with the inclusion of a simple formulation for canopy interception for the former. The results provide insight into how olive trees change hydrological processes in their neighbourhood. Copyright © 2016 John Wiley & Sons, Ltd.

Spatial Variability of Soil Moisture in a Forest Catchment: Temporal Trend and Contributors

Understanding the spatio-temporal dynamic of soil moisture is critical in hydrological and other land surface related studies. Until recently, however, there have been controversies about the relationship between spatial mean and spatial variance of soil moisture and the contributions of each of these factors to spatial variability. Therefore, in this study, spatial variability of soil moisture in a 7 km2 forest catchment is analyzed by time-series data on soil moisture obtained at a total of 12 observation sites. Results showed that soil moisture spatial mean and spatial variance varied almost synchronously and in three cyclic patterns during the monitoring period from 1 April 2015 to 31 October 2015. The spatial mean-variance relationship during the ascending and descending periods of spatial mean could be well-fitted by upward and downward convex quadratic curves, respectively, indicating possible clockwise hysteresis of this relationship. It was found that all through the monitoring period, contributions of time-invariant factors on total spatial variance increased from 68.9% to 88.2% with depth, and temporally stable ranking of sites was obtained. Because of the high spatial variation of soil moisture in our study area, it should be noted that a large number of sample plots would be needed to adequately estimate the spatial variability of soil moisture.

Comparative analysis on spatial variability of soil moisture under different land use types in orchard

Spatial variability of soil moisture under different land use types of orchard in Weibei rainfed highland of China was investigated by means of geostatistics. Classical statistical analysis showed that the average soil moisture content of clean tillage, grass land and straw land ranged from 9.36 to 20.86, 8.78 to 23.37 and 10.84 to 20.49, respectively. In 0–40cm soil layer, 10%<CV%<100%, which belongs to moderate variability. Depth in 120–160cm and 160–200cm, CV≤10%, which belong to weak variability. And with the increasing of depth, coefficient of variation decreased. S-W test values pointed out that the distribution of soil moisture content accorded with normal distribution.The results of variation function analysis indicated that the ranges of grass land were larger than clean tillage. Spatial autocorrelation in surface soil was weaker than that of the bottom soil. The reason was that surface soil was more easily influenced by exterior factors. Fractal dimension value decreased with the increasing of soil depth. While the average content of soil moisture showed the opposite trend. According to kriging interpolation, the high-value areas of clean tillage mainly concentrated in (13.4, 27.8), (28.0, 32.5) and (27.0, 10.4), and low-value areas were in (13.8, 6.6). However, the high-value of grass areas mainly focused on around (11.5, 11.5), and low-value were in (11.2, 11.2) and (25.5, 25.5). The change of the other areas’ soil moisture were not obvious in a wide range. It has a good consistency. Therefore, in the dry season, it was advisable to choose straw mulching, and reduce grass cultivation, to achieve the goal of improving soil moisture content.

Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures

AbstractThis study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large‐scale, high‐resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into Hydrus‐1D to estimate soil moisture as well as soil thermal and hydraulic properties. However, this approach was limited to bare soil and assumed that the cable depths were perfectly known. In order for Passive DTS to be more broadly applicable as a soil hydrology research and remote sensing soil moisture product validation tool, it must be applicable in vegetated areas. To address this first limitation, the forward model (Hydrus‐1D) was improved through the inclusion of a canopy energy balance scheme. Synthetic tests were used to demonstrate that without the canopy energy balance scheme, the PBS estimated soil moisture could be even worse than the open loop case (no assimilation). When the improved Hydrus‐1D model was used as the forward model in the PBS, vegetation impacts on the soil heat and water transfer were well accounted for. This led to accurate and robust estimates of soil moisture and soil properties. The second limitation is that, cable depths can be highly uncertain in DTS installations. As Passive DTS uses the downward propagation of heat to extract moisture‐related variations in thermal properties, accurate estimates of cable depths are essential. Here synthetic tests were used to demonstrate that observation depths can be jointly estimated with other model states and parameters. The state and parameter results were only slightly poorer than those obtained when the cable depths were perfectly known. Finally, in situ temperature data from four soil profiles with different, but known, soil textures were used to test the proposed approach. Results show good agreement between the observed and estimated soil moisture, hydraulic properties, thermal properties, and observation depths at all locations. The proposed method resulted in soil moisture estimates in the top 10 cm with RMSE values typically &lt;0.04 . This demonstrates the potential of detecting the spatial variability of soil moisture and properties in vegetated areas from Passive DTS data.

On the non-uniqueness of the hydro-geomorphic responses in a zero-order catchment with respect to soil moisture

This study advances mechanistic interpretation of predictability challenges in hydro-geomorphology related to the role of soil moisture spatial variability. Using model formulations describing the physics of overland flow, variably saturated subsurface flow, and erosion and sediment transport, this study explores (1) why a basin with the same mean soil moisture can exhibit distinctly different spatial moisture distributions, (2) whether these varying distributions lead to non-unique hydro-geomorphic responses, and (3) what controls non-uniqueness in relation to the response type. Two sets of numerical experiments are carried out with two physically-based models, HYDRUS and tRIBS+VEGGIE+FEaST, and their outputs are analyzed with respect to pre-storm moisture state. The results demonstrate that distinct spatial moisture distributions for the same mean wetness arise because near-surface soil moisture dynamics exhibit different degrees of coupling with deeper-soil moisture and the process of subsurface drainage. The consequences of such variations are different depending on the type of hydrological response. Specifically, if the predominant runoff response is of infiltration excess type, the degree of non-uniqueness is related to the spatial distribution of near-surface moisture. If runoff is governed by subsurface stormflow, the extent of deep moisture contributing area and its “readiness to drain” determine the response characteristics. Because the processes of erosion and sediment transport superimpose additional controls over factors governing runoff generation and overland flow, non-uniqueness of the geomorphic response can be highly dampened or enhanced. The explanation is sediment composed by multi-size particles can alternate states of mobilization or surface shielding and the transient behavior is inherently intertwined with the availability of mobile particles. We conclude that complex nonlinear dynamics of hydro-geomorphic processes are inherent expressions of physical interactions. As complete knowledge of watershed properties, states, or forcings will always present the ultimate, if ever resolvable, challenge, deterministic predictability will remain handicapped. Coupling of uncertainty quantification methods and space-time physics-based approaches will need to evolve to facilitate mechanistic interpretations and informed practical applications.

Severe depletion of soil moisture following land-use changes for ecological restoration: Evidence from northern China

Soil moisture is fundamental to ecosystem sustainability in arid and semi-arid regions, and characterizing temporal variations in soil moisture levels in response to changes in land use is important in assessing whether vegetation that has been restored as part of ecological restoration can be sustained. Such an assessment is presented here based on 78 recent publications focused on China’s initiatives at ecological restoration including the ‘Grain for Green’ programme and the ‘Three Norths Shelter Forest System’ project. The study analysed 1740 observations at 83 sites in eight provinces in northern China to determine temporal and spatial variations in soil moisture and the causes of those variations. Changes in land use for restoration of ecosystems led to severe depletion in soil moisture levels – as low as 9%, determined gravimetrically – in the 0–100cm layer of soil. The extent of depletion was influenced significantly by the choice of species for restoration (trees, shrubs, or grasses) and land use before the restoration. Deliberate restoration of vegetation may have the largest negative impact on soil moisture at sites that receive less than 600mm of annual precipitation and may be practical only when it exceeds 600mm. Afforestation decreased the levels of soil moisture significantly, whereas natural restoration had no significant effect on soil moisture. Therefore, natural restoration is the better option for maintaining the stability of water resources in arid and semi-arid regions. Afforestation would be a poor choice for places in which annual precipitation is close to or less than potential evapotranspiration but a better choice if annual precipitation is adequate. In planning revegetation initiatives, planners must understand that different environments support different vegetation types, and therefore require different solutions.

Spatial Variations of Soil Moisture under Caragana korshinskii Kom. from Different Precipitation Zones: Field Based Analysis in the Loess Plateau, China

Soil moisture scarcity has become the major limiting factor of vegetation restoration in the Loess Plateau of China. The aim of this study is: (i) to compare the spatial distribution of deep (up to 5 m) soil moisture content (SMC) beneath the introduced shrub Caragana korshinskii Kom. under different precipitation zones in the Loess Plateau and (ii) to investigate the impacts of environmental factors on soil moisture variability. Soil samples were taken under C. korshinskii from three precipitation zones (Semiarid-350, Semiarid-410, Semiarid-470). We found that the highest soil moisture value was in the 0–0.1 m layer with a large coefficient of variation. The soil water storage under different precipitation zones increased following the increase of precipitation (i.e., Semiarid-350 &lt; Semiarid-410 &lt; Semiarid-470), although the degree of SMC variation was different for different precipitation zones. The SMC in the Semiarid-350 zone initially increased with soil depth, and then decreased until it reached the depth of 2.8-m. The SMC in the Semiarid-410 zone showed a decreasing trend from the top soil to 4.2-m depth. The SMC in the Semiarid-470 zone firstly decreased with soil depth, increased, and then decreased until it reached 4.6-m depth. All SMC values then became relatively constant after reaching the 2.8-m, 4.2-m, and 4.6-m depths for Semiarid-350, Semiarid-410, and Semiarid-470, respectively. The low but similar SMC values at the stable layers across the precipitation gradient indicate widespread soil desiccation in this region. Our results suggested that water deficit occurred in all of the three precipitation zones with precipitation, latitude, field capacity, and bulk density as the main environmental variables affecting soil moisture. Considering the correlations between precipitation, SMC and vegetation, appropriate planting density and species selection should be taken into account for introduced vegetation management.

Analysis of the spatial variability of soil moisture and salinity in Ebinur Lake wetlands,Xinjiang

为揭示艾比湖湿地土壤退化程度空间分布特征，在离艾比湖湖滨5~15 km，绕湖一周160 km范围内，以湖心质点为中心，将艾比湖划分为东北、东南、西南、西北4个区域，采用传统统计学和地统计学相结合的方法对表层（0~20 cm）土壤盐分、含水量与pH的空间分异特征进行研究.结果表明：绕湖一周不同区域的土壤盐分均属中等变异强度；土壤含水量在西北部属强变异性，而东北、东南和西南部均属中等变异强度；土壤pH在不同区域内均属弱变异强度.绕湖一周除西北部土壤盐分的半方差理论模型较符合球状模型外，其它区域土壤盐分、含水量和pH均符合高斯模型；受结构性因素影响，不同区域土壤盐分、含水量和pH均具有较强的空间相关性；西南部土壤盐分、含水量和pH的Moran's I系数比其它区域的波动大，表明空间相关性较强.艾比湖湿地常年大风、干旱、缺水及沙化盐化的自然因素与引水围堰、种植耐盐碱植物的人为活动造成了采样区表层土壤盐分、含水量和pH的空间分布多呈现不规则条带状格局.艾比湖湿地土壤以盐土为主，重度盐化土次之，土壤盐渍化日益严重.;Systematic research of soil water and salt is commonly lack in previous studies for the Lake Ebinur, thus in this study, in order to reveal the spatial distribution characteristics of soil degradation degree in the Lake Ebinur wetland, by taking the lake side of a distance to the Lake Ebinur 5-15 km, a circle area of 160 km² as research area. The spatial variability of soil salinity,pH and moisture in the surface layer(0-20 cm) of in the circle sampling area of Lake Ebinur was analyzed by using traditional statistics and geo-statistics. The results indicated that the variation in salinity was moderate in the different directions. The soil moisture in the Northeast, Southeast and Southwest belongs to the medium variation intensity, while the northwest belongs to strong variability. The soil pH of different directions has weak variation. Except that the soil salinity of northwest follows with the spherical model, soil salinity, water content and pH in other different directions were in line with the Gaussian model. Soil salinity, water content and pH of different directions showed strong spatial autocorrelation, which were mainly affected by structural factors. Moran's I coefficient analysis proved that soil salinity in the southwest, water content and pH was stronger in spatial correlation than that in the other directions. The natural factors including winds, drought, water scarcity, desertification, salinization, and human activities including diversion cofferdam, planting drought-resistant and salt-tolerant plants, were contributed to sampling area of Lake Ebinur wetland spatial distribution of surface soil salinity, water content and pH. Soil in the Lake Ebinur wetland is mainly of saline-based type, followed by the type of severe salinization and more serious salinization.

Soil moisture dynamics with hydro-climatological parameters at different soil depths

The soil–water interaction is crucial for effective hydrological processes determination. The soil moisture (SM) is an important parameter to provide priori information for the interactions imparting and affecting the energy fluxes response for such kind of processes. This work investigated the effects of climatic, geophysical and hydrological parameters on SM at 9 stations within Utah State, USA, for daily data recorded between 2010 and 2012 at 5 different soil depths (approximately 5, 10, 20, 50, and 100 cm). A high correlation was found for soil temperature, evapotranspiration (ET), and surface temperature, respectively, in most of the stations at either α = 5 % or 1 %. All stations exhibited a downward trend in SM for the top three soil depths, whereas, for other depths some stations depicted an upward trend. From time series analysis, it was found that surface average temperature, ET and soil temperature varied on seasonal basis with maximum in June and minimum in January of each year. In addition, SM availability in the top 5 cm of soil depth showed more significance for having strong correlation with hydroclimatic variables and were essential in interpreting many hydrological processes. From analyses at shallow soil depths (5 and 10 cm), the spatial SM variability across the stations was consistent during winter and spring whereas inconsistent during summer and autumn. In addition, the SM exhibited a temporal cyclic variability for almost all stations.

Temporal and Spatial Variation of Soil Moisture in Upland Soil using AMSR2 SMC

Temporal and spatial variation of soil moisture is important for understanding patterns of climate change, for developing and evaluating land surface models, for designing surface soil moisture observation networks, and for determining the appropriate resolution for satellite-based remote sensing instruments for soil moisture. In this study, we measured several soil moistures in upland soil using Advanced Microwave Scanning Radiometer 2 (AMSR2) Soil Moisture Content (SMC) during eight-month period in Chungbuk province. The upland soil moisture properties were expressed by simple statistical methods (average, standard deviation and coefficient of variation) from the monthly context. Supplementary studies were also performed about the effect of top soil texture on the soil moisture responses. If the results from this study were utilized well in specific cities and counties in Korea, it would be helpful to establish the countermeasures and action plans for preventing disasters because it was possible to compare with the relationship between soil moisture and top soil texture of each region. And it would be the fundamental data for estimating the effect of future agricultural plan.

Distribución espacial de la humedad y su relación con la textura en un suelo

En Finca Esmeralda (Limón, Costa Rica), sembrada de banano cv. Valery, se analizó la distribución espacial de la humedad del suelo y su relación con algunas de sus propiedades físicas, para determinar la variabilidad entre el método tradicional y el uso de TDR (Time Domain Reflectrometer) en la determinación de la humedad del suelo. Se muestreó en forma de cuadrícula, con 36 puntos de medición georeferenciados con GPS a 2 profundidades del suelo. En cada punto se midió el agua volumétrica del suelo con 3 diferentes equipos de TDR (300, MP y MT) y se comparó con el método tradicional de determinación de humedad volumétrica (MHV). También se recolectaron muestras de suelo para análisis de textura; con estos datos se hizo un análisis geoestadísitico y se elaboraron de los mapas correspondientes. Los suelos de texturas Franco a Franco arcillosas, mostraron variabilidad entre las determinaciones con TDR y estas en relación con el MHV, independientemente de la profundidad. A nivel superficial (0-30 cm), la correlación más alta fue entre los valores del MHV y el TDR-300 (r=0,69), seguida del TDRMT (r=0,63) y finalmente del TDR-MP (r=0,59). En la capa subsuperficial (30 a 60 cm), se encontró igualmente una relación positiva, pero menor, entre los valores del MHV con respecto al TDR- 300 y TRD-MP (0,47 y de 0,38, respectivamente); no se encontró relación con la utilización del TDR-MT. En términos del mapa de humedad de campo, hubo buena representación entre los métodos, que en general fueron eficaces para representar la variación espacial de la humedad del suelo.

Evaluation of the 2012 Drought with a Newly Established National Soil Monitoring Network

Core Ideas New US soil moisture network provides new opportunity to evaluate drought Soil moisture at deeper depths did not fully recover from the 2012 drought in 2013 Soil moisture varied by region in the response to drought The NOAA United States Climate Reference Network (USCRN) deployed soil moisture sensors during 2009 to 2011 to monitor the temporal and spatial variability of soil moisture at 114 locations in the contiguous United States. These new soil observations will enhance our understanding of changing soil conditions for better drought monitoring. One year after full deployment of the network, a large drought occurred across most of the United States and provided an opportunity to evaluate the utility of this network for drought monitoring. The soil moisture signal of the 2012 drought in the continental United States was detected nationally at all observational depths (5, 10, 20, 50, and 100 cm), with an overall 11.07% decrease from the average of the 2011 to 2013 summers. The top three depths (5, 10, and 20 cm) experienced the largest decrease in soil moisture. Although 2013 national precipitation totals returned to normal values and national soil moisture levels recovered from the 2012 drought, the national average soil moisture concentrations combined at the 50‐ and 100‐cm depths remained around 18% below pre‐drought levels. Regional analysis of the 2012 drought identified that the Upper Midwest, Northeast, Northern Rockies and Plains, and Ohio Valley climate regions were most impacted and demonstrated a temporal pattern similar to the national analysis. These results demonstrate the utility of using USCRN for monitoring national soil moisture conditions, assessing droughts, and tracking climate change with time.

Field Observations of Regional Controls of Soil Hydraulic Properties on Soil Moisture Spatial Variability in Different Climate Zones

Knowledge of soil moisture spatial variability (SMSP) is important for many practical reasons. However, a significant gap still exists in our understanding of different controls on SMSP, especially the roles of soil hydraulic parameters due to their limited availability. Although modeling approaches have been used to assess the impacts of those parameters on SMSP, they have led to inconsistent findings. In this study, soil moisture data from Utah (5 yr) and the US Southeast (2 yr) were obtained from the Soil Climate Analysis Network (SCAN), along with estimated van Genuchten parameters. The method of mean relative difference (MRD) of soil moisture was used as a diagnostic tool for assessing different climate and soil controls on SMSP. The results show that instead of being controlled by climate variables (e.g., precipitation and potential evapotranspiration) as traditionally believed at regional scales (∼105 km2), MRD is mainly dependent on soil hydraulic properties. In Utah with a drier climate, the residual soil moisture content (θr) is the dominant control on MRD, followed by the saturated soil moisture content (θs). With wetter climates in the US Southeast, the impacts of θr and θs on MRD become comparable, mostly due to the high correlation between θr and θs in this region, and there exists a nonlinear negative relationship between MRD and the parameter n for coarser soils, indicated by larger n values tending to have lower MRDs. The findings of this study have important implications for verifying remotely sensed moisture data and initializing and parameterizing regional land surface and climate models.