Water Flooding Research Articles

Calculation of the Critical Liquid Production of Cyclic Steam Stimulation in Heavy Oil Reservoir with Edge Water

Abstract For heavy oil reservoirs with edge water, when the liquid production of cyclic steam stimulation is excessively high, there is a risk of edge-water invasion. Therefore, the liquid production of cyclic steam stimulation is of great significance to the prevention of edge-water invasion in heavy oil reservoir with edge water. Currently, many studies on the critical liquid production in oil reservoir by water flooding are conducted. However, there is few research on the critical liquid production in heavy oil reservoir by cyclic steam stimulation. To fill this gap, The formation after cyclic steam stimulation is divided into the heated zone and the unheated zone. A characterization method for the flow field parameters after cyclic steam stimulation is established. By transforming the length of the thermal swept zone, the comprehensive mobility of the heated zone is equivalently represented as the comprehensive mobility of the unheated zone. On this basis, considering the threshold pressure gradient in heavy oil, a calculation method for the critical liquid production after cyclic steam stimulation in oil reservoir is developed based on the theory of mirror reflection and the superposition of potentials. The results show: (1) Permeability being constant, the critical liquid production rate increases with the increase in cyclic steam injection quality. With a constant cyclic steam injection quality, the critical liquid production rate increases with the increase in permeability; (2) Guided by the established relationship curve diagram between critical liquid production and crude oil mobility, the development plan is designed. As a result, the comprehensive water cut in the oilfield is 8.1%, and no water invasion has occurred; (3) Guided by the established relationship curve diagram between the cumulative liquid production and cumulative heat injection corresponding to different critical liquid production rates, adjustments were made to the oilfield development plan. As a result, the critical liquid production rate for well A1 increased from 110 t/d in the first cycle to 150 t/d in the second cycle.

Variability, Attributes, and Drivers of Optimal Forecast-Informed Reservoir Operating Policies for Water Supply and Flood Control in California

Variability, Attributes, and Drivers of Optimal Forecast-Informed Reservoir Operating Policies for Water Supply and Flood Control in California

Integrated hydrological modelling and streamflow characterization of Gangotri Glacier meltwater

Runoff from glaciated catchments is an integrated process that includes glacier melt, snowmelt, rainfall and surface and subsurface runoff of meltwater from glacierized and non-glacierized areas. Monitoring and quantifying the contribution of the hydrologic components (snow, ice and rain) to river discharge in the Himalayan basins is essential for decision-making in the water sector, particularly in water resources management and flood risk reduction in the region. An attempt has been made to characterize and hydrologically model streamflow (Bhagirathi River) for the Gangotri Glacier (Central Himalaya, India). A semi-distributed conceptual hydrological model is used for the streamflow modelling and assessing the major streamflow components (snow melt, glacier melt and rainfall runoff). Initially, the model was calibrated using the available in situ hydro-meteorological records for the ablation seasons of 2013–14 to 2015–16 (3 years), and further validated for the ablation seasons of 2016–17 to 2018–19 (3 years). The model performed well for all the studied years except for some months, where abrupt changes in the contrasting weather parameters (precipitation and temperature) were recorded. In the Gangotri Glacier Valley (upper Bhagirathi River catchment), snowmelt contributed the largest portion (55.5%) to total streamflow followed by glacier melt (29.7%) and rainfall runoff components (14.7%).

Comparison and integration of physical and interpretable AI-driven models for rainfall-runoff simulation

Precise streamflow forecasting in river systems is crucial for water resources management and flood risk assessment. The Tagus Headwaters River Basin (THRB) in Spain is a key hydrological hub, providing regulated flow for agricultural, urban, and energy sectors, and facilitating water transfer to the Segura River Basin, a key semi-arid region. Given the basin's near-total allocation of water resources, accurate streamflow simulations are essential to optimize the socio-economic distribution and ensure sustainable management across both interconnected basins. This study conducts a comprehensive evaluation of the Soil and Water Assessment Tool (SWAT+), support vector regression (SVR), feed forward neural network (FFNN), and long short-term memory (LSTM) models in simulating the rainfall-runoff process at four gauging stations within the THRB. An ensemble machine learning technique is then applied to assess improvements in streamflow estimation. Results revealed that AI-based models significantly surpassed the SWAT+ model in performance. Furthermore, the application of an ensemble technique enhanced the precision of rainfall-runoff modeling by 18 to 26% during the calibration period and 4.1 to 9.2% during the validation period, compared to individual AI-based models. Additionally, the SWAT+ model's precision improved by 44 to 74% and 40 to 55% for the respective periods. The use of Shapley Additive Explanations (SHAP) methodology allowed the results of the ensemble with machine learning to be more interpretable by explaining how each model contributes to the prediction. This research offers significant contributions to hydrological modeling, highlighting the importance of ensemble techniques in elevating predictive accuracy for various river basins.

Impacts of LULC changes on runoff from rivers through a coupled SWAT and BiLSTM model: A case study in Zhanghe River Basin, China

Changes in river runoff have a significant impact on the sustainable use of water resources in a watershed, and these changes are closely linked to variations in land use/land cover (LULC). This research explores an innovative approach in the Zhang River Basin (ZRB), China, by coupling a concept-based hydrological model, the Soil and Water Assessment Tool (SWAT), with a deep-learning model, the Bidirectional Long Short-Term Memory Network (Bi-LSTM), to improve the accuracy of river runoff simulations. By analyzing LULC changes in 2002, 2012, and 2022, this study developed three SWAT models and three coupled SWAT-BiLSTM models to quantitatively assess the impacts of these changes on river runoff through eight LULC scenarios. The findings revealed significant LULC changes from 2002 to 2022, with cropland and grassland areas decreasing while forest and urban land areas increased. The total area of grassland, forest, and cropland made up over 93 % of the basin, indicating active land type conversions. Calibration and validation results demonstrated that the SWAT-BiLSTM model outperformed the conventional SWAT model, yielding higher accuracy in runoff simulations. Specifically, the SWAT-BiLSTM model achieved R2 values of 0.89 and 0.90 during calibration and validation, compared to the SWAT model's R2 values of 0.76 and 0.79. Scenario analyses indicated that expansions in farmland, grassland, and urban areas were correlated with increased river runoff, while an expansion in forested areas led to reduced runoff. Notably, urban land changes had the most pronounced impact on runoff, emphasizing the need for careful runoff management and flood risk mitigation in urban planning. By combining SWAT and Bi-LSTM models, this study provides an innovative assessment of the impact of LULC changes on water resources in the ZRB. The results offer valuable insights for water resource management, LULC optimization, and flood risk management, highlighting the potential application of deep learning techniques in hydrological simulation. This research serves as a scientific basis for policy-making and sustainable land use planning in the ZRB and similar regions.

A critical assessment of geological weighing lysimeters: Part 2—Modelling field scale soil moisture storage and hydrological fluxes

AbstractLand surface models (LSMs) are used to simulate the terrestrial component of water, energy, and biogeochemical cycles. These simulations are useful for water resources management, drought and flood prediction, and numerical climate/weather prediction. However, the usefulness of LSMs are dependent by their ability to reproduce states and fluxes realistically. Accurate measurements of water storage are useful to calibrate and validate LSMs outputs. Geological weighing lysimeters (GWLs) are instruments that can provide field‐scale estimates of integrated total water storage within a soil profile. We use field estimates of total water storage and subsurface storage to critically evaluate two different land surface models: the Modélisation Environnementale communautaire—Surface Hydrology (MESH) which uses the Canadian Land Surface Scheme (CLASS), and the Structure for Unifying Multiple Modeling Alternatives: (SUMMA). These models have differences in how the processes and properties of the land surface are represented. We attempted to parameterize each model in an equivalent manner, to minimize model differences. Both models were able to reproduce observations of total water storage and subsurface storage reasonably well. However, there were inconsistencies in the simulated timing of snowmelt; depth of soil freezing; total evapotranspiration; partitioning of evaporation between soil evaporation and evaporation of intercepted water; and soil drainage. No one model emerged as better overall, though each model had specific strengths and weaknesses that we describe. Insights from this study can be used to improve model physics and performance.

A novel hybrid spherical fuzzy multi-criteria decision-making approach to select the best hydroelectric power plant source in India

Hydroelectric power plants (HPPs) play a crucial role in India’s energy portfolio by providing renewable energy and decreasing dependency on fossil fuels. HPPs assist in flood control, irrigation, and water management, thereby supporting agricultural and economic advancement. However, persistent challenges such as environmental consequences, habitat depletion, and resettlement complications impede project advancement. Striking a balance between these advantages and addressing social and environmental issues is essential for shaping India’s energy trajectory. In this manuscript to achieve these goals, the research paper incorporates the opinions of three decision-makers along with 20 criteria. Each criterion is associated with 5 alternatives and further categorized as beneficial and non-beneficial. To determine the optimal power plant, a novel hybrid Multi-Criteria Decision Making (MCDM) method is employed within a spherical fuzzy environment to handle the uncertainties occurred in the HPPs. This paper also introduces a novel formula for calculating the weights of decision-makers and a novel score function for converting spherical fuzzy numbers into crisp values. Initially to examine the interrelationship between these criteria the spherical fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) method is utilized. The weight of the criteria is determined using the spherical fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) method, followed by determining the rank of the alternatives using the novel spherical fuzzy Multiple Criteria Ranking by Alternative Trace (MCRAT) method. Subsequently, the alternative with the highest score value is determined as the optimal choice for the hydroelectric power plant source in India. Furthermore, this research paper also discusses sensitivity analysis, comparative analysis, and the managerial implications of this study.

Spatiotemporal evolution of the physicochemical parameters of the waters of the Oum Errabiaa watershed dams (Morocco)

This study was conducted to determine the characteristics of the physicochemical parameters of the water of the dams of the Oum Errabiaa watershed during flood and low water periods. Data were collected by water sampling and measurements performed in the various dams from 2016 to 2021. The results showed that the water temperature varied from 11.77 °C to 30.20 °C, depending mainly on the sunshine. The water was alkaline with an average pH of 8.23 and had a weak to high electrical conductivity (143-3180µS/cm). The water was relatively well oxygenated at the surface and oxygen depleted in depth (1.44 – 15.04mg/L). The average concentration of suspended solids (SS) was 19.76mg/L, indicating that the dam water is relatively unpolluted. The average values of nutrients, NH4+, NTK and NO3- of 0.18mg/L, 0.53mg/L and 3.51mg/L, respectively, were in compliance with the WHO guidelines for drinking water production. The average concentration of SO42- was 90.60mg/L, which is considered high, exceeding the World Health Organization (WHO) water quality standard of 50mg/l. The average chlorophyll a was 5.51µg/L, which is considered to be low to moderate in dams. Overall, the Oum Errabiaa’s water dams of watershed have good physicochemical quality, except for the high concentration of sulfates. This pollution is likely due to agricultural and industrial activities in the watershed. The use of multivariate techniques (ACPN) enabled us to define the origin of nutrients through surface inputs, on the one hand, and through the photosynthetic activity of cyanobacteria, on the other hand.

Numerical simulation of two-phase oil–water flow in fractured-vuggy reservoirs based on the coefficient of porous medium proportion and coupled regions

Based on the flow characteristics of fluids in various reservoir media, fractured-vuggy oil reservoirs can be classified into seepage zones and conduit flow zones. An interface exists between these two regions, where the movement of formation fluid near this interface is characterized by a coupling or transitional phenomenon between seepage and conduit flow. However, the complexity of this coupling interface poses challenges for traditional numerical simulations in accurately representing the intricate fluid dynamics within fractured-vuggy oil reservoirs. This limitation impacts the development planning and production adjustment strategies for fractured-vuggy oil reservoirs. Consequently, achieving accurate characterization and numerical simulation of these systems remains a critical challenge that requires urgent attention. A new mathematical model for oil-water two-phase flow in fractured-vuggy oil reservoirs is presented, which developed based on a novel coupling method. The model introduces the concept of the proportion coefficient of porous media within unit grids and defines a coupling region. It employs an enhanced Stokes–Brinkman equation to address the coupling issue by incorporating the proportion coefficient of porous media, thereby facilitating a more accurate description of the coupling interface through the use of the coupling region. Additionally, this proportion coefficient characterizes the unfilled cave boundary, simplifying the representation of model boundary conditions. The secondary development on the open-source fluid dynamics software is conducted by using matrix & laboratory (MATLAB). The governing equations of the mathematical model are discretized utilizing finite volume methods and applying staggered grid techniques along with a semi-implicit calculation format for pressure coupling—the Semi-Implicit Method for Pressure Linked Equations algorithm—to solve for both pressure and velocity fields. Under identical mechanism models, comparisons between simulation results from this two-phase flow program and those obtained from Eclipse reveal that our program demonstrates superior performance in accurately depicting flow states within unfilled caves, thus validating its numerical simulation outcomes for two-phase flow in fractured cave reservoirs. Utilizing the S48 fault-dipole unit as a case study, this research conducted numerical simulations to investigate the water-in-place (WIP) behavior in fractured-vuggy oil reservoirs. The primary focus was on analyzing the upward trend of WIP and its influencing factors during production across various combinations of fractures and dipoles, thereby validating the feasibility of the numerical modeling approach in real-world reservoirs. The simulation results indicated that when multiple dissolution cavities at different locations communicated with the well bottom sequentially, the WIP in the production well exhibited a staircase-like increase. Furthermore, as the distance between bottom water and well bottom increased, its effect on water intrusion into the well diminished, leading to a slower variation in the WIP curve. These characteristics manifested as sudden influxes of water flooding, rapid increases in water levels, and gradual rises—all consistent with actual field production observations. The newly established numerical simulation method for fractured-vuggy oil reservoirs quantitatively describes two-phase flow dynamics within these systems, thus effectively predicting their production behaviors and providing guidance aimed at enhancing recovery rates typically observed in fractured-vuggy oil reservoirs.

Study on The Areal Sweep Efficiency and Water Breakthrough Time Prediction of Water Flooding in Carbonate Reservoirs

Abstract This study concentrates on the evaluation of areal sweep efficiency and the prediction of water breakthrough time in a representative medium-porosity, medium-high permeability thin carbonate reservoir, using the H oilfield in the Middle East as an example. Areal geological models, accounting for variations in high permeability streaks and regional heterogeneity, were established to study the impact of areal heterogeneity on the sweep coefficient and morphology of the water flooding front. The results revealed that areal heterogeneity significantly affects both the areal sweep efficiency and the morphology of the water flooding front. In models with high permeability streaks, a greater permeability ratio led to more uneven displacement in all directions, consequently, this resulted in a poorer overall development effect. Furthermore, regional heterogeneity was found to significantly impact sweep efficiency, the larger the area of relatively low permeability zones, the more severe the reduction in sweep efficiency and the overall injection production effect. A theoretical method for accurately predicting water breakthrough time was established based on the stream tube method. This method was applied to the H oilfield, which reduced the discrepancy between the predicted and actual breakthrough times, thereby confirming its feasibility. The novelty of this study lies in overcoming the limitations of the stream tube method and utilizing numerical simulation to calculate the areal sweep coefficient at the time of water breakthrough. This approach quantitatively characterized the affected streamline area, thereby enhancing the accuracy of water breakthrough time predictions. This research provides significant theoretical insights and practical references for understanding the areal sweep efficiency of thin carbonate reservoirs, predicting water breakthrough times, and optimizing injection production strategies.

Development Characteristics of Single Sand Body of Yan’An Formation in Western Ordos Basin

Abstract The precise characterization of the types and spatial distribution of strongly heterogeneous single sand bodies are a necessary prerequisite for the study of oil and gas reservoir formation. This article takes the Yan’an Formation in the western Ordos Basin as an example to systematically study the internal structure and profile distribution of strongly heterogeneous single sand bodies. The research results indicate that using mud interlayers, physical interlayers, and calcium interlayers as layered interfaces can effectively classify the single sand body types of each small layer in the Yan’an Formation. The drilling rate of a single sand body is between 50% and 85%, and the average number of sand layers is between 3 and 8. When two rivers intersect and are horizontally tangent, due to the mutual erosion of water flow, relatively thick sand bodies can be retained, ultimately resulting in a pattern of relatively thick on both sides and thin in the middle. The single sand body at the bottom is the most developed and has good continuity. In the transverse direction of the river, the continuity of a single sand body is relatively poor, and the extension range of a single sand body is 300m to 1200m. Along the river channel, single sand bodies are developed with good continuity, extending about 2km. The connectivity between the sand body and the well varies with the migration of the river in the transverse river profile of the research area. The lateral contact relationship of a single sand body determines the boundary of the river channel, and the profile characteristics of a single sand body also reflect its planar distribution. The intergranular pores of the Yan’an Formation sand body are relatively developed, and a large number of quartz particles offset the compressive stress of the rock. The corrosion of feldspar particles is relatively strong, retaining a large number of primary intergranular pores. There is a good quantitative relationship between the thickness of sand in a single level channel and the width of the channel. The control of the well network on the sand body is relatively small, and there is room for further densification of drilling. The vertical contact relationship of a single sand body in the Yan’an Formation of the research area can be divided into three modes: separation, stacking, and overlapping. Cut pile sand bodies with good connectivity have good production capacity. The different planar contact relationships reflect the degree of connectivity between channel sand bodies and wells, with lateral cutting type>docking type>isolation type. The side cut sand body has uniform longitudinal water absorption, small water absorption difference, and high-water drive degree. The isolation type has the greatest difference in water absorption rate and the lowest degree of water flooding.

Distribution rules of remaining oil by bottom water flooding and potential exploitation strategy in fault- controlled fractured-vuggy reservoirs

Based on the tectonic genesis and seismic data of fault-controlled fractured-vuggy reservoirs, the typical fractured-vuggy structure features were analyzed. A 3D large-scale visual physical model of “tree-like” fractured-vuggy structure was designed and made. The experiments of bottom-water flooding and multi-media synergistic oil displacement after bottom-water flooding were conducted with different production rates and different well-reservoir configuration relationships. The formation mechanisms and distribution rules of residual oil during bottom-water flooding under such fractured-vuggy structure were revealed. The producing characteristics of residual oil under different production methods after bottom-water flooding were discovered. The results show that the remaining oil in “tree-like” fractured-vuggy structure after bottom-water flooding mainly include the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones. There exists obvious water channeling of bottom-water along the fault at high production rate, but intermittent drainage can effectively weaken the interference effect between fault zones to inhibit water channeling. Compared with the vertical well, horizontal well can reduce the difference in flow conductivity between fault zones and show better resistance to water channeling. The closer the horizontal well locates to the upper part of the “canopy”, the higher the oil recovery is at the bottom-water flooding stage. However, comprehensive consideration of the bottom-water flooding and subsequent gas injection development, the total recovery is higher when the horizontal well locates in the middle part of the “canopy” and drills through a large number of fault zones. After bottom water flooding, the effect of gas huff and puff is better than that of gas flooding, and the effect of gas huff and puff with large slug is better than that of small slug. Because such development method can effectively develop the remaining oil of non-well controlled fault zones and the attic remaining oil at the top of well controlled fault zones transversely connected with oil wells, thus greatly improving the oil recovery.

Non-thermal recovery of a viscous oil with a surfactant-polymer process

The goal of this work is to improve recovery of a viscous oil reservoir at 70 °C using a non-thermal process. Polymer floods can improve sweep efficiency, but leave behind a residual oil saturation. A surfactant-polymer flood has the potential to improve both the sweep as well as the displacement efficiency. Phase behavior experiments with the viscous oil, water and surfactants were conducted to identify surfactants. 1D and 2D sandpack displacements were conducted to evaluate the efficacy of the process. Phase behavior experiments showed Winsor type I behavior with a low interfacial tension using a single surfactant, but not ultralow tension. Water flood recovered about 50% OOIP and reduced the oil saturation to about 45% in 1D floods. The subsequent SP flood increased the cumulative oil recovery to 99% in sandpacks when the viscosity of chemical slugs exceeded the oil viscosity. When the permeability decreased (as in a Bentheimer core), the oil recovery decreased to about 86%. Secondary SP floods also recovered most of the oil and faster than tertiary floods. Reduction of polymer concentration (and viscosity to about 1/4th of the oil viscosity) reduced the oil recovery, especially in 2D sandpack floods. Decrease in interfacial tension increased the requirement of polymer concentration to maintain flood front stability. This flood demonstrates the effectiveness of Winsor type I SP formulation for viscous oil, high permeability reservoirs. Such a SP process would reduce the carbon footprint of viscous oil recovery compared to that of thermal processes.

Research on oil well production analysis based on long-term slow-release tracer

Abstract Downhole monitoring the production profile is crucial for the development of oil and gas reservoirs. Currently, the commonly methods for monitoring the production profile include logging tools and using tracer monitoring. The tracer monitoring method is more popular in oil field operations due to its wide applicability, simple process, low cost, low risk, and long monitoring time. However, compared to traditional logging tool monitoring methods, tracer monitoring has drawbacks such as data lag, difficulty in downhole installation, and unstable long-term effects. Bohai Oilfield has developed a new type of solid tracer and solved the problem of downhole installation by improving the structure of the downhole screen tube. This tracer uses polymer material as the skeleton. After entering the designated position, the internal tracer can slowly diffuse into the solvent through the pores in the skeleton, achieving slow release and long-term monitoring of the production profile of the oil well. In 2023, this new type was first applied in the D6 well in Bohai Sea, and a half month stable production stage liquid production profile was obtained through sampling. The monitoring results showed that: (1) Solid slow-release tracer monitoring technology can continuously obtain production layer information in complex environments and can be used for short-term rapid water exploration and long-term water production monitoring, identifying water breakthrough time and main water breakthrough location, (2) The distance between water injection well and D6 production wells is small, and the water injection volume in the injection wells is large. The tracer monitoring results show that there is a certain degree of water flooding in all 6 sections of each test layer, (3) The first test layer is the main liquid production section, the first and sixth test layers are the main oil production sections, and the first and second test layers are the main water production sections. The research results can determine the oil and water production situation of each section of oil well, identify the water breakthrough time and water outlet position, and provide a basis for the next development adjustment.

Study of electrical resistivity vertical changes in carbonate oil-bearing reservoirs to determine the depth of free water level

Abstract The purpose of the study is to establish the depth of the free water level (FWL), the zone of oxidized oil, the oil-water transition zone, the zone of maximum and decreasing resistivity. Correct understanding of initial oil saturation zonation in carbonate oil-bearing reservoirs is very important for development planning. The article proposes a method for express assessment of the FWL depth and initial oil saturation zonation in carbonate oil-bearing reservoirs based on electrical resistivity study. The values of electrical resistivity determined from induction logging curves in more than 200 wells were used as initial data. The vertical change in the electrical properties is considered using the resistivity values of oil-bearing reservoirs averaged over all wells. The initial oil saturation zonation was analysed using the graphs of electrical resistivity against depth. As a result of the work done, the following conclusions were made regarding the zonation of initial oil saturation and the possible geological characteristics of carbonate oil-bearing reservoirs: 1) based on the graphs of electrical resistivity against depth it is possible to distinguish 3 zones of initial oil saturation: oil-water transition zone above FWL, zone of maximum resistivity in the middle part of the deposit, and zone of decreasing resistivity in the upper part of the deposit; 2) in general, the initial oil saturation in the reservoir (as a function of the electrical resistivity) upward from the initial FWL depth does not grow exponentially, as in the Leverett function, but linearly in each zone. Proposed express method for initial oil saturation zonation in carbonate reservoirs provides novel information for formation testing and perforation planning. In oil-water transition zone it is recommended to use the gentlest methods of perforation and production intensification to preserve the integrity of the oxidized oil zone, since this zone is water confining and can prevent premature water flooding of the product.

Water reservoir techniques using remote sensing and GIS: a literature survey

Abstract The issue of storing flood waters caused by rains and river floods is very important to address the problems of drought. This study reviewed the latest research to address the problems of water scarcity and conservation with advanced methods. these study methodologies range from employing Geographic Information Systems Programs to handle and analyses remote sensing data to incorporating contemporary techniques to enhance morphometric analysis, where researchers employed various analytical techniques. To determine if these watersheds are appropriate for storing water, some studies have preferred Multi-Criteria Decision-Making models (MCDM), more especially the fuzzy analytical hierarchy (FAHP) Fuzzy Analytical Hierarchy Process. Others have employed techniques for hydrological analysis, such as the ArcGIS program’s Arc hydrology tools. Researchers reached a consensus regarding the fundamental parameters required for morphometric analysis in the demarcation of watersheds, notwithstanding methodological variances. Additionally, many researchers have argued the importance of using the Shuttle Radar Topography Mission Digital Elevation Model (SRTM-DEM) mission and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER DEM) in morphometric and hydrologic studies.

An improved ResNet method for urban flooding water depth estimation from social media images

Social media images featuring high timeliness, large data volume, and low cost, is utilized for flooding depth estimation. Common flood depth estimation methods are to segment each reference instance, resulting in local water depths and contradictory results. This study added Coordinate Attention into Residual Neural Network (ResNet), and proposed Coordinate Attention-Residual Neural Network (CA-ResNet) to acquire global submerged water depths. The 2021 Henan rainstorm in China was used as case study and a flooding dataset from Chinese Sina Microblog was constructed, with total 5676 images and 4189 flooded. All the flooded depths class 0–9 reflected from the images were annotated manually. The proposed CA-ResNet method was compared with VGGNet, ResNet, GoogleNet, and EfficientNet, both accuracy and F1 score improved by 1% − 3%. The average accuracy of level 0–––8 within the error range of CA-ResNet reached 83.14%. It is proved that CA-ResNet could achieve flood depth estimation, facilitating efficient decision support for flood responding.

Parameter Estimation of the Inverted Kumaraswamy Distribution by Using L-Moments Method: An Application on Precipitation Data

Modeling precipitation data plays a critical role in water resource and flood management. Statistical distributions are frequently used in describing hydrological variables. Different distributions and estimation methods have been presented in previous studies for modeling precipitation data. In this study, the inverted Kumaraswamy distribution is considered for its advantageous properties, and the L-moments and maximum likelihood methods are employed in estimating the parameters of the inverted Kumaraswamy distribution. In the application part, the annual maximum monthly precipitations recorded in the Rize, Türkiye are modeled with the inverted Kumaraswamy distribution. To the best of the author’s knowledge, the L-moment method is considered for the first time to estimate the parameters of the inverted Kumaraswamy distribution. In addition, the efficiencies of the estimation methods are compared with a Monte-Carlo simulation study. For evaluating the performances of the estimation methods, the goodness of fit criteria including root mean square error, Kolmogorov Smirnov test, and coefficient of determination (R^2) are used in the application part of the study. The results show that for the data considered, the L-moments method yields more accurate results than the maximum likelihood method in estimating the parameters when the sample size is small. Accordingly, the corresponding distribution with L-moments estimations provides a better fit to precipitation data obtained from the Rize station.

Analysis of Flood Resistance of Masonry Arch Bridges Combining Numerical Simulation and Probabilistic Analysis

ABSTRACT In the context of global climate change, extreme weather events such as heavy rainfall and floods are becoming more frequent. The safety of masonry arch bridges is facing unprecedented challenges. This study aims to explore the collapse mechanism of bridges in flood environments by combining numerical simulation and stochastic analysis. Taking the collapse of the Original Zhenhai Bridge caused by heavy rainfall in July 2020 as a specific case, a three-dimensional numerical model is established to analyze the mechanical response of the bridge under the combined action of flood scour and water flow loads. Additionally, predictions of scour depth are made using both theoretical formulas and stochastic methods, comparing the impact of stochastic analysis on the mechanical performance of arch bridges under the same flood conditions. The study reveals that compared to pure scour, the structural characteristics of the bridge undergo significant changes under the coupled effects of scour and water flow loads. In extreme flood events, stochastic analysis has a significant impact on the structural safety under high flow conditions. The research results provide case references and scientific methods for the safety analysis of masonry arch bridges in flood environments.

Daily river flow simulation using ensemble disjoint aggregating M5-Prime model

Accurate prediction of daily river flow (Qt) remains a challenging yet essential task in hydrological modeling, particularly crucial for flood mitigation and water resource management. This study introduces an advanced M5 Prime (M5P) predictive model designed to estimate Qt as well as one- and two-day-ahead river flow forecasts (i.e. Qt+1 and Qt+2). The predictive performance of M5P ensembles incorporating Bootstrap Aggregation (BA), Disjoint Aggregating (DA), Additive Regression (AR), Vote (V), Iterative classifier optimizer (ICO), Random Subspace (RS), and Rotation Forest (ROF) were comprehensively evaluated. The proposed models were applied to a case study data in Tuolumne County, US, using a dataset comprising measured precipitation (Pt), evaporation (Et), and Qt. A wide range of input scenarios were explored for predicting Qt, Qt+1, and Qt+2. Results indicate that Pt and Qt significantly influence prediction accuracy. Notably, relying solely on the most correlated variable (e.g., Qt-1) does not guarantee robust prediction of Qt. However, extending the forecast horizon mitigates the influence of low-correlation input variables on model accuracy. Performance metrics indicate that the DA-M5P model achieves superior results, with Nash-Sutcliff Efficiency of 0.916 and root mean square error of 23 m3/s, followed by ROF-M5P, BA-M5P, AR-M5P, AR-M5P, RS-M5P, V-M5P, ICO-M5P, and the standalone M5P model. The ensemble M5P modeling framework enhanced the predictive capability of the stand-alone M5P algorithm by 1.2 %–22.6 %, underscoring its efficacy and potential for advancing hydrological forecasting.