Levels Of Soil Moisture Content Research Articles

CROP IMPROVEMENT THROUGH DIFFERENT MEANS TO ADDRESS CLIMATE CHANGE AND FOOD SECURITY

This study evaluated several crop development techniques in addition to the effects of climate change on productivity in agriculture. Climate affects agricultural productivity and the distribution of crops worldwide. Given the current and projected variations in temperature, precipitation, and carbon dioxide concentrations, it is unclear whether agroecosystems will be able to produce enough food to meet the world's needs. Crop output, water productivity, and soil water balance are frequently altered by climate change. Soil moisture content and groundwater levels will be affected by the immediate effects of global warming-induced changes in temperature and precipitation patterns. Agricultural output is affected by several factors, such as crop variety, growing circumstances, soil deterioration, and water availability. Modern agricultural systems use genetics, biotechnology, plant breeding, environmental monitoring, and adjustments to management techniques to adapt to climate change. On the other hand, without a more thorough approach to agricultural systems, development cannot proceed. A strategy like this would mean growing amounts of a wider variety of superior crops and advancing equity, sustainability, nutrition, and food security in the future.

Low soil moisture improved shading tolerance by regulating leaf functional traits in Tetracentron sinense Oliv. seedlings

Tetracentron sinense Oliv. is an endangered relict tree found in south-central China. A low number of seedlings among the natural populations has resulted in the poor regeneration of this species. However, the mechanisms underlying seedling survival and growth remain poorly understood. Leaf functional traits (LFT) likely characterize the growth and development of T. sinense in different ecological environments, playing a crucial role in its adaptive strategies to adversity. In this study, two-factor orthogonal control experiments with two levels of light intensity (L1: 50 % natural light intensity in forest edge; L2: 10 % natural light intensity in understory) and soil moisture content (W1: 30 % moisture content in valley; W2: 15 % moisture content in mountainside) were conducted to analyze the response of the LFT of 7-month-old T. sinense seedlings to different light and soil moisture conditions. With the light intensity decreased, superoxide dismutase activity decreased, and peroxidase activity increased. With a decrease in soil moisture, the contents of chlorophyll (Chl) a, Chl b, Chl t, and soluble sugar increased, and Chl a/b decreased. A decrease in light and soil moisture decreased leaf thickness, leaf dry weight, leaf dry matter content, leaf volume, chloroplast volume, and starch grains, but increased osmophilic grains, the total nitrogen, and phosphorus contents. Moreover, the chloroplast morphology of L2W2 was more complete than that of other treatments. The results showed that the LFT of T. sinense seedlings acted synergistically to adapt to different light and soil moisture conditions, low soil moisture alleviated the effects of shading in T. sinense seedlings, and T. sinense seedlings adopted the “quick investment-return strategy” adaptation strategy under L2W2. Finally, the soil moisture of the mountainside in the natural habitat was favorable to the survival and growth of T. sinense seedlings.

Drip irrigation shapes the soil bacterial communities and enhances jujube yield by regulating the soil moisture content and nutrient levels

In the agricultural zones of the arid Xinjiang region of China, reducing irrigation is mandatory. However, irrigation affects the composition and diversity of the soil bacterial community which is vital to crop yield. To the best of our knowledge, very little research has been conducted on the relationships among the soil bacterial community, irrigation method, and yield as well as their underlying in jujube agroecosystems. Here, we investigated the soil physicochemistry and bacterial communities in jujube fields subjected to drip irrigation (DI) and traditional flood irrigation (FI), and their associations with yield at the flowering and fruit set (FFS) and end-of-growth (EG) stages. Under DI, the jujube yield was 8712.00 ± 24.54 kg/hm2, which was 7.64% higher than that obtained under FI (8094.33 ± 43.67 kg/hm2). DI increased the relative soil bacteria community diversity by decreasing the moisture content and increasing the nutrient levels in the soil. DI also transformed the soil bacterial community so that Bacteroidota predominated at the FFS stage and the probiotics Chloroflexi and Firmicutes predominated at the EG stage. A co-occurrence network analysis showed that DI created stable complex Soil bacteria communities in jujube fields, Though Dependentiae and Deferriberota had low relative abundance, they were nonetheless key nodes in the soil bacterial community network. A neutral community model (NCM) revealed that stochastic processes drove the soil bacterial community assembly whereas DI promoted deterministic processes by regulating the soil moisture content and nutrient levels. Partial least squares path modeling (PLS-PM) disclosed that DI affected the soil bacterial community structure by decreasing the moisture content (−0.342 **) and increasing the nutrient levels (0.557 **) in the soil. The PLS-PM also demonstrated that the observed change in the soil bacterial community structure was the main reason for the increase in jujube yield (1.098 **). The present work provides insights into the mechanisms underlying the correlations between the soil bacterial community and crop yield in response to changes in the irrigation method.

Performance Evaluation of Engine-Operated Weeding Machine

Weeds constitute a serious problem to wheat crops and cause a great loss to the yield. Manual weeding is labor-intensive and time-consuming. Chemical weed control has a negative impact on both the environment and humans. Today the agricultural sector requires non-chemical weed control that safeguards consumers demand for high quality food products and pay special attention to food safety. The objectives of the study was to evaluate the performance of an-engine operated weeder by evaluating the weeding efficiency, plant damage, effective field capacity, field efficiency, fuel consumption, performance index, energy consumption, and cost economics of engine operated weeder in wheat crop. The experimental design was a randomized complete block design and evaluation was conducted at three weeder forward speeds (1.5, 2, and 2.5 km/hr), two depths of operation (from 0 to 20 and from 0 to 40 mm), and three levels of soil moisture content (9.4, 12.34 and 15.25%). The performance of the weeder was found to be optimum at 15.25 percent soil moisture content with 0 to 40 mm depth of operation at a forward speed of 1.5 km/hr. The results revealed that maximum weeding efficiency of 90.1 percent was obtained with lower plant damage of 3.31 percent whereas the effective field capacity, field efficiency, fuel consumption, performance index, and energy consumption were found to be 0.052 ha/hr, 85.99%, 0.41 l/hr, 276.78 ha/hp, and 481.71 MJ/ha, respectively. The analysis revealed that forward speed, depth of operation, and soil moisture had significant effects on weeding efficiency, plant damage, effective field capacity, and fuel consumption at P<0.05 level of significance. The cost of weeding per hectare were 758 and 1920 ETB/ha for engine-operated weeders and traditional weeding methods, respectively. Based on the performance results, it can be concluded that the weeding machine is efficient, effective, and economically viable option with high scope for acceptability among small and medium scale farmers.

Performance Evaluation of an Engine Operated Weeding Machine

Weeds constitute a serious problem to wheat crops and cause a great loss to the yield. Manual weeding is labor-intensive and time-consuming. Chemical weed control has a negative impact on both the environment and humans. Today the agricultural sector requires non-chemical weed control that safeguards consumers’ demand for high-quality food products and pay special attention to food safety. The objectives of the study was to evaluate the performance of engine operated weeding machine by evaluating the weeding efficiency, plant damage, effective field capacity, field efficiency, fuel consumption, performance index, energy consumption, and cost economics of engine operated weeder in wheat crop. The experimental design was a randomized complete block design and evaluation was conducted at three weeder forward speeds (1.5, 2, and 2.5 km/hr), two depths of operation (from 0 to 20 and from 0 to 40 mm), and three levels of soil moisture content (9.4, 12.34 and 15.25%). The performance of the weeder was found to be optimum at 15.25 percent soil moisture content with 0 to 40 mm depth of operation at a forward speed of 1.5 km/hr. The results revealed that maximum weeding efficiency of 90.1 percent was obtained with lower plant damage of 3.31 percent whereas the effective field capacity, field efficiency, fuel consumption, performance index, and energy consumption were found to be 0.052 ha/hr, 85.99%, 0.41 l/hr, 276.78 ha/hp, and 481.71 MJ/ha, respectively. The analysis revealed that forward speed, depth of operation, and soil moisture had significant effects on weeding efficiency, plant damage, effective field capacity, and fuel consumption at P<0.05 level of significance. The cost of weeding per hectare was 758 ETB/ha and 1920 ETB/ha for engine-operated weeders and traditional weeding methods, respectively. Based on the performance results, it can be concluded that the weeding machine is an efficient, effective, and economically viable option with high scope for acceptability among small and medium-scale farmers.

Fabrication and Performance Evaluation of an Engine-Operated Weeding Machine for Wheat plantation

Wheat crops are severely hampered by weeds, which also significantly reduce productivity. Manual weeding requires a lot of time and effort. Chemical weed management is harmful to both the environment and people. Today’s agriculture sector needs non-chemical weed management to meet consumer demand for premium food items and pay close attention to food safety. The objectives of the study was to evaluate the performance of an-engine operated weeder by evaluating the weeding efficiency, plant damage, effective field capacity, field efficiency, fuel consumption, performance index, energy consumption, and cost economics of engine operated weeder in wheat crop. The experimental design was a randomized complete block design and evaluation was conducted at three weeder forward speeds (1.5, 2, and 2.5 km/hr), two depths of operation (from 0 to 20 and from 0 to 40 mm), and three levels of soil moisture content (9.4, 12.34 and 15.25%). The performance of the weeder was found to be optimum at 15.25 percent soil moisture content with 0 to 40 mm depth of operation at a forward speed of 1.5 km/hr. The results revealed that maximum weeding efficiency of 90.1 percent was obtained with lower plant damage of 3.31 percent whereas the effective field capacity, field efficiency, fuel consumption, performance index, and energy consumption were found to be 0.052 ha/hr, 85.99%, 0.41 l/hr, 276.78 ha/hp, and 481.71 MJ/ha, respectively. The analysis revealed that forward speed, depth of operation, and soil moisture had significant effects on weeding efficiency, plant damage, effective field capacity, and fuel consumption at P<0.05 level of significance. The cost of weeding per hectare were 758 ETB/ha and 1920 ETB/ha for engine-operated weeders and traditional weeding methods, respectively. Based on the performance results, it can be concluded that the weeding machine is efficient, effective, and economically viable option with high scope for acceptability among small and medium scale farmers

Developing Functional Relationships between Soil Moisture Content and Corn Early-Season Physiology, Growth, and Development.

Drought is a severe threat to agriculture production that affects all growth stages of plants, including corn (Zea mays L.). Any factor affecting early seedling growth and development will significantly impact yield. Despite the recurrence of low rainfall during the growing seasons, corn responses to different early-season soil moisture content levels have not been investigated. In this study, we investigated how corn morpho-physiological and biomass traits responded to varied soil moisture content during the early vegetative stage. Two corn hybrids were grown in a pot-culture facility under five different soil moisture treatments (0.15, 0.12, 0.09, 0.06, and 0.03 m3 m-3 volumetric water content, VWC) to assess the growth and developmental responses to varied soil moisture content during early-season growth (V2 to V7) stage. Sub-optimal soil moisture content limited plant growth and development by reducing physiological and phenotypic expression. Stomatal conductance and transpiration were decreased by an average of 65% and 59% across stress treatments relative to optimum conditions. On average, soil moisture deficit reduced the total leaf area by 71% and 72% compared to the control in 'A6659VT2RIB' and 'P1316YHR', respectively. Shoot and root dry weights were reduced by 74% and 43% under 0.03 m3 m-3 VWC. An increase in the root-to-shoot ratio was noticed under low VWC conditions compared to the control. Based on the stress tolerance index, the physiology and leaf growth parameters were more sensitive to soil moisture deficit. Our results highlight the impact of sub-optimal soil moisture on physiology and morphological traits during early-season growth. 'P1316YHR' demonstrated better physiological performance under stress conditions, while 'A6659VT2RIB' produced relatively better root growth. The findings suggest that biomass partitioning between shoot and root components is dynamic and depends on stress intensity. The current findings can help to prioritize traits associated with the early-season drought tolerance in corn. The functional relationships developed between soil moisture content and growth and developmental responses can be integrated into corn crop modeling to allow better irrigation management decisions.

Effects of Corn Straw Biochar, Soil Bulk Density and Soil Water Content on Thermal Properties of a Light Sierozem Soil

This research aimed to quantify the effects of biochar derived from corn straw on soil thermal conductivity, capacity, and diffusivity. Firstly, the amount of biochar application (w/w) added to light sierozem soil was 0% to 5%, and the mixtures were packed into soil columns at a consistent bulk density (1.20 g.cm-3). Secondly, soil columns with a consistent biochar addition rate (5%) were packed to different bulk densities of 1.30, 1.25, 1.20, 1.15, and 1.10 g.cm-3. Soil thermal characteristics were measured under the control of soil moisture content from 0% to 40%. Under consistent bulk-density conditions, biochar could significantly reduce soil thermal conductivity and diffusivity. Still, there wasn’t a significant influence on soil heat capacity in most soil moisture content levels. With the decrease of soil bulk density, soil thermal conductivity, capacity, and diffusion coefficient reduced significantly. As soil water content increased, all the indexes of thermal properties largely improved, and the effects were much more significant than those of biochar amendment and bulk density change on soil thermal performances. This research could supply an implication to evaluate the influence of biochar amendment on soil thermal performances.

DEVELOPMENT OF SMART IRRIGATION SYSTEM WITH INTEGRATED GSM AND WIFI CONTROL

A functional smart irrigation system with integrated GSM and Wi-Fi features that enables the farmer to remotely check soil moisture status as well as turn on and turn off the irrigation pump remotely, where necessary had been developed in this study. The system consists of a DC pump, a GSM module, moisture sensor, and the NodeMCU microcontroller. The prototype is essentially a mix of hardware module and software program and made up of several subunits. It behaves functions intelligently as a switching system being able to detect the moisture content level of the soil and then automatically irrigate the crop where the conditions are necessary. The motor is automatically turned ON or OFF in accordance with the soil moisture content level. The readings of the soil sensor are sent to a processing unit which generates graphs for analysis thereby helping the farmer make informed decisions.

Performance Evaluation of an Engine-Operated Weeding Machine

Weeds constitute a serious problem to wheat crops and cause a great loss to the yield. Manual weeding is labor-intensive and time-consuming. Chemical weed control has a negative impact on both the environment and humans. Today the agricultural sector requires non-chemical weed control that safeguards consumers demand for high quality food products and pay special attention to food safety. The objectives of the study was to evaluate the performance of an-engine operated weeder by evaluating the weeding efficiency, plant damage, effective field capacity, field efficiency, fuel consumption, performance index, energy consumption, and cost economics of engine operated weeder in wheat crop. The experimental design was a randomized complete block design (RCBD) and evaluation was conducted at three weeder forward speeds (1.5, 2, and 2.5 km/hr), two depths of operation (from 0 to 20 and from 0 to 40 mm), and three levels of soil moisture content (9.4, 12.34 and 15.25%). The performance of the weeder was found to be optimum at 15.25 percent soil moisture content with 0 to 40 mm depth of operation at a forward speed of 1.5 km/hr. The results revealed that maximum weeding efficiency of 90.1 percent was obtained with lower plant damage of 3.31 percent whereas the effective field capacity, field efficiency, fuel consumption, performance index, and energy consumption were found to be 0.052 ha/hr, 85.99%, 0.41 l/hr, 276.78 ha/hp, and 481.71 MJ/ha, respectively. The analysis revealed that forward speed, depth of operation, and soil moisture had significant effects on weeding efficiency, plant damage, effective field capacity, and fuel consumption at P<0.05 level of significance. The cost of weeding per hectare were 758 and 1920 ETB/ha for engine-operated weeders and traditional weeding methods, respectively. Based on the performance results, it can be concluded that the weeding machine is efficient, effective, and economically viable option with high scope for acceptability among small and medium scale farmers. Keywords: Cost of weeding, Energy consumption, field efficiency, plant damage, Performance, Weeding efficiency DOI: 10.7176/JIEA/13-2-01 Publication date: March 31 st 2023

Biochar Amendment Combined with Straw Mulching Increases Winter Wheat Yield by Optimizing Soil Water-Salt Condition under Saline Irrigation

The freshwater deficit is the major constraint to winter wheat production. Saline water irrigation could alleviate wheat water stress while increasing the risk of soil salinization, which would result in wheat yield reduction due to additional salt stress. The objective of the present study is to explore the effect of a straw-returning mode to promote winter wheat production under saline water irrigation. A field experiment was conducted during the winter wheat growing seasons of 2017–2018 and 2018–2019. Four returning modes were set, based on an equivalent carbon input: straw mulching (SM), biochar amendment (BA), straw mulching combined with biochar amendment (SM+BA), and the control without straw-returning (CK), along with three salinity levels of irrigation water: 0.47 dS m−1 (I0, freshwater), 3.25 dS m−1 (I1), and 6.75 dS m−1 (I2). Saline water irrigation alone triggered soil salt accumulation and reduced the wheat grain yield by 9.43––18.19%. Returning straw to fields increased soil organic carbon content by 16.41––52.21% and decreased soil bulk density by 0.69––1.46%. The highest increase in wheat grain yield (16.60––21.80%) was always obtained when using treatment SM+BA, due to the increased soil moisture content (3.15––12.31%) and lower salt levels (24.79––44.29%) compared to CK. The results of the present study established that SM+BA provided better soil water–salt conditions and nutrient environment for winter wheat growth than a single treatment. Thus, the combined application of SM and BA was shown to be a proper mitigating strategy to cope with the adverse effects of saline irrigation on winter wheat production and to promote the sustainable use of saline water irrigation.

The Effects of Osmosis and Thermo-Priming on Salinity Stress Tolerance in Vigna radiata L.

A plant’s response to osmotic stress is a complex phenomenon that causes many abnormal symptoms due to limitations in growth and development or even the loss of yield. The current research aimed to analyze the agronomical, physiological, and biochemical mechanisms accompanying the acquisition of salt resistance in the Vigna radiata L. variety ‘Ramzan’ using seed osmo- and thermopriming in the presence of PEG-4000 and 4 °C under induced salinity stresses of 100 and 150 mM NaCl. Seeds were collected from CCRI, Nowshera, and sowing was undertaken in triplicate at the Department of Botany, Peshawar University, during the 2018–2019 growing season. Rhizospheric soil pH (6.0), E.C (2.41 ds/m), field capacity, and moisture content level were estimated in the present study. We observed from the estimated results that the agronomic characteristics, i.e., shoot fresh weight and shoot dry weight in T9 (4oC + 150 mM NaCl), root fresh weight and root dry weight in T4 (PEG + 100 mM NaCl), shoot moisture content in T5 (PEG + 100 mM NaCl), and root moisture content in T6 (PEG + 150 mM NaCl) were the highest, followed by the lowest in T1 (both shoot and root fresh weights) and T2 (shoot and root dry weights). Similarly, the shoot moisture content was the maximum in T5 and the minimum in T6, and root moisture was the highest in T6. We observed from the estimated results that agronomical parameters including dry masses (T4, T6, T4), leaf area index, germination index, leaf area, total biomass, seed vigor index under treatment T9, and relative water content and water use efficiency during T5 and T6 were the highest. Plant physiological traits such as proline, SOD enhanced by T1, carotenoids in treatment T2, and chlorophyll and protein levels were the highest under treatment T4, whereas sugar and POD were highest under treatments T7 and T8. The principal component analysis enclosed 63.75% of the total variation among all biological components. These estimated results confirmed the positive resistance by Vigna radiata during osmopriming (PEG) and thermopriming (4 °C) on most of the features with great tolerance under a low-saline treatment such as T4 (PEG), T5 (PEG + 100 mM NaCl), T7 (4 °C), and T8 (4 °C + 100 mM NaCl), while it was susceptible in the case of T6 (PEG + 150 mM NaCl) and T9 (4 °C + 150 mM NaCl) to high salt application. We found that the constraining impact of several priming techniques improved low salinity, which was regarded as economically inexpensive and initiated numerous metabolic processes in plants, hence decreasing germination time. The current study will have major applications for combatting the salinity problem induced by climate change in Pakistan.

Spatiotemporal Variations of Soil Moisture and Groundwater Level in a South Sumatra Peatland, Indonesia During 2015–2018

The peat hydrological unit of the Air Sugihan River – Air Saleh River, South Sumatra, Indonesia, experienced extreme fires during the 2015 El Niño event. Restoration of 2.0 Mha degraded peatlands has been conducted since 2016. This study aims to analyze spatiotemporal variations of soil moisture content and groundwater level in this site from 2015 to 2018. The soil moisture was estimated using a multiple regression analysis method based on the Sentinel-1A and the European Center for Medium-Range Weather Forecast dataset. The groundwater level model was calculated by using linear regression between the estimated soil moisture and water level observed from field measurements. A minimum moisture content of ~0.78 m3m-3 and a minimum groundwater depth of ~0.50 m below the peat surface were estimated to cause smoldering combustion. A sharp decline in the water table depth (around 1.53 m) led to a decrease in moisture content in October 2015. This month, peat fires severely burned both cultivation and protected areas having dense drainage canals and near rivers. Although there was an increasing trend in the groundwater level and moisture content in 2016, between 2017 to 2018 the water table declined to a depth of ~0.7 m with a corresponding moisture content of ~0.25 m3m-3. Such decline may have led to a few peat fires which occurred in the dry season of both 2017 and 2018. We recommended that law enforcement efforts should be conducted to raise the mean annual water table to shallower depths than 0.40 m

Developing a generalized vis-NIR prediction model of soil moisture content using external parameter orthogonalization to reduce the effect of soil type

Real-time soil moisture content (SMC) monitoring is an important parameter in precision agriculture that can be utilized to enhance soil and water management. Visible and near-infrared (vis-NIR) has been proposed as a promising method for SMC monitoring. However, vis-NIR reflectance response to soil moisture is strongly influenced by soil properties such as texture and organic matter content. Thus it is difficult to develop a general prediction model of vis-NIR that can estimate SMC of different soil types. To solve this problem, this study utilizes the External Parameter Orthogonalization (EPO) method to reduce the effect of soil type. Seven soils (CZ, GA, JN, PDS, PY, WF, and XZ) were collected from the North China Plain. A fiber-optic spectrometer (300–1000 nm) was used to obtain spectral response of seven soils adjusted to several SMC levels. The partial least square regression (PLSR) was used to model the pretreated vis-NIR spectra of the seven soils. The modeling results confirmed the feasibility of using vis-NIR spectroscopy to predict SMC on individual soils. However, the prediction models vary significantly between soil types. To obtain a generalized prediction model of SMC that can be applied to different soils, three soils were selected from the seven soils for calibration, while the rest were used for validation. The results showed that direct PLSR modeling failed to achieve a unified prediction model. To solve this problem, EPO was applied to minimize the influence of soil types. The results demonstrated that EPO-PLSR can realize a generalized SMC prediction model. It is suggested that the soils for building EPO-PLSR models should cover a wide span of soil organic matter (SOM) content. Soil with the least SOM content appeared to be best for developing an EPO transfer matrix.

Hydrological Effects of Agricultural Water Supplies on Paddy Fields using Surface–Groundwater Integrated Model

Agricultural water demands are mainly dependent on the supply from groundwater withdrawals and the supply from agricultural reservoirs. To understand the water cycle of the agricultural catchment, it is necessary to consider the actual situation of the water cycle of paddy fields in catchments through accurate hydrological modeling. In this study, streamflow simulations were implemented in consideration of the levee height of paddy fields and the irrigation period for one sub-catchment of the Boryeong Dam catchment using the integrated surface–groundwater model, CAT (Catchment Hydrologic Cycle Assessment Tool). To consider the agricultural reservoirs in modeling, the catchment was divided into the reservoir sub-catchments, upstream sub-catchments, downstream sub-catchments, and irrigated districts of each sub-catchment. This study aims to analyze the hydrological effects of agricultural reservoirs and groundwater pumping on the hydrological cycle of the catchment and on the soil moisture and groundwater level. As a result of the simulations, we found that the direct flow, baseflow, and groundwater recharge of the catchment increased with the agricultural reservoir supply water. In addition, the effect of drought on soil moisture content and groundwater level in the irrigated paddy fields from agricultural reservoirs was evaluated. The soil moisture increased by about 10% according to the water supply of agricultural reservoirs. The groundwater level rapidly decreased due to the groundwater abstraction during the irrigation period; however, it was analyzed that the water supply from agricultural reservoirs is significantly effective in preventing the decrease in the groundwater level in the irrigation season.

Analysis of metamaterial‐inspired soil moisture microwave sensor

AbstractIn this letter, the authors propose a microwave sensor capable to detect soil moisture content parameter for use in precision agriculture and agricultural smart monitoring applications. The novel sensor is based on complementary split‐ring resonator metamaterial topology, microstrip line and was built under biodegradable dielectric substrate of polylactic acid for sustainable purposes. The sensing mechanism relates the sensor's resonant frequency to the soil moisture content changes over time. For experimental validation purposes, a compact sensor prototype (75 mm × 35 mm × 1.55 mm and 12 g) with fundamental resonant frequency at 958 MHz was built and submitted to calibration process on typically sandy and clay soils to get fitting models capable to estimate soil moisture content. Simulated and experimental results are presented together and show good agreement with each other. The calibration data for both soil types were processed using the least‐squares method and the proposed curve‐fitting models are capable to estimate soil moisture content levels from 5% to 20% for sandy soil and from 12% to 23% for clay soil with satisfactory accuracy, proving the device viability.

Soil moisture content estimate with drying process segmentation using shortwave infrared bands

Soil moisture content (SMC) has been widely focused and studied in various fields of research, including atmosphere-land water/energy exchange, drought, and vegetation-related topics. Many indices and models have been proposed to illustrate the reflectance features changing with SMC, and to estimate SMC from the reflectance of narrow bands and broadbands, using lab, field, airborne and satellite data. These methods/indices were mostly developed for all levels of SMCs, from saturated to air-dry; however, we found that a single relationship mapping saturated to air-dry can lead to a false impression of accurate estimation. The inconsistency of a regression relationship between spectral reflectance features and SMCs over the whole drying process results in a low estimation accuracy for relatively low SMCs. In this study, a segmentation method is proposed with the goal of a more accurate SMC estimate. The whole drying process of three soil samples, representing varied soil characteristics, is monitored, and the transition points are determined by evaporation rate change (as stage-1 drying with high SMC and stage-2 drying with low SMC). An index, the shortwave normalized index (SNI), is built for SMC estimation, and the SNI index trend during drying is supported by a radiative transfer-based model. As validated, the SNI index is capable of SMC estimates, and the segmentation method improves estimation accuracy astonishingly compared with current methods.

Characterizing reflectance anisotropy of background soil in open-canopy plantations using UAV-based multiangular images

The canopy bidirectional reflectance distribution function (BRDF) plays a pivotal role in estimating the biophysical parameters of plants, whereas soil background anisotropy creates challenges for their retrieval. Soil optical properties affect canopy anisotropic characteristics, especially in open-canopy areas. However, the remote sensing of background anisotropy is challenging due to the difficulties of information extraction in complex forest ecosystems and varying illumination conditions. This study develops an efficient photogrammetric technique to extract the background soil bidirectional reflectance factor (BRF) from unmanned aerial vehicle (UAV)-based multiangular images and to verify the need for accurate soil anisotropy information in canopy radiative transfer modeling. Soil BRF profiles were measured over three open-canopy sample plots from multiangular remotely sensed multispectral images collected with a hexacopter. As validation, reference soil BRF profiles were synchronously acquired by a ground-based multiangular imaging system.A high level of consistency between the ground- and UAV-measured soil BRF was observed with an RMSE of less than 0.012. Uncertainty analysis of the measured soil BRF showed that multiple scattering between sunlit soil in large sunflecks and foliage elements contributed less than 5%. Both results demonstrated that soil anisotropy can be accurately extracted from UAV multiangular measurements. To explicitly demonstrate that the use of soil anisotropy can reduce uncertainties in canopy radiative transfer simulations, we simulated the canopy BRF with Lambertian soil and with anisotropic soil using a three-dimensional (3D) radiative transfer model under different soil moisture content (SMC) levels, canopy cover (CC) levels and solar zenith angles (SZAs) with simulated realistic forest scenes. We found that less CC, lower SZAs and less SMC lead to a more significant influence of soil anisotropy on canopy reflectance; e.g., the reflectance bias reaches up to 0.3 in the hotspot direction. This illustrates that neglecting soil anisotropy can cause considerable errors in the modeling of the canopy BRF of open forests (i.e., CC levels of less than 0.5). The proposed technique facilitates the characterization of anisotropic forest background soil, which is important for advancing canopy radiative transfer modeling and validation and for the retrieval of vegetation parameters.

Discrete Element Modelling of Soil Compaction of a Press-Wheel

Press-wheels are wheels designed to compact the soil above seeds in the “seed cover” region. Soil compaction, produced by the press-wheels of seeders, affects seedling emergence and early plant growth. The Discrete Element Method (DEM) was used to model the amount of soil compaction from a press-wheel with varying down forces. The model was used to predict sinkage and rolling resistance of the press-wheel. The model results were validated with data from soil bin tests of the press-wheel in a sandy loam soil under varying soil moisture content levels (low, medium, and high). The sinkage results from the soil bin tests were 27.7, 26.7, and 25.2 mm for the low, medium, and high soil moisture content levels, respectively. The corresponding rolling resistances obtained from the tests were 104.4, 89.9, and 113.6 N. The press-wheel model adequately predicted the sinkage and rolling resistance for each soil moisture content level with overall Relative Mean Errors (RME) ranging from 13 to 23%. Additional simulation results show that average peak soil stresses across the three soil moisture contents at a depth of 0.12 m were 22,466.7, 8700.0, and 6900.0 Pa for vertical, horizontal, and lateral directions, respectively. The results enhance the understanding of the dynamics of the soil–press-wheel interaction and provided useful information for seeder press-wheel design.

Canopy interception estimates in a Norway spruce forest and their importance for hydrological modelling

ABSTRACT This study presents a comparison of several interception modelling approaches and their impact on the simulation of discharge, soil moisture content and groundwater level using the Hydrologiska Byråns Vattenbalansavdelning (HBV)-light model. The study was based on 10-year measurements of interception loss in a mature Norway spruce forest. The interception modelled by the subtraction of the constant value from each individual rainfall event was proved to be the most efficient. The root mean square error (RMSE) between observed and simulated discharge increased by 5–6% compared to the reference model run, no differences in the soil moisture were observed and an increase in RMSE of 11% was observed concerning the groundwater level. The transpiration rate was overestimated by 3–5% on average. The study proved that even simple interception models can serve efficiently for hydrological modelling tasks focused on the simulation of particular water fluxes in forested catchments.