Subsurface Systems Research Articles

Quantifying local losses due to root intrusion in subsurface drip irrigation systems by monitoring inlet discharge and pressure head

Quantifying local losses due to root intrusion in subsurface drip irrigation systems by monitoring inlet discharge and pressure head

Evaluation of combined open ditch and subsurface drainage: Experimental data and optimization of specifications in arid Northwest China

Open ditches and subsurface drainage are effective measures for improving saline soils. Installations of subsurface drainage are now complementing surface drainage in Northwest China, but their optimisation has not been attempted. Therefore, the drainage and desalination performance of a combined subsurface drainage-open ditch system was analysed using two years of field experiments. The data were then utilised to calibrate and validate a water and salt transport model. The drainage volume in surface drains were 9-fold those in subsurface pipes. Additionally, 25 sets of orthogonal numerical experiments were designed with the subsurface pipe length, depth, and open ditch depth as variables. The results revealed that these three factors significantly affected the desalination efficiency of salinealkaline farmland (P <0.05). The ditch depth, pipe length, and pipe depth F values were 9.954, 50.286, and 6.557, respectively, and no interactions were observed among these factors. When a single open ditch was used for drainage, the desalination rate initially increased and then decreased as the distance from the open ditch increased. The inflection point varied with the open ditch depth and occurred within a range of 32–43 m when the ditch depth was 180–300 cm. The combination of an open ditch and a subsurface pipe produced a larger desalination area, and its efficiency was 170 % that of a single open ditch. Within the inflection point range, the desalination rate increased with increasing ditch depth. Beyond the inflection point, subsurface drainage played a primary role, and the desalination rate increased as the subsurface drainage depth increased but remained relatively stable along the drainage direction. The optimal installation depth for subsurface pipes was estimated to be 90–110 cm, and the depth of ditches was 180–210 cm in a combined system. The maximum length for full flow in long-distance subsurface drainage was 750–850 m. This study provides references for the optimal application of combined subsurface drainage–open ditch systems in arid Northwest China.

Introduction to this special section: Reservoir characterization

Reservoir characterization is at the forefront of the energy transition, having evolved from its traditional role in hydrocarbon exploration to playing a vital role in developing subsurface energy solutions. As our industry navigates the complexities of meeting global energy demands while pursuing climate goals, the accurate characterization of subsurface formations has never been more important. The integration of multiple disciplines — from geophysics and geology to petrophysics and reservoir engineering — aids in the characterization framework for understanding the complex subsurface systems that will help power our future.

Soft interface instability and gas flow channeling in low-permeability deformable media

Understanding gas percolation through a clay layer or a shale formation is of great importance for the development of a geologic repository for nuclear waste disposal, a subsurface system for gas storage, and an engineering approach for hydrocarbon extraction from unconventional reservoirs. Gas injection experiments have revealed complex dynamic behaviours of gas percolation through water saturated compacted bentonite, characterized by a high breakthrough pressure, rapid breakthrough, a pressure/stress decay after the breakthrough, a relatively high migration rate, high-frequency periodic/nonperiodic variations in flow rate, stepwise rate reductions during relaxation, and low gas saturation over the whole process, all indicating channelling nature of the processes. Using linear stability analyses, we show that this channelling can autonomously emerge from the instability of the deformable interface between the injected gas and the compacted bentonite matrix driven by local stress concentration, pore dilation, and hydrologic gradient. Channel patterns formed would possess a fractal geometry. We further show that, once a percolating channel is established, the gas injected would percolate through the channel in a chain of gas bubbles, also due to the interface instability, resulting in periodic/chaotic variations in gas flow rate. Our work provides a unified explanation for key features observed for gas percolation in low-permeability deformable media. The work also suggests a possibility of designing an engineered barrier system for a nuclear waste repository that can have controllable gas release while limit water transport.

Eco-physiological response of grain amaranth to regulated deficit and conventional deficit irrigation applied with surface and subsurface drip irrigation systems

Abstract Understanding the water use of drought-tolerant crops of the drought-prone Mediterranean regions is important for sustainable agriculture. The aim of this study was to evaluate the yield and yield responses of amaranth (Amaranthus hybridus L.) to different irrigation strategies conducted in 2019 and 2020 under Mediterranean climatic conditions using surface drip (SD) and subsurface drip (SSD) systems. Strategies investigated were: regulated deficit irrigation (RDI), conventional deficit irrigation (DI25, DI50, DI75), full irrigation (FI) and rainfed treatment. The highest grain yield was observed in FI treatments; RDI treatments produced 5% lower grain yield than the FI treatments, although the RDI treatments resulted in water savings of 23 and 21% for SD and SSD systems, respectively. DI treatments resulted in lower leaf water potential (LWP) and higher crop water-stress index (CWSI) compared to FI in both systems values. The results showed that optimum irrigation conditions to obtain the highest amaranth grain yields were associated with an LWP of −1.0 MPa and an average CWSI of about 0.25. The FI treatments under SSD systems had the highest grain production, followed by FI under SD and RDI under both the drip systems. Under SD and SSD systems, RDI saved 23 and 21% water, respectively, and produced a yield statistically comparable to that of FI. The SSD methods generated higher net income than SD. From these results it can be concluded that both RDI and DI75 could be a good alternative to FI under the conditions of water scarcity in the Mediterranean region.

Advancements and applications of GMS3: a surface and subsurface unified database system

Abstract GPR Mobile Mapping System 3D (GMS3) combines three-dimensional ground-penetrating radar (GPR) subsurface data with omnidirectional camera surface mobile mapping system (MMS) imagery to create a high-precision unified surface-subsurface database where underground features are easily localizable from the surface. In the context of Japan, the system is generally able to detect cavities as deep as 1.5 m (depending on soil water content) with a maximum horizontal positioning error of a few cm. The main application of GMS3 in Japan is road subsurface cavity investigations aimed at sinkhole prevention, detecting an average of 0.53 cavities per surveyed km in Japan’s national roads, and 4.76 cavities per km in municipal roads in the case of Matsuyama City. We also evaluate the feasibility of 3D mapping of buried pipes (necessary before undergrounding works) at the Johoku Campus of Ehime University. Since both services show increasing demand in Japan due to the country’s deteriorating infrastructure and its susceptibility to natural disasters, GMS3 is continuously being developed to stand out as a vital tool in subsurface surveying both in the Japanese and the international context.

Effect of center-pivot and subsurface drip irrigation systems on growth and evapotranspiration of volunteer corn in corn, soybean, and sorghum

Abstract Volunteer corn (Zea mays L.) is a competitive weed in corn-based cropping systems. Scientific literature does not exist about the water use of volunteer corn grown in different crops and irrigation systems. The objectives of this study were to characterize the growth and evapotranspiration (ETa) of volunteer corn in corn, soybean [Glycine max (L). Merr.], and sorghum [Sorghum bicolor (L.) Moench] under center-pivot irrigation (CPI) and subsurface drip irrigation (SDI) systems. Field experiments were conducted in south-central Nebraska in 2021 and 2022. Soil moisture sensors were installed at depths of 0 to 0.30, 0.30 to 0.60, and 0.60 to 0.90 m to track soil water balance and quantify seasonal total ETa. Corn was the most competitive, as volunteer corn had the lowest biomass, leaf area, and plant height compared with the fallow. Soybean was the least competitive with volunteer corn, as the plant height, biomass, and leaf area of volunteer corn in soybean were similar to fallow at 15, 30, 45, and 60 d after transplanting (DATr). Averaged across crop treatments, irrigation type did not affect volunteer corn growth at 15 to 45 DATr. Soil water depletion and ETa were similar across crop treatments with and without volunteer corn, as water was not a limiting factor in this study. The ETa of volunteer corn was the highest in soybean (623 mm), followed by sorghum (622 mm), and corn (617 mm) under CPI. The SDI had higher irrigation efficiency, because without affecting crop yield, it had 3%, 6%, and 8% lower ETa in soybean (605 mm), sorghum (585 mm), and corn (571 mm), respectively. Although soil water use did not differ with volunteer corn infestation, a soybean yield loss of 27% was observed, which suggests that volunteer corn may not compete for moisture under fully irrigated conditions; however, it can impact the crop yield potential due to competition for factors other than soil moisture.

Effect of chemical modification on hydraulic conductivity of stratified porous media

ABSTRACT Understanding hydraulic conductivity is essential in porous media as it dictates the capacity of fluids to permeate through these substances. This research investigated the impact of chemical modification using fly ash on hydraulic conductivity. The coefficient of hydraulic conductivity along the bedding plane at different angles of orientations was predicted by employing machine learning techniques such as gene expression programming (GEP), artificial neural networks (ANNs), and regression tree (RT), considering various influencing parameters. As the amount of fly ash in the porous medium rises, the hydraulic conductivity decreases. The statistical results demonstrate that the proposed ANN model effectively forecasted the horizontal hydraulic conductivity. It achieved the highest R2 value (0.989), the lowest mean absolute percentage error value (5.772), the lowest scatter index value (0.040), and the lowest Akaike Information Criterion value (−2,359.914) compared to the GEP, RT, and previously established approaches. Moreover, a novel equation has been proposed for determining horizontal hydraulic conductivity, which can be used for any stratified medium, distinguishing this work from previous ones. These findings can inform global practices in mitigating groundwater contamination, enhancing irrigation efficiency, and improving the design of subsurface fluid flow systems, making it a valuable contribution to both academic and practical applications worldwide.

Use of Deep-Learning-Accelerated Gradient Approximation for Reservoir Geological Parameter Estimation

The estimation of space-varying geological parameters is often not computationally affordable for high-dimensional subsurface reservoir modeling systems. The adjoint method is generally regarded as an efficient approach for obtaining analytical gradient and, thus, proceeding with the gradient-based iteration algorithm; however, the infeasible memory requirement and computational demands strictly prohibit its generic implementation, especially for high-dimensional problems. The autoregressive neural network (aNN) model, as a nonlinear surrogate approximation, has gradually received increasing popularity due to significant reduction of computational cost, but one prominent limitation is that the generic application of aNN to large-scale reservoir models inevitably poses challenges in the training procedure, which remains unresolved. To address this issue, model-order reduction could be a promising strategy, which enables us to train the neural network in a very efficient manner. A very popular projection-based linear reduction method, i.e., propel orthogonal decomposition (POD), is adopted to achieve dimensionality reduction. This paper presents an architecture of a projection-based autoregressive neural network that efficiently derives an easy-to-use adjoint model by the use of an auto-differentiation module inside the popular deep learning frameworks. This hybrid neural network proxy, referred to as POD-aNN, is capable of speeding up derivation of reduced-order adjoint models. The performance of POD-aNN is validated through a synthetic 2D subsurface transport model. The use of POD-aNN significantly reduces the computation cost while the accuracy remains. In addition, our proposed POD-aNN can easily obtain multiple posterior realizations for uncertainty evaluation. The developed POD-aNN emulator is a data-driven approach for reduced-order modeling of nonlinear dynamic systems and, thus, should be a very efficient modeling tool to address many engineering applications related to intensive simulation-based optimization.

Geostatistical Inversion of Frequency-Domain Electromagnetic Data for Near Surface Modelling

The detailed characterization of near-surface deposits is important for both environmental and economic reasons. These shallow subsurface systems can be very complex and heterogenous due to natural dynamics and anthropogenic interferences. Modeling techniques based exclusively on direct sampling generate limited informed three-dimensional models of the near-surface. Geophysical methods provide valuable and additional information to model the spatial distribution of the near-surface for locations where direct observations are not available. From this set of methods, frequency-domain electromagnetic induction (FDEM) has been successfully applied to image complex near-surface deposits. Yet, predicting the spatial distribution of relevant subsurface properties from geophysical data, and the integration of direct observations, is not straightforward. It requires solving a challenging geophysical inversion problem. Geostatistical modelling tools have been effectively applied to couple direct observations with geophysical data such as seismic reflection. We propose an iterative geostatistical FDEM inversion method able to integrate data from direct measurements of the near-surface with surface loop-loop FDEM measurements to simultaneously predict high-resolution models of electrical conductivity and magnetic susceptibility, and their associated uncertainty. The iterative geostatistical inversion method is based on stochastic sequential simulation and co-simulation as model perturbation and update techniques. The iterative optimization is based on the local data misfit between observed and simulated FDEM data, weighted by the sensitivity of the acquisition equipment. The proposed method is first demonstrated for a synthetic landfill data set created based on real data collected at a mine tailing disposal site in Portugal, and on a real data set collected at a site with archaeological features in Knowlton, UK. The results show the ability of the proposed method to accurately predict and characterize the spatial distribution of electrical conductivity and magnetic susceptibility down to the depth of interest while reproducing the recorded FDEM data.

Impact of freeze-thaw cycles and influent C/N ratios on N2O emissions in subsurface wastewater infiltration systems

Subsurface wastewater infiltration system (SWIS) is important source of N2O emission, biological denitrification process relies on organic carbon source as electron donor, enabling denitrifying reductase (NAR, NIR, NOR, and N2OR) to reduce nitrate nitrogen to N2. However, freeze-thaw cycles cause changes in soil structure through physical and biological processes that increase organic matter availability and microbial activity, thereby accelerating upper (aerobic) organic matter degradation. This leads to carbon deficiency in the lower (anaerobic) layer, which reduces denitrification efficiency increasing N2O production and emissions. This study investigated effects of influent C/N ratios on N2O emissions from SWIS under freeze-thaw stress, and changes in denitrifying reductase and microbial communities. Results showed that as influent C/N ratio increased from 6:1–10:1, average TN removal of SWIS decreased from 89.59 % to 84.95 %, while N2O emission rate decreased from 0.106 mg·m−2·h−1 to 0.0333 mg·m−2·h−1, a reduction of 68.61 %. Meanwhile, N2OR activity increased by 29.95 % with C/N ratio increasing from 6 to 10, showing a significant reduction of N2O. High-throughput sequencing results revealed that Proteobacteria and Firmicutes showed a linear relationship with influent C/N. As C/N increased from 6 to 8 and 10, Proteobacteria relative abundance increased from 22.24 % ± 1.79–32.51 % ± 2.51 % and 39.59 % ± 3.45 %, while Firmicutes relative abundance decreased from 31.73 % ± 7.87–3.34 % ± 0.27 % and 2.19 % ± 0.07 %. These results indicated that sufficient supply of organic carbon provided abundant electron donors for denitrifying reductases in freeze-thaw-affected SWIS, promoting influent NO3--N reduction and decreasing N2O release rates. Conversely, under low C/N ratio conditions, electron acceptance capacity of N2OR was limited and N2OR activity was inhibited, resulting in N2O accumulation and emission. SynopsisThis paper shows how increasing the organic carbon supply in SWIS can reduce N2O emissions and improve nitrogen removal under freeze-thaw stress.

Wetting Preference of Silica Surfaces in the Context of Underground Hydrogen Storage: A Molecular Dynamics Perspective.

The growing interest in large-scale underground hydrogen (H2) storage (UHS) emphasizes the need for a comprehensive understanding of the fundamental characteristics of subsurface environments. The wetting preference of subsurface rock is a crucial parameter influencing the H2 flow behavior during storage and withdrawal processes. In this study, we utilized molecular dynamics simulation to evaluate the wetting preference of the silica surface in subsurface hydrogen systems, with the aim of addressing disparities observed in experimental results. We conducted an initial comprehensive assessment of potential models, comparing the wettability of five common silica surfaces with different surface morphologies and hydroxyl densities in CO2-H2/water/silica systems against experimental data. After introducing the INTERFACE force field as the most accurate potential model for the silica surface, we evaluated the wetting behavior of the α-quartz (101) surface with a hydroxyl density of 5.9 number/nm2 under the impact of actual geological storage conditions (333-413 K and 10-30 MPa), the coexistence of cushion gases (i.e., CO2, CH4, and N2) at various mole fractions, and pH levels ranging from 2 to 11 characterized through considering the negative charges of 0 to -0.12 C/m2 via deprotonation of silanol on the silica surface. Our results indicate that neither pressure nor temperature has a significant impact on the wetness of the silica in the case of pure H2 (single component UHS operations). However, when CO2 coexists with H2, especially at higher mole fractions, an increase in pressure and a decrease in temperature lead to higher contact angles. Moreover, when the mole fraction of cushion gas ranges from 0 to 1, the contact angle increases 20, 9.5, and 4.5° for CO2, CH4, and N2, respectively, on the neutral silica substrate. Interestingly, at higher pH conditions where the silica surface carries a negative charge, the contact angle considerably reduces where surface charges of -0.03 and -0.06 C/m2 result in an average reduction of 20 and 80% in the contact angle, respectively. More importantly, at a pH of ∼11 (-0.12 C/m2), a 0° contact angle is observed for the silica surface under all temperatures, pressures, types of cushion gases, and varying mole fractions.

Maximizing Growth and Yield Components: Comparative Analysis of Surface and Subsurface Drip Irrigation in Intensively Farmed Rice Systems

Water scarcity is a critical issue in arid and semi-arid regions worldwide, necessitating efficient irrigation methods in agriculture. This study evaluated the effectiveness of surface and subsurface drip irrigation systems in direct-seeded rice (DSR) followed by zero-till wheat or maize, compared to conventional puddled transplanted rice (PTR) systems. The two-year experiment, conducted at the International Rice Research Institute's South Asia Regional Centre in Varanasi, India, employed a randomized complete block design with eight treatments. Results showed that DSR followed by zero-till wheat with subsurface drip irrigation at 60-cm spacing significantly outperformed other treatments. This system increased rice grain yield by 6.52% and 18.82%, straw yield by 7.68% and 13.45%, and total biomass by 8.30% and 9.73% in 2020 and 2021, respectively, compared to PTR followed by zero-till wheat. Subsurface drip irrigation also led to improved plant growth parameters, including plant height and number of tillers, and enhanced yield attributes such as number of panicles and filled grains per panicle. The study concludes that subsurface drip irrigation in DSR systems offers a promising solution for sustainable intensification and efficient use of water and energy in rice-based cropping systems. However, long-term, multi-location trials are recommended to establish precise water and energy savings under various conditions.

Hydrocarbon generation potential in Jurassic source rocks from hydrous pyrolysis experiments under ultradeep conditions

This study investigates the hydrocarbon generation potential of Jurassic source rocks under ultradeep conditions by utilizing semiclosed system hydrous pyrolysis experiments to simulate the geological processes at play. This study examines four distinct lithologies (shale, mudstone, carbonaceous mudstone, and coal) and three kerogen types (I, II, and III) across a temperature range of 250–650 °C and fluid pressures ranging from 34 to 100 MPa. The results indicate a bimodal distribution in total oil yields, with peak generation observed at approximately 350 °C and 600 °C. This pattern suggests a complex relationship between temperature, pressure, kerogen type, and hydrocarbon output. Notably, while I-Shale and II-Mudstone display higher hydrocarbon efficiency, III-type rocks exhibit superior oil and gas production rates because of their higher total organic carbon content. Research revealed that the oil expulsion rate exceeds 99% at temperatures above 500 °C, with the expelled oil predominantly comprising nonhydrocarbons and asphaltenes. Our findings suggest that Jurassic hydrocarbon source rocks maintain oil and gas potential under ultradeep conditions (high-over maturity stages at depths exceeding 6000 m). Under sustained fluid overpressure exceeding 70 MPa, the hydrocarbon generation peaks of various kerogen types in source rocks are markedly delayed. This phenomenon enables the source rocks to retain the potential for liquid hydrocarbon generation even during the stages of overmaturity. The results significantly enhance the theoretical framework of hydrocarbon generation under ultradeep conditions, thereby providing a crucial extension to the existing thermal boundary theory of hydrocarbon formation. These insights are crucial for the oil and gas industry, directing future exploration efforts towards ultradeep reservoirs and informing the development of new technologies to exploit these resources. This research not only enhances the understanding of subsurface hydrocarbon systems but also has implications for strategies aimed at maximizing resource recovery and managing the environmental impact of deep Earth exploration.

Effect of Drought Stress on Yield Quality, Water Productivity and Profit Net of Potato Crop under surface and subsurface drip irrigation systems

Effect of Drought Stress on Yield Quality, Water Productivity and Profit Net of Potato Crop under surface and subsurface drip irrigation systems

Growth Performance of Sabia Grass Irrigated by Drippers Installed in Subsurface

Studies to improve the use of subsurface drippers in pasture formation are needed. Therefore, the objective of this study was to evaluate the germination and emergence of Sabia grass as a function of drippers installed at different depths. The study was conducted in pots in Viçosa, Minas Gerais State, Brazil. The experiment was conducted using a completely randomized design with four replicates. The experimental layout featured split plots over time, where the main plots consisted of three cultivation cycles and the subplots represented various dripper installation depths. The three sowing dates were 26 March, 12 April, and 29 April 2022. Drip tapes were installed at seven different depths: 0 (superficial), 5, 10, 15, 20, 25, and 30 cm. The results showed that the reduction in water potential, associated with increased temperature, resulted in lower performance of Sabia grass seeds. Seed germination and parameters related to germination speed were negatively impacted by the increase in dripper installation depth, with a 30–40% reduction in germination speed observed at depths greater than 15 cm. Drippers installed at 15–20 cm depth in clayey soil were ideal, providing a balance between reducing soil water evaporation and maintaining seedling emergence rates. Compared to surface installation, this depth improved seed performance by up to 25%, while enhancing operability and minimizing water loss. It is recommended to install drippers at a depth of 15–20 cm in subsurface drip irrigation systems in clayey soil areas to achieve benefits such as decreased soil water evaporation and improved operability compared to surface systems.

Field Study and Numerical Modeling to Assess the Impact of On-Site Septic Systems on Groundwater Quality of Jeju Island, South Korea

Septic-derived nitrogen (N) sources have harmful effects on water resources, humans, and ecosystems in several countries. On Jeju Island, South Korea, the rapid increase in personal sewage treatment facilities (PSTFs, also known as on-site septic systems) raises concerns regarding the deterioration of groundwater quality, as groundwater is the sole water resource on the island. Therefore, this study employed a field study and numerical modeling to assess the impact of PSTF effluents on groundwater quality in the Jocheon area of northeastern Jeju. Water quality analysis revealed that the total nitrogen (T-N) concentrations in the effluent exceeded the effluent standards (75–92% PSTFs). The numerical model simulated the transport of N species, showing limited NH4+ and NO2− plume migration near the surface due to nitrification and adsorption. However, NO3− concentrations increased and stabilized over time, leaching on the water table with higher levels in lowland areas and clustered PSTFs. The predictive model estimated a 79% reduction in NO3− leaching when the effluents followed standards, indicating the necessity of effective PSTF management. This study highlights the importance of managing improperly operated septic systems to mitigate groundwater contamination based on an understanding of the behavior of N species in subsurface hydrologic systems.

Effects of phosphorus fertilizer type and dripline depth on root and soil nutrient distribution, nutrient uptake, and maize yield under subsurface drip fertigation

ContextSubsurface drip irrigation can potentially increase nutrient uptake by altering the spatial distribution of nutrients and roots, but the efficiency enhancement potential of different phosphorus (P) sources combined with varying dripline depths still requires further evaluation. MethodsWe established a 2-year field experiment with spring maize in 2021 and 2022 to determine the regulatory effects of three P sources [P1, monoammonium phosphate (MAP); P2, ammonium polyphosphate (APP); and P0, no P] and three dripline depths (D0, surface drip irrigation, 0 cm; D15, subsurface at 15 cm depth; and D30, subsurface at 30 cm depth) on the soil NO3-N, NH4-N and Olsen-P distribution, root distribution, nitrogen (N) fertilizer partial factor productivity (PFPN) and P use efficiency (PUE), and grain yield. ResultsWe found a significant coupling effect between the P source and dripline depth, both of which significantly impacted soil nutrients and root distribution, grain yield, PFPN, and PUE. In P1D15 and P2D15, the highest soil NO3-N and Olsen-P contents were observed at soil depths of 0–30 and 10–20 cm and at 0–30 and 10–30 cm, respectively. Similarly, in P1D30 and P2D30, which were 20–40 and 20–40 cm, and 20–40 and 30–60 cm, respectively. Compared to the other treatments, P2D15 and P1D30 exhibited considerable increases in root length density at the 30–60 cm soil depth of 37∼52 % and 28∼58 %, respectively. Regardless of the dripline depth, P0 resulted in the lowest yield during both growing seasons. P1D30 and P2D15 were found to be the optimal combinations for achieving higher grain yield, PFPN, and PUE, as they were able to achieve a high degree of coordination between soil available N and Olsen-P, as well as root distribution. ConclusionsThe recommended approach for optimizing nutrient and root spatial distributions under subsurface drip irrigation systems involves the use of poly-P fertilizer (APP) in conjunction with shallow dripline depth and ortho-P fertilizer (MAP) paired with deep dripline depth, which provides valuable guidance for co-fertigation practices involving N and P fertilizers.

Event classification, seismicity, and eruption forecasting at Great Sitkin Volcano, Alaska: 1999–2023

The frequency content of volcanogenic seismicity is often used to classify events and their spatial and temporal progression is then used to map subsurface volcanic processes. The progression of volcano-seismic events and associated source processes also plays a critical role in eruption forecasting. Here we develop and evaluate a computerized methodology for characterizing volcano-seismic event types using Frequency Index and Average Peak Frequency. We apply and test this technique at Great Sitkin Volcano, Alaska, classifying over 9000 hypocenters between 1999 and 2023. This 24-year time span covers periods of seismic quiescence, earthquake activity on nearby tectonic (bookshelf) faults, precursory unrest from 2016 to 2021, and the explosive onset in May 2021 of the ongoing effusive eruption. We use the spatial and temporal evolution of classified event types to map the active volcanic and tectonic processes, develop a conceptual model of the subsurface magmatic system, and perform a retrospective analysis of eruption forecasts at Great Sitkin Volcano between 2016 and the present. The classification and progression of hypocenters suggests the subsurface Great Sitkin Volcano magmatic system consists of a mid- to lower- crustal source zone between 10 and 40 km depth and an upper crustal magma storage area between −1 and 10 km depth (hypocenter depth is referenced to sea level and negative depths reflect height above sea level). The earliest precursors occurred in July 2016 and consisted of deep long-period and volcano-tectonic earthquakes at mid-crustal depths suggesting the subsequent unrest and eruption were triggered by a deeper intrusion of magma. This mid-crustal seismic activity was immediately followed by the onset upper-crustal long-period events and volcano-tectonic earthquakes VTs suggesting a strong linkage between the shallow and deeper portions of the magmatic system. The upper crustal area was likely capped by the 1974 lava dome until the magmatic explosion on May 26, 2021.

Interaction Effects of Water and Nitrogen Practices on Wheat Yield, Water and Nitrogen Productivity under Drip Fertigation in Northern China

Water resource shortage and unreasonable application of nitrogen (N) fertilizer have been problems in wheat production of northern China. However, the interaction effects of water regimes and N practices on wheat root growth, grain yield, soil water, and inorganic N changes as well as water-N use efficiency are still unclear under drip irrigation. A field experiment was conducted during the 2020–2021 and 2021–2022 winter wheat (Triticum aestivum) growing seasons. In this study, three irrigation schedules (i.e., irrigation was applied up to 80% [D1], 75% [D2], and 70% [D3] as soon as the soil water content decreased to 65%, 60% or 55% of field capacity) and two N practices (i.e., N applied at the base, jointing, booting stages were 90, 72, 48 kg ha−1 [N1], and the base, jointing, booting, filling stages were 90, 40, 40, 40 kg ha−1 [N2], respectively) were considered. The decease in irrigation water amount was offset by the increase in soil water consumption. In addition, N practices significantly interacted with irrigation on soil NO3−–N accumulation (2021–2022), NH4+–N accumulation, SPAD value (2020–2021), N content in stems and grains at maturity, and average root length and weight density at the flowering stage. Irrigation, rather than N practices, significantly affected grain yield, total N uptake, crop N transformations (NT), the contribution of NT to grain (NTPC), water and N productivity, in which, for the value of these two seasons, D2 increased total N uptake by 18.1% (p &lt; 0.05), and NT by 39.4% (p &lt; 0.05) under N1 as compared to D3. Additionally, the highest WUE and ANUE were found in D2 during 2021–2022. Heavy irrigation water amount caused high a LAI; further analysis proved that the LAI was the key factor affecting grain yield, and positively and significantly correlated to yield. However, no significant difference in the LAI between D1 and D2 was found. N1 was beneficial to prevent N leaching and increase water and N use efficiency, biomass, and N transformation amount. This study recommends that D2 + N1 might be a promising system for manipulating irrigation and fertilization practices under sub-surface drip irrigation systems to improve water and N use efficiency and grain yields in semi-arid regions.