Soil Moisture Fields Research Articles

Improvement of the “Triangle Method” for Soil Moisture Retrieval Using ECOSTRESS and Sentinel-2: Results over a Heterogeneous Agricultural Field in Northern India

For the purpose of deriving spatiotemporal estimates of soil moisture, the triangle method is one of the most widely used approaches today utilizing remote sensing data. Generally, those techniques are based on the physical relationships that exist when a satellite-derived land surface temperature (Ts) is plotted against a spectral vegetation index (VI). The present study proposes an improvement in the triangle method in retrieving soil moisture over heterogeneous areas. In particular, it proposes a new approach in robustly identifying the extreme points required for the technique’s implementation. Those extreme points are then used in calculating fractional vegetation cover (Fr) and scaled Ts. Furthermore, the study proposes a new approach for calculating the coefficients required to develop the relationships between surface soil moisture (SSM) and Fr/Ts, which is implemented using a model and field data. As a case study, an agricultural field in the Varanasi district in India has been used, on which the triangle method is implemented using ECOSTRESS and Sentinel-2 data. The much-improved spatial resolution satellite data of ~70 m from ECOSTRESS allowed deriving more vivid results of SSM spatial variability for the study area. Comparisons between field soil moisture calculated using the proposed method returned an RMSE of 0.03 and R2 value of 0.84, which are considered very satisfactory. The methodology proposed herein and the results obtained are of significant value with regards to the triangle method, contributing to ongoing efforts at present examining its use for operational product development at a global scale.

Identifying key processes driving Cd long-term adsorption and immobilization by biochar in soils and evaluating combined aging effects under simulated local climates

To investigate the effects of major environmental processes on biochar aging in field soils, four individual aging processes (dry-wet cycling, freeze-thaw cycling, leaching, and acidification) and a combination treatment including these four individual aging processes were conducted. The effects of five aging treatments on Cd transport between soils and biochar and Cd immobilization by pristine and KMnO4-modified biochars in soils were quantified. The results showed that the percentages of the total net effects of the aging treatments (the percentage sum of the decrease in Cd released into the environment and the increase in relatively stable Cd fractions in the soil) were in the following order: combined aging (−81.79% to −60.66%) < dry-wet cycling (−32.27% to −20.99%) < acidification (−21.93% to −14.46%) < freeze-thaw cycling (−22.69% to −6.91%) < leaching (8.51%–13.76%) for the CK, pristine biochar, and modified biochar treatments. The combined aging treatment had the most negative net effect on Cd immobilization because the effects of the four individual aging treatments superimposed to a certain degree. Modified biochar was more effective for Cd immobilization than pristine biochar under all five aging treatments. These results indicated that dry-wet cycling is a key environmental process among four individual aging processes in this study area, and that leaching is the only process that produces positive outcomes. Therefore, field soil moisture conditions can be adjusted to facilitate Cd immobilization by biochar. Moreover, combined environmental effects rather than individual aging processes should be considered under local climatic conditions when assessing biochar aging in field soils.

Effects of plastic film mulching on the spatiotemporal distribution of soil water, temperature, and photosynthetic active radiation in a cotton field.

Plastic film mulching (PFM) affects the spatiotemporal distribution of soil moisture and temperature, which in turn affects cotton growth and the spatiotemporal distribution of canopy photosynthetically active radiation (PAR). Due to the spatial heterogeneity of soil moisture, temperature and limited monitoring methods, the issues such as relatively few sampling points and long sampling intervals in most existing studies prevent the accurate quantification of spatiotemporal changes in moisture and temperature along soil profile. To investigate the effects of PFM on spatiotemporal changes in soil moisture, temperature, and canopy PAR in cotton fields, two field trials of plastic film-mulched (M) and nonmulched (NM) cultivations were performed in 2018 and 2019. The grid method was used for the soil information continuous monitoring and multiple-time fixed-site canopy PAR monitoring during the duration of cotton growth. Two-year field trial data showed that, M cultivation increased soil moisture by approximately 13.6%–25% and increased temperature by 2–4 °C in the 0–50 cm soil layer before the first irrigation (June 20) and by 1–2 °C in the 70–110 cm soil layer, compared with NM cultivation. In addition, the temperature difference between the two treatments gradually decreased with the increase in irrigation and air temperature. The M treatment reached the peak PAR interception rate 10 days earlier than the NM treatment. In 2018 and 2019, the PAR peak value under the M treatment was 4.62% and 1.8% higher than that under the NM treatment, respectively, but the PAR interception rate was decreased rapidly in the late growth stage. Overall, PFM had an effect on soil moisture retention during the whole growth period and greatly increased the soil temperature before budding stage, thus promoted the early growth of cotton. Considering this, we suggest that the irrigation quota and frequency could be appropriately decreased in the case of plastic film mulching cultivation. For nonmulching cultivation, the irrigation quota and frequency should be increased, and it is necessary to take measures to improve the soil temperature before middle July.

Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimes

Abstract. To reduce the underdispersion of precipitation in convective-scale ensemble prediction systems, we investigate the relevance of microphysical and land-surface uncertainties for convective-scale predictability. We use three different initial soil moisture fields and study the response of convective precipitation to varying cloud condensation nuclei (CCN) concentrations and different shape parameters of the cloud droplet size distribution (CDSD) by applying a novel combined-perturbation strategy. Using the new ICOsahedral Non-hydrostatic (ICON) model, we construct a 60-member ensemble for cases with summertime convection under weak and strong synoptic-scale forcing over central Europe. We find a systematic positive soil moisture–precipitation feedback for all cases, regardless of the type of synoptic forcing, and a stronger response of precipitation to different CCN concentrations and shape parameters for weak forcing than for strong forcing. While the days with weak forcing show a systematic decrease in precipitation with increasing aerosol loading, days with strong forcing also show nonsystematic responses for some values of the shape parameters. The large magnitudes of precipitation deviations compared to a reference simulation ranging between −23 % and +18 % demonstrate that the uncertainties investigated here and, in particular, their collective effect are highly relevant for quantitative precipitation forecasting of summertime convection in central Europe. A rainwater budget analysis is used to identify the dominating source and sink terms and their response to the uncertainties applied in this study. Results also show a dominating cold-rain process for all cases and a strong but mostly nonsystematic impact on the release of latent heat, which is considered to be the prime mechanism for the upscale growth of small errors affecting the predictability of convective systems. The combined ensemble spread when accounting for all three uncertainties lies in the same range as the ones from an operational convective-scale ensemble prediction system with 20 members determined in previous studies. This indicates that the combination of different perturbations used in our study may be suitable for ensemble forecasting and that this method should be evaluated against other sources of uncertainty.

Advances in the Quality of Global Soil Moisture Products: A Review

Soil moisture is a crucial component of land–atmosphere interaction systems. It has a decisive effect on evapotranspiration and photosynthesis, which then notably impacts the land surface water cycle, energy transfer, and material exchange. Thus, soil moisture is usually treated as an indispensable parameter in studies that focus on drought monitoring, climate change, hydrology, and ecology. After consistent efforts for approximately half a century, great advances in soil moisture retrieval from in situ measurements, remote sensing, and reanalysis approaches have been achieved. The quality of soil moisture estimates, including spatial coverage, temporal span, spatial resolution, time resolution, time latency, and data precision, has been remarkably and steadily improved. This review outlines the recently developed techniques and algorithms used to estimate and improve the quality of soil moisture estimates. Moreover, the characteristics of each estimation approach and the main application fields of soil moisture are summarized. The future prospects of soil moisture estimation trends are highlighted to address research directions in the context of increasingly comprehensive application requirements.

Land use affects the response of soil moisture and soil temperature to environmental factors in the loess hilly region of China.

Changes in soil moisture and soil temperature result from the combined effects of several environmental factors. Scientific determination of the response characteristics of soil moisture and soil temperature to environmental factors is critical for adjusting the sloping land use structure and improving the ecological environment in China’s loess hilly region. Soybean sloping fields, maize terraced fields, jujube orchards, and grasslands in the loess hilly region were selected as the research areas. The change in characteristics of soil moisture and soil temperature, as well as their interactions and statistical relationships with meteorological factors, were analyzed using continuously measured soil moisture, soil temperature, and meteorological factors. The results revealed that air temperature and humidity were the main controlling factors affecting soil moisture changes in the 0–60 cm soil layer of soybean sloping fields and grasslands in the normal precipitation year (2014) and the dry year (2015). Humidity and wind speed were the main meteorological factors affecting soil moisture changes in the maize terraced field. Air temperature had a significant negative effect on soil moisture in the jujube orchard. Soil moisture and soil temperature were all negatively correlated under the four sloping land use types. In normal precipitation years, atmospheric humidity had the greatest direct and comprehensive effect on soil moisture in soybean sloping fields, maize terraced fields, and grasslands; soil temperature had a relatively large impact on soil moisture in jujube orchards. The direct and comprehensive effects of soil temperature on soil moisture under all sloping land use types were the largest and most negative in the dry year. Air temperature had a high correlation with soil temperature in the 0–60 cm soil layer under the four sloping land use types, and the grey relational grade decreased as the soil layer deepened. The coefficient of determination between the 0–20 cm soil temperature and air temperature in the maize terraced field was low, indicating a weak response to air temperature. The above findings can serve as a scientific foundation for optimizing sloping land use structures and maximizing the efficient and sustainable utilization of sloping land resources in China’s loess hilly region.

Increased rice yield and reduced greenhouse gas emissions through alternate wetting and drying in a triple-cropped rice field in the Mekong Delta

For sustainable food production in the Mekong Delta, greenhouse gas (GHG) emissions from rice cropping activities need to be reduced without sacrificing rice productivity. Each year, a substantial amount of straw is incorporated into paddy soils through triple rice cropping, which is characterized by a short cropping period and nearly year-round flooding, such that a large amount of methane is emitted. Exposing these soils to oxidative conditions by altering the cropping-period water regime might have the potential to reduce GHG emissions with increased rice yield. To test this potential, a split-plot experiment was conducted in a typical triple-cropped alluvial farmer's paddy in a central delta area over five years and 15 consecutive cropping seasons.The emissions observed from the continuously inundated paddies were 1.1–2.7 times greater than the reported emission factors for Vietnamese continuously inundated paddies. A significantly higher emission peak was detected at the beginning of the rice cropping and flooding fallow periods in continuously flooded (CF) paddies than in alternate wetting and drying (AWD) paddies, although the differences in field water level and soil moisture among the paddies were negligible. AWD reduced annual methane emissions (−51 %) and increased rice yield (+9 %), presumably through enhanced translocation of carbohydrates from leaves to panicles. The amount of GHGs emitted from straw use also decreased (11 %) under AWD management because the straw production rate was significantly lowered (9 %) by enhanced nutrient translocation. These results indicate that GHG emission reduction potentials in the Mekong Delta have been underestimated by previous studies, corroborate the necessity of additional long-term observations of triple rice cropping systems and demonstrate the need for a robust methodology for monitoring the permanence of AWD effects after policies promoting its widespread dissemination take effect.

Relationships between leaf water potential and soil water potential in grasses subjected to water stress

For grasses and other crops in general, soil water potential has been widely studied to determine if there is a deficit or excess of water content in the soil. However, the plant water absorption process is not only modulated by soil water potential but also by the combination of meteorological, soil depth, and crop canopy factors, which could be elucidated through water relations responses. The objective of this work was to compare the water relations of grass species established in different soil depths and subjected to water stress. Santo Agostinho (Stenotaphrum secundatum), Esmeralda (Zoysia japonica), Tanzania (Panicum maximum) and Tifton 85 (Cynodon spp.) were used in this trial. The four species of grasses were tested in four different soil rooting depths: 10, 20, 30 and 40 cm. The grasses were irrigated at soil moisture field capacity level, until the time of imposing the water stress period. Soil depth had a direct influence on leaf water potential and soil water potential. Moreover, correlation coefficients are higher in deeper soil profiles. The strongest correlations between leaf water potential and soil water potential were found in the deeper soil depth treatments. Therefore, for the soil depth treatment of 40 cm, the average R² for the four species was 0.55, the highest being 0.70 in Tanzania grass. It is possible to relate leaf water potential and soil water potential independently of the grass species used or the depth of soil available to the roots, which would allow the creation of new irrigation management strategies.

Value addition in coupled model intercomparison project phase 6 over phase 5: global perspectives of precipitation, temperature and soil moisture fields

Value addition in coupled model intercomparison project phase 6 over phase 5: global perspectives of precipitation, temperature and soil moisture fields

SISTEM MONITORING PENGENDALIAN PENGAIRAN SAWAH MENGGUNAKAN METODE DECISION TREE PADA PLATFORM THINGSPEAK BERBASIS INTERNET OF THINGS (IOT)

This research aims to find out how to design IoT-based rice field watering monitoring and control systems using decision tree data processing. The process of irrigation of rice fields is a way of draining or bringing water to the rice field area or lading regularly. Irrigation can also be interpreted using water sources as something beneficial for plant life. If there is excessive water in lading, especially rice fields, it will interfere with the plant growth process. Irrigation is a major factor because the majority of rice production in Indonesia comes from irrigation fields.&#x0D; The design of the system uses hc-sr04 ultrasonic sensors to read irrigation water, soil moisture sensors to read soil moisture in rice fields, water level sensors to read water volumes in rice fields, and Arduino Uno as controlling and signaling to the cloud. Data from sensors sent to Arduino is then sent and displayed to the cloud with the platform thingspeak data from the platform in the process using data mining techniques with algorithm C. 45 on algorithm C.45 initial data in numerical form is transformed into categorical data according to standard standards. In C.45 the data is processed through the first calculated stage looking for the total entropy, entropy of each attribute, and looking for the highest gain according to the parameters for the class.&#x0D; Results of accuracy algorithm C.45 using the matric confusion method obtained an accuracy result of 99.50% in the next researchers expected action after receiving notification of field condition and irrigation both in the low or high state. So that monitoring the irrigation of these rice fields becomes more effective for the future.

Impacts of winter cover cropping on soil moisture and evapotranspiration in California's specialty crop fields may be minimal during winter months

As fresh water supplies become more unreliable, variable and expensive, the water-related implications of sustainable agriculture practices such as cover cropping are drawing increasing attention from California's agricultural communities. However, the adoption of winter cover cropping remains limited among specialty crop growers who face uncertainty regarding the water use of this practice. To investigate how winter cover crops affect soil water and evapotranspiration on farm fields, we studied three systems that span climatic and farming conditions in California's Central Valley: processing tomato fields with cover crop, almond orchards with cover crop, and almond orchards with native vegetation. From 2016 to 2019, we collected soil moisture data (3 years of neutron hydroprobe and gravimetric tests at 10 field sites) and evapotranspiration measurements (2 years at two of 10 sites) in winter cover cropped and control (clean-cultivated, bare ground) plots during winter months. Generally, there were not significant differences in soil moisture between cover cropped and control fields throughout or at the end of the winter seasons, while evapo-transpirative losses due to winter cover crops were negligible relative to clean-cultivated soil. Our results suggest that winter cover crops in the Central Valley may break even in terms of actual consumptive water use. California growers of high-value specialty crops can likely adopt winter cover cropping without altering their irrigation plans and management practices.

Understanding root-zone soil moisture in agricultural regions of Central Mexico using the ensemble Kalman filter, satellite-derived information, and the THEXMEX-18 dataset

ABSTRACT An Ensemble Kalman Filter (EnKF)-based assimilation algorithm was implemented to estimate root-zone soil moisture (RZSM) using a Soil-Vegetation-Atmosphere Transfer (SVAT) model during a complete growing season of corn in Central Mexico. Synthetic and field soil moisture (SM) observations and NASA SMAP SM retrievals were used to understand the effect of vertically spatial updates and uncertainties in meteorological forcings on RZSM estimates. Assimilation of RZSM every 3 days using SM observations at 4 depths lowered the averaged standard deviation (ASD) and the root mean square error (RMSE) by 60 % and 50 %, respectively, compared to the open-loop ASD. The assimilation of synthetic SM at the top 0-5 cm obtained RZSM closer to observations compared to THEXMEX-18 SM measurements and SMAP SM retrievals. Differences between EnKF estimates and SM observations and SMAP SM retrievals are mainly due to misrepresentation of vegetation conditions. The results improved SM estimates up to 10-cm depth using SMAP SM retrievals; however, additional studies are needed to improve SM at deeper layers. The implemented methodology can estimate SM at the top 10 cm of the soil every 3 days to mitigate the impact of the climate change on agricultural production over rainfed areas, particularly in developing countries.

Modification and upscaling of S–W model based on vertical distributions of soil moisture and vegetation root biomass

Soil water is the dominant factor controlling evapotranspiration (ET) in arid and semi-arid regions. However, the widely used ET simulation models, such as the Shuttleworth-Wallace model (S–W model), are insufficient in simulating the direct influence of soil moisture (SM), especially in the root zone. Based on SM and ET field data, we found that the influence of SM on ET increased with soil depth in the grassland. Evaporation in the S–W model was optimized by SM at 0–5 cm as the root mean square error (RMSE) decreased from 1.4 to 0.17, while transpiration was optimized by SM at 10–20 cm as the RMSE decreased from 0.26 to 0.07. The modified S–W model incorporating SM was called the S–W-ϴ model. To up-scale application and to verify the accuracy of the S–W-ϴ model under watershed water balance, we replaced the ET simulation module based on the S–W model with our S–W-ϴ model and the Block-wise TOPMODEL with Muskingum-Cunge routing method (BTOPMC) model that we used as the basis of our simulation. The influence of SM was determined by the proportion of root biomass of different vegetation types at different depths, and each depth interval was assigned a weighting reflecting its degree of influence. The results showed that the S–W-ϴ model improved accuracy with all the modification schemes tested. The modification scheme determined by the vegetation root distribution pattern had the greatest effect, providing a 4% accuracy improvement. The modified ET and hydrological models have the potential to support water basin management to a greater extent.

Evaluation of surface soil moisture models over heterogeneous agricultural plots using L-band SAR observations

The goal of this study is to evaluate the efficiency of surface soil moisture models based on L-band SAR data at two different crop stages in typical Indian agricultural plots. Agricultural fields examined include paddy, tomato, sugarcane, at two distinct crop stages, and a reference fallow field. Among the evaluated models, X-Bragg model underestimates soil moisture in all agricultural fields, whereas the Oh 2004 model fits into three agricultural plots for two crop stages without any necessity of auxiliary field information. All models underperformed in the case of sugarcane at the grand growth stage. Although WCM gave best result, it came at the cost of field data utilized to calibrate model parameters. Overall, the Oh 2004 model outperforms other models across crop types and growth stages. To the best of our knowledge, this is the only study that deals with soil moisture estimations at the plot scale across different crops.

Development and Application of Fiber-Optic Sensing Technology for Monitoring Soil Moisture Field

Accurate acquisition of the moisture field distribution in in situ soil is of great significance to prevent geological disasters and protect the soil ecological environment. In recent years, rapidly developed fiber-optic sensing technology has shown outstanding advantages, such as distributed measurement, long-distance monitoring, and good durability, which provides a new technical means for soil moisture field monitoring. After several years of technical research, the authors’ group has made a number of new achievements in the development of fiber-optic sensing technology for the soil moisture field, that is, two new fiber-optic sensing technologies for soil moisture content, including the actively heated fiber Bragg grating (AH-FBG) technology and the actively heated distributed temperature sensing (AH-DTS) technology, and a new fiber-optic sensing technology for soil pore gas humidity are developed. This paper systematically summarizes the three fiber-optic sensing technologies for soil moisture field, including sensing principle, sensor development and calibration test. Moreover, the practical application cases of three fiber-optic sensing technologies are introduced. Finally, the development trend of fiber-optic sensing technology for soil moisture field in the future is summarized and prospected.

Investigation of Multi-Frequency SAR Data to Retrieve the Soil Moisture within a Drip Irrigation Context Using Modified Water Cloud Model.

The objective of this paper was to estimate soil moisture in pepper crops with drip irrigation in a semi-arid area in the center of Tunisia using synthetic aperture radar (SAR) data. Within this context, the sensitivity of L-band (ALOS-2) in horizontal-horizontal (HH) and horizontal-vertical (HV) polarizations and C-band (Sentinel-1) data in vertical-vertical (VV) and vertical-horizontal (VH) polarizations is examined as a function of soil moisture and vegetation properties using statistical correlations. SAR signals scattered by pepper-covered fields are simulated with a modified version of the water cloud model using L-HH and C-VV data. In spatially heterogeneous soil moisture cases, the total backscattering is the sum of the bare soil contribution weighted by the proportion of bare soil (one-cover fraction) and the vegetation fraction cover contribution. The vegetation fraction contribution is calculated as the volume scattering contribution of the vegetation and underlying soil components attenuated by the vegetation cover. The underlying soil is divided into irrigated and non-irrigated parts owing to the presence of drip irrigation, thus generating different levels of moisture underneath vegetation. Based on signal sensitivity results, the potential of L-HH data to retrieve soil moisture is demonstrated. L-HV data exhibit a higher potential to retrieve vegetation properties regarding a lower potential for soil moisture estimation. After calibration and validation of the proposed model, various simulations are performed to assess the model behavior patterns under different conditions of soil moisture and pepper biophysical properties. The results highlight the potential of the proposed model to simulate a radar signal over heterogeneous soil moisture fields using L-HH and C-VV data.

Calibration and Multiple-Parameter Optimization of the Hybrid-Maize Model for Improve Simulation of Soil Moisture and Grain Yield in Farmer's Fields

Calibration and Multiple-Parameter Optimization of the Hybrid-Maize Model for Improve Simulation of Soil Moisture and Grain Yield in Farmer's Fields

Impacts of winter cover cropping on soil moisture and evapotranspiration in California's specialty crop fields may be minimal during winter months

As fresh water supplies become more unreliable, variable and expensive, the water-related implications of sustainable agriculture practices such as cover cropping are drawing increasing attention from California's agricultural communities. However, the adoption of winter cover cropping remains limited among specialty crop growers who face uncertainty regarding the water use of this practice. To investigate how winter cover crops affect soil water and evapotranspiration on farm fields, we studied three systems that span climatic and farming conditions in California's Central Valley: processing tomato fields with cover crop, almond orchards with cover crop, and almond orchards with native vegetation. From 2016 to 2019, we collected soil moisture data (3 years of neutron hydroprobe and gravimetric tests at 10 field sites) and evapotranspiration measurements (2 years at two of 10 sites) in winter cover cropped and control (clean-cultivated, bare ground) plots during winter months. Generally, there were not significant differences in soil moisture between cover cropped and control fields throughout or at the end of the winter seasons, while evapo-transpirative losses due to winter cover crops were negligible relative to clean-cultivated soil. Our results suggest that winter cover crops in the Central Valley may break even in terms of actual consumptive water use. California growers of high-value specialty crops can likely adopt winter cover cropping without altering their irrigation plans and management practices.

Effects of Different Irrigation Regimes on Spatio-Temporal Variations of Soil Moisture and Cotton Growth in Non-Film Drip Irrigation Cotton Fields in Southern Xinjiang, China

Effects of Different Irrigation Regimes on Spatio-Temporal Variations of Soil Moisture and Cotton Growth in Non-Film Drip Irrigation Cotton Fields in Southern Xinjiang, China

Predicted effects of simulated ambient warming and moisture on forage nutrient quality and community composition in Mongolian an arid grassland

Sustainable forage and livestock production in grazed grasslands are threatened by global climatic change. In this study, we examined how forage quality at the species and community levels in Mongolian drylands might be affected by warming and additional moisture. Four different treatments, a control, open-top chambers (OTCs) only, OTCs with heaters, and OTCs with additional watering, were set up in the field, and air and soil temperature and soil moisture were monitored. A vegetation survey was conducted and plants were harvested during summer, 1 and 2 years after experimental treatments were established. The harvested plant samples were separated into a dominant species (Stipa) or ‘other species’, and analysed to determine acid detergent fibre (ADF) and in vitro dry-matter digestibility (IVDMD). ADF was measured with the detergent method and the digestibility with the pepsin–cellulase assay. Overall, the warming treatments alone (OTC and OTC with heater) increased ADF 10% and 5% more than did the control at the species and community levels respectively, and decreased digestibility 12% and 11% below the control at the community level. Changes in plant nutritional value may have occurred as a result of changes in plant structure for some or all the plant species monitored, and an indirect effect of the shift in botanical species composition owing to warming. Unlike moist grassland, grass nutrition in arid grasslands was sensitive to treatments associated with the predicted effects of global warming as the results of changes in plant nutrition. It is therefore highly possible that Mongolian livestock production will be negatively affected as a result of ongoing global warming.