Soil Moisture Conditions Research Articles

Dynamic hydrological niche segregation: How plants compete for water in a semi-arid ecosystem

Hydrological niche segregation (HNS), specifically the variation in root water uptake depth among coexisting species, is an understudied area of research. This is especially the case in semi-arid ecosystems, such as China’s Loess Plateau (CLP), where seasonal aridity necessitates adaptive water use strategies among plant species. In this study, we conducted a two-year investigation to understand the water sources and intrinsic water use efficiency (WUEi) of four coexisting plant species: Populus simonii (tree), Caragana korshinskii and Salix psammophila (shrubs), and Artemisia ordosica (semi-shrub). We analyzed the isotopic compositions of xylem and soil water (δ2H and δ18O) and leaf δ13C to identify the water sources and WUEi, respectively, of each species. We then used the nicheROVER model to quantify HNS based on the variations in xylem water δ2H and δ18O. Our results show that the four co-existing species occupied distinct positions on a hydrological niche axis, delineated by their respective water sources and disparate WUEi. The tree P. simonii exhibited a preference for deep soil water and demonstrated a high WUEi. Both shrubs, S. psammophila and C. korshinskii, utilized intermediate and deep soil water, respectively, and with comparable WUEi. Conversely, the semi-shrub A. ordosica relied on shallow soil water and displayed a low WUEi. These differences in water sources and WUEi led to HNS between A. ordosica and the other three species in a relatively wet year. However, in a relatively dry year, HNS between A. ordosica and the other three species contracted and WUEi increased as species increased the use of deep soil water. Overall, these results demonstrate that HNS is a dynamic phenomenon that varies on at least an annual basis. It expands and contracts as plants regulate their water uptake and loss in response to changing soil moisture conditions.

Nitrous Oxide Emissions during Cultivation and Fallow Periods from Rice Paddy Soil under Urea Fertilization

Rice cultivation serves as a significant anthropogenic source of methane (CH4) and nitrous oxide (N2O). Although N2O emissions remain relatively small compared to CH4 emissions, they are remarkably affected by nitrogen-fertilized soil conditions during rice cultivation. While numerous studies have investigated nitrous oxide emissions in response to nitrogen fertilization, existing research assessing nitrous oxide emissions based on nitrogen fertilizer levels has often been limited to cultivation periods. Therefore, there is a need for comprehensive analyses covering the entire year, including the dry periods, to address nitrous oxide emissions as an important source throughout the entire agricultural cycle. In this case study, we investigated the characteristics of N2O emissions in a central region of South Korea, where a single rice-cropping cycle occurs annually over a span of three whole years, from May 2020 to May 2023. We investigated the impact of variations in temperature and soil moisture on N2O emissions during rice cultivation and fallow periods. In this context, we attempted to discover the complex dynamics of N2O emissions by comparing longer fallow periods with the rice cultivation periods and extended non-dry periods with irrigated periods. We discovered that the greater contribution of cumulative N2O emissions during the fallow period made a much greater contribution (up to approximately 90%) to the whole-year N2O emissions than those during the rice cultivation period. During the fallow period from rice harvest to rice planting in the following year, variations in N2O emissions were associated with high-flux events after rainy periods on dry soils. This highlights the considerable influence of soil moisture content and weather conditions on N2O emissions during the fallow period. This affects high emission events, which in turn significantly impact the cumulative emissions over the entire period. We underscore that assessing N2O emissions solely based on the rice cultivation period would underestimate annual emissions. To prevent underestimation of N2O emissions, periodic gas collection throughout a year covering both rice cultivation and fallow phases is required in alignment with the monitoring of different temperature and soil moisture conditions. We captured statistical differences in cumulative N2O emissions due to nitrogen fertilization treatments across the three years. However, no significant difference was observed in the three-year average emissions among the different (one, one-and-a-half, and double) nitrogen fertilization treatments, with the exception of the control treatment (no fertilization). Based on the findings, we recommend at least three whole-year evaluations to ensure the estimation accuracy of N2O emissions under different nitrogen fertilization conditions. The findings from this study could help prepare the further revision or refinement of N2O emission factors from rice cultivation in the national greenhouse gas inventories defined by the inter-governmental panel on climate change (IPCC).

Farmer insights on harvesting peanut: A survey from the Virginia–Carolina region of the United States

Plain Language SummaryPeanut harvest is a two‐step process that requires digging pods and inverting vines and threshing after pods and vines have dried for an adequate amount time. Weather patterns, including temperature and soil moisture, can affect the pod maturation process. Additionally, inclement weather, soil moisture conditions, farm logistics, balance of equipment and acreage, plant health and disease incidence, and equipment setting and operation can affect harvest efficiency and yield. A survey of 166 farmers in North Carolina, South Carolina, and Virginia, representing 25% of acreage, was administered to determine their perceptions of challenges they face at harvest and how they address those challenges. The majority of growers indicated that they would dig pods and invert vines prior to a storm. Peanut maturity was as important as soil conditions and concerns over tropical weather when deciding when to dig peanut.

Estimation of soil water storage according to its multi-scale correlations with environmental factors

Soil water storage (SWS) is a crucial parameter for vegetation restoration and a variety of hydrological processes in semi-arid regions. Its dynamics reflect the integrated influence of different factors operating at various intensities and scales. In this study, we investigated the scale-specific correlations between SWS and six selected environmental factors along a 1340-m long sampling transect in a semi-arid catchment using multivariate empirical mode decomposition (MEMD). The six factors were bulk density, elevation, clay, silt, sand, and soil organic carbon content. The multivariate data series of the SWS and factors of interest were separated into seven intrinsic mode functions (IMFs) and residue. IMF1, IMF3, and IMF5 were identified as the primary scales according to the percentage of total variance (about 50%) in SWS under different soil moisture conditions. The scale-specific correlations between SWS and the corresponding factors varied with scale but were irrelevant to soil moisture condition. SWS at each IMF and residue could be estimated using the associated scale-specific environmental factors at the same IMF or residue. SWS at the measurement scale was satisfactorily estimated by summarizing all the predicted IMFs and residue, which outperformed measurement-scale SWS estimation based on multivariate stepwise linear regression between SWS and the associated factors. Soil moisture condition could affect the relative importance of the environmental factors in overall SWS estimation. In general, soil properties were the dominant predictor of SWS under different soil moisture conditions. MEMD provides a useful opportunity to deal with scale-specific correlations between various variables.

SISTEM MONITORING DAN PENYIRAMAN OTOMATIS TANAMAN SRIGADING (NYCTANTHES ARBOR-TRISTIS) BERBASIS IOT (INTERNET OF THINGS) DENGAN MENGGUNAKAN SENSOR KELEMBAPAN TANAH DAN SUHU RUANG PADA POT

This automatic plant monitoring and watering system is designed to make it easier to manage plants around pots or indoors such as greenhouses. This tool uses two main sensors, namely the DHT11 sensor to detect temperature and the soil moisture sensor to measure soil moisture. The microcontroller used is NodeMCU ESP8266. The output of this system includes a mini water pump, DC fan, and the Blynk application on Android devices. Based on the tests that have been carried out, if the temperature is detected above 33ᵒC, the fan will activate; but if it is below 33ᵒC, the fan will turn off. When soil moisture is detected above 90ᵒC, the water pump will activate as it indicates dry soil. The Blynk app features 3 monitoring controls, including 2 LCD screens. The first LCD monitors indoor temperature, while the second LCD is used to monitor soil moisture and fan conditions. There is also a Gauge display which displays the condition of the soil moisture sensor embedded in the plant pot.

Improved Agricultural Drought Monitoring with an Integrated Drought Condition Index in Xinjiang, China

Drought is a natural disaster with severe global agricultural and economic impacts. Accurate drought indices are needed for improved assessment and monitoring; however, most existing drought indices poorly represent agricultural drought due to complex interactions among meteorological factors, crop and soil conditions. Here, we compute an integrated drought condition index (IDCI) based on the 3-month standardized precipitation evapotranspiration index (SPEI3), vegetation cover index (VCI) and soil moisture condition index (SMCI). We apply the IDCI to monitoring agricultural drought in Xinjiang, China. After regional evaluations with soil moisture, precipitation and air temperature observations, as well as with the scaled crop yields index, the IDCI was used to describe spatiotemporal changes in regional drought in Xinjiang during 2000–2018, revealing adverse impacts on crop yield (beet, wheat and vegetables). The IDCI is strongly correlated with observed soil moisture and performs better than SMCI, VCI or SPEI3, demonstrating that the IDCI is suitable for agricultural drought monitoring. The most severe drought occurred in the spring to autumn of 2008. Droughts before 2008 were more serious than those after 2008, in terms of both severity and frequency. Droughts in northern, southern and eastern Xinjiang, as well as in the Tianshan Mountains, were generally increasing before 2008 and then weakened after 2008.

Water uptake by plants under nonuniform soil moisture conditions: A comprehensive numerical and experimental analysis

The spatiotemporal pattern of root water uptake (RWU) depends on multiple factors, such as plant root biomass, soil water availability, and prevailing weather conditions at the site. The water uptake reduction due to the nonuniformity in soil water contents is often mitigated through compensated root water uptake (CRWU) and hydraulic redistribution (HR). Although previous studies have often considered these two processes independently due to the simplicity and feasibility of analyzing them separately, CRWU and HR can coexist in field conditions. Therefore, this work demonstrates the importance of considering CRWU and HR simultaneously in estimating daily transpiration and RWU distribution for nonuniform soil moisture conditions. For that, we have implemented the mechanistic RWU models developed by de Jong van Lier et al. (denoted below as the DJ model), Couvreur (CR), and Nimah and Hanks (NH) (see the references in the main text) into the widely-used HYDRUS-1D model, in addition to the previously available Jarvis (JF) and Feddes (FD) models. The performance of these models was then compared for varying soil water contents and boundary conditions using experimental data and hypothetical modeling scenarios. Our analysis has shown that these models are beneficial in estimating RWU with varying degrees of accuracy. The DJ and CR models are effective in simultaneously simulating CRWU and HR. NH and JF models can simulate CRWU but cannot simulate HR satisfactorily. Implementing these models into the HYDRUS platform for simultaneously considering CRWU and HR will significantly improve the accuracy of RWU predictions.

Seasonal dynamics and spatial patterns of soil moisture in a loess catchment

Abstract. The spatial and seasonal patterns in soil moisture and the processes controlling them in semi-arid landscapes are not well understood. Loess landscapes minimize any confounding effects of variation in soil characteristics and are thus ideal for studying topographic influences on soil moisture in drylands. In this study, volumetric soil moisture was monitored monthly for 5.5 years at 20 cm intervals between the surface and 5 m depth at 89 sites across a small (0.43 km2) catchment on the Chinese Loess Plateau. The median soil moisture was computed for each month and depth for each monitoring site as a measure of the typical soil moisture conditions. Seasonal changes in soil moisture were mainly concentrated in the shallow (0–100 cm) soil, with a clear seasonal separation between wet conditions in October–March and dry conditions in May–July, even though precipitation is highest in July–August. Soil moisture was higher on the northwest-facing slopes due to increased drying from solar radiation on the southeast-facing slopes. This effect of slope aspect was greater between October and March, when the zenith angle of the sun was lower and the aspect-dependent difference in solar radiation reaching the surface was larger. The wetter, northwest-facing slopes were also characterized by larger annual soil moisture storage changes. Soil texture was nearly uniform across both slopes, and soil moisture was not correlated with the topographic wetness index, suggesting that variations in evapotranspiration dominated the spatial pattern of soil moisture in shallow soils under both wet and dry conditions. Water balance calculations indicate that over 90 % of the annual precipitation was seasonally cycled in the soil between 0 and 300 cm, suggesting that only a minor fraction infiltrates to groundwater and becomes streamflow. Our findings may be broadly applicable to loess regions with monsoonal climates and may have practical implications for catchment-scale hydrologic modeling and the design of soil moisture monitoring networks.

Strong plastic responses in aerenchyma formation in F1 hybrids of Imperata cylindrica under different soil moisture conditions.

Hybrids can express traits plastically, enabling them to occupy environments that differ from parental environments. However, there is insufficient evidence demonstrating how phenotypic plasticity in specific traits mediates hybrid performance. Two parental ecotypes of Imperata cylindrica produce F1 hybrids. The E-type in wet habitats has larger internal aerenchyma than the C-type in dry habitats. This study evaluated relationships between habitat utilisation, aerenchyma plasticity, and growth of I. cylindrica accessions. We hypothesize that plasticity in expressing parental traits explains hybrid establishment in habitats with various soil moisture conditions. Aerenchyma formation was examined in the leaf midribs, rhizomes and roots of two parental ecotypes and their F1 hybrids in their natural habitats. In common garden experiments, we examined plastic aerenchyma formation in leaf midribs, rhizomes and roots of natural and artificial F1 hybrids and parental ecotypes and quantified vegetative growth performance. In the natural habitats where soil moisture content varied widely, the F1 hybrids showed larger variation in aerenchyma formation in rhizomes than their parental ecotypes. In the common garden experiments, F1 hybrids showed high plasticity of aerenchyma formation in rhizomes, and their growth was similar to that of C-type and E-type under drained and flooded conditions, respectively. The results demonstrate that F1 hybrids of I. cylindrica exhibit plasticity in aerenchyma development in response to varying local soil moisture content. This characteristic allows the hybrids to thrive in diverse soil moisture conditions.

The Potential Impact of Changes in Soil and Climate Conditions on Development of the Herb Layer Vegetation of Public Parks in Krakow (Southern Poland)

Today, urban greenery is at the center of attention, especially in the context of climate change. Shaped in large part by natural factors, the herb layer of public parks is a part of urban greenery that is the most sensitive to climate and soil condition changes. In this paper, we present a study intended to answer how resilient is the species composition and herb layer structure against the soil and climate condition changes in parks. To this end, we analyzed Ellenberg and Zarzycki’s ecological index numbers for species recorded in different groups in terms of historical-geographical, life forms, prevalence within the flora of Poland, and relationships with different vegetation types (phytoassociation classes) in comparison to the conditions present in parks. It was found that a large part of various species groups showed an optima and ecological tolerance spectra that went beyond the park conditions, indicating that at least some park vegetation can be expected to show resilience to changing conditions. However, changes in temperature and humidity will alter the composition and structure of the park herb layer. The direction of changes in climate and soil conditions can be decisive for herb layer transformation directions. With rising temperatures, humidity can be crucial. Poor soil moisture conditions will promote an increased share of foreign, synanthropic species, while local natural and semi-natural species will disappear. When climate change that leads to a decrease in temperatures is concerned, it is temperature and not humidity that will be the key factor in the transformation of park herb layer species compositions. The herb layer of Krakow’s parks will have the least resilience to changes in conditions within local non-synanthropic species, rare species and geophytes and to some extent also forest and meadow species.

Differential modulation of crown allometry and stem growth at gap edges in five European tree species by drought conditions

BackgroundIn Central Europe, forests are increasingly affected by various disturbances, resulting in an increasing gap formation in the canopy. In order to support goal-oriented management, more knowledge is required about the acclimation of the crown and its effects on the basal area growth of trees at the edge of a gap. MethodsThis work compared trees' growth and crown structure at the edge of a transient gap, with a gap size of more than 80 ​m2, with trees in the stand that were at least 30 ​m away from the gap. A total of 249 European beeches (Fagus sylvatica L.), Norway spruces (Picea abies L. Karst), Scots pines (Pinus sylvestris L.), oaks (Quercus spp.; Quercus petraea (Matt.) Liebl., Quercus robur L.), and silver firs (Abies alba Mill.) were examined on long-term experimental plots in southern Germany. Various crown measures were developed and calculated using high-resolution terrestrial laser scanning (TLiDAR) to capture the three-dimensional crown structures. Growth responses to edge conditions were measured based on tree rings. Using linear mixed models, we predict the basal area increment of edge trees relative to trees in the stand under wet and dry soil moisture conditions after the gap formation. ResultsWe identified i) species-specific acclimation of the crown of edge trees after the gap formation, ii) under wet soil moisture conditions a growth increase of 25%–45% for beech, pine, and oak edge trees and growth losses of 5%–60% for spruce and fir and iii) coniferous tree species benefited from the edge position regarding their basal area increment under dry soil moisture conditions and deciduous tree species grew regardless of the soil moisture conditions at the edge of a gap. ConclusionGaps have a species-specific effect on the habitus and growth of edge trees and can have both positive and negative impacts on silviculture.

SCIENTIFIC SUBSTANTIATION OF THE PRODUCTIVITY OF SOWING ALFALFA DEPENDING ON SOIL AND CLIMATIC CONDITIONS OF THE FOREST-STEPPE OF UKRAINE

The article presents a review of literature sources on the study of alfalfa productivity depending on the influence of sowing dates, mineral phosphorus-potassium nutrition, soil liming, pre-sowing seed treatment with bacterial preparations and modes of grass stand use when grown for fodder purposes. It was found that the change of photoperiod in the year of sowing was a signal in alfalfa plants to pass through the microstages of growth and development, which was determined by the length of daylight hours and sowing dates, regardless of hydrothermal resources. Observations showed that the crop reached the beginning of flowering phase (code 61-62 of the BBSN) at daylight hours of 14:53-16:12 h, while at 12:48 h it reached the budding phase (code 49 of the BBSN). Regardless of climate change, which has been observed for more than a decade, sowing alfalfa provided the highest productivity indicators with early spring sowing and long-term use of the grass stand. Over the three years of vegetation, its leaf mass yield averaged 47.03 t/ha, dry matter yield was 11.09 and 2.07 t/ha of crude protein, and gross and metabolizable energy were 204.72 and 104.52 GJ/ha, respectively. At the same time, with the recommended summer sowing date (20 July), the indicators decreased by 9.1, 11.5, 13.1, 12.2 and 11.7%, respectively. Analysing the agro-ecological resources of Ukraine, given the natural soil fertility, moisture, temperature and light conditions, they are quite favourable for the maximum realisation of the biological potential of the fodder productivity of sowing alfalfa within the yield of fodder units of 10-12 t/ha and 1.8-2.2 t/ha of digestible protein. Among the elements of intensifying the cultivation of seed alfalfa for the production of plant raw materials and harvesting of various types of fodder, fertilisation is the most effective factor influencing their quantity and quality. To calculate the amount of mineral fertiliser, we take into account the biological characteristics of the crop, its cyclical growth and development during the growing season, the method of sowing and the duration of grassland use. Regardless of the geographical origin of the seed alfalfa, for two years of using the grass stand and observing technological measures of cultivation (lime, phosphorus-potassium mineral fertilisers, seed inoculation), alfalfa provided the highest yield of crude protein of 5.83-5.97 t/ha when mowing the first mowing in the flowering phase, the second - at the beginning of flowering and the third in the budding phase. Mowing of three mowings of sowing alfalfa at the beginning of the flowering phase contributes to the effective use of the light regime of the growing season as the main factor in increasing productivity. Innovative technologies for growing seed alfalfa use growth-regulating agents of various origins, microfertilisers and biological seed treatment products to increase yields and dry matter quality for foliar feeding. The complex application of these preparations provides an increase in the yield of leaf mass by 16.6-18.2%. Thus, in the context of modern agricultural development, alfalfa is one of the components of reducing the anthropogenic load on the agro-ecological system and increasing the production of environmentally friendly high-protein feed and livestock products for the purpose of efficient use of hydrothermal resources and environmental protection.

Persistent net release of carbon dioxide and methane from an Alaskan lowland boreal peatland complex.

Permafrost degradation in peatlands is altering vegetation and soil properties and impacting net carbon storage. We studied four adjacent sites in Alaska with varied permafrost regimes, including a black spruce forest on a peat plateau with permafrost, two collapse scar bogs of different ages formed following thermokarst, and a rich fen without permafrost. Measurements included year-round eddy covariance estimates of net carbon dioxide (CO2 ), mid-April to October methane (CH4 ) emissions, and environmental variables. From 2011 to 2022, annual rainfall was above the historical average, snow water equivalent increased, and snow-season duration shortened due to later snow return. Seasonally thawed active layer depths also increased. During this period, all ecosystems acted as slight annual sources of CO2 (13-59 g C m-2 year-1 ) and stronger sources of CH4 (11-14 g CH4 m-2 from ~April to October). The interannual variability of net ecosystem exchange was high, approximately ±100 g C m-2 year-1 , or twice what has been previously reported across other boreal sites. Net CO2 release was positively related to increased summer rainfall and winter snow water equivalent and later snow return. Controls over CH4 emissions were related to increased soil moisture and inundation status. The dominant emitter of carbon was the rich fen, which, in addition to being a source of CO2 , was also the largest CH4 emitter. These results suggest that the future carbon-source strength of boreal lowlands in Interior Alaska may be determined by the area occupied by minerotrophic fens, which are expected to become more abundant as permafrost thaw increases hydrologic connectivity. Since our measurements occur within close proximity of each other (≤1 km2 ), this study also has implications for the spatial scale and data used in benchmarking carbon cycle models and emphasizes the necessity of long-term measurements to identify carbon cycle process changes in a warming climate.

Shift of soil moisture-temperature coupling exacerbated 2022 compound hot-dry event in eastern China

Compound hot-dry events (CHDEs) are among the deadliest climate hazards and are occurring with increasing frequency under global warming. The Yangtze River Basin in China experienced a record-breaking CHDE in the summer of 2022, causing severe damage to human societies and ecosystems. Recent studies have emphasized the role of atmospheric circulation anomalies in driving this event. However, the contribution of land–atmosphere feedback to the development of this event remains unclear. Here, we investigated the impacts of soil moisture-temperature coupling on the development of this concurrent heatwave and drought. We showed that large amounts of surface net radiation were partitioned to sensible heat instead of latent heat as the soil moisture-temperature coupling pattern shifted from energy-limited to water-limited under low soil moisture conditions, forming positive land–atmosphere feedback and leading to unprecedented hot extremes in August. The spatial heterogeneity of hot extremes was also largely modulated by the land–atmosphere coupling strength. Furthermore, enhanced land–atmosphere feedback has played an important role in intensifying CHDEs in this traditional humid region. This study improves the understanding of the development of CHDEs from three aspects, including timing, intensity, and spatial distribution, and enables more effective early warning of CHDEs.

Systematic Modeling Errors Undermine the Application of Land Data Assimilation Systems for Hydrological and Weather Forecasting

Abstract Due to recent advances in the development of land data assimilation systems (LDAS) and the availability of high-quality, satellite-based surface soil moisture (SSM) retrieval products, we now have unambiguous evidence that the assimilation of SSM retrievals, or their proxy, can improve the precision (i.e., correlation versus truth) of surface state estimates provided by a land surface model (LSM). However, this clarity does not yet extend to the estimation of LSM surface water fluxes that are key to hydrologic and numerical weather forecasting applications. Here, we hypothesize that a key obstacle to extrapolating realized improvements in water state precision into comparable improvements in water flux accuracy (i.e., mean absolute error) is the presence of water state–water flux coupling strength biases existing in LSMs. To test this hypothesis, we conduct a series of synthetic fraternal twin data assimilation experiments where realistic levels of state–flux coupling strength bias—involving both evapotranspiration and runoff—are systematically introduced into an assimilation LSM. Results show that the accuracy of the resulting water flux analysis is sharply reduced by the presence of such bias, even in cases where the precision of soil moisture state estimates (e.g., SSM) is improved. The rescaling of SSM observations prior to their assimilation (i.e., the most common approach for addressing systematic differences between LSMs and assimilated observations) is not always a robust strategy for addressing these errors and can, in certain circumstances, degrade water flux accuracy. Overall, results underscore the critical need to assess, and correct for, LSM water state–water flux coupling strength biases during the operation of an LDAS. Significance Statement Land data assimilation is the process by which land surface model estimates of water states (e.g., soil moisture) and water fluxes (e.g., runoff and evapotranspiration) are improved via the incorporation of observations. Over the past decade, substantial improvements have been made in the precision of land surface model states via the assimilation of satellite-based soil moisture information. However, to date, these improvements have not yet been extended into water flux estimates like runoff and evapotranspiration. This is a critical shortcoming since advances in important weather and hydrologic forecasting applications are dependent on the improved estimation of such fluxes. We demonstrate that this shortcoming is linked to the inability of existing land surface models to accurately describe the impact of variations in water states on water fluxes and propose strategies for overcoming this issue in future land data assimilation systems.

Compilation of Benchmark Pluvial Flood Datasets

Urban pluvial flooding is a dangerous natural hazard that has become more common in recent years, making it a global threat to metropolitan areas. Surface water floods and flash floods are two common types of pluvial flooding. The second one is extremely hazardous and damaging due to both the power of the water and the debris that is frequently swept up in the flow. Buildings and their contents are damaged by pluvial floods, which also disrupt stormwater drainage, transportation, and electrical supply. Future flood risks are anticipated to rise because of urbanization, climate change, and global warming. Many essential features of urban flood hazards are still poorly understood due to the complex nature of the relevant processes and the paucity of long-term field observations. Therefore, in this paper, we have collected different sources of data that are used for flood forecasting. Satellite data, gauge measurements, and citizen observations are the most important sources of precipitation and flood data. Conducting a global case study review also showed that the Digital elevation model (DEM) and rainfall are the most crucial variables when it comes to floods, and they are nearly universally employed in all models. The discussion suggests that soil moisture conditions are likely to be the predominant mechanism causing the observed flood trends.

Scalar Flux Profiles in the Unstable Atmospheric Surface Layer Under the Influence of Large Eddies: Implications for Eddy Covariance Flux Measurements and the Non‐Closure Problem

AbstractHow convective boundary‐layer (CBL) processes modify fluxes of sensible (SH) and latent (LH) heat and CO2 (Fc) in the atmospheric surface layer (ASL) remains a recalcitrant problem. Here, large eddy simulations for the CBL show that while SH in the ASL decreases linearly with height regardless of soil moisture conditions, LH and Fc decrease linearly with height over wet soils but increase with height over dry soils. This varying flux divergence/convergence is regulated by changes in asymmetric flux transport between top‐down and bottom‐up processes. Such flux divergence and convergence indicate that turbulent fluxes measured in the ASL underestimate and overestimate the “true” surface interfacial fluxes, respectively. While the non‐closure of the surface energy balance persists across all soil moisture states, it improves over drier soils due to overestimated LH. The non‐closure does not imply that Fc is always underestimated; Fc can be overestimated over dry soils despite the non‐closure issue.

Monitoring drought dynamics using remote sensing-based combined drought index in Ergene Basin, Türkiye

Abstract Remote sensing-based approaches have gained widespread usage in drought monitoring studies. However, relying on single-variable drought indices may be inadequate to provide a comprehensive understanding of drought dynamics. In this study, principal component analysis was employed to derive a combined index, namely, the combined drought index (CDI), from multiple indices such as vegetation condition index, temperature condition index, precipitation condition index, and soil moisture condition index. The CDI was subsequently employed to analyze drought occurrences in the Ergene Basin-Türkiye period from 2001 to 2020 (May to October) using MODIS data. Correlations were computed with standardized precipitation index (SPI) and standardized precipitation evapotranspiration index (SPEI) at 1-, 3-, and 6-month scales and crop yield. The results revealed that drought incidents transpired in the Ergene Basin for at least 1 month annually. May exhibited the wettest, while September stood as the driest month. The severity of drought and its spatial extent displayed an increasing trend followed by a subsequent decline during the aforementioned period. The CDI demonstrated stronger correlations with the 1-month standardized indices than the 3- and 6-month SPI-SPEI. A robust correlation of 0.79 was also observed between the CDI and the crop yield. In general, the CDI performed well in determining the spatial and temporal patterns of the historic droughts. As a result, the CDI could be leveraged to develop effective drought monitoring and management, which could help mitigate the negative impact of drought in the fragile environment of the Ergene Basin.

Towards Affordable Precision Irrigation: An Experimental Comparison of Weather-Based and Soil Water Potential-Based Irrigation Using Low-Cost IoT-Tensiometers on Drip Irrigated Lettuce

Predictive weather-based models are widely used to schedule irrigation through the estimation of crop evapotranspiration. However, perceiving real-time crop water requirements remains a challenge. This research aims at field validating and exploiting a low-cost IoT soil moisture tensiometer prototype to consequently compare weather-based irrigation to soil water moisture-based irrigation in terms of yield and crop water productivity. The prototype is based on the ESP32 microcontroller and BMP180 barometric sensor. When compared to a mechanical tensiometer, the IoT prototype proved its accuracy, registering an average R2 equal to 0.8 and an RMSE range of 4.25–7.1 kPa. In a second step, the irrigation of a Romaine lettuce field (Lactuca sativa L.) cultivated under a drip system was managed according to two different scenarios: (1) using the data feed from the IoT tensiometers, irrigation was performed to keep the soil water potential between −15 and −25 kPa; (2) using the data provided by the in-situ weather station to estimate the crop water requirements. When comparing the yield, no significant difference was registered between the two scenarios. However, the water productivity was significantly higher, registering a 36.44% increment in scenario 1. The experiment highlights the water-saving potential achievable through real-time monitoring of soil moisture conditions. Since it is a low-cost device (82.20 USD), the introduced prototype facilitates deploying and managing a fleet of sensors for soil water potential live mapping.

Utilization of Actinomycetes to increase phosphate availability at different soil moisture conditions in Andisols Namanteran, North Sumatera

The high phosphate retention in Andisols causes the availability of P to be low, can not be absorbed by plants. Actinomycetes are capable of solubilizing bound phosphates. This research aimed to identify Actinomycetes in Andisols Namanteran, assess their ability to increase phosphate availability, and understand how they work to increase phosphate availability in this soil. The research design used a factorial randomized block design with 2 factors; factor 1 was Actinomycetes isolate, consisting of A₀ = No Inoculant, A₁ = Inoculant A₁₃₂ (vegetable crops; 32 × 10⁸ CFU mL⁻¹), A₂ = A₄₆₈ (forest plants; 41 × 10⁸ CFU mL⁻¹), A₃ = A₄₅₈ (forest plant; 58 × 10⁸ CFUmL⁻¹), A₄ = A₄₇₁ (coffee plant; 35 × 10⁸ CFU mL⁻¹), A₅ = A₄₅₉ (forest plant; 63 × 10⁸ CFU mL⁻¹), A₆ = A₃₂₁ (hibiscus plant; 37 × 10⁸ CFU mL⁻¹), and A₇ = A₃₅₆ (vegetable plant; 33 × 10⁸ CFU mL⁻¹), and factor 2 was soil water content, consisting of K₁ = 50%, K₂ = 75% and K₃ = 100% of field capacity. The results showed that the availability of P in Andisols increased due to the application of Actinomycetes from 42.46 ppm to 159.20−266.60 ppm. The population of Actinomycetes in Actinomycetes treatment ranged from 27.33−31.58 × 10⁸ CFU mL⁻¹), with a soil pH of 4.41. Water content of 100% was the best in increasing soil pH and Actinomycetes population, but not having significant effects on the available P of the soil. The results of molecular identification of Actinomycetes that have the best potential in dissolving P include A₃>A₅>A₂>A₄>A₁.