Search Results (13)

Maintaining the integrity of impermeable strata between mine workings and overlying aquifers is critical, because seepage pathways may cause mine flooding and surface subsidence. In the Upper Kama potash deposit, the impermeable sequence is a 50–140 m thick layered sequence of evaporites and clays overlying mined-out chambers. Under long-term loading, salt rocks tend to creep, soften, and localize damage, which can cause failure in the impermeable strata. In this paper, the Concrete damage-plasticity model, supplemented by the N2PC-MCT viscoplastic creep model, is applied to simulate the initiation and evolution of seepage pathways in the Upper Kama impermeable strata. Model parameters are obtained from published laboratory tests (uniaxial and triaxial compression and tension) and validated using observed ground-surface subsidence. A plane-strain finite-element model incorporates the stratified lithology, interface elements between layers, and sequential excavation. Long-term simulations up to 50 years investigate two operational scenarios: with and without backfilling. The calibrated model reproduces the main stages of surface subsidence and chamber closure. Without backfilling, simulations indicate that tensile damage localizes mainly in a stiff central salt layer of the impermeable strata, with most cracks appearing approximately between 33 and 37 years after the start of mining. With backfill, tensile crack propagation stops and damage remains stable. A hypothetical homogeneous impermeable strata case confirms that the observed central-layer cracking is associated with stiffness contrasts and composite bending in the stratified system. An approximate analytical multilayer beam solution, based on energy minimization, predicts bending stress concentration in stiff intermediate layers and is consistent with the numerical stress distribution. The combined numerical and analytical results provide insight into the mechanisms of long-term conductive fracture initiation in stratified impermeable strata and may serve as a basis for preliminary hazard indication and for planning mitigation measures, including backfilling and focused monitoring of stiff central layers. Because the study is based on a 2D plane-strain model, the quantitative estimates should be regarded as preliminary and require verification by 3D modelling and further field observations. Full article

The tight gas reservoirs developed in the central Shenfu block are characterized by ultra-low porosity and permeability (typically < 10% porosity, <1 mD permeability), and high irreducible water saturation (40–60%). The frequent water blocking issue sharply reduces gas relative permeability during the production period, severely limiting well productivity. In this study, core flooding experiments using artificial cores were conducted to systematically evaluate the feasibility of CO₂ injection for enhanced gas recovery (EGR). The results show that the effectiveness of CO₂ EGR is sensitive to many factors, such as injection pressure, injection rate, total injection volume, and core permeability. The higher injection pressure and rate would improve the pressure gradient, CO₂ sweep efficiency, and EGR. An optimal total volume with the value (around 2.0 pore volumes, PV) was recommended as the amount of CO₂ injection are varied in the range of 0.5–2.5 PV. A higher permeable tight reservoir is prone to a higher nature gas recovery. The experimental findings, within the controlled conditions of this study, suggest that a flowback strategy of “slow startup and controlled depressurization” could be considered. Combining CO₂ injection with managed pressure drop of production and optimized fracturing process is proposed as a potential comprehensive strategy focused on “energy supplement, damage mitigation, and water control,” which may provide a useful reference for the efficient development of high-water-saturation tight gas reservoirs. Full article

The archaeological terraces of Petra (southern Jordan) have long been recognized for their role in agriculture and flood mitigation. Despite the dominance of fine-grained sediments behind many terrace walls, these systems exhibit high infiltration capacity and remarkable resistance to erosion. This study investigates the hydrological behavior of terrace-trapped sediments through detailed soil texture, aggregate stability, salinity, and chemical analyses across eight representative sites in and around Petra. Grain-size distributions derived from dry and wet sieving, supplemented by laser diffraction, reveal that dry sieving substantially overestimates sand content due to aggregation of fine particles into unstable peds. Wet analyses demonstrate that many terrace soils are clay- or sandy-clay-dominated yet remain highly permeable. Chemical indicators (nitrate, phosphate, potassium, pH, and salinity) further suggest that terracing enhances downward water movement and salt leaching irrespective of clay content. The nature of the terrace settings and their sediment structure (especially the coarse-grained framework) exerts a stronger control on hydrological functioning than texture alone. The results have direct implications for understanding ancient land management in Petra and for informing sustainable terracing practices in modern arid and semi-arid landscapes, as they are effective both in harvesting water and reducing sediment mobilization. Full article

Monitoring rainfall is essential to understanding hydrological processes, managing water resources, and mitigating drought and flood risks. Many regions, particularly in developing countries, have sparse rain gauge networks, which limit spatial coverage and result in inaccurate rainfall estimates. By combining remote sensing data with rain gauge measurements, rainfall estimates can be improved, and spatial coverage can be enhanced. Remote sensing techniques provide a valuable resource for supplementing and enhancing rainfall monitoring in such areas. This study leverages Global Precipitation Measurement (GPM) satellite data to enhance rainfall estimation in White Nile State, Sudan, where only two rain gauge stations are operational and the state’s total area is 39.600 km². GPM data, well-known for its high temporal and spatial resolution, offers a promising alternative to mitigate the limitations of sparse ground-based networks. The study integrates GPM satellite data with ground-based measurements through statistical and geostatistical techniques, as well as validation, to improve rainfall accuracy. The results show that, on average, GPM data and rain gauge measurements exhibit a strong correlation of 0.87, with an annual RMSE of 10.23 mm and an AME of 8.25 mm. These findings demonstrate that GPM data effectively complements traditional rain gauge observations by accurately capturing spatial rainfall distributions and extreme precipitation events. The findings underscore the potential of remote sensing to provide reliable rainfall information in data-scarce regions, contributing to better water resource management and disaster risk reduction strategies. Full article

The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research aims to optimize the Blue–Green Infrastructure (BGI) network to maximize rainfall utilization within the watershed. The ultimate goal is to restore natural water balance processes and reduce reliance on artificial supplementation while mitigating urban flood risks. First, the Soil Conservation Service Curve Number (SCS–CN) model is employed to estimate the maximum potential of natural convergent flow within the watershed. Second, drawing on landscape connectivity theory, a multi-level BGI network optimization model is developed by integrating the Minimum Cumulative Resistance (MCR) model and the gravity model, incorporating both hydrological connectivity and flood safety considerations. Third, a water balance model based on the Storm Water Management Model (SWMM) framework and empirical formulas is constructed and coupled with the network optimization model to simulate and evaluate water budget performance under optimized scenarios. The results indicate that the optimized scheme can reduce artificial supplementation to Xuanwu Lake by 62.2% in June, while also ensuring effective supplementation throughout the year. Annual runoff entering the lake reaches 13.25 million cubic meters, meeting approximately 13% of the current annual supplementation demand. Moreover, under a 100-year return period flood scenario, the optimized network reduces total watershed flood volume by 35% compared to pre-optimization conditions, with flood-prone units experiencing reductions exceeding 50%. These findings underscore the optimized BGI network scheme’s capacity to reallocate rainwater resources efficiently, promoting a transition in urban water governance from an “engineering-dominated” approach to an “ecology-oriented and self-regulating” paradigm. Full article

Floods are one of the most frequent and costly natural hazards worldwide, causing significant damage to infrastructure, agriculture, and livelihoods. The Lancang-Mekong River is a major river in Southeast Asia, but the basin is prone to flood disasters that may be exacerbated by climate change. Therefore, to better understand disaster risk and tailor disaster risk reduction measures, this study conducted multiscale flood disaster risk assessments at the watershed and community levels using indicator-based and hydrodynamic model-based methods. Both methods adopted open data with the supplement of local survey data. The results of the study showed that the flood risk is generally higher in the lower reach of the river due to high levels of both hazard and vulnerability. However, the community-scale risk assessment revealed that high flood-risk communities exist in low-risk zones, and vice versa, when the flood risk was assessed at the watershed scale. Such phenomena can lead to inadequate community preparedness for flooding or unnecessary allocation of resources for flood mitigation measures. These findings provide valuable insights for the development of disaster risk reduction strategies, policies, and plans based on an understanding of the risks. Furthermore, they offer a basis for prioritizing and targeting resources, particularly in areas with high population density or vulnerable communities. Full article

Numerous algorithms have been developed to automate the process of delineating water surface maps for flood monitoring and mitigation purposes by using multiple sources such as satellite sensors and digital elevation model (DEM) data. To better understand the causes of inaccurate mapping information, we aim to demonstrate the advantages and limitations of these algorithms through a case study of the 2022 Madagascar flooding event. The HYDRAFloods toolbox was used to perform preprocessing, image correction, and automated flood water detection based on the state-of-the-art Edge Otsu, Bmax Otsu, and Fuzzy Otsu algorithms for the satellite images; the FwDET tool was deployed upon the cloud computing platform (Google Earth Engine) for rapid estimation of flood area/depth using the digital elevation model (DEM) data. Generated surface water maps from the respective techniques were evaluated qualitatively against each other and compared with a reference map produced by the European Union Copernicus Emergency Management Service (CEMS). The DEM-based maps show generally overestimated flood extents. The satellite-based maps show that Edge Otsu and Bmax Otsu methods are more likely to generate consistent results than those from Fuzzy Otsu. While the synthetic-aperture radar (SAR) data are typically favorable over the optical image under undesired weather conditions, maps generated based on SAR data tend to underestimate the flood extent as compared with reference maps. This study also suggests the newly launched Landsat-9 serves as an essential supplement to the rapid delineation of flood extents. Full article

Current flood protection capacities will become inadequate to protect many low-lying coastal cities from climate change-induced flooding in the future. Under climate change uncertainty, an adaptive strategy is required to provide supplemental flood mitigation. Green Stormwater Infrastructure (GSI) in developed areas has the potential to provide substantial catchment runoff reduction. However, individual properties vary in their Flood Mitigation Capability (FMC) depending on their land characteristics. An effective methodology is needed to evaluate the FMC of properties to help urban planners determine which to target for GSI and when to implement GSI in light of increased climate change impacts. We advance the Hydrology-based Land Capability Assessment and Classification (HLCA+C) methodology for evaluating the FMC of large properties over the long term (80 to 100-year). It builds on the strengths of existing methodologies and uses a land unit analysis approach for assessing FMC, considering interdependent hydrological and geographical variables. The FMC classification system groups properties with similar flood mitigation characteristics, helping urban planners to understand their potentials and limitations for flood mitigation toward the development of adaptive strategies through time. Step-by-step instructions demonstrate how to apply the methodology to any low-lying coastal city. Full article

Climate change (CC) is now a global challenge due to uncertainties on the drivers and the multifaceted nature of its impacts. It impacts many sectors such as agriculture, water supply, and global economies through temperature and precipitation, affecting many livelihoods. Although there are global, regional, and national studies on CC, their application to determine local CC occurence mitigation and adaptation measures is not ideal. Therefore, this study aimed to determine climate change trends in Lake Kyoga Basin using standardized precipitation and anomaly indexes. Short-term (39 years, 1981–2020) and long-term (59 years, 1961–2020) monthly data from eight strategic meteorological stations were acquired from the Uganda National Meteorological Authority and supplemented with satellite and model reanalysis climate datasets. Change in precipitation was determined by SPI-6, while SAI determined change in temperature. The Mann–Kendall test was used to determine the trend significance. Whereas two (Serere and Lira) long-term data stations showed significant changes in precipitation, all the short-term data stations showed a significant increasing trend. Decadal relative rainfall anomaly increased from 85.6–105 in 1981–1990 to 92.0–120.9 in 2011–2020, while mean temperature anomaly increased from 0.2–0.6 °C to 1.0–1.6 °C in the same period. The frequency of severe wet weather events was more than for dry weather events in many stations, indicating an increase in precipitation. Maximum, mean, and minimum temperatures increased, with resultant warmer nights. The findings showed that the Lake Kyoga basin is experiencing climate change, with both temperature and rainfall increasing spatially and temporarily. Climate change affects agriculture, which is the main economic activity, and causes the destruction of infrastructure from floods, landslides, and mudslides. The results of this study are helpful in pointing out climate change-affected areas, and hence for designing mitigation and adaption strategies for local communities by policy and decision-makers from relevant stakeholders. Full article

Increased global temperatures resulting from anthropogenically induced climate changes have increased the frequency and severity of adverse weather events, including extreme rainfall events, floods, and droughts. In recent years, nature-based solutions (NBS) have been proposed to retain storm runoff temporarily and mitigate flood damages. These practices may help rural farm and forest lands to store runoff and reduce flooding on farms and downstream communities and could be incorporated into a conservation program to provide payments for these efforts, which would supplement traditional farm incomes. Despite their potential, there have been very few methodical assessments and detailed summaries of NBS to date. We identified and summarized potential flood reduction practices for the Coastal Plain of North Carolina. These include agricultural practices of (1) cover cropping/no-till farming; (2) hardpan breakup; (3) pine or (4) hardwood afforestation, and (5) agroforestry; establishing the wetland and stream practices of (6) grass and sedge wetlands and earthen retention structures, (7) forest wetland banks, and (8) stream channel restoration; and establishing new structural solutions of (9) dry dams and berms (water farming) and (10) tile drainage and water retention. These practices offer different water holding and storage capacities and costs. A mixture of practices at the farm and landscape level can be implemented for floodwater retention and attenuation and damage reduction, as well as for providing additional farm and forest ecosystem services. Full article

Replanting trees helps with avoiding desertification, reducing the chances of soil erosion and flooding, minimizing the risks of zoonotic disease outbreaks, and providing ecosystem services and livelihood to the indigenous people, in addition to sequestering carbon dioxide for mitigating climate change. Consequently, it is important to explore new methods and technologies that are aiming to upscale and fast-track afforestation and reforestation (A/R) endeavors, given that many of the current tree planting strategies are not cost effective over large landscapes, and suffer from constraints associated with time, energy, manpower, and nursery-based seedling production. UAV (unmanned aerial vehicle)-supported seed sowing (UAVsSS) can promote rapid A/R in a safe, cost-effective, fast and environmentally friendly manner, if performed correctly, even in otherwise unsafe and/or inaccessible terrains, supplementing the overall manual planting efforts globally. In this study, we reviewed the recent literature on UAVsSS, to analyze the current status of the technology. Primary UAVsSS applications were found to be in areas of post-wildfire reforestation, mangrove restoration, forest restoration after degradation, weed eradication, and desert greening. Nonetheless, low survival rates of the seeds, future forest diversity, weather limitations, financial constraints, and seed-firing accuracy concerns were determined as major challenges to operationalization. Based on our literature survey and qualitative analysis, twelve recommendations—ranging from the need for publishing germination results to linking UAVsSS operations with carbon offset markets—are provided for the advancement of UAVsSS applications. Full article

Floods are threats seriously affecting people’s lives and property globally. Risk analysis such as flood susceptibility assessment is one of the critical approaches to mitigate flood impacts. However, the inadequate field survey and lack of data might hinder the mapping of flood susceptibility. The emergence of user-generated content (UGC) in the era of big data provides new opportunities for flood risk management. This research proposed a flood susceptibility assessment model using UGC as a potential data source and conducted empirical research in Ji’an County in China to make up for the lack of ground survey data in mountainous-hilly areas. This article used python crawlers to obtain the geographic location of the floods in Ji’an City from 2016 to 2019 from social media, and the state-of-the-art MaxEnt algorithm was adopted to obtain the flood occurrence map. The map was verified by the flood data crawled from reliable official media, which achieved an average AUC of 0.857% and an overall accuracy of 93.1%. Several novel indicators were used to evaluate the importance of conditioning factors from different perspectives. Land use, slope, and distance from the river were found to contribute most to the occurrence of floods. Our findings have shown that the proposed historical UG C-based model is practical and has good flood-risk-mapping performance. The importance of the conditioning factors to the occurrence of floods can also be ranked. The reports from stakeholders are a great supplement to the insufficient field survey data and tend to be valuable resources for flood disaster preparation and mitigation in the future. Finally, the limitations and future development directions of UGC as a data source for flood risk assessment are discussed. Full article

A field study was conducted in six Village Development Committees (VDCs) of Ilam district to identify common disasters linked with climate change and people’s response mechanisms to those disasters in farming communities. Altogether, 300 randomly selected households facing different disaster problems were interviewed using a structured and semi-structured questionnaire, which was supplemented by direct observation, timeline analysis, a key informant interview, and a focus group discussion. In addition, secondary data were collected from the District Agriculture Development Office (DADO), Ilam, the Central Bureau of Statistics (CBS) and the Nepal Red Cross Society (NRCS), Ilam. Farmers’ perceptions and the reviewed literature revealed that floods, landslides, droughts, insect pests, hailstorms, and fires comprise a major disaster risk, and they have been affecting agriculture, livelihood, physical infrastructure, and property for years. It was found that different types of loss, such as landslides, have the following risks and impacts: loss of land (45% of families) and crops (90%), property loss (10%), loss of physical resources (50%), effects on water resources (69%), loss of livestock (5%), forest degradation (72%) and loss of human life (3%). The risks and impacts of flood, drought, and fire are also presented in this study. It was also found that local communities adopt different mitigation measures for different disasters including afforestation, checking dam construction, awareness creation, contour farming, relocation, shed reconstruction, construction of plastic ponds, and conservation of local varieties (different frequencies for different measures). Social networks play an important role in mitigating disaster risks. People get help from government (38% families) and non-government (50% families) organizations, friends (22%), neighbors (44%) and relatives (20%) in the form of loans (18%), helping hands or physical support (77%), information (62%), and basic need materials (48%) to manage or respond to disaster risks. The paper suggests that local mitigation measures need to be supplemented by more sustainable solutions to make the efforts sustainable, which requires local level integrated planning and coordinated efforts. Full article