Temporal Dynamics Of Soil Moisture Research Articles

How effective is information on soil-landscape units for determining spatio-temporal variability of near-surface soil moisture?

In the last decades, a growing interest in fostering advanced interdisciplinary studies is leading to the establishment of observatories in pilot catchments for long-term monitoring of hydrological variables and fluxes. Nevertheless prior to sensor network installation, this investment necessitates preliminary surveys on key-variables such as near-surface soil moisture in order to prevent risks of erronously distributing sensors by missing sufficient spatial information for understanding hydrological processes within the landatmosphere interactions. The availability of maps describing areas with similar morphological, topographical, soil, and vegetation characteristics enable preliminary surveys to be organized for capturing spatio-temporal variability of soil moisture as best as possible. The soil-landscape classification can be considered as an interesting approach for grouping mapping units with similar hydrological behavior. Therefore, we assume the soil-landscape units as hydrotopes or hydrological similar units. Six transects were established along two hillsides of the Upper Alento River catchment (southern Italy) which is a proper candidate to become a Critical Zone Observatory. In this paper we use a soil-landscape map to infer spatial and temporal dynamics of soil moisture measured along these transects, whereas quantitative analyses were obtained by using multivariate techniques. The effectiveness of available information on soil-landscape mapping units is evaluated with respect to different observed patterns of soil moisture: wetter- and drier-than average observation points belong to agricultural and forested hillslopes, respectively. Soil texture and topographical controlling factors, especially clay content and slope gradient, are found to explain approximately 70% of the observed spatial variations in soil moisture along the forested hillslopes. The spatial structure explained by the environmental controlling factors decreases to 45% in the cases of the agricultural hillslopes mainly due to perturbations induced by grazing and tillage practices.

Validation of ECMWF Multi-Layer Reanalysis Soil Moisture Based on the OzNet Hydrology Network

Soil moisture reanalysis products can provide soil water information for the surface and root zone soil layers, which are significant for understanding the water cycle and climate change. However, the accuracy of multi-layer soil moisture datasets obtained from reanalysis products remains unclear in some areas. In this study, we evaluated the root zone soil moisture of the ERA-Interim soil moisture product, as well as the surface soil moisture based on in situ measurements from the OzNet hydrological measurement network over southeast Australia. In general, the ERA-Interim soil moisture product presents good agreement with in situ soil moisture values and can nicely reflect time variations, with correlation coefficient (R) values in the range of 0.73 to 0.84 and unbiased root mean square difference (ubRMSD) values from 0.035 m3·m−3 to 0.060 m3·m−3. Although the ERA-Interim soil moisture also can reflect temporal dynamics of soil moisture at root zone layer at depths of 28–100 cm, low correlations were found in winter. In addition, the ERA-Interim soil moisture product overestimates in situ measurements at depths of 0–7 cm and 7–28 cm, whereas the product shows underestimated values compared with in situ soil moisture at the root zone of 28–100 cm. Consequently, the ERA-Interim soil moisture product has both high absolute and temporal accuracy at depths of 7–28 cm, and the ERA-Interim soil moisture product can nicely capture temporal dynamics at all the evaluated soil level depths, except for the depth of 28–100 cm during the winter months. The contributions of terrain, vegetation cover, and soil texture to the model error were addressed by feature importance estimations using the random forest (RF) algorithm. Results indicate that terrain features may have an impact on the model errors. It is clear that the accuracy of the ERA-Interim soil moisture can be improved by adjusting the assimilation scheme, and the results of this study are expected to provide a comprehensive understanding of the model errors and references for optimizing the model.

Temporal dynamics of soil moisture and rainfall erosivity in a tropical volcanic archipelago

Soil water availability has a strong role on vegetation conservation and biodiversity, particularly at vulnerable environments such as archipelagos, subject to significant temporal changes of climate and rainfall, which influence soil weathering and erosion processes. Few field studies on hydrology of volcanic islands in the Atlantic Ocean have been developed focusing on soil and water temporal dynamics and conservation, mainly because such studies require data with high temporal resolution, and also due to the financial costs involved with field data acquisition at such remote places. Considering the importance of soil moisture content to several hydrological processes and islands environmental sustainability, this study aimed to investigate the soil water temporal dynamics in relation to different rainfall patterns and also the rainfall erosivity and its temporal variation, and the resulting infiltration depths, during a typical hydrological period, in an experimental plot at the main watershed of Fernando de Noronha, in the Brazilian Atlantic Coast. Rainfall was recorded every 5 min, and soil moisture was intensely monitored by 16 moisture probes, installed at 10–40 cm and 40–70 cm layers, during three years, representing the typical local hydrological regime and seasons. Rainfall bursts pattern were identified and described. Experimental data allowed a hydrological model to be calibrated and validated, providing estimates of infiltration depths, which can be valuable for water resources planning and management. Hydrological patterns were determined for each erosive rainfall, depending on the precipitation peak position, as advanced, intermediate and delayed. The soil water effectiveness was also evaluated and related to the different rainfall patterns. Soil moisture is highest from April to June, close to saturation; whilst for the other months the values were close to the residual value. The rainfall erosivity in the archipelago was identified as moderate to strong, and the most frequent rainfall pattern was the advanced. Fast wetting-drying cycles during the rainfall events were observed, due to rainfall intermittency, evapotranspiration, and to soil hydraulic conductivity. It was observed the prevalence of high moisture indexes, with percentages higher than 40% (extremely effective level) for both investigated depths within the first 70 cm of soil, essential for plant water uptake. The observed rainfall erosivity highlights the importance of defining local strategies for soil and water conservation aimed at water security in the island. Based on a simulation model, which was successfully calibrated (Nash-Sutcliffe Efficiency Index NS = 0.76) and validated (NS = 0.81) for periods in the wet season, high infiltration depths have been identified, which contributes to canopy conservation in the archipelago.

Soil Moisture Monitoring in a Temperate Peatland Using Multi-Sensor Remote Sensing and Linear Mixed Effects

The purpose of this research was to use empirical models to monitor temporal dynamics of soil moisture in a peatland using remotely sensed imagery, and to determine the predictive accuracy of the approach on dates outside the time series through statistically independent validation. A time series of seven Moderate Resolution Imaging Spectroradiometer (MODIS) and Synthetic Aperture Radar (SAR) images were collected along with concurrent field measurements of soil moisture over one growing season, and soil moisture retrieval was tested using Linear Mixed Effects models (LMEs). A single-date airborne Light Detection and Ranging (LiDAR) survey was incorporated into the analysis, along with temporally varying environmental covariates (Drought Code, Time Since Last Rain, Day of Year). LMEs allowed repeated measures to be accounted for at individual sampling sites, as well as soil moisture differences associated with peatland classes. Covariates provided a large amount of explanatory power in models; however, SAR imagery contributed to only a moderate improvement in soil moisture predictions (marginal R2 = 0.07; conditional R2 = 0.7, independently validated R2 = 0.36). The use of LMEs allows for a more accurate characterization of soil moisture as a function of specific measurement sites, peatland classes and measurement dates on model strength and predictive power. For intensively monitored peatlands, SAR data is best analyzed in conjunction with peatland Class (e.g., derived from an ecosystem classification map) to estimate the spatial distribution of surface soil moisture, provided there is a ground-based monitoring network with a sufficiently fine spatial and temporal resolution to fit the LME models.

Mapping soil moisture with the OPtical TRApezoid Model (OPTRAM) based on long-term MODIS observations

The OPtical TRApezoid Model (OPTRAM) has recently been proposed for estimation of soil moisture using only optical remote sensing data. The model relies on a physical linear relationship between the soil moisture content and shortwave infrared transformed reflectance (STR) and can be parameterized universally (i.e., a single calibration for a given area) based on the pixel distribution within the STR-Normalized Difference Vegetation Index (NDVI) trapezoidal space. The main motivation for this study was to evaluate how the universal parameterization of OPTRAM works for long periods of time (e.g., several decades). This is especially relevant for uncovering the soil moisture and agricultural drought history in response to climate change in different regions. In this study, MODIS satellite observations from 2001 to 2017 were acquired and used for the analysis. Cosmic-ray neutron (CRN) soil moisture data, collected with the COsmic-ray Soil Moisture Observing System (COSMOS) at five different sites in the U.S. covering diverse climates, soil types, and land covers, were applied for evaluation of the MODIS-OPTRAM-based soil moisture estimates. The OPTRAM soil moisture estimates were further compared to the Soil Moisture Active and Passive (SMAP) (L-band), the Soil Moisture Ocean Salinity (SMOS) (L-band), and the Advanced AScatterometer (ASCAT) (C-band) soil moisture retrievals. OPTRAM soil moisture data were also analyzed for potential monitoring of agricultural drought through comparison of the OPTRAM-based Soil Water Deficit Index (OPTRAM-SWDI) with the widely-applied Crop Moisture Index (CMI). Evaluation results indicate that OPTRAM-based soil moisture estimates provide overall unbiased RMSE and R between 0.050 and 0.085 cm3 cm−3 and 0.10 to 0.70, respectively, for all investigated sites. The performance of OPTRAM is comparable with the ASCAT retrievals, but slightly less accurate than SMAP and SMOS. OPTRAM and the three microvave satellites captured CRN soil moisture temporal dynamics very well for all five investigated sites. A close agreement was observed between the OPTRAM-SWDI and CMI drought indices for most selected sites. In conclusion, OPTRAM can estimate temporal soil moisture dynamics with reasonable accuracy for a range of climatic conditions (semi-arid to humid), soil types, and land covers, and can potentially be applied for agricultural drought monitoring.

Soil moisture estimation in Ferlo region (Senegal) using radar (ENVISAT/ASAR) and optical (SPOT/VEGETATION) data

The sensitivity of the radar signal to the seasonal dynamics in the Sahel region is a considerable asset for monitoring surface parameters including soil moisture. Given the sensitivity of the radar signal to vegetation mass production, roughness and soil moisture, the main problem has been to estimate the contribution of these three parameters to the signal. This study aims to circumvent this problem by combining radar with optical data. The DMP (Dry Mater Product) extracted from SPOT data allowed to estimate vegetation mass production. Surface roughness was estimated from radar data during the dry season. Because during the dry season, radar signal is only conditioned by soil roughness in this region a Radiative Transfer Model (RTM) was used: it consists in a microwave scattering model of layered vegetation based on the first-order solution of the radiative transfer equation and it accounts for multiple scattering within the canopy, surface roughness of the soil, and the interaction between canopy surface and soil.This model was designed to account for the branch size distribution, leaf orientation distribution, and branch orientation distribution for each size. In this study, the RTM has been calibrated with ESCAT (European Radar Satellite Scatterometer) data, and has been used in order to estimate soil moisture.The results obtained have allowed to track the spatial and temporal dynamics of soil moisture on the one hand, and on the other hand the influence of geology and morphopedology on the spatial dynamics of the soil moisture variability. These results are promising despite the fact that the inversed RTM often faces difficulties to interpret the signal for saturated soils, giving an aberrant value of soil moisture more often than not.

Comparison of remotely sensed and modelled soil moisture data sets across Australia

Abstract This study compared surface soil moisture from 11 separate remote sensing and modelled products across Australia in a common framework. The comparison was based on a correlation analysis between soil moisture products and in situ data collated from three separate ground-based networks: OzFlux, OzNet and CosmOz. The correlation analysis was performed using both original data sets and temporal anomalies, and was supported by examination of the time series plots. The interrelationships between the products were also explored using cluster analyses. The products considered in this study include: Soil Moisture Ocean Salinity (SMOS; both Land Parameter Retrieval Model (LPRM) and L-band Microwave Emission of the Biosphere (LMEB) algorithms), Advanced Microwave Scanning Radiometer 2 (AMSR2; both LPRM and Japan Aerospace Exploration Agency (JAXA) algorithms) and Advanced Scatterometer (ASCAT) satellite-based products, and WaterDyn, Australian Water Resource Assessment Landscape (AWRA-L), Antecedent Precipitation Index (API), Keetch-Byram Drought Index (KBDI), Mount's Soil Dryness Index (MSDI) and CABLE/BIOS2 model-based products. The comparison of the satellite and model data sets showed variation in their ability to reflect in situ soil moisture conditions across Australia owing to individual product characteristics. The comparison showed the satellite products yielded similar ranges of correlation coefficients, with the possible exception of AMSR2_JAXA. SMOS (both algorithms) achieved slightly better agreement with in situ measurements than the alternative satellite products overall. Among the models, WaterDyn yielded the highest correlation most consistently across the different locations and climate zones considered. All products displayed a weaker performance in estimating soil moisture anomalies than the original data sets ( i.e. the absolute values), showing all products to be more effective in detecting interannual and seasonal soil moisture dynamics rather than individual events. Using cluster analysis we found satellite products generally grouped together, whereas models were more similar to other models. SMOS (based on LMEB algorithm and ascending overpass) and ASCAT (descending overpass) were found to be very similar to each other in terms of their temporal soil moisture dynamics, whereas AMSR2 (based on LPRM algorithm and descending overpass) and AMSR2 (based on JAXA algorithm and ascending overpass) were dissimilar. Of the model products, WaterDyn and CABLE were similar to each other, as were the API/AWRA-L and KBDI/MSDI pairs. The clustering suggests systematic commonalities in error structure and duplication of information may exist between products. This evaluation has highlighted relative strengths, weaknesses, and complementarities between products, so the drawbacks of each may be minimised through a more informed assessment of fitness for purpose by end users.

HydroBlocks: a field‐scale resolving land surface model for application over continental extents

AbstractLand surface spatial heterogeneity plays a significant role in the water, energy, and carbon cycles over a range of temporal and spatial scales. Until now, the representation of this spatial heterogeneity in land surface models has been limited to over simplistic schemes because of computation and environmental data limitations. This study introduces HydroBlocks – a novel land surface model that represents field‐scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs). HydroBlocks is a coupling between the Noah‐MP land surface model and the Dynamic TOPMODEL hydrologic model. The HRUs are defined by clustering proxies of the drivers of spatial heterogeneity using high‐resolution land data. The clustering mechanism allows for each HRU's results to be mapped out in space, facilitating field‐scale application and validation. The Little Washita watershed in the USA is used to assess HydroBlocks' performance and added benefit from traditional land surface models. A comparison between the semi‐distributed and fully distributed versions of the model suggests that using 1000 HRUs is sufficient to accurately approximate the fully distributed solution. A preliminary evaluation of model performance using available in situ soil moisture observations suggests that HydroBlocks is generally able to reproduce the observed spatial and temporal dynamics of soil moisture. Model performance deficiencies can be primarily attributed to parameter uncertainty. HydroBlocks' ability to explicitly resolve field‐scale spatial heterogeneity while only requiring an increase in computation of one to two orders of magnitude when compared with existing land surface models is encouraging – ensemble field‐scale land surface modelling over continental extents is now possible. Copyright © 2016 John Wiley & Sons, Ltd.

Retrieval of Both Soil Moisture and Texture Using TerraSAR-X Images

The aim of this paper is to propose a methodology combing multi-temporal X-band SAR images (TerraSAR-X) with continuous ground thetaprobe measurements, for the retrieval of surface soil moisture and texture at a high spatial resolution. Our analysis is based on seven radar images acquired at a 36° incidence angle in the HH polarization, over a semi-arid site in Tunisia (North Africa). The soil moisture estimations are based on an empirical change detection approach using TerraSAR-X data and ground auxiliary thetaprobe network measurements. Two assumptions were tested: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. By considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved. Maps of soil moisture, clay and sand percentages at the studied site are derived.

Temporal variations in soil moisture for three typical vegetation types in inner Mongolia, northern China.

Drought and shortages of soil water are becoming extremely severe due to global climate change. A better understanding of the relationship between vegetation type and soil-moisture conditions is crucial for conserving soil water in forests and for maintaining a favorable hydrological balance in semiarid areas, such as the Saihanwula National Nature Reserve in Inner Mongolia, China. We investigated the temporal dynamics of soil moisture in this reserve to a depth of 40 cm under three types of vegetation during a period of rainwater recharge. Rainwater from most rainfalls recharged the soil water poorly below 40 cm, and the rainfall threshold for increasing the moisture content of surface soil for the three vegetations was in the order: artificial Larix spp. (AL) > Quercus mongolica (QM) > unused grassland (UG). QM had the highest mean soil moisture content (21.13%) during the monitoring period, followed by UG (16.52%) and AL (14.55%); and the lowest coefficient of variation (CV 9.6-12.5%), followed by UG (CV 10.9-18.7%) and AL (CV 13.9-21.0%). QM soil had a higher nutrient content and higher soil porosities, which were likely responsible for the higher ability of this cover to retain soil water. The relatively smaller QM trees were able to maintain soil moisture better in the study area.

A Nested Ecohydrological Wireless Sensor Network for Capturing the Surface Heterogeneity in the Midstream Areas of the Heihe River Basin, China

This letter introduces the ecohydrological wireless sensor network (EHWSN), which we have installed in the middle reach of the Heihe River Basin. The EHWSN has two primary objectives: the first objective is to capture the multiscale spatial variations and temporal dynamics of soil moisture, soil temperature, and land surface temperature in the heterogeneous farmland; and the second objective is to provide a remote-sensing ground-truth estimate with an approximate kilometer pixel scale using spatial upscaling. This ground truth can be used for validation and evaluation of remote-sensing products. The EHWSN integrates distributed observation nodes to achieve an automated, intelligent, and remote-controllable network that provides superior integrated, standardized, and automated observation capabilities for hydrological and ecological processes research at the basin scale.

Soil moisture variability in a temperate deciduous forest: insights from electrical resistivity and throughfall data

In deciduous forests, soil moisture is an important driver of numerous physical, microbial, and biogeochemical processes. Therefore, characterizing the interactions between vegetation and soil moisture is critical to forecast long-term water resources and ecosystem health. However, these interactions are difficult to measure, both in time and space. Recent studies have shown the ability of electrical resistivity imaging (ERI) to characterize the spatial and temporal dynamics of soil moisture at a range of scales. However, no study has yet attempted to use ERI to describe spatiotemporal variability of soil water in relation to vegetation structure and throughfall. In this study, at a mature forest site in Michigan, USA, we captured spatial and temporal dynamics of soil moisture using weekly ERI measurements augmented with throughfall and soil temperature measurements, and a detailed vegetation survey for five adjacent quadrats. Our results show that throughout the growing season, the soil moisture gradually declined despite strong variations in cumulative monthly rainfall. This decline was occasionally halted, but not reversed, during weeks with high precipitation. Spatial variability of electrical resistivity and soil moisture was not related to soil temperature differences but showed a strong correlation with canopy variables.

Significance of scale and lower boundary condition in the 3D simulation of hydrological processes and soil moisture variability in a forested headwater catchment

• 3D-simulation of hydrology and soil moisture at two spatial and temporal resolutions. • Topsoil soil moisture dynamics and patterns well captured by all model versions. • Influence of bedrock aquifer on hydrological processes and soil moisture dynamics. • Role of bedrock for water balance is larger than that of spatio-temporal resolution. The measurement and simulation of soil moisture patterns and their spatio-temporal variability are current challenges in hydrology. This study investigated the capability of the three-dimensional model HydroGeoSphere to simulate hydrological processes, soil moisture dynamics and patterns at 25 and 100 m resolutions with daily and hourly time steps in a forested headwater catchment. All simulations reproduced discharge dynamics well, calculated a dominance of the baseflow component but missed macropore driven discharge peaks in the summer and slightly overestimated the discharge. A comparison of discharge and water balance results between daily and hourly time steps revealed considerable scaling issues of saturated conductivity values and in the model’s interception module. Temporally and spatially highly resolved soil moisture measurements were used to calibrate residual saturations and porosities at daily time steps. Therefore, all model setups simulated the long-term temporal soil moisture dynamics well, but short-term soil moisture dynamics were poorly simulated because the simulation did not take into account the effect of macropore flow. The spatial soil moisture patterns of the topsoil were well reproduced except for certain parts in the western part of the catchment. A correlation analysis revealed that the influence of the topography was overestimated in the simulated soil moisture pattern. The spatial scale dependency of all aforementioned results was small due to independent calibration. The consideration of bedrock damped discharge peaks, increased low flow and slightly improved temporal soil moisture simulation.

Improving soil moisture retrievals from a physically-based radiative transfer model

Near surface soil moisture is being estimated from space-borne passive microwave observations through inverting a physically-based radiative transfer model (RTM), the land surface microwave emission model (LSMEM) at Princeton University for the past several years. The existing retrieval scheme utilizes only the horizontal (H) polarization measurement from a single channel (10.65GHz). This physically-based approach requires a relatively large number of parameters, and it generally suffers from large biases/errors due to the difficulty in determining the correct parameters. This study characterizes these errors in order to improve the retrieval performance. Through model sensitivity analysis, this study finds that a dual polarization approach (using both horizontal and vertical polarizations) is needed to infer the correct vegetation opacity and correct polarization mixing measured by the space-borne sensor. Revisions are then made to the LSMEM formulations and soil moisture retrieval algorithm by 1) combining two vegetation parameters and one roughness parameter into one effective vegetation optical depth (VOD) value; and 2) providing an additional model equation that estimates the effective VOD from both polarizations and an initial guess of soil moisture value. The new retrieval algorithm is implemented to produce a daily 0.25° gridded soil moisture dataset based on observations from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E). Validations are performed globally against land surface model simulations and at local/point scale against in-situ data within the continental United States. The new retrievals are shown to have good and robust performance over most parts of the world in terms of reproducing the spatial and temporal dynamics of soil moisture.

Remote Sensing for Vadose Zone Hydrology—A Synthesis from the Vantage Point

Ground‐based, air‐borne, and space‐borne remote sensing techniques have evolved over the past several decades and provided many new techniques for estimating various land surface attributes at multiple scales related to mass and energy dynamics. The vadose zone, encompassing land surface, root zone, and the deeper soil profile down to the groundwater table, is a complex domain, particularly related to various hydrologic and biological processes across different scales. In this zone, spatial distributions and temporal dynamics of soil moisture and evapotranspiration (ET), including their interdependence, are critical to climate feedback, hydrology, and plant canopy health. Their temporal and spatial variability across catchments affect surface and subsurface runoff, modulates evaporation and transpiration, determines the extent of groundwater recharge and contaminant transport, and initiates or sustains feedback between the land surface and the atmosphere. With the recent development and deployment of various remote sensing platforms working with different techniques such as optical, microwave, gravitational, infrared, and other sensors, improved temporal and spatial measurement or estimates of soil moisture, evapotranspiration, soil hydraulic parameters, soil salinity, and vegetation attributes are possible. In this special section “Remote Sensing for Vadose Zone Hydrology,” 14 contributions on fundamental and applied studies using different remote sensing platforms, including satellite retrieval algorithm development, data assimilation techniques, scaling issues, ground validation, and field applications in the context of vadose zone hydrology are presented. The foci of these papers range across root zone soil moisture retrieval and variability, evapotranspiration dynamics and distribution, agricultural water management, soil hydraulic and mechanical property estimation, ecosystems assessment, land–atmosphere interaction, and land surface hazard assessment. Here we organized the summary of these papers in four overlapping sections including (i) estimation, variability, scaling, and data assimilation of soil moisture by microwave remote sensing; (ii) estimating evapotranspiration by remote sensing and water management applications; (iii) estimating vadose zone properties by remote sensing; and (iv) ground‐based soil moisture for calibration and validation of microwave remote sensing.

Towards closing the watershed nitrogen budget: Spatial and temporal scaling of denitrification

AbstractEnhanced consideration of the hydrogeomorphic template of watersheds is critical to understanding watershed nitrogen budgets. We developed a framework to estimate the spatial distribution and temporal dynamics of soil moisture and soil oxygen in surficial soils to scale nitrogen transformations for a forested watershed (Pond Branch) in Maryland, USA. We sampled soil cores in upland, hillslope hollow, riparian hollow, and riparian hummock landscape positions in different seasons for biogeochemical fluxes including measurement of N2gas produced via denitrification. We extrapolated these rates in space and time with information derived from in situ soil oxygen and soil moisture probes to scale fluxes from plots to the catchment level. We addressed three questions: (1) How important are seasonal, daily, and storm event variations in soil oxygen for denitrification? (2) How is denitrification spatially distributed through the watershed? (3) How important is denitrification to the watershed nitrogen budget? We found that microtopography within the riparian zone is a significant influence on soil oxygen dynamics and therefore redox‐sensitive biogeochemical processes such as denitrification. Riparian zone hollows (lower topographic positions) represented 0.5%–1.0% of the catchment area, but accounted for >99% of total denitrification. Interestingly, topography was a much stronger controller of oxygen than rainfall, which had little influence on temporal variation in soil oxygen levels. Spatial and temporal extrapolations of measured rates suggest that a minimum of 16%–27% of atmospheric nitrogen deposition is lost to denitrification. These results suggest that the importance of denitrification in the nitrogen budget of forested watersheds depends fundamentally on the presence of landscape elements, such as riparian hollows that function as “hot spots” of activity.

Temporal dynamics of soil moisture in a northern temperate mixed successional forest after a prescribed intermediate disturbance

Forested ecosystems may experience intermediate disturbances that involve changes of crown-scale canopy characteristics. When such changes occur, soil moisture under disturbed canopy may become either drier or wetter, depending on the interplay between small-scale hydrological processes, tree-scale vegetation function, and meteorological forcing. Understanding the contributing factors that impact small-scale soil water dynamics is vital for predicting long-term and larger-scale changes of forest hydrology following disturbances, succession, and management processes. In this study, we initiated half-hourly, three-meter deep measurements of soil moisture at four plots in a northern temperate mixed forest near the University of Michigan Biological Station. Two of the plots (one aspen- and the other oak-dominated) are located near the AmeriFlux tower; this forest area represents an undisturbed control site. Two other plots are located near the Forest Accelerated Succession Experiment (FASET) flux tower. An intermediate disturbance was prescribed in this area through stem girdling of all canopy-dominant, early successional aspen and birch trees to simulate the anticipated large-scale succession process in the Upper Great Lakes area. The data collected at the four plots provide observational evidence of changes in hydrological dynamics that were induced by species-specific crown-scale disturbances of the canopy structure.Data analysis reveals that the soil water storage under the girdled aspen was persistently higher, as compared to the undisturbed plots over the observational period of 2009–2011. The study argues that the larger water storage resulted from increased net precipitation and reduced transpiration during growing seasons following the girdling operation. These processes “outcompeted” the presumably enhanced interception and transpiration by understory plants as well as increased soil evaporation. Additionally, surface soil layer at the disturbed plot exhibited highest temporal variability among all monitored plots. The moisture profiles at the four plots were different, with the disturbed plot exhibiting relatively wetter shallow soil layers. Furthermore, water loss at the disturbed plot was concentrated in shallower soil layers, signifying a shift of uptake and/or change of dominant processes.

Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table

Many of the hydrological and ecological functions of alluvial flood plains within watersheds depend on the water flow exchanges between the vadoze soil zone and the shallow groundwater. The water balance of the soil in the flood plain is investigated, in order to evaluate the main hydrological processes that underlie the temporal dynamics of soil moisture and groundwater levels. The soil moisture and the groundwater level in the flood plain were monitored continuously for a three-year period. These data were integrated with the results derived from applying a physically-based numerical model which simulated the variably-saturated vertical water flow in the soil. The analysis indicated that the simultaneous processes of lateral groundwater flow and the vertical recharge from the unsaturated zone caused the observed water table fluctuations. The importance of these flows in determining the rises in the water table varied, depending on soil moisture and groundwater depth before precipitation. The monitoring period included two hydrological years (September 2009–September 2011). About 13% of the precipitation vertically recharged the groundwater in the first year and about 50% in the second. The difference in the two recharge coefficients was in part due to the lower groundwater levels in the recharge season of the first hydrological year, compared to those observed in the second. In the latter year, the shallow groundwater increased the soil moisture in the unsaturated zone due to capillary rise, and so the mean hydraulic conductivity of the unsaturated soil was high. This moisture state of soil favoured a more efficient conversion of infiltrated precipitation into vertical groundwater recharge. The results show that groundwater dynamics in the flood plain are an important source of temporal variability in soil moisture and vertical recharge processes, and this variability must be properly taken into account when the water balance is investigated in shallow groundwater environments. Citation Pirastru, M. and Niedda, M., 2013. Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table. Hydrological Sciences Journal, 58 (4), 898–911.

The impact of changes in the timing of precipitation on the herbaceous understorey of Mediterranean evergreen oak woodlands

Climate change scenarios for the Iberian Peninsula predict increasing temperatures and increasingly variable precipitation regimes, which will challenge the sustainability and biodiversity of Mediterranean ecosystems such as the semi-natural evergreen oak woodlands.To assess the effects of precipitation variability on productivity, species composition and vegetation gas exchange of the understorey vegetation in a typical managed cork oak woodland, a large-scale rainfall manipulation experiment was established. We studied the impacts of a change in the timing of precipitation events on this ecosystem, without altering total annual precipitation inputs. The two water manipulation treatments were: ‘weekly watering treatment’, where natural conditions were simulated with a normal dry period of 7 days, and ‘3-weekly watering treatment’, with the normal dry period increased three-fold to 21 days.Our experimental precipitation patterns resulted in significant differences in temporal soil moisture dynamics between the two treatments. Average soil water content (SWC) at 3cm depth during the growing season was 16.1±0.17% and 15.8±0.18% in the weekly and 3-weekly watering treatments, respectively, with a mere 5% increase in the variability of SWC when extending the dry period from one to three weeks. Water infiltration into deeper soil layers (>50cm) was significantly higher in the 3-weekly watering treatment as compared to the weekly watering treatment. This might be beneficial to Quercus suber, the tree component in this ecosystem, as its extensive tree root system enables water acquisition from deeper soil layers.However, manipulation of the within-season precipitation variability, with a shift to fewer, but larger rain events, without change in total precipitation amount, had no significant effect on aboveground net primary productivity (ANPP), belowground net primary productivity (BNPP) and species composition, with average values of peak biomass of 385gm−2 and 222gm−2 for ANPP and BNPP, respectively.The experimental precipitation patterns did not result in significant differences in the vegetation gas exchange between the two watering treatments. The CO2 and H2O exchange parameters correlated well with air temperature. In addition, evapotranspiration showed a good correlation with SWC.Incorporating the data of SWC in the conceptual ‘bucket model’ showed that, independently of the watering regime, soil water availability during the life-cycle of these annual plants did not reach severe water stress conditions, which can explain the lack of a significant treatment effect in our study. In addition, our results showed that the annual plant community in these Mediterranean ecosystems is well adapted to short-term drought, through their phenological patterns and physiological adaptations.

Spatial and temporal dynamics of soil moisture in a Mediterranean mountain area (Vallcebre, NE Spain)

ABSTRACTKnowledge of soil moisture dynamics at reasonable temporal and spatial resolutions is required to improve hydrological understanding and modelling. However, in the Mediterranean area, considered as one of the most vulnerable areas to global change, there is a severe lack of detailed soil moisture data sets. The objective of this study is to investigate the inter‐annual and intra‐annual spatial and temporal distributions of soil moisture in a Mediterranean mountain area, using the detailed hydrological data set gathered in the Vallcebre Research catchments (NE Spain). With the use of time‐domain reflectometry, soil moisture was measured weekly between 1998 and 2003 at eight representative profiles. Time series of soil moisture showed a clear seasonal pattern. Results obtained revealed that soil moisture on hillslopes under forest cover was lower than in downslope areas covered with grasses. However, differences were not persistent through the year but were minimal during the driest and wettest conditions and maximal during the drying and wetting‐up periods. During the wetting‐up and drying‐down periods, the soil moisture distribution depended mainly on local controls. However, during wet conditions, soil moisture patterns were controlled by nonlocal factors that limited the vegetation‐related variability of soil moisture. In this mountain area, forest cover is likely to increase as the climate changes, which will most probably reduce the average soil moisture at the catchment scale as well as its spatial variability. These changes may ultimately be seen as a threat to the future of water resources in this area. Copyright © 2012 John Wiley & Sons, Ltd.