Zone Water Research Articles

Machine learning and AVO class II workflow for hydrocarbon prospectivity in the Messinian offshore Nile Delta Egypt

This study presents a comprehensive workflow to detect low seismic amplitude gas fields in hydrocarbon exploration projects, focusing on the West Delta Deep Marine (WDDM) concession, offshore Egypt. The workflow integrates seismic spectral decomposition and machine learning algorithms to identify subtle anomalies, including low seismic amplitude gas sand and background amplitude water sand. Spectral decomposition helps delineate the fairway boundaries and structural features, while Amplitude Versus Offset (AVO) analysis is used to validate gas sand anomalies. The entire seismic volume is classified into facies domains using machine learning, which isolates target features from seismic background data. The study area, covering 1850 km2, includes major structures such as the Rosetta fault and Nile Delta offshore anticline, with reservoirs consisting of layered sandstones and mudstones. Over 90 wells, including exploration and development wells, have been drilled in the area. Seismic amplitude data, including full and partial offset stacked, were analyzed to classify gas, water, and shale zones. The workflow’s performance is demonstrated through the successful identification of the low-amplitude Swan-E Messinian anomaly, characterized as a high-risk gas prospect. Machine learning techniques, specifically neural network models, were trained to differentiate seismic features such as low-amplitude gas sand from background-amplitude water sand and shale. By iterating over multiple attributes and validating the models on blind test sets and on a blind section, which excluded a known shallow gas field, the workflow significantly improved the ability to detect potential hydrocarbon reservoirs characterized by low seismic amplitude. The results show that this integrated approach reduces exploration risk, quantifies the chance of success, and enhances decision-making in well placement and hydrocarbon exploration. This method is particularly useful for identifying low seismic amplitude anomalies, which are often challenging to detect with conventional seismic analysis. (1) This study developed a workflow to detect low seismic amplitude gas fields in near-field exploration. (2) It uses a machine learning algorithm to classify and explore low-seismic-amplitude gas sand reservoirs. (3) This approach helps estimate the likelihood of success and reduces the risk associated with hydrocarbon exploration wells.

The Effect of Mulching on the Root Growth of Greenhouse Tomatoes Under Different Drip Irrigation Volumes and Its Distribution Model

Despite the continuous development of greenhouse cultivation technology, the influence mechanism of covering conditions on the root distribution of greenhouse crops remains unclear, which is emerging as a significant research topic at present. The interaction between mulching and irrigation plays a key role in the root growth of greenhouse tomatoes, but its specific impact awaits in-depth exploration. To explore the response patterns of greenhouse crop root distribution to the drip irrigation water amount under mulching conditions, the tomato was chosen as the research object. Three experimental treatments were set up: mulched high water (Y0.9), non-mulched high water (N0.9), and mulched low water (Y0.5) (where 0.9 and 0.5 represent the cumulative evaporation from a 20 cm standard evaporation pan). We analyzed the water and thermal zone of tomato roots as well as the root distribution. Based on this, a root distribution model was constructed by introducing a mulching factor (fm) and a water stress factor (Ks). After carrying out two years of experimental research, the following results were drawn: (1) The average soil water content in the 0–60 cm soil layer was Y0.9 > N0.9 > Y0.5, and the average soil temperature in the 0–30 cm soil layer was Y0.5 > Y0.9 > N0.9. (2) The interaction between mulching and irrigation had a significant impact on the distribution of tomato roots. In the absence of mulch, the root surface area, average root diameter, root volume, and root length density initially increased and then decreased with depth, with the maximum root distribution concentrated around the 20 cm soil layer. Under mulched conditions, roots were predominantly located in the top layer (0–20 cm). Under the film mulching condition, the distribution range of root length density of low water (Y0.5) was wider than that of high water (Y0.9). (3) Root length density exhibited a significant cubic polynomial relationship with both the soil water content and soil temperature. In the N0.9 treatment, root length density had a bivariate cubic polynomial relationship with soil water and temperature, with a coefficient of determination (R2) of 0.97 and a normalized root mean square error (NRMSE) of 20%. (4) When introducing the film mulching factor (fm) and water stress factor (Ks) into the root distribution model to simulate the root length density distribution of Y0.9 and Y0.5, it was found that the NRMSE was 22% and R2 was 0.90 under the Y0.9 treatment, and the NRMSE was 24% and R2 was 0.98 under the Y0.5 treatment. This study provides theoretical support for the formulation of scientifically sound irrigation and mulching management plans for greenhouse tomatoes.

Gridded drought response assessment of winter wheat in Oklahoma using big data and AquaCrop-OS.

Winter wheat is the most dominant crop in Oklahoma and critically important to the economy of agricultural industry in this state and the region. However, weather anomalies such as droughts, which are frequent in Oklahoma, pose serious threats to winter wheat yield. This study was conducted to assess the effects of droughts on the simulated yield of dryland winter wheat (Ysd) in Oklahoma employing a gridded approach with the AquaCrop Open Source (AquaCrop-OS). Long-term (30-year) simulations showed that the average Ysd ranged from 0.9 to 7.1Mgha-1 across the 3281 grids of the Oklahoma winter wheat belt. At the climate division level, Ysd ranged from 2.9Mgha-1 in Panhandle to 5.5Mgha-1 in Central divisions. Fluctuation in Ysd generally agreed with the actual dryland yield measured at several research fields across the study area. However, the model tended to underestimate Ysd during certain drought events at some sites. The coefficient of variation (CV) for Ysd ranged from 0.1 to 1.6. Panhandle climate division had the largest CV, mainly due to inconsistency in growing season precipitation and temperature related stresses. In addition, grids with smaller total available water in the root zone, such as those with coarser textures near streams, had lower yields and larger CV. The strongest correlations between Ysd and drought indices (SPEI, Z-index, PDSI) existed in the months of March to May, when the crop is highly sensitive to water stress. Largest drought sensitivity of winter wheat, based on Ysd-drought index regression slopes, was estimated in West Central division for short to long-term droughts.

Developments in Nodal Data Acquisition in the Transition Zone and Shallow Water

Developments in Nodal Data Acquisition in the Transition Zone and Shallow Water

Predicting Transient Anomalous Transport in Two‐Dimensional Discrete Fracture Networks With Dead‐End Fractures

AbstractPollutant transport in discrete fracture networks (DFNs) exhibits complex dynamics that challenge reliable model predictions, even with detailed fracture data. To address this issue, this study derives an upscaled integral‐differential equation to predict transient anomalous diffusion in two‐dimensional (2D) DFNs. The model includes both transmissive and dead‐end fractures (DEFs), where stagnant water zones in DEFs cause non‐uniform flow and transient sub‐diffusive transport, as shown by both literature and DFN flow and transport simulations using COMSOL. The upscaled model's main parameters are quantitatively linked to fracture properties, especially the probability density function of DEF lengths. Numerical experiments show the model's accuracy in predicting the full‐term evolution of conservative tracers in 2D DFNs with power‐law distributed fracture lengths and two orientation sets. Field applications indicate that while model parameters for transient sub‐diffusion can be predicted from observed DFN distributions, predicting parameters controlling solute displacement in transmissive fractures requires additional field work, such as tracer tests. Parameter sensitivity analysis further correlates late‐time solute transport dynamics with fracture properties, such as fracture density and average length. Potential extensions of the upscaled model are also discussed. This study, therefore, proves that transient anomalous transport in 2D DFNs with DEFs can be at least partially predicted, offering an initial step toward improving model predictions for pollutant transport in real‐world fractured aquifer systems.

Numerical Simulation of Flow Behavior in an Open Channel Incoperating A Series of Groins

Rivers in Nepal, India and Bangladesh exhibit significant instability due to their loose banks, gentle slopes at both the riverbed and water surface, and irregular sedimentation patterns resulting from substantial sediment loads originating upstream. To mitigate the impact of this instability, groins are constructed along the riverbanks to redirect the flow of water away from areas at risk. However, in numerous instances, traditional groins have proven ineffective. It is essential to conduct comprehensive studies on the performance of groins with various configurations to protect riverbanks from erosion, enhance navigation, and promote the biodiversity of aquatic species. The primary aim of this research is to simulate flow in an open channel using a series of groin models through the application of the 2D numerical model, iRIC Nays2DH. This numerical simulation employs the K-ε model for turbulence and the Cubic Interpolation Pseudo-particle (CIP) method for handling advective terms. Simulation of flow fields due to interaction of series of impermeable, permeable and combined groins placed in a straight channel has been made. A given flow condition is applied for all the groins. The simulation results depict that combined groins in series influence favorable flow fields compared to impermeable and fully permeable groins. This causes water zone near bank at the downstream of impermeable part, then slow flow through the permeable part. No strong circulation of flow at groin field and strong current after the groin head is present.

Simulating water and salt changes in the root zone of salt-alkali fragrant pear and the selection of the optimal surface drip irrigation mode.

Faced with the increasingly serious problem of water scarcity, developing precise irrigation strategies for crops in saline alkali land can effectively reduce the negative effects of low water resource utilization. Using a model to simulate the dynamic changes in soil water and salt environment in the root zone of fragrant pear trees in saline alkali land, and verifying them from a production practice perspective with comprehensive benefits as the goal, can optimize the irrigation amount and irrigation technology elements of saline alkali fruit trees, broaden the comprehensive evaluation perspective of decision-makers, and have important significance for improving the yield and production efficiency of forestry and fruit industry in arid and semi-arid areas worldwide. In this study, a two-year field experiment based on three irrigation levels (3000, 3750, and 4500 m3·ha-1) and four emitter discharge rates (1, 2, 3, and 4 L·h-1) was conducted in Xinjiang, China. The root zone soil water content (SWC) and soil salinity content (SSC) dynamics were simulated during the fertility period of fragrant pear using the numerical model HYDRUS-2D and field data. The results showed that the R2, root mean squared error (RMSE), and Nash-Sutcliffe efficiency coefficient (NSE) of the HYDRUS-2D simulated soil water content (SWC) (soil salinity content SSC) reached 0.89-0.97 (0.91-0.97), 0.02-0.16 cm3·cm-3 (0.22-1.54 g·kg-1), and 0.76-0.95 (0.68-0.96), respectively, indicating the strong performance of the model. A positive correlation was observed between the irrigation amount and soil infiltration depth. Moderately increasing irrigation amount could effectively leach soil salinity at a depth of 80-100 cm and maintain a water and salt environment in the main root zone of 0-80 cm, benefiting the growth and development of the main root system of fragrant pear, as well as the yield and quality of above-ground fruits. The irrigation amount and emitter discharge were optimized and quantified based on multi-objective optimization methods, normalization processing, and spatial analysis methods to maximize yield, fruit weight, soluble solids, and net profits. When the yield, fruit weight, soluble solids, and net profits simultaneously reached 90% of their maximum value, the irrigation amount and emitter discharge ranges were 4274-4297 m3·ha-1 and 3.79-3.88 L·h-1, respectively. Our study provides new insights into regulating soil water and salt environmental factors in the saline fragrant pear root zone and assessing the impact of soil water and salt management under precision irrigation strategies, and profoundly influences decision-making for irrigation of forest fruits in saline arid zones based on a production practice perspective.

The specificity of the composition, abundance and trophic structure of the summer macrozoobenthos of the Rybinsk Reservoir in the modern period

The main structural characteristics of the summer macrozoobenthos of the Rybinsk Reservoir have been studied according to the data of the expanded grid of stations in 2019 and 2021. 80 species and forms of benthic invertebrates were identified, most of which were chironomids, oligochaetes and mollusks. In all zones and parts of the reservoir, the basis of benthos species richness is represented by chironomids. The dominant complex on all soils included Limnodrilus hoffmeisteri Claparede, 1862, in most cases – Chironomus f. l. plumosus, with the exception of silted sand, where Cladotanytarsus gr. mancus and Tubifex newaensis (Michaelsen, 1902) were added to them. On the silted-up shell, the dominants included Potamothrix moldaviensis Vejdovsky et Mrazek, 1902. The basis of the quantity (93%) and biomass (86%) of animals were chironomids and oligochaetes. The greatest abundance of benthic invertebrates was recorded on gray silts and in the deep-water zone of the reservoir. The Sheksninsky part was characterized by the largest benthic biomass, and the Volzhsky part was characterized by the largest quantity. Among the trophic groups in the quantity of macrozoobenthos on all main soils, in all parts, in the deep-water zone and estuarine areas of the tributaries of the reservoir, the basis was formed by detritophages–swallowers. In the zone of open shallow water, phytodetritophages–filtrators + collectors dominated in quantity. This trophic group made the greatest contribution to the benthic biomass of gray and peaty silts, in all zones and parts, except the Volzhsky part. On silted-up shell, the largest share in the total biomass was made up of phyto-detritophages–filtrators + collectors and detritophages–swallowers. Detritophages–swallowers formed the main part of benthic biomass on silted sand and in the Volzhsky part. When conducting a comparative analysis with the results obtained in 1978, a decrease in the biomass of oligochaetes on gray silts was recorded by ~3 times. Likely, this is due to a decrease in the occurrence and abundance of a large oligochaete that previously dominated on gray silts, an indicator of β-mesosaprobic conditions, Tubifex newaensis. In 2019 and 2021, this oligochaete was not included in the dominant complex of gray silts. It began to be represented by polysaprobes Limnodrilus hoffmeisteri. This can serve as an indirect sign of an increase in the trophic status of a reservoir to a typically eutrophic one and an increase in the accumulation of organic matter in soils.

A hybrid approach: remote sensing, analytic hierarchy process and geographic information system for groundwater potential mapping in Dediapada, India.

In recent years, the overexploitation of groundwater accompanied by a significant climatic shift has placed a burden on the world's groundwater supply. This has generated a rising need for potential groundwater zones. In recent year the ever-increasing demand for potable water across the world for various groundwater exploration investigation. The present study explores the utility of remote sensing (RS) and geographic information system (GIS) to identify potential water zones in the dry deciduous forest area of Dediapada Taluka, Narmada District, Gujarat, India. Twelve thematic layers of different environmental variables including geology, geomorphology, land use/land cover (LULC), drainage density, lineament density, rainfall, soil, slope, roughness, topographic wetness index (TWI), topographic position index (TPI), and curvature were integrated. GIS mode was subjected to weight analysis using Saaty's 9-point scale. The result was normalized using analytic hierarchy process (AHP), and five distinct groundwater potential zones (GWPZs) were identified namely very high, high, moderate, low, and very low. The area occupied by each category was 6.52%, 3.1%, 60.1%, 14.32%, and 15.99%. The output aids in validation assessment with the existing well data. The groundwater potential zones maps generated using AHP technique can prove beneficial for designing strategies for water management for the present taluka and can be extended to the different talukas also.

An innovative approach for quality assessment and its contamination on surface water for drinking purpose in Mahanadi River Basin, Odisha of India, with the integration of BA-WQI, AHP-TOPSIS, FL-DWQI, MOORA, and RF methodology

Water is essential for life, as it supports bodily functions, nourishes crops, and maintains ecosystems. Drinking water is crucial for maintaining good health and can also contribute to economic development by reducing health-care costs and improving productivity. The present study evaluated the surface water quality of Mahanadi River (Odisha, India). Hence, to evaluate the hydro-chemical processes, sources of contamination, and water quality, a methodical examination was conducted using an integrated approach, namely Bayesian Approximation (BA), Analytical Hierarchy Process (AHP)-Technique of Order of Preference by Similarity to Ideal Solution (TOPSIS), Fuzzy Logic (FL), Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), and Random Forest (RF) method. For this, water samples from 16 locations were taken for a period of 2018–2024, to test 21 physicochemical parameters in the selected sampling sites. From the assessment of parameters, with respect to WHO standards, pH indicates alkaline, TKN, and TC in all samples surpassed the prescribed drinking water limit. However, major ion and hardness spatial interpolation maps typically show that the quality of the water declines from upstream to downstream, with extreme values found in the downstream. The index for BA-WQI value revealed that 50% of samples belong to unsatisfactory water quality. This was also accompanied by several parameter’s high values, namely TDS, NO3−, Cl−, and SO42−, which were also highest among all the locations. Again, it is noticed that 12.50% of sites come under the zone of excellent water. However, 37.50% of samples indicated a good water class. As a result, a renowned MCDM model, such as AHP-TOPSIS, was presented, which makes use of rough set theory and Bayesian weights to provide a trustworthy and objective assessment of the total pollution levels at each sample site. Hence, this innovative technique depicted that W-(9) was the most polluted region if compared to other places, followed by W-(8), (16), (2), and (7), respectively. Based on FL-DWQI values, 12.5% of monitored specimens point towards excellent category, and rest 18.75% indicated as good quality. The remaining samples, or 68.75%, consist of ‘poor, very poor, and unsuitable qualities'. However, it was relevant that the degree of pollution at these stations was more closely linked to a variety of expanding human activities, such as excessive water use, fertilizer effects, agricultural runoff, and industrial activity in and around the river corridor. Additionally, MOORA has been conducted and performance scores were extracted. These four polluted sites such as W-(9), (8), (16), and (4), which contain higher performance scores, were 0.89, 0.093, 0.06, and 0.04. The major four places containing variables that exceeded the WHO limits, which account for TKN, coliform, and EC properties, were named accordingly. It was discovered that the main causes of the river’s water quality adulteration were agricultural runoff and home waste water. Furthermore, a RF analysis of the 16 sites was carried out and five critical variables such as Cl−, TH, TDS, EC, and TC were obtained on the basis of R2 and RMSE score. Here, the first four RF factors were sufficient to explain 83.86%, 84.27%, 84.14%, and 85% of the model accuracy for correlation matrix. In the end, the target TC suggests about 89% of the total accuracy. Afterwards, water quality at all sampling locations was expressed in terms of RF-WQI. The value obtained varied between 15 and 243, denoting good to poor water. The main finding of the investigation was that at eight inadequate water sites, the main sources of adulteration of the river’s water quality were agricultural runoff, illegally deposited municipal solid waste, and deteriorating household water supplies. This work highlights the viability and dependability of integrating these techniques for monitoring and evaluating river water quality. Hence, these findings are essential for comprehending surface water sustainability, for human consumption in the research area.

Short-term wave forecasting for offshore wind energy in the Baltic Sea

The increasing interest in ocean-based renewable energy sources and the consequent need for advanced marine infrastructure have heightened the demand for accurate short-term forecasting of significant wave height (SWH). Given the impending investments in offshore infrastructure within the Baltic Sea, it becomes imperative to devise artificial intelligence strategies that can accurately predict wave parameters under the unique conditions of a shallow, tideless sea. This study presents an extensive evaluation of established machine learning techniques tailored to site specific wave spectra. We explore the effectiveness of artificial neural networks (ANNs) in the short-term prediction of SWH. Rigorous optimization of neural network hyperparameters is applied to improve forecast accuracy, with models validated on real-world datasets, proving their ability to predict SWH accurately across various forecast horizons. In addition, the performance of ANNs models is compared to optimized traditional forecasting methods, noting significant improvements in both accuracy and reliability. The results underscore the critical role of careful optimization in achieving precise short-term forecasts at targeted locations. They also suggest that even relatively simple models, when fine-tuned, can surpass the performance of more complex approaches commonly found in the literature. Building upon the foundational advancements in ANNs from the early 2000s, this research adopts a direct forecasting methodology utilizing data from marine observational platforms. Significantly, the networks are trained and validated with data directly obtained from a measurement buoy positioned in a deep water zone, devoid of seabed wave interactions. This aspect is particularly crucial for the strategic placement of future floating offshore farms, where these algorithms will be directly applied for short-term SWH predictions. Our findings underscore the importance of selecting optimal methods to ensure the utmost accuracy of short-term forecasts at targeted locations.

Carbon Dioxide Hydrate Formation in Porous Media Under Dynamic Conditions for CO2 Storage in Low-Temperature Water Zones

Injecting carbon dioxide (CO2) into subsea water zones, where the in situ temperatures are below the hydrate-forming temperature of CO2, has been recently proposed to lock CO2 inside the water zones in a solid hydrate form. It is a common concern that CO2 may form hydrates during the injection period, which would reduce well injectivity. CO2 injection into sandstone cores under simulated subsea temperatures ranging from 0 °C to 5 °C was investigated in this study. Experimental results show that flowing CO2 at Darcy velocity 0.033 cm/s begins to form hydrate in the sandstone core at dynamic pressures higher than the minimum required pressure under static conditions. At temperatures changing from 0 °C to 5 °C, the observed hydrate-forming pressure changes from 1.87 to 2.5 times the pressures required for CO2 hydrates under static conditions. The reason why the required minimum pressure for CO2 to form hydrates in dynamic conditions is higher than that in static conditions is attributed to the shear rate effect of flowing fluids that should slow down the growth of hydrate crystals and/or break down formed hydrate films in the dynamic conditions. Therefore, higher pressure energy, or fugacity, is required to promote the growth of hydrate crystals and hydrate films in dynamic conditions. More rigorous investigations in this area are needed in the future.

Determining Aqueous and Gaseous Product Composition of High-Preforming Titanium for Nitrate Reduction to Ammonia

Reactive nitrogen species are a key commodity and serve as fertilizers that sustain the global agricultural system, however, their use poses two significant challenges. First, most reactive nitrogen compounds are synthesized from ammonia (NH3) generated via the Haber-Bosch process. The Haber-Bosch process is energy-intensive, as it accounts for 2% of the world’s annual energy use (19.3 kWh/kg-N).1 Secondly, fields are often times overfertilized, leading to the release of reactive forms of nitrogen, such as nitrate (NO3 -), to the environment. This reactive nitrogen pollution can lead to harmful algal blooms, hypoxic dead zones in open water and other harmful effects to the environment.2 There is a need for new methods and technologies to separate reactive forms of nitrogen in wastewater and reuse these nutrients as an inexpensive fertilizer supply. To meet this need, our research aims to understand, design, and control a multifunctional electrochemical unit process that enables NH3 manufacturing and water purification in tandem. To this end, we must develop electrocatalysts that have high selectivity towards NH3 and understand the associated reaction mechanisms. Previous research from our group has demonstrated promise to transform NO3 -R to NH3 using titanium (Ti) as the electrocatalyst.3 Ti showed an optimal NH3 Faradaic efficiency of 82% and partial current density of -22 mA/cm2 while using an electrolyte containing 0.4 M NO3 - with a pH of 0.77 and applying a potential of -1 V vs the reversible hydrogen electrode (RHE). Despite this promise with Ti, given the high overpotential of -1 V vs RHE and only NH3 production quantified, this leaves an analytical gap of what other products are being produced and how can we quantify them.Recently, our group has developed an analytical method using ion and gas chromatography (IC and GC), nuclear magnetic resonance (NMR), gas chromatography-mass spectroscopy (GC-MS) and 15N isotope labeling to track all possible NO3 -R products to close the nitrogen mass balance. Thus far we have identified and quantified the aqueous and gaseous products of NO3 -, NO2 -, NOx, NH3, NH4 +, N2, N2O and H2. Furthermore, to understand the NO3 -R mechanism on Ti, we have implemented operando electrochemical mass spectroscopy (EC-MS) to identify and quantify gaseous products at various given potentials. This technique, paired with ex-situ characterization elucidates properties of NO3 -R to NH3 and product production that can inform the experimentation and molecular design of NO3 -R systems.References Erisman, J. W.; Sutton, M. A.; Klimont, Z.; Galloway, J.; Winiwarter, W. How a century of ammonia synthesis changed the world; Nature Publishing Group, 2008.Guest, J. S.; Skerlos, S. J.; Barnard, J. L.; Beck, M. B.; Daigger, G. T.; Hilger, H.; Jackson, S. J.; Karvazy, K.; Kelly, L.; Macpherson, L.; et al. A new planning and design paradigm to achieve sustainable resource recovery from wastewater. Environ Sci Technol 2009, 43 (16), 6126-6130. DOI: 10.1021/es9010515 From NLM Medline.McEnaney, J. M.; Blair, S. J.; Nielander, A. C.; Schwalbe, J. A.; Koshy, D. M.; Cargnello, M.; Jaramillo, T. F. Electrolyte Engineering for Efficient Electrochemical Nitrate Reduction to Ammonia on a Titanium Electrode. Acs Sustain Chem Eng 2020, 8 (7), 2672-2681. DOI: 10.1021/acssuschemeng.9b05983. Blair, S.J., Doucet, M. et al. ACS Energy Lett., 7, 6, 1939-1946 (2022).

Test Study on Water and Salt Transport in Soil Transition Layer under Water Storage Irrigation Based on Big Data Technology and its Mechanism

At present, it is necessary to vigorously transform saline-alkali wasteland, dry land and coastal tidal flat to realize the balance of cultivated land occupation and compensation. In this paper, the experiment and mechanism of water and salt transport in soil transition layer under water storage irrigation are studied by combining big data technology. Moreover, based on the basic principle of water and salt balance, the numerical model of water and salt transport in vadose zone of study area under brackish water irrigation is constructed on the basis of existing data. The model is a set of numerical models for simulating water transport, heat transport, solute transport and root water uptake in one-dimensional variable saturated media. The model analysis shows that soil water and salt transport is a complex natural phenomenon under the joint action of a large number of natural factors and human factors. In addition, this paper uses normal test analysis to find out whether the salt content of each soil layer conforms to the normal distribution, and combines with big data technology to perform mechanism analysis and verify the effectiveness of this method.

A bright spot of conservation in a Brazilian hotspot of cumulative impacts considering ecosystem quality in a cross-shelf gradient: Perspectives to MPAs network

Coastal regions are the main populated areas in the world and the effectiveness of Marine Protected Areas (MPAs) depends on management, stakeholder engagement, and environmental settings, which differ across land-to-sea gradients. This study describes the patterns of biological diversity and the abiotic environment along a densely inhabited stretch of the Brazilian coastline. We examined sea surface temperature and chlorophyll-a concentrations among urbanized coasts, inshore, and open water zones. Locally, we considered sites under contrasting protection status (partially restrictive MPA, multiple-use MPA, and no protection areas), the impact of sedimentation, the structure of sessile (algae, corals, and other invertebrates) and fish communities (abundance and diversity). Urban coastal sites are dominated by filamentous turfs (∼55 % coverage), exhibit high sedimentation rates (mean ∼180 mg/cm2/day), and low fish diversity (mean below 9 species/60m2). Open water zones have higher benthic and fish diversity. The highest biomass of fishes (mean ∼575 g/m2) as well as native corals (mean ∼13 %) and calcareous algal turf abundance (mean ∼38 %) was observed in the Alcatrazes archipelago, which increased its no-take MPA limits recently. In an unmanaged multiple-use protected Island, reefs were dominated by the invasive sun coral Tubastraea spp. The expansion of this alien coral is a real threat to the regional biodiversity, and its risk should be considered in management practices, which is done in the Alcatrazes archipelago. Our analysis demonstrates that effective management of multiple-use coastal settings may need to include flexible approaches that include land-based management, which can complement MPA tools to protect and conserve biodiversity. Since the region is considered a hotspot of cumulative impacts, ecosystem quality of the Alcatrazes archipelago could be considered substantially better than expected, being a bright spot of conservation. The expansion of its no-take area might help the role of MPAs within a comprehensive global conservation strategy.

The Saturation Calculation of NMR Logging Based on Constructing Water Spectrum Function

Tight sandstone oil reservoirs are characterized by complex structures, poor pore connectivity, and strong heterogeneity, with features such as low porosity and ultra-low permeability. Conventional methods for calculating saturation cannot accurately evaluate the hydrocarbon saturation of these reservoirs. To address this, a study was conducted from the perspective of non-electrical logging methods, focusing on the inherent nuclear magnetic resonance (NMR) characteristics of different fluids to develop a saturation calculation method that avoids the influence of the rock matrix, thus enabling precise saturation measurement in tight sandstone oil reservoirs. The traditional NMR porosity model was modified by segmenting it using the clay-bound water cutoff value, aiming to identify the distribution pattern of fluids in pores outside the clay-bound water zone. Through theoretical derivation and water spectrum function simulation, a water spectrum function and its parameter range suitable for the NMR T2 distribution in tight sandstone reservoirs were determined. Using core-sealed core saturation as a reference, the particle swarm optimization (PSO) algorithm was applied to optimize the parameter range and construct the final water spectrum function tailored to tight sandstone oil reservoirs. The accuracy and practicality of this method were validated by applying the derived water spectrum function to NMR logging in the exploration block, allowing for precise saturation calculations and the accurate evaluation of tight reservoir saturation.

Seasonal changes of species- and guild-based benthic diatom communities in the transitional water zone of the Yellow River Delta

Benthic diatoms serve as exemplary indicators for the assessment of ecological conditions in freshwater ecosystems. However, an approach to assessing and managing transitional water zones by benthic diatoms is relatively less. This study entailed a detailed analysis and comparison of the seasonal dynamics in species- and guild-based benthic diatom communities and their driving factors in a small-scale transitional water zone of the Yellow River Delta. Our findings revealed substantial seasonal variations in the composition and abundance of dominant species, as well as in the α and β diversity of the species-based community. Temperature emerged as the predominant environmental factor driving significant seasonal variations in the species-based community. However, no significant seasonal changes were observed in the composition and relative abundance of dominant guilds, as well as in the α, β, and functional diversity of the guild-based community. Redundancy analysis and Mantel tests demonstrated the guild-based community exhibited a stronger correlation with environmental factors compared to the species-based community. The guild-based community exhibited resilience to the influence of seasonal temperature fluctuations and exhibited a strong correlation with phosphate concentration variations. Our findings suggest that the guild-based community is a feasible approach to assessing ecological status across various seasons in the transitional water zone of the Yellow River Delta.

A Floristic Study of Aquatic and Wetland Plants of Lal Nalla Dam of Samadrapur Tehsil, District Wardha, Maharashtra

The floristic diversity studywas carried out at Lal Nalla Dam. It was constructed on the Lal Nalla River, the nearest city to the dam is Samudrapur in Wardha District of Maharashtra. Extensive and repeated field surveys were carried out from January 2020 to December 2021 in the study area, covering all the seasons of the year to document the species richness of the wetland. The three sites were selected from where a comprehensive list of aquatic and wetland plants occurring in the study areais prepared. During field surveys, emphasis was given to document the type of vegetation, growth form, and associated species. Morphological characters were recorded based on fresh material in the field. The open water zone of the lake has less growth of submerged and free-floating plants. The Marginal shallow zone with a depth of 30-40 cm is inhibited by the floating-leaved-like and emergent plants. In the study area total of 41 species were investigated from three major habitats as open-water zone, marginal shallow zone, and seasonal puddles were studied and according to the sites, the growth formlike one floating-leaved,five submerged plants, twenty-nine emergent, and six other plants was identified belonging to 22 different families in which Cyperaceae was a dominant family with 6 species. The study area shows species diversity but because of seasonal water level change and grazing by domestic livestock the disturbance is seen in vegetation.

Seasonal dynamics of bacterial community structure and function in the surf zone seawater of a recreational beach in Ostend, Belgium.

Despite the importance of bacteria in surf zone water quality, detailed insights into their community composition, functions, and seasonal dynamics at recreational beaches are scarce. This study conducted year-long, weekly monitoring of bacterial communities and environmental factors at a recreational beach in Ostend, Belgium. Using full-length 16S rRNA gene sequencing, we correlated bacterial composition and predicted functions with environmental factors to identify potential drivers. Bacterial communities were significantly affected by seasonal variations in chlorophyll a (Chl a), net primary productivity (NPP), and seawater temperature (SWT), with minimal influence from faecal inputs due to human activities. Spring showed distinct abundances of Planktomarina, Amylibacter, and Sulfitobacter, positively correlated with Chl a and related to sulphur oxidation potential. Summer had higher abundances of Cryomorphaceae, likely enhancing chemoheterotrophy. Beginning in mid to late fall and extending into winter, bacterial communities underwent substantial changes. Fall featured a distinctive enrichment of Thioglobaceae, inversely correlated with Chl a. Winter was dominated by Methylophilaceae (OM43 clade), negatively correlated with Chl a, NPP, and SWT. Both seasons exhibited elevated levels of potentially pathogenic phenotypes and predicted functions related to methanol oxidation and methylotrophy. This study provides a baseline for understanding how surf zone bacterial communities respond to environmental changes and impact health.

The dominant mechanisms of nutrient cycling in high-dam reservoirs: retention, transport or transformation?

Abstract High-dam reservoirs can significantly affect nutrient cycling processes across the globe. However, the research community now has two contradictive views (i.e. retention versus transformation) about the impact of high-dam reservoirs on nutrient cycling due to incomplete information obtained from limited field samplings. To resolve this issue, we develop a physically-based, three-dimensional water quality model to examine the spatiotemporal distributions of biogenic elements (nitrogen and phosphorus) in high-dam reservoirs with high spatial and temporal details. We apply the model to the Xiaowan Reservoir, a representative high-dam reservoir in the Lancang River Basin. By scrutinizing the spatiotemporal distributions of biogenic elements across space and over time, we find a unique ‘retention-transformation-transportation’ process of nitrogen and phosphorus in the high-dam reservoir, with dominant transformation occurring in the water zone before the dam during non-flood period while dominant retention occurring in the middle part of a reservoir during flood period. We further find that transformations of biogenic elements are enhanced only in low-temperature and low-oxygen environments. Our findings show solid scientific basis to resolve the contradictive views about nutrient cycling mechanisms in high-dam reservoirs, and provide important policy implications for the operation of high-dam reservoirs to achieve improved water quality while maintaining clean energy supply.