Soil Moisture Conditions Research Articles

Modelling net primary productivity using near real-time land cover data and soil moisture information

ABSTRACT The objective of this study is to develop a methodological approach to assess ecosystem functioning in terms of carbon uptake and sequestration. To achieve this, a model was developed to forecast Net Primary Productivity (NPP) and tested in a rural area, the Thrace region (NE Greece). Monthly net photosynthesis data from July 2015 to February 2024 was estimated using the MODerate Resolution Imaging Spectroradiometer (MODIS) Aqua MYD17A2H v061 dataset for the study area. This dataset was used as the dependent variable in an Autoregressive Integrated Moving Average (ARIMA) model. The predictive ability of monthly Land Cover (LC) and Soil Moisture (SM) data at various time lags was examined, and variables found to be significant predictors were introduced into the model as external predictors. The study found that crop areas and SM conditions exert the greatest influence on NPP, with areas containing trees exerting a lesser impact. Additionally, NPP was estimated for seven different LC and SM scenarios from March 2023 to February 2024.

Physiological Behavior of Rubber Plants (<i>Hevea Brasilliensis</i>) to Different Soil Moisture Conditions

Drought conditions can severely impact rubber (<i>Hevea brasiliensis</i>) plantations, leading to economic loss in Malaysia. The study aimed to assess the impact of varying soil moisture levels on the physiological characteristics of five latex timber clones (LTCs) of rubber, with the goal of identifying the most suitable clone for specific soil moisture conditions. These conditions include (1) field capacity, (2) 75% available water (AW), (3) 50% AW, (4) 25% AW, and (5) wilting point, with the ultimate objective of optimizing cultivation methods and fostering sustainable rubber production in Malaysia. The five clones under investigation include RRIM3001, RRIM2025, RRIM2001, RRIM928, and PB350. Leaf chlorophyll content, stomatal conductance, and net photosynthesis were measured 4 and 8 months after treatment (MAT). The findings indicated significant effects of moisture stress on various physiological attributes, including total chlorophyll content, relative chlorophyll content, stomatal conductance, and net photosynthesis rate. At 4 and 8 MATs, the clones subjected to field capacity exhibited the highest values for these physiological characteristics, followed by those exposed to 75% available water, with the lowest values observed at the wilting point. RRIM3001 consistently exhibited the highest total chlorophyll content, stomatal conductance, and net photosynthesis among the clones at both sampling dates. The highest net photosynthesis was observed in the RRIM3001 clone under field capacity conditions. Furthermore, a significant positive correlation was identified between total chlorophyll and relative chlorophyll contents, as well as between net photosynthesis and stomatal conductance. These findings carry practical implications for water management during the initial growth phase of rubber seedlings and for replanting initiatives in rubber plantations.

Revealing the Feedback Loop: Comparing Satellite and Sensor-derived Meteorological Parameters in Groundnut Cultivation

Background: Studying soil moisture’s impact on groundnut, particularly under rainfed conditions, is crucial for improving quality and yield. This research explores soil moisture dynamics using satellite and in-situ sensor data to enhance water management and crop predictions, focusing on the feedback mechanisms between soil moisture and weather variables. Methods: The study was conducted at the Oil Seed Research Station (TNAU) in Tindivanam, Tamil Nadu, using the groundnut variety TMV 14. Soil moisture and weather parameters were monitored at critical crop growth stages, using an in-situ soil moisture sensor (Cr 300) and compared with satellite data from SMAP, ERA5 and Sentinel 1A with environmental factors. Statistical analysis was carried out using SAS JMP Pro and network analysis via Cytoscape 3.8.2 software. Result: Pre-monsoon soil moisture SMAP, SMAP-RZSM and sensor (VWC at 10cm) were found to increase in post-monsoon. Strong positive correlations were attained between SMAP-SM and SMAP-RZSM (r=0.94), indicating a reinforcing loop. Whereas, the negative feedback was observed between SMAP-SM and deeper soil temperatures (-0.91). It underscores the dynamic interplay between soil moisture and atmospheric conditions, essential for developing efficient water management strategies and enhancing crop resilience to climate variability.

Spatial Aggregations of the Grey Field Slug Deroceras reticulatum Are Unstable Under Abnormally High Soil Moisture Conditions.

Deroceras reticulatum in arable fields display spatio-temporally stable slug patches that have been well documented under typical soil moisture conditions. The effect of abnormally high soil moisture on slug patch stability, however, is unknown. In this study, stepped gradient choice tests comparing soil moisture levels of 50-125% soil capacity showed slug preferences for levels in a range near to 125%. Activity became erratic, however, when given a choice of high moisture levels (125-370%), potentially because slugs searched for preferred conditions. Slug spatial aggregation was investigated in 21 commercial fields in 2023/24, a season of extreme rainfall, and then compared to years exhibiting typical rainfall (2015-2018). Slug patches occurred in 27.2% of assessment visits to fields during 2023/24 compared to 96.4% in typical years, suggesting weather conditions leading to abnormally high soil moisture are significantly associated with the breakdown of slug spatial aggregation behaviour. Random forest models identified the weather predictors (precipitation, relative humidity, temperature) with the highest impact on slug distribution and relative abundance, with the assessment date and region also related to relative abundance. However, a complex of environmental parameters affects soil moisture content, and no statistically significant effects of individual weather predictors emerged. The results are discussed in relation to slug behaviour in the context of their impact on targeted slug treatments.

Адаптация форм Pinus sylvestris с разным цветом семян на избыточно увлажненных почвах

Adaptive changes in biochemical parameters of different pine forms under conditions of constant excessive soil moisture in the northern latitudes of the European part of Russia have been studied. The influence of seasonal variability on the dynamics of the photosynthetic pigment complex of pine forms with different seed colours has been shown. It has been established that elevated temperatures in early autumn contribute to the accumulation of chlorophyll, and this can negatively affect the hardening of trees in preparation for overwintering. The proportion of chlorophylls localized in the light-harvesting complexes of chloroplasts fluctuates from May to November from 43 to 60 %, which is associated with the adaptation of the photosynthetic apparatus of trees of different forms to the light conditions of high latitudes and other environmental factors. It has been determined that anthocyanins accumulate significantly more in pine needles in autumn, which increases their antioxidant role in this season. It has been revealed that peroxidase activity in 1-year-old needles increases in the autumn period. This can be considered as a protective reaction of different forms of pine, preventing the development of uncontrolled processes with a limited oxygen supply to the organs. A significant new formation of water-soluble proteins in pine needles with dark-coloured seeds has been detected due to the deterioration of weather conditions. This form, compared to pine with light seeds, probably reacts more strongly to the effect of stress factors that increase hypoxia of the root system. It has been concluded that the concentration of proline in needles is a very variable indicator, reacting sharply to the action of stress factors. No general trends in the seasonal dynamics of the indicator have been identified. It has been established that the content of ascorbic acid in the needles of trees of different forms of pine in late spring is significantly lower than in the summer and autumn seasons. This indicates the development of protective mechanisms to prevent oxidative stress under adverse weather conditions.

Time-dependent redistribution of soil arsenic induced by transformation of iron species during zero-valent iron biochar composites amendment: Effects on the bioaccessibility of As in soils

Zero-valent iron biochar composites (ZVI/BC) are considered as effective amendments for arsenic (As)-contaminated soils. However, the mechanisms of transformation of various soil As species during ZVI/BC amendments remain unclear. This study investigated As transformation in four soils (namely, GX, ZJ, HB, and HN) treated with ZVI/BC for 65 days under two soil moisture conditions, unsaturated and oversaturated. Results showed that the 65-day treatment was divided into two stages based on the variation of labile As content. Within 2 days (stage 1), ZVI/BC addition quickly reduced labile As content by 5.91–90.3 % in soils under unsaturated conditions. During days 2–65 (stage 2), labile As ultimately decreased by 0.06–0.31 mg/kg in GX, ZJ, and HB while increasing by 22.1 mg/kg in HN soil, due to its lower pH value and Fe content. The variations of labile As were attributed to changes in multiple Fe minerals and associated As species. In stage 1, the corrosion of ZVI/BC generated amorphous Fe oxides to immobilize labile As, resulting in the accumulation of meta-stable As. In stage 2, amorphous Fe oxides were transformed into crystalline Fe oxides, resulting in the release and re-precipitation of As along with transformation, thus redistributing immobilized As into labile and stable As, which was evidenced by multiple methods, including chemical extraction, XRD, and TEM-EDX. The elevated soil moisture condition would enhance the corrosion of ZVI/BC in stage 1, further forming a reductive environment to facilitate the transformation of Fe minerals in stage 2. Besides, As bioaccessibility in soils was reduced by 10.8–38.7 % after ZVI/BC treatment in in-vitro gastrointestinal simulations. Overall, our study revealed the time-dependent transformation mechanism of soil As species and associated Fe minerals under different soil moisture with ZVI/BC treatments, and highlighted the effectiveness of ZVI/BC as a long-term amendment for As-contaminated soils.

Single and combined effects of metal-based fungicides on Eisenia andrei in different scenarios of climatic change.

This study evaluated the ecotoxicity of metal-based fungicides under the current scenarios of global climatic change (20°C and 25°C) and moisture content (30% and 50%) in single and binary mixtures of copper oxychloride (CuOx) [200, 500 and 1000mg/kg] and mancozeb (MnZn) [44, 850 and 1250mg/kg]. Endpoints assessed included mortality, changes in biomass, avoidance behaviour, and reproduction utilising standardised protocols (ISO and OECD). The changes in biomass and mortality tests lasted 28days, followed by a 28-day reproduction test and a two-day avoidance test. In all temperature-moisture combinations, the mortality rate in the exposure groups exceeded 10% only in the CuOx1000 and CuOx1000 + MnZn1250 mg/kg groups. However, at 20°C and 30% moisture, the mortality rate exceeded 10% only in the CuOx500 + MnZn850 mg/kg treatment. Relative growth rates in the CuOx and MnZn treatment groups decreased with increasing concentrations. In CuOx MnZn and the binary mixture treatments at 20°C 30% and 25°C 50% conditions, avoidance response behaviour was greater than 80% throughout the exposure, except in CuOx200 mg/kg, MnZn44 mg/kg and CuOx200 + MnZn44 mg/kg. The reproduction of exposed earthworms in all treatment groups was concentration-dependent and influenced by varying temperatures and soil moisture conditions. No juveniles or cocoons were produced in the CuOx1000 mg/kg treatment at 25°C 30%, indicating that copper oxychloride may be more toxic than mancozeb, especially in drought conditions. This study found that different temperatures and soil moisture levels altered the ecotoxicity of CuOx and MnZn. It can be concluded that climate change is likely to significantly impact the outcomes of metals to earthworms and their ecological activities.

Combined Drought Index Using High-Resolution Hydrological Models and Explainable Artificial Intelligence Techniques in Türkiye

We developed a combined drought index to better monitor agricultural drought events. To develop the index, different combinations of the temperature condition index, precipitation condition index, vegetation condition index, soil moisture condition index, gross primary productivity, and normalized difference water index were used to obtain a single drought severity index. To obtain more effective results, a mesoscale hydrologic model was used to obtain soil moisture values. The SHapley Additive exPlanations (SHAP) algorithm was used to calculate the weights for the combined index. To provide input to the SHAP model, crop yield was predicted using a machine learning model, with the training set yielding a correlation coefficient (R) of 0.8, while the test set values were calculated to be 0.68. The representativeness of the new index in drought situations was compared with established indices, including the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Self-Calibrated Palmer Drought Severity Index (scPDSI). The index showed the highest correlation with an R-value of 0.82, followed by the SPEI with 0.7 and scPDSI with 0.48. This study contributes a different perspective for effective detection of agricultural drought events. The integration of an increased volume of data from remote sensing systems with technological advances could facilitate the development of significantly more efficient agricultural drought monitoring systems.

Comparative analysis of event runoff coefficients and curve numbers in contrasting urban environments based on observed rainfall-runoff data

Recently, there has been a growing recognition that the generic values of runoff coefficient (C) and curve number (CN) from standard lookup tables in the literature may not accurately capture the specific characteristics of a given catchment. This study aims to estimate and compare the event C and CN of two contrasting urban catchments in Ljubljana, Slovenia using observed rainfall-runoff data. Estimated parameter values were compared to the tabulated values from the literature (i.e., ASCE, 1992; USDA-NRCS, 2004). Seasonal changes of C and CN, along with diurnal streamflow patterns, were also analyzed to understand the eco-hydrological processes in the urban forest. The results demonstrated that the urban mixed forest exhibited high variability of Cs across all rainfall events with a mean and median of 0.11 and 0.062, respectively. Most of the C values observed in the urban area are clustered around the central tendency with a mean and median of 0.60. These mean C values in both catchments were lower than the tabulated values in the ASCE (1992) design manual. Mean and median CN values in the urban area were 95.45 and 96.81, respectively, lower than the urban mixed forest’s CN values of 82.69 and 83.95. An asymptotic CN∞ of 90.69 was found for the urban area and 71.71 for the urban mixed forest. Central tendency-derived CN values tend to be slightly higher than the tabulated values from USDA-NRCS (2004) and gridded values from GCN250 (Jaafar et al., 2019), while asymptotic CN∞ values were lower. Using central tendency measures as the single lumped value of C and CN may provide a reasonable representation of the runoff behavior in the studied urban area. However, this may present certain challenges in the urban forest catchment. Additionally, pre-event soil moisture conditions and specific storm characteristics contributed to the observed variations in C and CN. Bi-monthly analysis showed that C and CN were high during the autumn and winter months. Diurnal streamflow pattern is most prevalent during low-flow and precipitation-free periods while exhibiting seasonal structures in terms of the shape and timing of maxima and minima. Local estimation of C and CN allows for a more tailored representation of the catchment’s hydrological behavior.

Comparative Study on the Thermomechanical Behavior and Bearing Capacity of Energy Piles in Dry and Moist Soil Conditions

Comparative Study on the Thermomechanical Behavior and Bearing Capacity of Energy Piles in Dry and Moist Soil Conditions

The effects of roots and earthworms on aggregate size distribution and their associated carbon under contrasting soil types and soil moisture conditions

Soil’s potential as a carbon sink is uncertain due to biotic and abiotic interactions. Soil aggregates are important carriers of organic carbon (OC), and clarifying the response of aggregates and their associated OC to plant roots and earthworms can better understand the carbon cycle in terrestrial ecosystems. Herein, we determined the regulatory role of plant roots (Lolium perenne) and earthworms (Metaphire tschiliensis) in isolation and in combination on aggregate size distribution and their associated OC and readily oxidizable OC (ROOC) under contrasting soil types (Phaeozems and Anthrosols) and soil moisture conditions (constant wetting, CW; wetting–drying cycle repeated four times, 4WD) by a laboratory microcosm experiment. Results showed that earthworm presence significantly increased plant biomass by 30 % and 221 % in Phaeozems and Anthrosols, respectively (p < 0.05). For Phaeozems, plant alone (P) and plant and earthworm in combination (PE) had lower proportion of large aggregate (5–8 and 2–5 mm) than bare soil (CK) under 4WD condition (p < 0.05). For Anthrosols, the PE treatment decreased the proportion of 5–8 and 2–5 mm aggregate by 45 % and 25 %, respectively, under CW condition, and decreased the proportion of 5–8 mm aggregate by 37 % under 4WD condition (p < 0.05). Moreover, the proportion of 5–8 and 2–5 mm aggregate in P treatment was lower under CW condition (6.92 % and 22.13 %) but was higher under 4WD condition (11.49 % and 32.55 %) than those in CK (14.69 % and 29.91 %; 8.85 % and 20.56 %) (p < 0.05). Our results further indicated that the PE treatment had relatively higher OC and ROOC contents, especially for small aggregates in Anthrosols. The study indicates that plant roots and earthworms significantly influence aggregate turnover and the carbon cycle, with soil type and moisture playing a crucial role.

Genotype by environment interaction across water regimes in relation to cropping season response of quinoa (Chenopodium quinoa).

Genotype × environment (GxE) interaction effects are one of the major challenges in identifying cultivars with stable performance across agri-environments. In this study we analysed GE interactions to identify quinoa (Chenopodium quinoa) cultivars with high and stable yields under different soil moisture regimes, representing control conditions, waterlogging and drought. Waterlogging and drought treatments were artificially induced using normoxia, a combination of hypoxia-normoxia, and 10% PEG (Polyethylene glycol) under hydroponic growth conditions, respectively. Both waterlogging and drought conditions significantly reduced the plant height (PH), number of leaves (NoL) and number of branches (NoB), stem diameter (SD), leaf area (LA) and dry weight (DW) of quinoa genotypes. The genotype, water regime, and genotype by water regime effects all significantly affected the measured quinoa traits. Based on the additive main effects and multiplicative interaction (AMMI) model for DW, the genotypes G18, Puno, Q4, 2-Want, Puno, Real1 x Ruy937 and Titicaca were found to exhibit tolerance and were stable across water regimes. A second-stage evaluation was conducted to test genotype × environment interaction effects in crop production field trials, selecting two contrasting seasons based on soil moisture conditions involving a diverse set of genotypes (58 varieties in total). Our results demonstrate significant variations in both growth and yield among the quinoa genotypes across the cropping seasons. The GGE analysis for grain yield indicate that field conditions matched to G × E under hydroponic experimental conditions and the cultivars G18, Q1, Q4, NL-3, G28, 42-Test, Atlas and 59-ALC were classified within a range of high productivity. Our findings provide a basis for understanding the mechanisms of wide adaptation, while identifying germplasm that enhances the water stress tolerance of quinoa cultivars at early growth stages.

Modeling the response of crop emergence to sowing depth and soil water deficit in direct-seeded rice

Abstract Background and aims Dry direct seeding of rice in the tropics often suffers from poor crop establishment owing to soil water deficit. A potential solution is sowing deeply to utilize residual soil moisture farther below the surface. We evaluated rice emergence under various sowing depths and soil moisture conditions and tested a model framework of it as a simultaneous function of sowing depth and soil moisture. Methods We combined data from three field experiments and one growth chamber experiment to collect emergence data for four rice cultivars (Dontokoi, Dular, Rc222 and Rc420). We independently parameterized the relationships between emergence and sowing depth or soil water tension using logistic functions. We expressed the final emergence as the product of the two functions. Results Emergence responses to sowing depth and soil moisture fitted the cultivar-specific logistic functions well. For Dular, a cultivar that tolerates deep sowing, emergence was greatest when sown at 4 to 5 cm below the surface under soil water deficit, versus 1 to 2 cm under wet conditions, and our combined model successfully reproduced this result. Conclusion Our emergence model framework supports adjustment of sowing depth to account for available soil water, making the model a powerful new tool for drought adaptation in direct-seeded rice.

Effects of initial soil moisture on rill erodibility and critical shear stress factors in the WEPP model across diverse soil types

Rill erosion, a significant issue in agricultural regions, is intricately linked to initial soil moisture conditions, affecting the development of concentrated flow erosion processes. However, understanding its dynamics amidst varying soil moisture conditions remain challenging. This study aimed to assess the impact of different soil moisture levels on rill erodibility parameters in the Water Erosion Prediction Project (WEPP) model and to evaluate soil cohesion across a spectrum of soils. Through laboratory experiments employing a small V-shaped rill channel, we investigated rill erodibility (Kr) and critical hydraulic shear stress (τcr), under three soil moisture scenarios: initially dry, saturated, and drainage, with incremental surface inflow rates. Additionally, we examined the efficiency of soil cohesion obtained from an Automated Soil Cohesion Measurement Apparatus in predicting Kr and τcr across various soil textures. Our analysis encompassed twenty soils representing nine texture classes, revealing significant correlations between basic soil properties, cohesion parameters, and WEPP model rill erodibility. Notably, initial soil moisture conditions exerted substantial influence on erodibility potentials. Soils with higher silt contents demonstrated better fits in terms of Nash-Sutcliffe model efficiency, particularly under initially dry and saturated conditions. However, predictions for initially drained soils yielded poor fits, emphasizing the intricate interplay between soil properties and hydrological conditions. In conclusion, our findings emphasize the critical role of topsoil water dynamics in rill erodibility. We propose that soil cohesion serves as a valuable predictor, complementing friction forces within the soil and enhancing simulations of rill erodibility under shallow flow conditions in rills, particularly in next-generation process-based modeling approaches.

In situ soil moisture and thermal properties estimated using a dual-probe heat-pulse

In situ monitoring of the temporal and spatial distribution of soil moisture and thermal properties are important for studying the water and energy transport in the vadose zone. The single-probe heat-pulse method based on fiber Bragg grating technology (SPHP-FBG) has become a research focus in field monitoring because of its capability to realize quasi-distributed and real-time monitoring. However, the SPHP-FBG method can only obtain thermal conductivity. This study developed a dual-probe heat-pulse method based on FBG (DPHP-FBG). The DPHP-FBG method can measure thermal conductivity (λ), volumetric heat capacity (Cv), and thermal diffusivity (k). Consequently, volumetric soil water content (θ) can be estimated from its linear relationship with Cv. The accuracy of the DPHP-FBG method in the estimation of Cv, λ, and θ was tested under different heating duration and various soil moisture conditions. In addition, Monte Carlo simulation was performed to investigate the impact of FBG measurement errors on accuracy. Finally, a field test was conducted to verify the effectiveness of the developed DPHP-FBG system. The results show that the DPHP-FBG method allows accurate soil moisture and thermal properties estimation without soil-specific calibration. The mean errors of the Cv and θ decrease with the extended heating duration. When the heating lasts 20 s, the measured Cv and θ have mean errors of 0.02 MJ m−3 K−1 and 0.01 m3/m3, respectively, for various moisture conditions. In the field test, the spatio-temporal distribution of soil moisture and thermal properties can be obtained in real time. Thereby, the proposed DPHP-FBG monitoring system is potential to conduct in situ coupled heat and soil moisture measurements at a large scale.

Arctic Tundra Plant Dieback Can Alter Surface N2O Fluxes and Interact With Summer Warming to Increase Soil Nitrogen Retention.

In recent years, the arctic tundra has been subject to more frequent stochastic biotic or extreme weather events (causing plant dieback) and warmer summer air temperatures. However, the combined effects of these perturbations on the tundra ecosystem remain uninvestigated. We experimentally simulated plant dieback by cutting vegetation and increased summer air temperatures (ca. +2°C) by using open-top chambers (OTCs) in an arctic heath tundra, West Greenland. We quantified surface greenhouse gas fluxes, measured soil gross N transformation rates, and investigated all ecosystem compartments (plants, soils, microbial biomass) to utilize or retain nitrogen (N) upon application of stable N-15 isotope tracer. Measurements from three growing seasons showed an immediate increase in surface CH4 and N2O uptake after the plant dieback. With time, surface N2O fluxes alternated between emission and uptake, and rates in both directions were occasionally affected, which was primarily driven by soil temperatures and soil moisture conditions. Four years after plant dieback, deciduous shrubs recovered their biomass but retained significantly lower amounts of 15N, suggesting the reduced capacity of deciduous shrubs to utilize and retain N. Among four plant functional groups, summer warming only increased the biomass of deciduous shrubs and their 15N retention, while following plant dieback deciduous shrubs showed no response to warming. This suggests that deciduous shrubs may not always benefit from climate warming over other functional groups when considering plant dieback events. Soil gross N mineralization (~ -50%) and nitrification rates (~ -70%) significantly decreased under both ambient and warmed conditions, while only under warmed conditions immobilization of NO3 - significantly increased (~ +1900%). This explains that plant dieback enhanced N retention in microbial biomass and thus bulk soils under warmed conditions. This study underscores the need to consider plant dieback events alongside summer warming to better predict future ecosystem-climate feedback.

Land and Atmospheric Drivers of the 2023 Flood in India

AbstractFloods in India are recurring natural disasters resulting from extreme precipitation during the summer monsoon season (June–September). The recent flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure. However, what led to the 2023 North India flood and the role of atmospheric and land drivers still need to be examined. Using in situ observations, satellite data, and ERA5 reanalysis combined with hydrological and hydrodynamical modeling, we examine the role of land and atmospheric drivers in flood occurrence and its impacts. Extreme precipitation in a large region during 7–10 July 2023 created favorable conditions for the flood in the hilly terrains and plains of north India. More than 300 mm of precipitation fell in just 4 days, which was eight times higher than the long‐term average (2001–2022). Anomalously high moisture transport over northern India was recorded on 7 July 2023, making atmospheric conditions favorable for intense landfall. Increased column water vapor and specific humidity at different pressure levels confirmed the continuous moisture presence before the extreme rainfall that caused floods in northern India from 7 to 12 July 2023. Atmospheric and land (high antecedent soil moisture) conditions contributed to a more than 200% rise in streamflow at several gauge stations. Satellite‐based flood extent shows a considerable flood inundation that caused damage in the Sutlej and Yamuna River basins. Our findings highlight the crucial role of the favorable land and atmospheric conditions that caused floods and flash floods in north India in July 2023.

Role of Initial Conditions and Meteorological Drought in Soil Moisture Drought Propagation: An Event‐Based Causal Analysis Over South Asia

AbstractThe role of meteorological droughts and initial conditions (land and atmosphere) in soil moisture drought (SMD) propagation are not yet fully understood. This work uses a drought event‐based causal framework to investigate the relative importance of meteorological drought (MD) duration and intensity and initial conditions that result in surface and rootzone SMD, considering their event‐level propagation time (PT) over South Asia. Initially, spatial variability of drought propagation is assessed by the Propagation Ratio (PR) computed based on MD counts that trigger SMD at various lags. PR depicts 2–3 months slower rootzone propagation than at surface. The gradual decrease in PR with increasing regional aridity indicates faster propagation over humid regions. The causal impact of initial conditions and MD parameters on propagating SMD are evaluated using normalized mutual information and a newly proposed normalized conditional mutual information. We found greater importance of triggering MD parameters followed by initial soil moisture condition on propagating SMD. This behavior is more evident for the surface layer propagation at shorter PT. There is a confounding effect of initial atmospheric conditions on drought propagation through initial soil moisture, depicting the significance of land‐atmosphere interactions prior to propagation. In the rootzone propagation, initial soil moisture has a greater influence on propagation, especially at longer PT, indicating the significance of soil moisture persistence. Stronger causal links obtained through the joint influence of MD parameters on SMD suggest the importance of accounting for MD duration and intensity simultaneously, which are not considered in drought index‐based propagation studies.

Effect of potassium application on maize to sandy soil under deficit irrigation conditions

Maize is widely growth in arid and semi-arid region where, drought is common and a limiting factor for crop production. Potassium plays a key role in enhancing plant growth under drought condition. The objective of this study is to determine the effect of K fertilization with and without NP on maize growth grown in sandy loam soil under adequate and deficit irrigation conditions. The following treatments were investigated in pot experiment: (1) control with no fertilizer application (C); (2) 128 kg N + 328 kg P2O5 ha-1 (NPK0); (3) 128 kg N + 328 kg P2O5 ha-1 + 152.5 kg K2O ha1 (NPK1); (4) 128 kg N + 328 kg P2O5 ha-1 + 305 kg K2O ha-1 (NPK2); and 128 kg N + 328 kg P2O5 ha-1 + 457.5 kg K2O ha-1 (NPK3). Treatments were investigated under adequate and deficit soil moisture content. Each pot filled with 3.5 kg air-dry soil and seeded with maize and pots were watered according to the treatments. The results indicated that plant growth and nutrient uptake were significantly reduced under water stress condition. The application of NP increased plant growth and nutrient uptake and further were increased with K application. K application also enhanced plant tolerance to deficit soil moisture condition. In addition, K enhanced nutrient uptake and leaf chlorophyll content. Based on the results, it can be concluded that application of NP for maize was not adequate to achieve the highest plant growth, unless it is combined with K application. In addition, K application enhances plant tolerance to water stress.

Soil Moisture Detection and Linear Deceleration Control Strategy Enhancing Trenching Depth Precision and Stability for Rapeseed Sowing

Sowing depth significantly affects the germination of rapeseed, and different soil moisture conditions require corresponding sowing depths. However, most current trenching devices do not account for soil moisture content, and commonly used hydraulic or constant-force trenching equipment also exhibits deficiencies in stability and consistency. To address these challenges, this study developed an automatic depth adjustment control system based on soil moisture content. A soil moisture detection device and an innovative sliding mechanism that maintained the soil moisture sensor in a relatively stationary position relative to the soil during seeder movement were introduced. An automatic sowing depth adjustment device was designed to modulate the sowing depth. A control strategy that incorporated the Kalman filtering algorithm and linear deceleration equations was conducted. At an observation noise covariance matrix (Q/R) of 0.001, a deceleration range of 40 mm and a minimum speed of 10, the control system exhibited minimal overshoot (approximately 4%) and steady-state error (approximately 3.2 mm). It effectively adjusted the trenching depth while operating at speeds ranging from 2 to 3.6 km/h, successfully adapting to variations in soil topography. The system performance tests revealed that the control system adjustment time (ts) was 534 ms and the steady-state error remained within 1 mm. Under three different soil moisture content conditions, the sowing depth qualification rate and stability coefficients consistently surpassed 90% and 80%, respectively. This research offers a sowing depth adjustment control system based on soil moisture content, contributing to more precise depth regulation for rapeseed sowing.