Zone Management Research Articles

Prediction of Groundwater Quality Index Using Classification Techniques in Arid Environments

Assessing water quality is crucial for improving global water resource management, particularly in arid regions. This study aims to assess and monitor the status of groundwater quality based on hydrochemical parameters and by using artificial intelligence (AI) approaches. The irrigation water quality index (IWQI) is predicted by using support vector machine (SVM) and k-nearest neighbors (KNN) classifiers in Matlab’s classification learner toolbox. The classifiers are fed with the following hydrochemical input parameters: sodium adsorption ratio (SAR), electrical conductivity (EC), bicarbonate level (HCO3), chloride concentration (Cl), and sodium concentration (Na). The proposed methods were used to assess the quality of groundwater extracted from the desertic region of Adrar in Algeria. The collected groundwater samples showed that 9.64% of samples were of very good quality, 12.05% were of good quality, 21.08% were satisfactory, and 57.23% were considered unsuitable for irrigation. The IWQI prediction accuracies of the classifiers with the standardized, normalized, and raw data were 100%, 100%, and 90%, respectively. The cubic SVM with the normalized data develops the highest prediction accuracy for training and testing samples (94.2% and 100%, respectively). The findings of this work showed that the multiple regression model and machine learning could effectively assess water quality in desert zones for sustainable water management.

Multilayer Data and Artificial Intelligence for the Delineation of Homogeneous Management Zones in Maize Cultivation

Variable rate application (VRA) is a crucial tool in precision agriculture, utilizing platforms such as Google Earth Engine (GEE) to access vast satellite image datasets and employ machine learning (ML) techniques for data processing. This research investigates the feasibility of implementing supervised ML models (random forest (RF), the support vector machine (SVM), gradient boosting trees (GBT), classification and regression trees (CART)) and unsupervised k-means clustering in GEE to generate accurate management zones (MZs). By leveraging Sentinel-2 satellite imagery and yielding monitor data, these models calculate vegetation indices to monitor crop health and reveal hidden patterns. The achieved classification accuracy values (0.67 to 0.99) highlight the potential of GEE and ML models for creating precise MZs, enabling subsequent VRA implementation. This leads to enhanced farm profitability, improved natural resource efficiency, and reduced environmental impact.

Using an open source and resilient technology framework to generate and execute prescription maps for site-specific manure application

The development of precision farming solutions and the required network infrastructure appear to be progressing at different speeds and levels of deployment. In most of the world's rural areas, where farming takes place, network coverage and infrastructure is at a basic level. However, where digital farming solutions are applied, internet-dependent applications need backup solutions to enable the same or a comparable performance towards maintaining the functionality of the specific practice and ultimately food production. The aim is to avoid regressing to basic practices waiving advantages of established precision farming technologies. Based on a conceptual framework, defined by the authors in a previous work, site-specific slurry application was chosen as a concrete use case to implement and demonstrate fallback options to maintain efficient and reliable application even during internet outages. Initially, the differences between conventional and resilient IT infrastructure were contrasted and investigated. The generation of a prescription map (PM) based on the fusion of multiple parameters, clustered in the domains of soil, yield, and remote sensing, was performed utilizing open-source and offline usable software. For seamless transmission of the generated PMs, a new and innovative hardware platform was integrated into the machinery fleet and working process of a machinery ring (MR), which was acting as a service contractor in the inter-farm slurry application. Interoperability was considered by enabling the executing software to accept PMs of altering origin. The on- and off-line generation of PMs including data fusion, were also compared. Here the multi-parametric approach corresponded to the ground truth data, whereas the PMs generated in an online farm management information system (FMIS), using only one data source, showed deviations in management zone patterns and relative dose rates. In addition, the impact of the lack of online accessible data on the delineation of management zones was investigated and resulted in a switch from the medium to the high dose rate (DR) level in 9.1% of the field's area.

Scale effects on the supply–demand mismatches of ecosystem services in Hubei Province, China

Understanding the patterns, relationships, and driving forces between ecosystem services (ESs) supply–demand at multiple spatial scales can facilitate sustainable hierarchical management. However, the scale effects of ESs supply–demand mismatches were typically ignored, resulting in inadequate targeted ecosystem promotion policies. This study identified the supply–demand mismatches of the key ESs (grain production, water yield, carbon sequestration, and soil conservation) using the ecological supply–demand ratio and bivariate Moran's I at three grid and county scales from 2000 to 2020 in Hubei Province, China. Then the spatial regression models were applied to explore the driving forces of these mismatches. The major results revealed that (1) Hubei Province and counties located away from urban areas were self-sufficient in the ESs supply–demand, but the numbers of these counties declined over the twenty years. The characteristics of ESs mismatches in some patches may be obscured at coarser scales. (2) The directions of socioecological drivers were robust, but their intensities changed significantly at the four scales. The normalized difference vegetation index was the primary positive driver at the fine scale, while population, economy, and proportion of construction land became dominant drivers at coarser scales. Factors influencing mismatches were more diverse at the fine scale compared to the coarse scale. (3) Efficient strategies were scale-dependent and place-based. Different management units should clarify their responsibilities and strengthen linkages between upper and lower levels to achieve sustainable ESs development. At the provincial level, strengthening interregional cooperation and allocating surplus grain and water resources from the southwest to urban regions contributes to balancing regional ESs. At the county level, adopting region-specific strategies based on delineating ESs management zones is crucial. At finer management levels, incorporating micro-scale mismatch locations and natural background information can provide valuable guidance for localized ecological protection and restoration projects. The findings underscore the strengths of conducting assessments of ESs supply–demand at multiple scales, enabling different government levels to enhance effective ecosystem management and prevent misinformation.

Evaluation of new pivoting linear‐move precision irrigation machine

AbstractDue to population growth, freshwater resources around the world are becoming increasingly scarce, and the water supply in agriculture has emerged as one of the limitations of food production. Variable‐rate irrigation (VRI), a type of precision irrigation, allows water‐efficient irrigation techniques to ensure an optimal water supply. The University of Debrecen, in collaboration with Magtár Kft., was the first in Hungary to develop a new laterally mobile irrigation machine equipped with VRI. The subject of our study was the testing of this system. According to the research, high and homogeneous irrigation uniformity was achieved in practice, with a Christiansen uniformity coefficient (CUc%) of 93 ± 2, distribution uniformity (DU%) of 88 ± 2 and coefficient of variation (CV) of 9 ± 2. Irrigation accuracy was also found to be satisfactory (mean absolute error 0.6 ± 0.1, mean bias error 0.2 ± 0.2, normalized root mean square error 8.6 ± 2), and only 1.4% ± 2% was overirrigated and 0.4% ± 0.3% underirrigated. In addition, the uniformity and accuracy of irrigation in different management zones along the pipeline were also investigated, and significant differences (p < 0.05) were found between irrigation water depths. Based on the above, a new laterally mobile irrigation machine equipped with VRI can be used to develop more uniform and accurate irrigation schedules in the future in arable fields as this is critical for water‐saving irrigation management.

Ground-Penetrating Radar and Electromagnetic Induction: Challenges and Opportunities in Agriculture

Information on the spatiotemporal variability of soil properties and states within the agricultural landscape is vital to identify management zones supporting precision agriculture (PA). Ground-penetrating radar (GPR) and electromagnetic induction (EMI) techniques have been applied to assess soil properties, states, processes, and their spatiotemporal variability. This paper reviews the fundamental operating principles of GPR and EMI, their applications in soil studies, advantages and disadvantages, and knowledge gaps leading to the identification of the difficulties in integrating these two techniques to complement each other in soil data studies. Compared to the traditional methods, GPR and EMI have advantages, such as the ability to take non-destructive repeated measurements, high resolution, being labor-saving, and having more extensive spatial coverage with geo-referenced data within agricultural landscapes. GPR has been widely used to estimate soil water content (SWC) and water dynamics, while EMI has broader applications such as estimating SWC, soil salinity, bulk density, etc. Additionally, GPR can map soil horizons, the groundwater table, and other anomalies. The prospects of GPR and EMI applications in soil studies need to focus on the potential integration of GPR and EMI to overcome the intrinsic limitations of each technique and enhance their applications to support PA. Future advancements in PA can be strengthened by estimating many soil properties, states, and hydrological processes simultaneously to delineate management zones and calculate optimal inputs in the agricultural landscape.

The role of behavior accessibility and individual risk perceptions in chronic wasting disease risk mitigation behaviors among Minnesota deer hunters

ABSTRACT Human activities, including the movement of harvested cervids, pose significant risks for spreading chronic wasting disease (CWD) to new locations. This study used hierarchical agglomerative clustering to compare Minnesota, USA hunters’ carcass disposal habits and likelihood of CWD testing as a function of individual differences in risk perceptions and hunting area. We utilized a survey of Minnesota hunters conducted during Spring 2020 that included a random sample of individuals that hunt statewide and in a local disease management zone (N = 5,000, response rate = 33%). We did not detect a significant difference in disposal behaviors as a function of CWD risk perceptions, but rather because of increased accessibility of low-risk disposal methods. Conversely, we found perceived likelihood of conducting CWD testing was positively associated with perceptions of risk. These findings have implications for vector tracing for future CWD outbreaks and highlight the benefit of understanding constituent habits and regulation compliance in disease management.

Toxic Communication Zones and Emotive Markers in the Russian-Language Work Environment

The paper addresses the problems of toxic communications in the workplace and considers lexical and grammatical means of expressing emotions. The material for the study was former workers' comments and anonymous questionnaires completed by current employees of Russian enterprises. Based on empirical data processed under Fisher's angular transformation method, which enabled highly accurate comparison of small samples, three toxic communication zones in industry were identified: the zones of toxic bosses, toxic management, and toxic workers. The authors performed a Likert scale survey of executives, managers, and workers. The results of single-factor and two-factor analysis of variance helped us to establish the relation between toxic communication and so-called toxicity focuses, that is, standard topics which are constantly in the centre of destructive communications in the workplace. The paper determines lexical and grammatical means of expressing emotions which are emotive markers of toxic communication (affectives and connotatives). It shows that abusive words and phrases, zoolexics, vernacular and slang vocabulary, colloquial emotionally colored vocabulary, and phraseological units are equally relevant for all three zones of toxic communication zones. Quantitative analysis of the identified emotive markers in terms of their structural and morphological characteristics revealed the abundance of interjections, nouns, adjectives, and adverbs of degree and intensity.

Legal and institutional assessment at Kedah’s Shoreline, Malaysia: A study report

The present paper examines the existing legal framework and administrative instruments outlined and adopted by various agencies to promote the sustainable development of the coastal areas for public safety, the protection of coastal communities and properties along the coast, and protection of environment at Kedah’s shoreline. The study provides an insight on the various laws and regulations governing developments in the coastal areas. An integrated and coordinated approach was proposed for the application of reclamation projects. The process which involved 11 stages is commonly adopted model by various state and planning authorities in Malaysia. Hence, the coastal development management strategies including deep sea zone management, coastal sea zone management and municipal sea zone management was seen to be the effective mechanism for long-term sustainability of coastal area and resources as well as able to improve the life quality in the coastal region.

Detection of the Spatial Variability of Soil Salinity East of the Bitter Lake of the Suez Canal, Egypt, as a Basis for Management Zones Using Sentinel-2 Multispectral Imagery

ABSTRACT Soil salinity is one of the more serious problems that cause soil degradation, particularly in semi-arid and arid regions. In agricultural lands, it threatens plant growth and productivity, which requires specific management decisions for various inputs, such as fertilizers. Accurate prediction and mapping of soil salinity have become possible through remote sensing techniques. The focus of this research is to derive soil salinity from spectral indices measured from different bands of sentinel-2 satellite in order to delineate management zones (MZs). Four spectral salinity indices were used for the purpose of this study, using blue, green, red, and NIR bands in different combinations. Exponential regression best describes the relationship between salinity indices and soil electrical conductivity (EC) through groundtruthing. The results indicate that salinity indices 2 () and 4 () (SI2 and SI4) outperformed the other indices and could describe 70% and 71% of the variability in soil EC with prediction models of: and , respectively. The generated models were validated by normalized root mean square error and the d coefficient of agreement. The results of the best-fit models were 16.5% and 0.86 for SI2 and 16.7% and 0.84 for SI4, respectively. The box-and-whiskers diagram proposed that the field can be divided into four soil EC-dependent groups, which are considered MZs to support a variety of management decisions. This study shows that through sentinel-2 multispectral imagery, the spatial variability of soil salinity can be mapped and used as a basis for MZs within the studied region.

Temporal groundwater quality, health risks and source point management zonation of multi-aquifers in Jilin Qian'an, Northeastern China.

Jilin Qian'an, located in Northeastern China's Songnen Plain, relies almost exclusively on groundwater for drinking. The quaternary phreatic aquifer (Q3) is distinguished by high geogenic fluoride and arsenic concentrations, which necessitates reliance on quaternary confined (Q1) and neogene confined (N) aquifers (deeper aquifers) as source point management (SPM) alternatives. However, deeper aquifers are contaminated, necessitating temporal monitoring and unique management strategies. Using 165 samples, this study investigated the appropriateness of deeper restricted aquifers as a continuous SPM alternative by assessing the spatiotemporal groundwater quality and human health risk of the multi-aquifers in Jilin Qian'an from the 1980s to the 2010s. In addition, a source point management zonation (SPMZ) was implemented to define the specific intervention necessary in various portions of the study area. Results indicate water quality parameters were within recommended limits for most samples except fluoride, while arsenic was the most significant heavy metal pollutant. Mean groundwater mineralization in all the aquifers increased with time. Deeper aquifers are still a better alternative to the shallow phreatic aquifer as groundwater quality in the study is of the order N > Q1 > Q3 in the respective aquifers. Cancer risk assessment (CR) shows increases from 2001 to the 2010s in all aquifers except in Q3. SPMZ delineated: High As and high F zones; high As and low F zones; high As zones; high F zones; low F zones; and safe zones. Localized intervention based on SPMZ is recommended, along with the use of alternative water sources.

Fuel reduction burning reduces wildfire severity during extreme fire events in south-eastern Australia

Extreme fire events have increased across south-eastern Australia owing to warmer and drier conditions driven by anthropogenic climate change. Fuel reduction burning is widely applied to reduce the occurrence and severity of wildfires; however, targeted assessment of the effectiveness of this practice is limited, especially under extreme climatic conditions. Our study utilises fire severity atlases for fuel reduction burns and wildfires to examine: (i) patterns in the extent of fuel treatment within planned burns (i.e., burn coverage) across different fire management zones, and; (ii) the effect of fuel reduction burning on the severity of wildfires under extreme climatic conditions. We assessed the effect of fuel reduction burning on wildfire severity across temporal and spatial scales (i.e., point and local landscape), while accounting for burn coverage and fire weather. Fuel reduction burn coverage was substantially lower (∼20–30%) than desired targets in fuel management zones focused on asset protection, but within the desired range in zones that focus on ecological objectives. At the point scale, wildfire severity was moderated in treated areas for at least 2–3 years after fuel treatment in shrubland and 3–5 years in forests, relative to areas that did not receive fuel reduction treatments (i.e., unburnt patches). Fuel availability strongly limited fire occurrence and severity within the first 18 months of fuel reduction burning, irrespective of fire weather. Fire weather was the dominant driver of high severity canopy defoliating fire by ∼3–5 years after fuel treatment. At the local landscape scale (i.e., 250 ha), the extent of high canopy scorch decreased marginally as the extent of recently (<5 years) treated fuels increased, though there was a high level of uncertainty around the effect of recent fuel treatment. Our findings demonstrate that during extreme fire events, very recent (i.e., <3 years) fuel reduction burning can aid wildfire suppression locally (i.e., near assets) but will have a highly variable effect on the extent and severity of wildfires at larger scales. The patchy coverage of fuel reduction burns in the wildland-urban interface indicates that considerable residual fuel hazard will often be present within the bounds of fuel reduction burns.

Delimiting supervision zones to inform the revision of land reclamation management modes in coal mining areas: A perspective from the succession characteristics of rehabilitated vegetation

The rational delimitation of supervision zones is an important means of regional management that can effectively solve the problem of unbalanced development among reclaimed coal mine areas. In this study, 32 years of vegetation fractional coverage (VFC) series data from 1989 to 2020 were obtained for the area around the Pingshuo opencast coal mine. Then, the S-logistic function was applied to fit the VFC series data for each reclamation dump unit. Combined with the recognition results of coal mining and land reclamation years and by setting three delimitation criteria, the supervision zones of land reclamation that need to be better managed in the reclaimed dump sites were delimited. Finally, optimization revisions of the land reclamation management mode were proposed. The results showed that the effective reclamation zones of land reclamation occupied most of the study area, especially in the early reclaimed west dump, south dump and inner dump I areas of the Antaibao coal mine. The level one supervision zones, which were delineated as the general management zones, were mainly concentrated in the Anjialing inner dump, Nansigou dump, east dump, and west dump. The level two supervision zones, which were delineated as special management zones, were mainly concentrated in the Anjialing Nansigou dump site. Moreover, the Pingshuo coal mine dump sites were divided into four mode areas, namely, ecological conservation, ecological monitoring, ecological restoration, and ecological reconstruction, for the revision of land reclamation management. The proportion of area corresponding to each management mode was 49 %, 23 %, 24 % and 4 %, respectively. The management modes applicable to different reclaimed dump sites differed, and the specific management measures to be adopted depend on the succession pattern of the whole processes of rehabilitated vegetation. This study provides a new approach for delimitating the supervision zones of land reclamation and proposes revision management modes for the precise implementation of land reclamation development plans in coal mining areas.

Growing degree-hours and degree-days in two management zones for each phenological stage of wheat (Triticum aestivum L.).

Monitoring the climatic conditions of crops is essential for smart agriculture development and adaptation of agricultural systems in the era of global change. Thereby, it is possibly better to understand the stages of development of the crop, thus adopting management practices more efficiently and planning the harvest with greater accuracy. This study was developed to analyze the growing degree-hours and degree-days in two management zones (MZs) for each phenological stage of wheat (Triticum aestivum L.) and the application of low-cost agroclimatological stations to monitor the climatic conditions of the field production. The study was developed in a Ferralsol in Céu-Azul/Brazil. Ten low-cost agrometeorological stations were installed in two MZs delineated based on elevation data using the web platform AgDataBox. Data on solar radiation, atmospheric pressure, wind speed, precipitation, relative humidity, air, and soil temperature were evaluated over two wheat crop seasons. Our results showed different climatic conditions, especially humidity and temperature, between MZs and crop seasons, which could probably cause yield variability. By the low-cost agroclimatological stations, it is possible to collect data on the thermal accumulation by the culture in growing degree-hours, which is a more accurate parameter than the growing degree-days (commonly used in similar studies). With the growing degree-hours data, it was possible to follow the development of the phenological stages of wheat. In conclusion, the results obtained suggest the importance of evaluating agroclimatological parameters in monitoring wheat crops. However, more studies are needed in regions with greater slopes, which may have microclimates that intensely influence the crop.

Site‐specific estimation of spatiotemporal crop evapotranspiration through field‐level sensing data

AbstractThis study integrated field‐level sensor data into the FAO‐56 Penman–Monteith algorithm to provide a site‐specific estimate of crop evapotranspiration. This was carried out at two contrasting sites for pea and bean (Manawatū) and barley (Hawke's Bay) crops managed within two irrigation management zones, at each site, under variable‐rate irrigation systems in New Zealand. Daily crop evapotranspiration estimates were calculated using data from a weather station situated at the field site combined with in‐field crop sensing data (spectral reflectance, canopy temperature, and canopy height). In addition, calibrated soil moisture data were used with a soil water balance model to compare estimations of daily crop evapotranspiration with those estimated using the crop sensing method. The results indicated that variable crop responses to different irrigation strategies and soil types provided a good opportunity to quantify different levels of spectral reflectance, canopy temperature, and consequently the estimation of crop water use. The statistical comparisons revealed that the modified FAO‐56 Penman–Monteith using crop sensor data compared well with the more conventional soil water balance approach using soil moisture data (R2 = 0.70, 0.83, 0.91 for barley, pea, and bean, respectively). Overall, the results from this study indicated that crop sensing approaches combined with the FAO‐56 Penman–Monteith model have potential to provide a more easily determined site‐specific field estimation of crop evapotranspiration than other methods, and it can take into consideration the spatiotemporal variability of crop growth in a field.

How much noise is too much? Methods for identifying thresholds for soundscape quality and ecosystem services

The United States National Park Service mandate is to conserve park resources and provide superlative visitor experience. In the context of acoustic resources, Denali National Park and Preserve provides an advantageous opportunity to understand the effect of aircraft noise on visitor experience because it possesses high levels of air tour traffic in a park renowned for its remote, wilderness character. Park visitors in four different settings were asked to rate the acceptability of recordings of aircraft noise, presented in randomized order relative to noise level. A cumulative link mixed model fitted visitor assessments to acoustic and nonacoustic factors. In addition to noise level, interest in an air tour was an important predictor of sound clip acceptability. For visitors uninterested in an air tour, the probability of rating aircraft noise as unacceptable at 54 dB LAeq,30 s or higher was 26%. For reference, this aligns with federal guidance that identified 55 dB as a threshold for interference with outdoor activities at rural residences and schools. Predictions of visitor response were joined to a spatial model of aircraft noise propagation to map visitor acceptability of aircraft noise in Denali’s entrance area (frontcountry). This map can be used to assess the condition of park management zones, to inform hiking recommendations for visitors, and to predict the range of soundscape conditions experienced by park visitors.

Spatial variability of soil properties and delineation of management zones for Suketi basin, Himachal Himalaya, India

Spatial variability of soil properties and delineation of management zones for Suketi basin, Himachal Himalaya, India

Revisiting environmental management zones toward conserving globally important species in western Philippines

The establishment of environmental management zones is an important strategy for biodiversity conservation. However, identifying and assigning appropriate zones is a challenging task that is critical to the management’s success. The Environmentally Critical Areas Network (ECAN) of the Palawan province is among the management strategies being implemented in the western Philippines. Under this strategy, natural resources needing the highest degree of protection are designated as core zones (CZ). Our study revisited this strategy to assess the current placement of the core zones with respect to species distributions and vegetation types. We conducted a series of field surveys in four municipalities of Palawan to assess the status of biodiversity. Gathered data was used to identify potential critical habitats by generating species distribution models and performing vegetation analysis using land satellite images. The placement of the CZ was evaluated using the identified critical habitats. Our assessments show that many Palawan endemic species persist despite increasing pressures from anthropogenic activities. We also found that a considerable extent of natural forest remains, generally confined in high elevations and steep terrains. The assessment of critical habitats and CZ revealed vital gaps in protection, suggesting that a revision is necessary to accommodate important habitats of threatened and endemic species. Overall, our study highlights the significance of integrating biodiversity data in improving conservation and management strategies, which has been overlooked in the current ECAN zones.

Delineation and optimization of cotton farmland management zone based on time series of soil-crop properties at landscape scale in south Xinjiang, China

Traditional farmland management approaches treat farmland as a homogeneous unit, leading to uneven distribution and waste of resources, which is contrary to precision agriculture. Management zones (MZ) delineation is an essential method of site-specific management (SSM) for accomplishing variable rate input of resources in subregions by recognizing the heterogeneity of farmland soils. Aimed at the soil salinization problem in Xinjiang, this study estimates the salt content of soil profiles and essential nutrient content using time series Sentinel-2 images and machine learning methods, and describes crop growth conditions through dynamic time warping. Subsequently, geographically weighted principal component analysis and possibilistic fuzzy C-means algorithm were employed to outline MZ based on soil-crop characteristics. Three scales (10 m, 100 m, and field scales divided by ridges) were examined to obtain the optimal scale of delineation. Soil-crop properties were estimated at a spatial resolution of 10 m using machine learning methods with R2 > 0.65. In the zoning process, the field scale was selected with accuracy and practicality in agricultural practices, with comparatively higher homogeneity within zones and variation between zones. The soils in the study area were categorized into three zones at field scale with a fuzzy performance index of 0.68, a normalized classification entropy of 0.71, and fuzzy class of 0.30. Soil function is primarily restricted by salinity and fertility. Fertilizer recommendation strategies were given for the three zones. This study uses time-series remote sensing images to obtain a high-precision estimation of soil-crop characteristics at 10 m, and optimize the scale of farmland management zoning, which provides a valuable technology and scale selection for SSM for cotton management zone delineation in saline farmland in arid and semi-arid regions.

Methanogenic archaea community in relation to methane production in oil palm planted on tropical peatland

Understanding the microbial processes that regulate methane emissions in the tropical peatlands can facilitate their future management. However, the microbiota of Malaysian tropical peatlands specifically the methanogens (methane producers) and methanotrophs (methane consumers) remains poorly characterised. This study aimed to determine the key players in methane production and to assess their spatial distribution in different oil palm management zones (i.e., avenue, cover crop, frond pile, and weeded circle) across depths namely 0–15 cm, 15–30 cm, and 30–45 cm in an 11-year-old oil palm plantation that was established on the peatland of Sarawak. Based on high-throughput Illumina sequencing targeting the 16S hypervariable V4–V5 regions of archaeal rRNA amplicon, the diversity indices (Shannon and Simpson) and richness (Chao1 and ACE) were highest in the upper peat layers across management zones, and the microbial diversity and composition are influenced by depths. Taxonomic profiling revealed that the domain Archaea was dominated by Halobacteriota, Thermoproteota, and Thermoplasmatota that increased with depth across management zones. Meanwhile, the order Methanomassiliicoccales was predominant, with Methanomethylophilus sp002495325 as the most abundant species in the upper peat layers in the frond pile zone due to a high decomposition rate of organic matter. The key players of methanogenic archaea belonging to Methanomassiliicoccales, Methanosarcinales, Methanomicrobiales, and Methanobacteriales were detected in oil palm peat soils, providing indirect genetic evidence for the biogeochemical processes associated with methane production in the oil palm plantation. Having established the feasibility of utilising high-throughput sequencing to characterise the archaeome of Malaysian oil palm plantation, future works in correlating the relative abundance of methanogens and methanotrophs with methane production will be instrumental in providing valuable insights for prediction and mitigation of methane emissions in oil palm cultivation on peat.