Variability Of Surface Soil Moisture Research Articles

Spatial and temporal variations in surface soil moisture and vegetation cover in the Loess Plateau from 2000 to 2015

The “Grain for Green” project utilizes large-scale revegetation to improve the local environment in the Loess Plateau. Understanding the trends in the variations in soil moisture content (SMC) and vegetation after the implementation of this project is necessary. This study examined the spatial and temporal variations in SMC and vegetation cover in the Loess Plateau after 1999. Furthermore, interactions between SMC and vegetation cover (e.g., spatial distribution and temporal variation) were assessed. The results of this study showed that (1) the SMC and vegetation cover increased in most of the Loess Plateau from 2000 to 2015; (2) both SMC and vegetation cover are predicted to decrease after 2015; (3) the increase in precipitation promoted SMC in the northwestern region, but the impact on vegetation cover was not significant; (4) the spatial variation in SMC exhibited a positive correlation with the spatial variation in vegetation cover, however, the difference in their cycle of change indicated that the interaction between SMC and vegetation cover varied over time. The most important results indicated that SMC and vegetation cover have begun to decrease since 2015.

Regional co-variability of spatial and temporal soil moisture–precipitation coupling in North Africa: an observational perspective

Abstract. The magnitude and sign of soil moisture–precipitation coupling (SMPC) is investigated using a probability-based approach and 10 years of daily microwave satellite data across North Africa at a 1∘ horizontal scale. Specifically, the co-existence and co-variability of spatial (i.e. using soil moisture gradients) and temporal (i.e. using soil moisture anomaly) soil moisture effects on afternoon rainfall is explored. The analysis shows that in the semi-arid environment of the Sahel, the negative spatial and the negative temporal coupling relationships do not only co-exist, but are also dependent on one another. Hence, if afternoon rain falls over temporally drier soils, it is likely to be surrounded by a wetter environment. Two regions are identified as SMPC “hot spots”. These are the south-western part of the domain (7–15∘ N, 10∘ W–7∘ E), with the most robust negative SMPC signal, and the South Sudanese region (5–13∘ N, 24–34∘ E). The sign and significance of the coupling in the latter region is found to be largely modulated by the presence of wetlands and is susceptible to the number of long-lived propagating convective systems. The presence of wetlands and an irrigated land area is found to account for about 30 % of strong and significant spatial SMPC in the North African domain. This study provides the first insight into regional variability of SMPC in North Africa, and supports the potential relevance of mechanisms associated with enhanced sensible heat flux and mesoscale variability in surface soil moisture for deep convection development.

Impact of Surface Soil Moisture Variations on Radar Altimetry Echoes at Ku and Ka Bands in Semi-Arid Areas

Radar altimetry provides information on the topography of the Earth surface. It is commonly used for the monitoring not only sea surface height but also ice sheets topography and inland water levels. The radar altimetry backscattering coefficient, which depends on surface roughness and water content, can be related to surface properties such as surface soil moisture content. In this study, the influence of surface soil moisture on the radar altimetry echo and backscattering coefficient is analyzed over semi-arid areas. A semi-empirical model of the soil’s complex dielectric permittivity that takes into account that small-scale roughness and large-scale topography was developed to simulate the radar echoes. It was validated using waveforms acquired at Ku and Ka-bands by ENVISAT RA-2 and SARAL AltiKa respectively over several sites in Mali. Correlation coefficients ranging from 0.66 to 0.94 at Ku-band and from 0.27 to 0.96 at Ka-band were found. The increase in surface soil moisture from 0.02 to 0.4 (i.e., the typical range of variations in semi-arid areas) increase the backscattering from 10 to 15 dB between the core of the dry and the maximum of the rainy seasons.

Exploiting the synergy between SMAP and SMOS to improve brightness temperature simulations and soil moisture retrievals in arid regions

The objective of this study was to exploit the synergy between SMOS and SMAP based on vegetation optical depth (VOD) to improve brightness temperature (TB) simulations and land surface soil moisture (SM) retrievals in arid regions of the world. In the current operational algorithm of SMAP (level 2), vegetation water content (VWC) is considered as a proxy to compute VOD which is calculated by an empirical conversion function of NDVI. Avoiding the empirical estimation of VOD, the SMOS algorithm is used to retrieve simultaneously SM and VOD from TB observations. The present study attempted to improve SMAP TB simulations and SM retrievals by benefiting from the advantages of the SMOS (L-MEB) algorithm. This was achieved by using a synergy method based on replacing the default value of SMAP VOD with the retrieved value of VOD from the SMOS multi angular and bi-polarization observations of TB. The insitu SM measurements, used as reference SM in this study, were obtained from the International Soil Moisture Network (ISMN) over 180 stations located in arid regions of the world. Furthermore, four stations were randomly selected to analyze the temporal variations in VOD and SM. Results of the synergy method showed that the accuracy of the TB simulations and SM retrievals was respectively improved at 144 and 124 stations (out of a total of 180 stations) in terms of coefficient of determination (R2) and unbiased root mean squared error (UbRMSE). Analyzing the temporal variations in VOD showed that the SMOS VOD, conversely to the SMAP VOD, can better illustrate the presence of herbaceous plants and may be a better indicator of the seasonal changes in the vegetation density and biomass over the year.

Modeling Surface Soil Moisture from Microwave Remote Sensing Data in Solani River Catchment, Uttarakhand, India

The spatiotemporal variation of surface soil moisture is a key subject variable need to be assessed accurately since it plays a crucial role in partitioning of rainfall into runoff and infiltration. Active microwave remote sensing has offered prominent potential towards accurate estimation of surface soil moisture. Present study utilizes ERS-2 SAR image for estimating surface soil moisture by incorporating the effect of topography, vegetation and surface roughness over three land cover types namely; sugarcane, wheat and barren land through Multiple Linear Regression (MLR) approach. Five independent variables considered for MLR analysis include backscatter coefficient (σ0 ), local incidence angle (αi), surface roughness height (hs), Leaf Area Index (LAI) and Plant Water Content (PWC), respectively. Results indicate retrieval of soil moisture within ± 20% accuracy for all the three land cover types with higher accuracy for barren land (i.e. R2 ~ 0.78 and RMSE = 1.31) as compared to the other two land cover types (i.e. sugarcane; R2 ~ 0.67 and RMSE = 3.60 and wheat; R2 ~ 0.72 and RMSE = 1.94). The present study reveals the effectiveness of MLR approach in the retrieval of surface soil moisture using fewer numbers of variables.

Preliminary validation of two temporal parameter-based soil moisture retrieval models using a satellite product and in situ soil moisture measurements over the REMEDHUS network

ABSTRACTThis study aims to preliminarily validate two newly developed temporal parameter-based surface soil moisture (SSM) retrieval models, namely the mid-morning model and daytime model, using both microwave satellite soil moisture product and in situ SSM measurements over a well-organized soil moisture network named REd de MEDición de la HUmedad del Suelo (REMEDHUS) in Spain. Ground SSM measurements and geostationary satellite observations were primarily implemented to obtain the model coefficients for the two SSM retrieval models for each cloud-free day. These model coefficients were subsequently used to estimate SSM using the Meteosat Second Generation products over the study area. Preliminary verification using both a satellite product and in situ SSM measurements demonstrated that SSM variation can be well detected by both SSM retrieval models. Specifically, a generally similar accuracy (coefficient of determination R2: 0.419–0.379, root mean square error: 0.046–0.051 m3 m−3, Bias: −0.020 to −0.025 m3 m−3) was found for the mid-morning model and the daytime model with the microwave missions based climate change initiative SSM product, respectively. Moreover, except for the comparable R2 (0.614–0.675), a better accuracy (Bias: 0.032–0.044 m3 m−3, RMSE: 0.043–0.050 m3 m−3) are achieved for the daytime model and the mid-morning model with network SSM measurements, respectively. These results indicate that the daytime model exhibited generally comparable or better accuracy than that of the mid-morning model over the study area. This study has strengthened the feasibility of using multi-temporal information derived from the geostationary satellites to estimate SSM in future research.

Spatiotemporal variability of surface-soil moisture of land uses in the middle reaches of the Heihe River Basin, China

Surface-soil water at the active interface of the soil and atmosphere varies strongly both temporally and spatially. Understanding the nature of the variation is necessary for improving the efficiency and management of the use of water resources. We used classical statistical and geostatistical methods to analyze a high density of measurements of surface-soil water contents (SWCs) to determine the spatiotemporal variability of SWC for three types of land uses in the middle reaches of the Heihe River Basin: desert, woodland, and farmland. Surface-soil moisture varied seasonally with the distribution of the precipitation. The mean surface SWCs for the desert, woodland, and farmland sites were 4.2, 10.2, and 17.4 %, respectively. The spatial variation and coefficients of variation (CVs) of the moisture in the surface soil were moderate to high and differed significantly (P < 0.05) among the land uses in the order desert < farmland < woodland. The CVs of the spatial variation of moisture decreased as mean SWC increased at the woodland and farmland sites but increased with mean SWC at the desert site. The semivariation parameters nugget, sill, and range were all in the order desert < woodland < farmland. Soil moisture sampling densities or spacings should be determined under different soil-water conditions and land-use types based on the semivariation parameters. Soil mechanical composition and mean soil moisture conditions are the primary factors affecting the spatial variation of surface SWC. Land-use type, cultivation management, and irrigation also have an effect on the spatial moisture heterogeneity.

Estimation of soil moisture using multispectral and FTIR techniques

Soil moisture is a key capricious in hydrological process, the accessibility of moisture content in soil reins the mechanism amid the land surface and atmospheric progression. Precise soil moisture determination is influential in the weather forecast, drought monitoring, hydrological modeling, agriculture management and policy making. The aims of the study were to estimate soil moisture through remotely sensed data (FTIR & optical) and establishment of the results with field measured soil moisture data. The ground measurements were carried out in 0–15cm depth. Permutation of normalized difference vegetation index (NDVI) and land surface temperature (LST) were taken to derive temperature vegetation dryness index (TVDI) for assessment of surface soil moisture. Correlation and regression analysis was conceded to narrate the TVDI with in situ calculated soil moisture. The spatial pattern of TVDI shows that generally low moisture distribution over study area. A significant (p<0.05) negative correlation of r=0.79 was found between TVDI and in situ soil moisture. The TVDI was also found adequate in temporal variation of surface soil moisture. The triangle method (TVDI) confers consistent appraisal of moisture situation and consequently can be used to evaluate the wet conditions. Furthermore, the appraisal of soil moisture using the triangular method (TVDI) was possible at medium spatial resolutions because the relationship of soil moisture with LST and NDVI lends an eloquent number of representative pixels for developing a triangular scatter plot.

Playa Soil Moisture and Evaporation Dynamics During the MATERHORN Field Program

We present an analysis of field data collected over a desert playa in western Utah, USA in May 2013, the most synoptically active month of the year, as part of the Mountain Terrain Atmospheric Modeling and Observations (MATERHORN) program. The results show that decreasing surface albedo, decreasing Bowen ratio and increasing net radiation with increasing soil moisture sustained a powerful positive feedback mechanism promoting large evaporation rates immediately following rain events. Additionally, it was found that, while nocturnal evaporation was negligible during dry periods, it was quite significant (up to 30 % of the daily cumulative flux) during nights following rain events. Our results further show that the highest spatial variability in surface soil moisture is found under dry conditions. Finally, we report strong spatial heterogeneities in evaporation rates following a rain event. The cumulative evaporation for the different sampling sites over a five-day period varied from \(\approx \)0.1 to \(\approx \)6.6 mm. Overall, this study allows us to better understand the mechanisms underlying soil moisture dynamics of desert playas as well as evaporation following occasional rain events.

Spatio-temporal variation of surface soil moisture over the Yellow River basin during 1961–2012

Abstract. Soil moisture plays a significant role in agricultural and ecosystem development. However, in the real world soil moisture data are very limited due to many factors. VIC-3L model, as a semi-distribution hydrological model, can potentially provide valuable information regarding soil moisture. In this study, daily soil moisture contents in the surface soil layer (0–10 cm) of 1500 grids at 0.25 × 0.25 degree were simulated by the VIC-3L model. The Mann-Kendall trend test and Morlet wavelet analysis methods were used for the analysis of annual and monthly average surface soil moisture series. Results showed that the trend of surface soil moisture was not obvious on the basin scale, but it varied with spatial and temporal conditions. Different fluctuation amplitudes and periods of surface soil moisture were also discovered on the Yellow River basin during 1961 to 2012.

Spatiotemporal variability of hydrologic soil properties and the implications for overland flow and land management in a peri-urban Mediterranean catchment

Summary Planning of semi-urban developments is often hindered by a lack of knowledge on how changes in land-use affect catchment hydrological response. The temporal and spatial patterns of overland flow source areas and their connectivity in the landscape, particularly in a seasonal climate, remain comparatively poorly understood. This study investigates seasonal variations in factors influencing runoff response to rainfall in a peri-urban catchment in Portugal characterized by a mosaic of landscape units and a humid Mediterranean climate. Variations in surface soil moisture, hydrophobicity and infiltration capacity were measured in six different landscape units (defined by land-use on either sandstone or limestone) in nine monitoring campaigns at key times over a one-year period. Spatiotemporal patterns in overland flow mechanisms were found. Infiltration-excess overland flow was generated in rainfalls during the dry summer season in woodland on both sandstone and limestone and on agricultural soils on limestone due probably in large part to soil hydrophobicity. In wet periods, saturation overland flow occurred on urban and agricultural soils located in valley bottoms and on shallow soils upslope. Topography, water table rise and soil depth determined the location and extent of saturated areas. Overland flow generated in upslope source areas potentially can infiltrate in other landscape units downslope where infiltration capacity exceeds rainfall intensity. Hydrophilic urban and agricultural-sandstone soils were characterized by increased infiltration capacity during dry periods, while forest soils provided potential sinks for overland flow when hydrophilic in the winter wet season. Identifying the spatial and temporal variability of overland flow sources and sinks is an important step in understanding and modeling flow connectivity and catchment hydrologic response. Such information is important for land managers in order to improve urban planning to minimize flood risk.

Spaceborne altimetry and scatterometry backscattering signatures at C- and Ku-bands over West Africa

This study presents a comprehensive comparison of radar signatures acquired over West Africa (between latitudes 0°–25°N and longitudes 5°W–25°E) at both C- and Ku-bands using nadir-looking altimeters (35-day orbital period ENVISAT RA-2 over 2003–2010 and 10-day orbital period Jason-2 over mid-2008–2011) and side-looking scatterometers (QuikSCAT over 2003–2009 and ASCAT over mid-2008–2011) that covers the major bioclimatic zones, soil and vegetation types encountered in this region.The backscattering coefficient's time series measured by both radar instruments are generated over regional transects and local sites. Meridian transects from the wet tropics to the arid regions of the Sahara desert demonstrate the spatial and temporal changes of the radar response over the West African bioclimatic gradient in terms of surface roughness, land cover and soil wetness. Nadir-looking altimetry appears more sensitive to variations of surface soil moisture than side-looking scatterometry at both C- and Ku-bands. In contrast, the impact of vegetation on the backscattered signals is found to be lower for nadir-looking instruments compared to side-looking ones.

Monitoring Spatiotemporal Surface Soil Moisture Variations During Dry Seasons in Central America With Multisensor Cascade Data Fusion

Soil moisture is a critical element in the hydrological cycle, which is intimately tied to agriculture production, ecosystem integrity, and hydrological cycle. Point measurements of soil moisture samples are laborious, costly, and inefficient. Remote sensing technologies are capable of conducting soil moisture mapping at the regional scale. The advanced microwave scanning radiometer on earth observing system (AMSR-E) provides global surface soil moisture (SSM) products with the spatial resolution of 25 km which is not sufficient enough to meet the demand for various local-scale applications. This study refines AMSR-E SSM data with normalized multiband drought index (NMDI) derived from the moderate resolution imaging spectroradiometer (MODIS) data to provide fused SSM product with finer spatial resolution that can be up to 1 km. Practical implementation of this data fusion method was carried out in Central America Isthmus region to generate the SSM maps with the spatial resolution of 1 km during the dry seasons in 2010 and 2011 for various agricultural applications. The calibration and validation of the SSM maps based on the fused images of AMSR-E and MODIS yielded satisfactory agreement with in situ ground truth data pattern wise.

Evaluating the influence of surface soil moisture and soil surface roughness on optical directional reflectance factors

SummaryFine‐scale information on soil surface roughness (SSR) is needed for calculating heat budgets, monitoring soil degradation and parameterizing surface runoff and sediment transfer models. Previous work has demonstrated the potential of using hyperspectral, hemispherical conical reflectance factors (HCRFs) to retrieve the SSR of different soil crusting states. However, this was achieved by using dry soil surfaces, generated in controlled laboratory conditions. The primary aim of this study was therefore to test the impact that in situ variations in surface soil moisture (SSM) content had on the ability of directional reflectance factors to characterize SSR conditions. Five soil plots (20 cm × 20 cm in area) representing different agricultural conditions were subjected to different durations of natural rainfall to produce a range of different levels of SSR. The values of SSM varied from 8.7 to 20.1% across all soil plots. Point laser data (4‐mm sample spacing) were geostatistically analysed to give a spatially‐distributed measure of SSR, giving sill variance values from 3.2 to 23.0. The HCRFs from each soil state were measured using a ground‐based hyperspectral spectroradiometer for a range of viewing zenith angles from extreme forward‐scatter (θr = −60°) to extreme back‐scatter (θr = +60°) at a 10° sampling resolution in the solar principal plane. The results showed that despite a large range of SSM values, forward‐scattered reflectance factors exhibited a very strong relationship with SSR (R2 = 0.84 at θr = −60°). Our findings demonstrate the operational potential of HCRFs for providing spatially‐distributed SSR measurements, across spatial extents containing spatio‐temporal variations in SSM content.

Trajectory based detection of forest-change impacts on surface soil moisture at a basin scale [Poyang Lake Basin, China

Surface soil moisture plays a critical role in hydrological processes, but varies with both natural and anthropogenic influences. Land cover change unavoidably alters surface property and subsequent soil moisture, and its contribution is yet hard to isolate from the mixed influences. In combination with trajectory analysis, this paper proposes a novel approach for detection of forest-change impacts on surface soil moisture variation with an examination over the Poyang Lake Basin, China from 2003 to 2009. Soil moisture in permanent forest trajectory represents a synthetic result of natural influences and serves as a reference for isolating soil moisture alternation due to land cover change at a basin scale. Our results showed that soil moisture decreased in all forest trajectories, while the absolute decrease was lower for permanent forest trajectory (2.53%) than the whole basin (2.61%), afforestation trajectories (2.70%) and deforestation trajectories (2.81%). Moreover, afforestation has a high capacity to hold more soil moisture, but may take more than 6 years to reach its maximum capacity. Soil moisture increased from 14.09% to 14.94% for the afforestation trajectories with tree aging from 1 to 6 years. Finally, land cover change may affect soil moisture alternation toward different transformation directions. Absolute soil moisture decreases by 0.08% for the whole basin, 0.17% for afforestation and 0.28% for deforestation trajectories, accounting for 3.13%, 6.47% and 10.07% of the total decrease in soil moisture. More specifically, the transformation from woody Savannas, cropland and other lands to forest generated absolute soil moisture deceases of 0.20%, −0.08% and 0.27%, accounting for 7.26%, −3.52% and 9.57% of the decreases. On the other hand, the reverse transformation generated soil moisture deceases of 0.29%, 0.21% and 0.35%, accounting for 10.43%, 7.69% and 12.14% of the total decrease. Our findings should be valuable for evaluating the impacts of land cover change on soil moisture alternation and promoting effective management of water resources.

The effect of fractional vegetation cover on the relationship between EVI and soil moisture in non-forest regions

Surface soil moisture (SM) is critical for terrestrial ecological and hydrological processes, particularly in non-forested arid and semi-arid regions. On the large scale, the relationship of vegetation greenness to SM is often considered to be a reflection of spatiotemporal changes in SM. In this study, we investigated the empirical relationship between the remotely sensed enhanced vegetation index (EVI) and in situ SM, using observations from 16 Ameriflux sites in non-forest regions. The linear relationship between SM and EVI could be classified by the fractional vegetation cover (FVC), and the ratio of EVI to SM became higher as the FVC increased. In addition, multiple regressions for SM using both EVI and FVC showed a higher correlation than that of the single regressions using EVI or FVC separately. We found that EVI and FVC were critical parameters in representing the SM variations related with the surface vegetation changes, but further studies are necessary before the relationship can be applied.

Freeze/thaw and soil moisture effects on wind erosion

Wind erosion is very pronounced in semiarid regions during late winter–early spring and has major impacts on regional desertification and agriculture. In order to identify the effects of freeze/thaw and soil moisture on wind erosion, wind tunnel experiments were conducted to compare wind erosion effects under various soil moisture gradients in frozen and thawed soil. The variation of surface soil moisture after wind erosion and the effective soil particle size distribution was tested to explain the differences. The results showed that surface soil moisture content decreased in thawed soil and increased in frozen soil after wind erosion. The mean weight diameter, which increased with increasing soil moisture, was smaller in thawed soil than in frozen soil. The wind-driven sediment flux of frozen and thawed soil both decreased with increasing moisture, owing to the heavier soil particle weight and stronger interparticle bonding forces. The critical soil moisture content for suppressing wind erosion was around 2.34% for frozen soil and around 2.61% for thawed soil. The wind-driven sediment flux of thawed soil was always larger than that of frozen soil at the same moisture content, but this difference became negligible at moisture contents above 3.38%. We may speculate that wind erosion will be more severe in the future because of the lower soil moisture content and fewer soil freezing days as a result of global warming.

Spatio-temporal variability in remotely sensed surface soil moisture and its relationship with precipitation and evapotranspiration during the growing season in the Loess Plateau, China

The distribution and variability of surface soil moisture at regional scales is still poorly understood in the Loess Plateau of China. Spatial and temporal dynamics of surface soil moisture is important due to its impact on vegetation growth and its potential feedback to atmospheric and hydrologic processes. In this study, we analyzed surface soil moisture dynamics and the impacts of precipitation and evapotranspiration on surface soil moisture using remote sensing data during the growing season in 2011 for the Loess Plateau, which contain surface soil moisture, precipitation, vegetation index and evapotranspiration. Results indicate that the areas with low surface soil moisture are mainly located in the semi-arid region. Under dry surface soil moisture, evapotranspiration temporal persistence has a higher positive correlation (0.537) with surface soil moisture temporal persistence, and evapotranspiration is very sensitive to surface soil moisture. But under wet surface soil moisture regime, surface soil moisture temporal persistence has a higher negative correlation (-0.621) with evapotranspiration temporal persistence. Correlation of surface soil moisture and monthly precipitation, evapotranspiration and vegetation index illustrated that precipitation was a significant factor influencing surface soil moisture spatial variance. The correlation coefficients between monthly surface soil moisture and precipitation was varied in different climatic regions, which was 0.304 in arid, 0.364 in semi-arid, 0.490 in transitional and 0.300 in semi-humid regions. Surface soil moisture is more sensitive to precipitation, evapotranspiration, in transitional regions between dry and wet climates.

Patterns and drivers ofAraucaria araucanaforest growth along a biophysical gradient in the northern Patagonian Andes: Linking tree rings with satellite observations of soil moisture

Araucaria araucana (Araucaria) is a long-lived conifer growing along a sharp west–east biophysical gradient in the Patagonian Andes. The patterns and climate drivers of Araucaria growth have typically been documented on the driest part of the gradient relying on correlations with meteorological records, but the lack of in situ soil moisture observations has precluded an assessment of the growth responses to soil moisture variability. Here, we use a network of 21 tree-ring width chronologies to investigate the spatiotemporal patterns of tree growth through the entire gradient and evaluate their linkages with regional climate and satellite-observed surface soil moisture variability. We found that temporal variations in tree growth are remarkably similar throughout the gradient and largely driven by soil moisture variability. The regional spatiotemporal pattern of tree growth was positively correlated with precipitation (r = 0.35 for January 1920–1974; P < 0.01) and predominantly negatively correlated with temperature (r = −0.38 for January–March 1920–1974; P < 0.01) during the previous growing season. These correlations suggest a temporally lagged growth response to summer moisture that could be associated with known physiological carry-over processes in conifers and to a response to moisture variability at deeper layers of the rooting zone. Notably, satellite observations revealed a previously unobserved response of Araucaria growth to summer surface soil moisture during the current rather than the previous growing season (r = 0.65 for 1979–2000; P < 0.05). This new response has a large spatial footprint across the mid-latitudes of the South American continent (35°–45°S) and highlights the potential of Araucaria tree rings for palaeoclimatic applications. The strong moisture constraint on tree growth revealed by satellite observations suggests that projected summer drying during the coming decades may result in regional growth declines in Araucaria forests and other water-limited ecosystems in the Patagonian Andes.

The role of vegetation and soil properties on the spatio-temporal variability of the surface soil moisture in a maize-cropped field

• Surface soil moisture dynamic is analysed in a cropped field. • The role of soil and crop properties is quantitatively evaluated. • Strong seasonality of the controls depending on the mean soil moisture content. • Crop seasonality is explicitly considered and it improves the correlations analysis. • Crop affects directly and through interactions in dry and intermediate condition. Soil moisture dynamics are affected by complex interactions among several factors. Understanding the relative importance of these factors is still an important challenge in the study of water fluxes and solute transport in unsaturated media. In this study, the spatio-temporal variability of surface soil moisture was investigated in a 10 ha flat cropped field located in northern Italy. Soil moisture was measured on a regular 50 × 50 m grid on seven dates during the growing season. For each measurement campaign, the spatial variability of the soil moisture was compared with the spatial variability of the soil texture and crop properties. In particular, to better understand the role of the vegetation, the spatio-temporal variability of two different parameters – leaf area index and crop height – was monitored on eight dates at different crop development stages. Statistical and geostatistical analysis was then applied to explore the interactions between these variables. In agreement with other studies, the results show that the soil moisture variability changes according to the average value within the field, with the standard deviation reaching a maximum value under intermediate mean soil moisture conditions and the coefficient of variation decreasing exponentially with increasing mean soil moisture. The controls of soil moisture variability change according to the average soil moisture within the field. Under wet conditions, the spatial distribution of the soil moisture reflects the variability of the soil texture. Under dry conditions, the spatial distribution of the soil moisture is affected mostly by the spatial variability of the vegetation. The interaction between these two factors is more important under intermediate soil moisture conditions. These results confirm the importance of considering the average soil moisture conditions within a field when investigating the controls affecting the spatial variability of soil moisture. This study highlights the importance of considering the spatio-temporal variability of the vegetation in investigating soil moisture dynamics, especially under intermediate and dry soil moisture conditions. The results of this study have important implications in different hydrological applications, such as for sampling design, ranking stability application, indirect measurements of soil properties and model parameterisation.