Spatial Distribution Of Soil Moisture Research Articles

Reforestation Will Lead to a Long-Term Downward Trend in the Water Content of the Surface Soil in a Semi-Arid Region

The spatial distribution of soil moisture is a critical determinant for the success of vegetation restoration initiatives in semi-arid and arid regions. The Qilian Mountains, situated within a semi-arid zone in China, have been subject to significant water-induced soil erosion, which has led to extensive restoration activities, predominantly utilizing the species P. crassifolia. However, the interconnections between soil moisture and various land cover types within this region remain unclear, presenting challenges to effective woodland rehabilitation. This study examines the surface soil moisture dynamics in afforested areas with varying ages of plantation to determine the influence of tree planting on the moisture content of the upper soil layer. It investigates the characteristics and temporal patterns of surface soil moisture as the age of the plantation increases. The findings indicate that: (1) soil moisture levels follow a descending sequence from natural forest, through shrubland and grassland, to planted forest and mixed forest, with statistically significant differences observed between natural and mixed forests (p < 0.05); (2) young afforested areas (less than 50 years old) have lower soil moisture levels compared to natural forests, shrublands, or grasslands, and the ecohydrological impacts of afforestation become apparent with a temporal delay; and (3) the analysis using Generalized Additive Mixed Models (GAMM) and the application of Kriging interpolation to determine the spatial distribution of soil moisture reveals that in semi-arid and arid regions, several factors have a pronounced a non-linear relationship with the moisture content of the surface soil. These factors include the duration of afforestation, the position on the lower slope, the presence of shade on the slope, and the scale at which the study is conducted. Therefore, a comprehensive understanding of the dynamics of soil water content is essential to prevent the potential failure of artificially established forests due to inadequate soil moisture in their later stages.

Analysis of Effects of Spatial Distributed Soil Properties and Soil Moisture Behavior on Hourly Streamflow Estimate through the Integration of SWAT and LSM

This study addresses the challenge of accurately estimating hourly flow and soil moisture by integrating the Soil and Water Assessment Tool (SWAT) with a Land Surface Model (LSM). Our approach enhances SWAT by incorporating spatially distributed soil properties and a physically-based soil moisture process, using the Noah LSM for hourly soil moisture estimation. This integration captures spatial variations in soil moisture and hydraulic properties from remote sensing across the watershed. The parameter sensitivity analysis and the calibration of hourly flow were significantly impacted by the physically-based hourly soil moisture routing and the incorporation of spatially distributed soil properties. Consequently, the modified SWAT model showed improved accuracy in hourly flow simulations for long-term and multiple rainfall events. Validation results showed significant improvements, with Coefficient of Determination (R2) and Nash and Sutcliffe Efficiency (NSE) increasing by 25.95% and 33.3%, respectively, and Percent Bias (PBIAS) decreasing by 85.8%. Notably, the average error for peak flows across eight events decreased by 49%. These findings highlight the importance of initializing soil parameters based on spatial soil moisture distribution and incorporating physical process-based moisture routing to enhance hourly flow simulation accuracy. Future research should focus on validating the physical feasibility of the soil parameter set in the study area with detailed hourly flow and soil moisture data and exploring its applicability in various regions. This study provides valuable insights for the scientific community, water resources, and agricultural decision-makers regarding integrated modeling of soil moisture and hourly flow, which can inform dam operation management, disaster planning, and crop yield improvement.

Estimation of spatial distribution of soil moisture on steep hillslopes by state-space approach (SSA)

Soil moisture is a critical variable that quantifies precipitation, floods, droughts, irrigation, and other factors with regard to decision-making and risk evaluation. An accurate prediction of soil moisture dynamics is important for soil and environmental management. However, the complex topographic condition and land use in hilly and mountainous areas make it a challenge to monitor and predict soil moisture dynamics in these areas. In this study, the determinants of soil moisture variability were determined by structural equation modeling, and then an attempt was made to estimate the spatial distribution of soil moisture content on steep hillslope using the state-space method. Herein, soil moisture at different depths (0–10, 10–20, and 20–30 cm) was monitored by portable time-domain reflectometer (TDR) along this hillslope (100 m × 180 m). It showed that the spatial variability of soil moisture decreased with increasing soil wetness, primarily in the topsoil (0–10 cm). Soil moisture was correlated with elevation (r = 0.28, 0.50, and 0.28), capillary porosity (r = 0.06, 0.37, and 0.28), soil texture (r for Clay: 0.20, 0.24, and 0.16; r for Sand: −0.25, −0.18, and −0.28), organic carbon (r = −0.31, −0.08, and 0.10) and land use (r = −0.01, 0.28, and 0.24) under different conditions (dry, moderate, and wet). Among these determinants, elevation made direct contributions to soil moisture variation, especially under moderate conditions, while land use made its impacts by altering soil texture. It is encouraging that the state-space approach yielded precise and cost-effective predictions of soil moisture dynamics along this steep hillslope since it gives the minimum root-mean-square error (RMSE) and Akaike information criterion (AIC). Moreover, soil organic carbon (AIC = −4.497, RMSE = 0.104, R2 = 0.899), rock fragment contents (AIC = −4.366, RMSE = 0.111, R2 = 0.878), and elevation (AIC = −3.693, RMSE = 0.156, R2 = 0.629) effectively anticipated the spatial distribution of soil moisture under dry, moderate, and wet conditions, respectively. This study confirms the efficacy of the state-space approach as a valuable tool for soil moisture prediction in areas characterized by complex and spatially heterogeneous conditions.

Modeling the weight moisture content of soils in Anabar tundra using ground-based research and remote sensing data of the earth

Presently, the climate is warming, with average annual temperatures rising every year, and the Arctic remaining one of the most vulnerable regions. This has a noticeable effect on the northern forests, which leads to the displacement of the tundra zone. Assessing the consequences of a projected increase in air temperature under climate change conditions requires spatial and instant monitoring of hard-to-reach areas. In the last few years, the use of remote sensing techniques and combinations of satellite imagery to calculate vegetation indices has generated great interest in obtaining high-definition ground data. The article presents the results of modeling soil moisture in Anabar tundra, which is located in the north-west of Yakutia. The study was conducted on the border of tundra and forest tundra in three reference areas (tundra, tundra young forest, tundra indigenous forest). The simulation is presented by comparing the field data and the normalized difference index of humidity NDMI. The NDMI index uses the NIR and SWIR channels, calculates a multi-channel raster object and creates a raster image with index values from -1 to 1, which show the humidity level with a spatial resolution of 10 meters. The data showed that the value of humidity pixels according to NDMI in the tundra zone is 0.04, in the tundra young forest is 0.09 and, in the tundra, native forest is 0.15. It was found that the index data correlated with field humidity data obtained from a depth of 0.2 m. A comparison of remote sensing decryption data with field data made it possible to simulate the spatial distribution of soil moisture over the vast study area by extrapolation.

Long-Term Characteristics of Surface Soil Moisture over the Tibetan Plateau and Its Response to Climate Change

Soil moisture over the Tibetan Plateau (TP) can affect hydrological cycles on local and remote scales through land–atmosphere interactions. However, TP long-term surface soil moisture characteristics and their response to climate change are still unclear. In this study, we firstly evaluate two satellite-based products—SSM/I (the Special Sensor Microwave Imagers) and ECV COMBINED (the Essential Climate Variable combined)—and three reanalysis products—ERA5-Land (the fifth generation of the land component of the European Centre for Medium-Range Weather Forecasts atmospheric reanalysis), MERRA2 (the second version of Modern-Era Retrospective Analysis for Research and Applications), and GLDAS Noah (the Noah land surface model driven by Global Land Data Assimilation System)—against two in situ observation networks. SSM/I and GLDAS Noah outperform the other soil moisture products, followed by MERRA2 and ECV COMBINED, and ERA5-Land has a certain degree of uncertainty in evaluating TP surface soil moisture. Analysis of long-term soil moisture characteristics during 1988–2008 shows that annual and seasonal mean soil moisture have similar spatial distributions of soil moisture decreasing from southeast to northwest. Additionally, a significant increasing trend of soil moisture is found in most of the TP region. With a non-linear machine learning method, we quantify the contribution of each climatic variable to warm-season soil moisture. It indicates that precipitation dominates soil moisture changes rather than air temperature. Pixel-wise partial correlation coefficients further show that there are significant positive correlations between precipitation and soil moisture over most of the TP region. The results of this study will help to understand the role of TP soil moisture in land–atmosphere coupling and hydrological cycles under climate change.

Viscum album subsp. austriacum (Santalaceae R. Br.) in Volyn Polissia and Zhytomyr Polissia (Ukraine): current distribution, ecology and prediction of future spread

Background. One of the subspecies of the European mistletoe, the so called pine mistletoe (Viscum album subsp. austriacum (Wiesb.) Vollm.) is a hemiparasitic, evergreen, epiphytic phanerophyte that parazitizes predominantely on the Scots pine (Pinus sylvestris L.) in Ukraine. The pine trees infested with V. album subsp. austriacum lack moisture for transpiration and photosynthesis, which reduces their primary productivity, viability and health. The purpose of this study was: 1) to determine the current distribution of V. album subsp. austriacum in Volyn and Zhytomyr Polissia regions using GIS-technology; 2) study the main taxation parameters of pine stands infested with V. album subsp. austriacum; 3) predict the possible further spread of V. album subsp. austriacum in the studied Region. Materials and Methods. The grid mapping method based on GIS technology, with a grid size of 10×10 km and 20×20 km, was used to create the map of the species distribution. The spatial distribution of soil moisture in the forest soils of Drevlyanskyi Nature Reserve was determined using satellite images and data on soil moisture from the Earth Engine Data Catalog. The taxation parameters of the mistletoe-infested pine stand (i.e., participation of the Scots pine in the stand composition, area distribution of pine stands by age, relative completeness, stand quality class, trophotope, and hygrotope) were obtained from standard taxation descriptions. Results and Discussion. The study found that V. album subsp. austriacum is more widespread in Volyn Polissia than in Zhytomyr Polissya – 87 and 20 localities respectively. It was shown that the forest plantations colonized by V. album subsp. austriacum in Drevlyansky Nature Reserve are located in areas with the lowest moisture content, with a moisture reserve of 16–70 mm in the 0–100 cm soil layer, which corresponds to dry and fresh hygrotopes. Conclusions. V. album subsp. austriacum is more widely distributed in such nature reserves of the region as Shatskyi National Nature Park and Drevlianskyi Nature Reserve, and less so in Rivne, Cheremskyi, Polissia Nature Reserves and Pripyat-Stokhid National Nature Park. In the region under study, V. album subsp. austriacum mostly affects pure pine forests aged 80‒140 years, of medium completeness (0.5‒0.7), and relatively high and high stand quality classes – Ic–II, in fresh hygrotopes – 67.3 % of the area and in fairly infertile pine site type (trophotope B) – 51.5 %. Based on the distribution of forest site types in the region and their susceptibility to V. album subsp. austriacum, the possibility of its further intensive spread in the study region can be predicted.

Applicability evaluation of three improved temperature vegetation dryness indices in High Mountain Asia

Study regionHigh Mountain Asia (Qinghai-Tibet Plateau and surrounding areas) (HMA) Study focusSoil dryness and wetness in HMA respond dramatically to global climate change. Monitoring soil moisture can provide a scientific foundation for water security in the plateau, middle, and lower basins. In this study, the applicability of the Temperature Vegetation Dryness Index (TVDI) with three improved protocols was evaluated to rectify the long-standing misuse of the TVDI method for regional drought assessment. New hydrological insights for the regionsThe unsuitability of the TVDI in alpine regions was demonstrated by the nonlinear correlation between soil moisture and the TVDI. Among the three improvement schemes, TVDIm (obtained by controlling the temperature variable) best reflected the temporal and spatial distribution of soil moisture in the growing season of HMA, especially for surface soil moisture in the middle- and high-altitude areas. The TVDI, TVDIf (obtained by controlling the wet edge), and TVDI_A (obtained by controlling the partition) are not suitable for drought evaluation in medium- and long-term regions because the correlations between the three indicators and soil moisture are inconsistent in space and time. This study provides a new method to identify whether the TVDI can effectively evaluate regional drought. It also provides a more comprehensive reference for monitoring soil moisture and evaluating dryness in alpine regions using optical remote sensing.

A Pixel-Scale Measurement Method of Soil Moisture Using Ground-Penetrating Radar

Ground validation of remote sensing soil moisture requires ground measurements corresponding to the pixel scale. To date, there is still a lack of simple, fast and reasonable methods for soil moisture measurement at pixel scale between point measurements and remote sensing observations. In this study, a measurement method of soil moisture using ground-penetrating radar (GPR) was proposed for pixel scale. We used a PulseEKKOTM PRO GPR system with 250 MHz antennas to measure soil moisture by Fixed Offset (FO) method in four 30 × 30 m2 plots chosen from the desert steppe. This study used a random combination method to analyze soil moisture measurements acquired by different numbers of GPR survey lines. The results showed that two survey lines of GPR would be sufficient under confidence level of 90% with the relative error of 7%, and four survey lines of GPR would be eligible under confidence level of 95% with the relative error of 5% for each plot. GPR measurement can reproduce the spatial distribution of soil moisture with higher resolution and smaller error, especially when two and four survey lines are designed in cross shape and grid shape, respectively. The method was applied to ground validation for the soil moisture from Landsat 8, showing the advantages of stable relative errors, less contingency and reliable evaluation when compared to point measurements. This method is fast and convenient and not limited to a certain pixel, and thus largely benefits the scale matching of remote sensing results and field measurements in ground validation.

Elucidating the composition of organic matter in water-repellent forest soils using analytical pyrolysis combined with gas chromatography–mass spectrometry (Py-GC–MS)

Soil water repellency (SWR) is an inability of soil to spontaneously absorb water. It affects the spatial distribution of soil moisture, may cause formation of preferential flow, increase surface runoff and the risk of water erosion, or affect nutrient availability for crops. Although there is a general agreement among published data that SWR is caused by hydrophobic components of soil organic matter (SOM), more comprehensive information is needed. Additionally, the link between SWR occurrence and SOM genesis has not been studied sufficiently. In this work, we analyzed SOM in water-repellent soils by pyrolysis combined with gas chromatography and mass spectrometry (Py-GC–MS). The samples were taken from two forest ecosystems in Slovakia: relatively dry pine–oak forest, located in the Záhorská nížina lowland (Záhorie), and spruce forest in the High Tatras with a colder and more humid climate. The results showed that the composition of SOM at both sites is dominated by partially decomposed residues of plant biomass. Whereas most compounds detected in the Záhorie samples were identified as pyrolysis products of lignin, the pyrolysates of the High Tatras soils originated mainly from polysaccharide-like substances. Although lauric (12:0), myristic (14:0) and palmitic (16:0) fatty acids were detected in pyrograms of water-repellent samples, the results suggest that the residues of lignin decomposition may contribute to SWR as well. Pyrolysates such as methylguaiacol, vinylguaiacol, dimethylphenol, or the methyl ester of vanillic acid are examples of less polar lignin-like moieties. Py-GC–MS data, as well as other soil properties, suggest that SWR at both sites is associated with the accumulation of certain SOM components in the topsoil. Acidic pH, higher C/N ratio and coarse soil texture prevent organic carbon stabilization in the studied soils. As a result, SOM is in great part composed of accumulated particulate residues with lignin-like origin and lipidic coatings, which contribute to SWR development during drier conditions.

Effects of multiwalled carbon nanotube and Bacillus atrophaeus application on crop root zone thermal characteristics of saline farmland

Presently, the effects of crop roots on crop root zone thermal characteristics are poorly understood, and new fertilizers are rarely considered from the perspective of changing crop root zone thermal characteristics. This study explored the effect of applying two new fertilizers, multiwalled carbon nanotubes (MWCNTs) and Bacillus atrophaeus (B. atrophaeus), on the crop root zone thermal characteristics of saline farmland soils through in situ measurements. The results showed that MWCNTs and B. atrophaeus could indirectly affect crop root zone thermal characteristics by changing the crop root growth. Combined application of MWCNTs and B. atrophaeus could promote both to induce positive effects, promote crop root growth, and significantly alleviate the adverse effects of soil salinization. The thermal conductivity and heat capacity of the shallow root zone were reduced due to the presence of crop roots, while the opposite was true in the deep root zone. For example, the thermal conductivity of the 0–5 cm rich root zone in the MWCNT treatment was 0.8174 W m−1 ·K−1, and the thermal conductivity of the poor root zone was 13.42% higher than that of the rich root zone. MWCNTs and B. atrophaeus can also change the spatial distribution of soil moisture, soil salt, and soil particle size characteristics by influencing the root-soil interactions and indirectly affecting crop root zone thermal characteristics. In addition, MWCNTs and B. atrophaeus could directly affect the root zone thermal characteristics by changing the soil properties. The higher the soil salt content was, the more obvious the effect of the MWCNTs and B. atrophaeus on the crop root zone thermal characteristics. The thermal conductivity and heat capacity of the crop root zone were positively correlated with the soil moisture content, soil salt content and soil particle specific surface area and negatively correlated with the soil particle size and the fresh and dry root weights. In summary, MWCNTs and B. atrophaeus significantly affected crop root zone thermal characteristics directly and indirectly and could adjust the temperature of the crop root zone.

Soil Moisture Retrieval by Integrating SAR and Optical Data over Winter Wheat Fields

Soil moisture (SM) retrieval over agricultural fields using synthetic aperture radar (SAR) data is often hindered by the vegetation layer and soil roughness. Most SM inversion algorithms require in situ SM data for a calibration to eliminate these two disturbing factors, while collecting in situ data is a project that consumes a lot of manpower and resources. This paper aims to tentatively develop an inversion algorithm for retrieving SM in the absence of in situ SM in areas covered by winter wheat vegetation. Based on the analysis of the data set simulated by the Michigan Microwave Canopy Scattering (MIMICS) model, an improved ratio model is proposed to remove the effect of the vegetation layer. Through the parameterization of the advanced integral equation model (AIEM), the effect of the soil roughness on the inversion of soil moisture is eliminated. The spatial distribution of SM in winter wheat fields is obtained using the Sentinel-1 SAR and Sentinel-2 images. The comparison results between the inverted SM and the in situ measured data reveal a good correlation (R = 0.85, RMSE = 0.032 cm3·cm−3), and the result confirms that the algorithm developed only based on theoretical models can also effectively monitor the spatial changes of SM over winter wheat fields.

Assessment of Spatial Heterogeneity of Soil Moisture in the Critical Zone of Gully Consolidation and Highland Protection

The Gully Consolidation and Highland Protection (GCHP) project (such as for gully head landfills), a consideration of soil and water conservation measures, has been explored and developed continuously in recent decades in the Chinese Loess Plateau. Using high-precision images taken by drones to extract the topography of the basin, the changes in vegetation and land use were also analyzed. The observation of soil moisture in the critical gully head area of the GCHP was carried out. The results indicated that the critical zones of the GCHP project implementation include the gully head landfill, the gully, and the highland farming area. The soil moisture of the landfill area was 6.91% and 23.61% higher than that of the gully and farming area, respectively, with obvious spatial heterogeneity. The soil sand content in the gully head landfill area was higher than that in the gully area and the agricultural area of the plateau. The main reason for the high soil moisture in the gully head landfill area is that the terrain at the outlet is low, and it is at the lowest point of the whole basin. Analyzing the spatial distribution of soil moisture can point out the direction for the monitoring, prevention, and treatment of geological disasters, such as landslides and debris flow, induced by water erosion. This study will help to understand in detail the spatial heterogeneity and influencing factors of soil moisture under the implementation of the GCHP and improve the GCHP project management system.

The Seasonal and Diurnal Variation Characteristics of Soil Moisture at Different Depths from Observational Sites over the Tibetan Plateau

Using observational data of soil moisture from the third Tibetan Plateau Experiment for atmospheric science (TIPEX III), the seasonal and diurnal variations characteristics of soil moisture at different depths of 5–160 cm from seven stations were analyzed, with emphasis on the comparative analysis of the differences of soil moisture between different sites and the differences of the synergistic relationship between soil moisture and temperature. The soil moisture was wet in the southeast and dry in the northwest. The studied sites were Lhari, Biru, Nyainrong, Amdo, Nagqu, Baingoin and Seng-ge Kambab in descending order, according to the soil moisture. The seasonal variation of soil moisture at the different sites showed a significant three-peak structure, which was more obvious in the shallow layer than in the deep layer. The first peak occurred from March to May, which was mainly due to the soil thawing in spring. The other two peaks corresponded to the two rainy seasons in the plateau. Soil moisture was the greatest during this rainy period. The diurnal variations of soil moisture and temperature in Amdo, Nagqu, Nyainrong and Baingoin showed a significant positive correlation in the four seasons. The soil moisture and temperature in Lhari and Biru were significantly positively correlated in winter and spring but negatively correlated in summer and autumn. The profiles of the soil moisture with depth varied greatly at different stations in different seasons. The distribution of soil water content at each observational site did not increase or decrease with depth but showed a certain high aquifer, which might be related to the types of the underlying surface and physical properties of soil. During the summer monsoon period, soil moisture in the shallow layer of 5–10 cm was higher at all observational sites. The spatial distribution of soil moisture in the plateau was more heterogeneous than that in the plain area, and only in the central part of the Tibetan Plateau, the soil moisture varied greatly from site to site. This also indicated that it was unreasonable to only use the soil moisture of several stations to represent the overall soil moisture of the region. The results provided a multi-angle observational basis for the validation of satellite data and parameterization of the numerical model of soil moisture over the Tibetan Plateau.

Response of Soil Moisture to Long-Duration Rainstorms in Three Forest Stands in Mountainous Areas of North China

Rainfall is one of the core components of the water cycle in terrestrial ecosystems and is closely related to hydrothermal balance, plant and animal growth, and stability of the whole ecosystem. Long-duration rainstorms can alter the soil structure of forest ecosystems and affect the spatial distribution of soil moisture, thus affecting the water supply from the soil to trees and being one of the factors that increase the vulnerability of forest ecosystems. In recent years, changes in rainfall patterns have normalized prolonged heavy rainfall in the mountainous areas of North China. However, there are few reports on the response of soil water at different depths to historically long rainstorms in forested areas. By quantifying the relationship between precipitation characteristics and soil water, the soil water transport patterns of Platycladus orientalis (PO), Quercus variabilis (QV) and Pinus tabuliformis (PT) during the long-duration rainstorms of 21–22 July 2012 were evaluated separately, and the roles of different plants in response to the historically long rainstorm were determined. The results showed that (1) the response of different forest stands to rainfall had a lag. Among them, the soil water of PO and PT were less affected by rainfall and could maintain a relatively stable state. (2) The soil moisture transport trend of PO was significantly greater than that of other vegetation zones and covered the whole process of rainfall. Under the three typical vegetation covers, there was a continuous zero-flux plane in the soil at each observed depth (the direction of soil moisture flow is more stable over the rainfall period), but there was no regular transport trend. (3) The root system was an important factor, influencing the differences in soil moisture response of the three vegetation types. QV had a higher average effective water recharge rate than lateral cypress and oleander and could better utilize the water recharge from storm water.

Spatial variability of soil moisture in a mining subsidence area of northwest China

The current study investigated the impact of coal mining on deep soil moisture from the perspective of the absolute value of soil moisture. A combined classical statistics and multi-dimensional geo-statistics approach was employed to analyze the temporal and spatial changes in soil moisture from 0 to 10 m in the mining face of the Nalin River No. 2 Mine in Northwest China from the perspective of spatial variability. The results of the study show that compared with the control area, the average value of soil moisture in 1- and 2-year subsidence areas decreased by 1.18% and 0.96%, respectively, whereas the coefficient of variation increased by 17.92% and 3.63%, respectively. Interpolation of soil moisture spatial distribution results showed that the spatial variability of soil moisture in the control area was less than that in the subsidence areas, and the spatial variability of soil moisture in the 2-year subsidence area was less than that in the 1-year subsidence area, indicating that mining increases the spatial variability of soil moisture and that the degree of spatial variability of soil moisture decreases as the subsidence enters the stable period. These results provide evidence for the mechanism by which coal mining subsidence affects soil moisture. Preferential flow caused by surface cracks, soil texture, the soil pore microstructure, and other factors in the coal mining subsidence area are the primary drivers of the increase in spatial variability of soil moisture.

Drainage congestion due to road network on the Kosi alluvial Fan, Himalayan Foreland

We use surface soil moisture content as a proxy to assess the effect of drainage congestion due to structural barriers on the alluvial Fan of the Kosi River on the Himalayan Foreland. We used Sentinel-1 satellite images to evaluate the spatial distribution of soil moisture in the proximity of structural barriers (i.e., road network). We applied modified Dubois and a fully connected feed-forward artificial neural network (FC-FF-ANN) models to estimate soil moisture. We observed that the FC-FF-ANN predicts soil moisture more accurately (R = 0.85, RMSE = 0.05 m3/m3, and bias = 0) as compared to the modified Dubois model. Therefore, we have used the soil moisture from the FC-FF-ANN model for further analysis. We identified the road network that traverses on the Kosi Fan horizontally, vertically, and with inclination. We create a buffer of 1 km along either side of the road. Within this, we assessed the spatial distribution of soil moisture. We observed a high concentration of soil moisture near the structural barrier, and decreases gradually as we move farther in either direction across the orientation of the road. The impact of structural barriers on the spatial distribution of soil moisture is prominent in a range between 300 to 750 m within the road buffer. This study is a step towards assessing the effect of structural interventions on drainage congestion and flood inundation.

Validation of Four Satellite-Derived Soil Moisture Products Using Ground-Based In Situ Observations over Northern China

Accurately obtaining the spatial distribution of soil moisture and its variability are the basis for the land-atmosphere interaction study. We investigated the fidelity of four satellite-based soil moisture products (AMSR2, CCI, SMAP, and SMOS) using in situ observation during the period 2019–2020. The spatial distribution and variability of different soil moisture products in northern China were analyzed for different seasons and climate zones. The satellite products showed the best performance of summer soil moisture with the bias and uncertainty of the three products (CCI, SMAP, and SMOS) being less than 0.041 and 0.097, whereas soil moisture showed a large bias in winter. For all seasons, AMSR2 and CCI demonstrated a positive bias whereas SMAP and SMOS showed a negative bias. CCI product had little bias in spring, summer, and fall in northern China, while SMAP and SMOS had the smallest bias in winter. For different climate zones, CCI product performed better in describing the temporal variability of soil moisture in arid climate zones with the correlation coefficients > 0.50 for most areas, while AMSR2 product provided a similar spatial distribution. In the eastern monsoon region, the soil moisture from SMAP and SMOS was found to have a large bias, whereas the bias in CCI product was small. Four products failed to reproduce the observed soil moisture characteristics in the transitional zones affected by the summer monsoon, with a positive bias found in AMSR2 and CCI and the largest biases in SMAP and SMOS products. We also suggest several reasons for the bias and error in the satellite soil moisture products. These results have important implications for soil moisture studies over midlatitude regions.

Spatiotemporal Analysis of Soil Moisture Variation in the Jiangsu Water Supply Area of the South-to-North Water Diversion Using ESA CCI Data

The South-to-North Water Transfer Jiangsu Water Supply Area (JWSA) is a mega inter-basin water transfer area (water source) that provides water resources from JiangHuai, combines drainage and flooding management, and regulates nearby rivers and lakes. Analyzing the spatiotemporal soil moisture dynamics in the area will be informative regarding agricultural drought along with flood disaster assessment and will provide early warning studies. Therefore, we evaluated the quality of European Space Agency Climate Change Initiative Soil Moisture (ESA CCI_SM) data in the South-North Water Transfer JWSA. Furthermore, we utilized ensemble empirical modal decomposition, Mann-Kendall tests, and regression analysis to study the spatiotemporal variation in soil moisture for the past 29 years. The CCI _SM data displayed a high correlation with local soil measurements at nine sites. We next analyzed the CCI_SM data from three pumping stations (the Gaogang, Hongze, and Liushan stations) in the South-North Water Transfer JWSA. These stations had similar periodic characteristics of soil moisture, with significant periodic fluctuations around 3.1 d. The overall soil moisture at the three typical pumping stations demonstrated an increasing trend. We further investigated whether abrupt soil moisture changes existed at each station or not. The spatial distribution of soil moisture in the South-North Water Transfer JWSA was characterized as “dry north and wet south”, with higher soil moisture in winter, followed by autumn, and low soil moisture in spring and summer. Although the linear trend of soil moisture in the South-North Water Transfer JWSA varied in significance, the overall soil moisture in the JWSA has increased over the past 29 years. The areas with significantly enhanced soil moisture are mostly distributed in the Yangzhou and Huai’an areas in the southeastern part of the study area. The areas with significantly decreased soil moisture are small in size and mostly located in northern Xuzhou.

Thermal Hydraulic Disaggregation of SMAP Soil Moisture Over the Continental United States

A thermal hydraulic disaggregation of soil moisture (THySM) algorithm was implemented to downscale NASA's soil moisture active passive (SMAP) enhanced soil moisture (SM) product to 1 km over the continental United States (CONUS). This algorithm was developed by combining thermal inertia theory with a soil hydraulic-based approach that considers fine-scale SM spatial distribution driven by both heat fluxes and hydraulic conductivity in soils. Relative soil wetness values were estimated using land surface temperature and normalized difference vegetation index for the thermal inertia model and using soil properties for the hydraulic model. The relative soil wetness values at 1 km from both models were then combined by using weighting functions whereby the spatial distribution of SM was governed more by thermal fluxes during times of strong heat transport and infiltration during moisture abundant soil conditions. THySM values were evaluated using <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> SM measurements from SMAP Core Validation Sites (CVS), the US Department of Agriculture Soil Climate Analysis Network, and the National Oceanic and Atmospheric Administration Climate Reference Network over CONUS. THySM shows higher accuracy than the SMAP / Sentinel-1 (SPL2SMAP_S) 1 km SM product when compared to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> measurements. The accuracy of THySM is 0.048 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> based on unbiased root mean square error (ubRMSE), outperforming SPL2SMAP_S by 0.01–0.02 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> . The ubRMSE of THySM 1 km SM over the SMAP grassland/rangeland-dominated CVS sites is better than 0.04 m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> /m <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> , which meets the SMAP mission SM accuracy requirement applied at 9 and 36 km.

Stereoscopic Planting in Ridge and Furrow Increases Grain Yield of Maize (Zea mays L.) by Reducing the Plant’s Competition for Water and Light Resources

Increasing planting density is an important ways to increase maize yield. A hot topic of conversation in the current research is how to improve crop light efficiency and yield potential by optimizing the cultivation mode under high density planting is a hot topic in current research. Thus, in this study, a field experiment was conducted to explore the effects of stereo-planting patterns on water and the utilization light resource and maize yields. Planting patterns included the conventional flat planting pattern (as the control, CK) and the stereo-planting in ridge and furrow (T). Each planting pattern had three planting densities, i.e., 60,000 plants ha−1 (D1), 75,000 plants ha−1 (D2) and 90,000 plants ha−1 (D3). The results showed that stereo-planting affected the physiological characteristics of plants by changing the spatial distribution of soil moisture. At the silking stage (R1), photosynthetic rate (Pn) of plants on the ridge was similar to CK, and transpiration rate (Tr) was significantly lower than that of CK. Pn of maize in the furrow was significantly higher than that of CK, and Tr was similar to CK. Stereoscopic planting had different effects on intraspecific competition intensity in maize population in different growing stages. In the six-leaf stage (V6), stereo-planting increased competition intensity of maize on the ridge, but lowered that of maize in the furrow by affecting the spatial distribution of soil moisture. During the R1 stage, stereo-planting increased the light transmittance rate within the canopy and eased the plant’s competition for light by reducing plant height and leaf area of maize under three density conditions. Stereo-planting had no effect on grain yield and dry matter accumulation of ridge-planted maize in the later growing stage, but it did increased the dry matter accumulation and grain yield of furrow-planted maize due to the improvement of the light environment and photosynthetic characteristics of the population. In two test years, stereo-planting increased 5.0–11.0% average yield of maize compared to CK under three density conditions. These results indicate that stereo-planting can reduce the plant’s competition for light and water resources and improve its physiological traits of plant by optimizing its spatial distribution of soil moisture and canopy structure, thus further increasing grain yield of maize under high-density planting conditions.