Flood Conditions Research Articles

A High‐Performance Coupled Human And Natural Systems (CHANS) Model for Flood Risk Assessment and Reduction

AbstractIn recent years, flood risk in urban areas has been rapidly increasing due to unsustainable urban development, changes of hydrological processes and frequent occurrence of extreme weather events. Flood risk assessment should realistically take into account the complex interactions between human and natural systems to better inform risk management and improve resilience. In this study, we propose a novel Coupled Human And Natural Systems (CHANS) modeling framework to capture the intricate interactive human behaviors and flooding process at a high spatial resolution. The new CHANS modeling framework integrates a high‐performance hydrodynamic model with an agent‐based model to simulate the complex responses of individual households to the evolving flood conditions, leveraging the computing power of graphics processing units (GPUs) to achieve real‐time simulation. The framework is applied to reproduce the 2015 Desmond flood in the 2,500 km2 Eden Catchment in England, demonstrating its ability to predict interactive flood‐human dynamics and assess flood impact at the household‐level. The study also further explores the effectiveness of different flood risk management strategies, including the provision of early warning and distribution of sandbags, in mitigating flood impact. The new CHANS model potentially provides a useful tool for understanding short‐term human behaviors and their impact on flood risk during a flood event, which is important for the development of effective disaster risk management plans.

Urban flash flood prediction modelling using probabilistic and statistical approaches

The development of a detailed strategy to mitigate the negative consequences of any natural calamities depends on accurately identifying sensitive zones where natural hazards frequently happen. In the present investigations, three widely utilized probabilistic approaches viz., frequency ratio (FR), statistical index (SI), and weighting factor (WF) have been utilized for prediction of flsh flood susceptibility zones in the Coochbehar urban and peri-urban area (CUPUA) (area = 26.22 km2). Ten flash flood conditioning factors have been used in this assessment based on previous literatures and experts' opinions. In the FR model, 29.40 % area is observed in the high and very high flood zones, whereas 36.27 % and 31.16 % area is identified in SI and WF model, respectively. The FR model demonstrates that five conditioning factors, viz., topographic position index (TPI), land use and land cover (LULC), normalized difference vegetation index (NDVI), distance to drainage (DtD) and rainfall were highly impacted in flash flood prediction (FFP) analysis; in SI model, LULC is the major influencing parameter, and in WF model LULC, rainfall, NDVI, and distance to road (DtR) are the effective parameters. The success rate curve of the FR, SI and WF models manifest SI model has highest training (AUC=0.903) and prediction (AUC=0.925) accuracy, and FR and WF also have very good accuracy as their AUC values are 0.899 and 0.877 (in success rate curve) and 0.900 and 0.881 (in prediction rate curve). Therefore, the application of probabilistic approaches in this active flash flood-prone region is excellently performed, and the results of this study will help hydrologists, engineers, and water management administrators to control the areas that are extremely susceptible to flash floods and reduce possible damages.

Assessing dynamic congestion risks of flood-disrupted transportation network systems through time-variant topological analysis and traffic demand dynamics

Amid escalating climate change and extreme weather events, urban road networks face increasingly severe flood risks. Current congestion risk analyses on transportation systems, largely grounded in static network characteristics, fall short of capturing the dynamic impacts of evolving flood events on network topology. A notable gap in integrating dynamic flood models with detailed temporal network property measurements impedes a deep understanding of the cascading mechanisms of traffic disruptions caused by floods. The research introduces an innovative framework for assessing dynamic congestion risks within transportation networks under flooding conditions. This framework comprises four distinct layers. The Data and Context layer collates and contextualizes primary data, encompassing road networks, commuter behaviour patterns and hydrological risks. This layer establishes a baseline for understanding the structure of the transportation system and its environmental vulnerabilities. The Computation layer focuses on calculating context-based betweenness centrality values to capture the importance of road segments within the network, setting a static indicator. Concurrently, this layer examines the dynamic exposure flag under flood conditions, providing a dynamic indicator that accounts for the fluctuating susceptibility of road networks to flooding. The Integration layer bridges the topological analysis and the functional performance of the transportation system. It creates a dynamic series that describes the topological properties of the network, reflecting its vulnerability to disruptions. Simultaneously, the time-variant traffic demand series are tracked to capture the system’s operational response to flood-induced conditions. Finally, the Evaluation layer synthesizes data and analyses from the previous modules. This synthesis involves a novel dual assessment: generating a time-variant vulnerability index series and evaluating the time-variant congestion risk map on the transportation system under flooding. The London case study is developed based on this proposed framework to identify critical areas of congestion risks. This study offers valuable data-driven insights for urban planning and disaster management, aiding policymakers, planners and emergency teams to enhance urban resilience against flood-induced transport disruptions.

The Bibliometric Study of Flood Discharge by Unit Hydrograph Method Nakayasu Synthetic (HSS) and Soil Conservation Service (SCS)

Urban territorial expansion and forest disclosure are two examples of large-scale modifications necessary because of population growth and the rising demand for land. The paper analyzes the various facets of urban development and the essential role that hydrology plays in planning construction projects and water infrastructure. Hydrology study becomes essential for engineers designing and developing structures involving water resources, especially when flood conditions arise. The paper explores two commonly used flood hydrograph approaches, the Nakayasu Synthetic and the Soil Conservation Service (SCS) Unit Synthetic, concentrating on the design of flood discharge and its significance in flood management. The study provides insight into the feasibility of existing hydrograph techniques for determining flood discharge and is based on bibliometric data from earlier studies.

Correlating Late-Holocene climate change and population dynamics at Cahokia Mounds (American Bottom, USA)

Food insecurity and the disruption of agricultural systems are often cited as explanations for the correlations observed between climate change and demographic shifts in past agricultural societies. While these narratives are abundant with data pertaining to climate and demographic changes, they often lack substantial information regarding the processes contributing to agricultural destabilization. In this article, we employ stable carbon isotopes extracted from paleosols collected at Cahokia Mounds, the largest Indigenous settlement in North America, to illustrate that vegetative communities did not respond to the multi-decadal drought that afflicted the mid-continent region at the end of the 13th century. This research underscores the existing gaps in our understanding of how plant communities respond to climate variations. To effectively utilize historical examples in shaping future strategies for adapting to contemporary climate change, it is imperative that we acquire deeper insights into the tolerance of Indigenous crops and culturally significant plants to various drought and flood conditions.

Post Flood Economic Challenges; Resilience and Rehabilitation Strategies With Thematic Analysis Approach. A Case of Larkana

Climate change has exacerbated the frequency and severity of floods, leading to devastating impacts worldwide. Pakistan has seen two catastrophic floods in recent years; at present, the full extent of the consequences of these calamities is still not fully acknowledged. Scarcity of water, rise in temperature, and floods are some cruel consequences that Pakistan has to bear. Floods may lead to huge economic problems not only for people in general but also for the communities. For instance, the condition of flooding in Larkana, which is the province where the agricultural activities are too much, could bring about financial and mental health problems. To tackle this research gap, this study implemented a qualitative research approach and conducted a thematic analysis to explore the economic challenges encountered in the Larkana region as a result of floods. Theme analysis is a method by which the researcher finds the sequential patterns in the data. Thus, the researcher is able to point out the issues that people face in reality. Resilient plans and rehabilitation measures can contribute to the solutions to these challenges, varying from immediate recovery to sustainable development. A multifaceted plan that encompasses immediate rescue operations and strengthening of resilience is a must. Social cohesion, environmental protection measures and governance issues are most relevant for the effective economic recovery after floods. The economic regeneration strategy in flood-prone areas must address complex issues to ensure local resilience and preparedness for the coming years.

Different Phenotypic, Photosynthetic, and Physiological Responses to Flooding between Q. nuttallii and Q. palustris.

Flooding stress is an increasingly serious problem in wetlands, often affecting large areas of crops and timber production areas. The current study aimed to explore the species differences in responses to flooding stress between Q. nuttallii and Q. palustris in an outdoor environment. All the tested plants survived after a 60-day flooding treatment that left 5 cm of water above the soil surface. This suggests that the two species are flood-tolerant, so they can be applied in the construction of riparian protection forests and wetland restoration. Compared with control conditions, flooding treatment significantly decreased seedling height and diameter and the Pn, Gs, Tr, Fv/Fm, ABS/CSm, TR0/CSm, ET0/CSm, RE0/CSm, IAA, and GA3 content and significantly increased the content of MDA, H2O2, soluble sugars, SOD, POD, ADH, ABA, and JA. Under control conditions, Q. nuttallii showed significantly greater growth and photosynthetic capability than Q. palustris. In contrast, Q. palustris exhibited less inhibition of growth and photosynthesis, oxidative stress levels, and antioxidant enzyme activities than Q. nuttallii under flooding conditions. The findings indicate that Q. palustris has better defense mechanisms against the damage caused by flooding stress than Q. nuttallii. Q. nuttallii was more sensitive and responsive to flooding than Q. palustris.

Rapid mapping of global flood precursors and impacts using novel five-day GRACE solutions

Floods affect communities and ecosystems worldwide, emphasizing the importance of identifying their precursors and enhancing resilience to these events. Here, we calculated Antecedent Total Water Storage (ATWS) anomalies from the new 5-day (5D) Gravity Recovery and Climate Experiment (GRACE) and its Follow-On (GRACE-FO) satellite solutions to enhance the detection of pre-flood and active flood conditions and to map post-flood storage anomalies. The GRACE data were compared with ~ 3300 flood events reported by the Dartmouth Flood Observatory (2002–2021), revealing distinct ATWS precursor signals in 5D solutions, in contrast to the monthly solutions. Specifically, floods caused by saturation-excess runoff—triggered by persistent rainfall, monsoonal patterns, snowmelt, or rain-on-snow events—show detectable ATWS increases 15 to 50 days before and during floods, providing a valuable opportunity to improve flood monitoring. These 5D solutions also facilitate a more rapid mapping of post-flood storage changes to assess flood recovery from tropical cyclones and sub-monthly weather extremes. Our findings show the promising potential of 5D GRACE solutions, which are still in the development phase, for future integration into operational frameworks to enhance flood detection and recovery, facilitating the rapid analysis of storage changes relative to monthly solutions.

Physicochemical characterization of the aquatic-terrestrial transition zone of a tropical wetland (Ayapel-Colombia)

Contextualization: The aquatic-terrestrial transition zone (ZTAT) in the floodplain (alluvial plain) Ramsar Ayapel (Colombia) remains flooded for more than half of the year, and its coastal strip generates a strong influence on the ecosystem. An approach to the spatial and temporal characterization of this zone is crucial for further functional analysis, especially when tropical floodplains are little explored except for some Amazonian ecosystems. Knowledge gap: Floodplain dynamics are mainly regulated by flood pulses, directly influencing he physical and chemical conditions of water and sediment. Therefore, the biota is adapted to the flooding and waterlogging conditions of the ecosystem. However, research has addressed the terrestrial and aquatic phases as separate systems, making it necessary to resort to methodologies that demonstrate connectivity in the system and facilitate the interpretation of key factors in the ecological functioning of tropical wetlands. Purpose: The research analyzed the structure and functioning of the ZTAT through physical and chemical variables at different times of the flood pulse. Methodology: In two wetlands of the muddy complex, sensitive to the flood pulse, three samplings were carried out: rising water (July/2021), high water (September/2021), and declining water (March/2022). The ZTAT was monitored by delimiting it into four subzones: water, sediments, floodable soil, and soil. Results and conclusions: Significant changes in time associated with water level and nitrogen concentrations were revealed; while in space, assisted by the contrast of the ZTAT at the two sites, differences were reflected through in situ variables and soil characteristics. It was detected that depth, transparency, and a higher concentration of nitrogen forms, and some ions such as aluminum and magnesium generated differences on a time level. On the contrary, conductivity, calcium concentration, and variables associated with soil characteristics expressed it at the spatial level due to exploring the ZTAT. Therefore, the physicochemical dynamics of moments and sites in a wetland require a sampling design that, using the ZTAT, facilitates the scale of physicochemical analysis.

Design of an Android-Based Dam Flood and Drought Early Warning Information System (SI BANKER) in West Nusa Tenggara

Dam construction in Indonesia is currently very developed, namely 235 dams that have been built and West Nusa Tenggara Province contributes 30% of the number of dams in Indonesia, namely 70 dams spread across the islands of Lombok and Sumbawa, where 32 dams are in the Lombok River Basin and 38 dams in the Sumbawa River Basin. The current problem for the Europeanization and maintenance of existing dams in West Nusa Tenggara province is that there is no information system that can make it easier for officers at each dam to report the latest condition of the water level of each dam and provide early warning of the condition of the dam's water level whether it will be close to flood or dry conditions. Currently, to report water level conditions in each dam, officials at each dam can only report the results of water level monitoring under normal circumstances, floods or droughts only manually. The purpose of this study is to provide early warning information / notifications on flood and drought conditions in dams in West Nusa Tenggara province based on android. The research method used in the process of developing this system is the waterfall development method which consists of 5 stages, namely defining needs, designing, coding and implementation, testing and documentation. The results of this study are in accordance with the description in the previous chapter including interface implementation, system testing and evaluating the system. Evaluation is carried out to determine the shortcomings of the system, so that it can be better for future development. The conclusion of this study from the design and testing that has been carried out shows that all functions have run in accordance with the proposed system. For further research, it is recommended to create a similar Android mobile application but using a more complete framework and having many references to perfect some features in the application that are still not perfect.

Machine learning models and machinability analysis for comparison of various cooling and lubricating mediums during milling of Hardox 400 steel

Martensitic steels are widely used in many areas such as automotive, mining, and agriculture mostly thanks to their thermal loading ability property. On the other hand, these special steels exhibit extreme tool wear tendency and low surface quality which can be associated with abrasive resistance. This situation makes this steel hard-to-cut and requires further investigation with several approaches. Sustainable machining environments are highly effective as modern strategies to improve the machinability index. Also, machine learning models have pivotal role on decreasing the total consumption in the way of lean manufacturing. In the light of above-mentioned information, this work focuses on the machining performances and optimization of dry, flood, and MQL conditions during the milling of Hardox 400 martensitic stainless steel. A novel approach was applied with using several cutting environments and machine learning models to enhance machinability of Hardox which is an industrially important material. Results were analyzed with different machine learning models using heat map and decision trees. Seemingly, cutting fluid assistance in the milling of Hardox steel is critical where flood and MQL provided a considerable effect on the tool wear for reducing it under some level. Also, this technology was found useful in determining the best conditions of machinability in terms of surface roughness, chip morphology, energy consumption, and cutting temperatures. Machine learning models provided hopeful results in analyzing the correlations between parameters used in the model. In machine learning, the heat map being close to 1 and the MSE and MAE values being close to 0 indicated that the model was suitable. This study is expected to observe the contributions of different types of cutting environments to the machinability criteria during milling of industrially important materials.

River floodplains as source or sink for fine sediment and total phosphorus export in an agricultural watershed

AbstractFloodplains constitute a vital and integrated component of the riverine network ensuring the connectivity and continuity of the river with the upland watershed areas. However, the sediment trapping efficiency of floodplains has not been well investigated. The purpose of this experimental study was to evaluate the functionality of floodplains to act as either sources or sinks for fine sediments and sediment‐bound nutrients (e.g., total phosphorus) during floods of various return periods. Thus, we hypothesized that (i) soil texture, in terms of topsoil erodibility and (ii) the magnitude of the incoming flood, in terms of the applied shear stress, are the two key parameters govern river floodplains' ability to store or release fine sediments and total phosphorus, during major flood conditions. Topsoil erodibility experiments were coupled with site‐specific flood inundation maps to estimate the eroded fine sediment mass and the total phosphorus release rates per unit area per unit time of each flood condition considered. Results suggested that the floodplain soils of the upstream reaches act as net sources, the floodplains of the midstream reaches have a dual functionality; during low magnitude flood events (up to 10‐year return periods), they act as net sinks, while during higher flood events, they act as sources; and the floodplains of the downstream reaches largely act as sinks. This study results are applicable for watershed managers to identify floodplain areas vulnerable to erosion and sources of nutrient pollution.

Response mechanism of Cynodon dactylon to flooding stress based on integrating metabonomics and transcriptomics analysis

Cynodon dactylon, a perennial herbaceous of Poaceae, possessing unique abilities in flooding tolerance and clonal propagation. However, evidences on molecular response mechanism from field are missing. Here, the differential responses of above-ground (stolon) and below-ground (root) organs of C. dactylon under flooding and non-flooding (CK) conditions were compared at the transcriptional and metabolomic levels. Under flooding stress, significant enrichment of differentially expressed genes (DEGs) related to dehydration responses, including cell water homeostasis and ion transmembrane transport were observed in both roots and stolons. The stolons were more sensitive to flooding, while enrichment in energy metabolism in roots were higher, such as the glycolytic process and glycogen biosynthetic process. The DEGs of photosynthesis in stolons were significantly down-regulated compared to roots. Under flooding stress, oxidative phosphorylation (OXPHOS) is inactivated, and the terminal oxidase of the mitochondrial electron transport chain (mtETC), cytochrome c oxidase (COX), is inhibited. Consequently, the expression of pyruvate decarboxylase (PDC) and alcohol dehydrogenase (ADH) involved in fermentative metabolism is upregulated. The combined analysis indicated that phenylalanine, tyrosine, and tryptophan biosynthetic pathways in roots were significantly enriched in the flooding group. In contrast, there was a significant increase in phenylalanine biosynthesis in stolons, and the metabolite phenol exhibited up-regulated expression. In summary, phenylalanine metabolism and phenylalanine biosynthesis are the major responses to flooding stress, indicating the crucial role of these pathways in the flood tolerance of C. dactylon. These findings provide valuable evidence for understanding plant regulatory mechanisms underlying flooding tolerance.

3D Numerical Simulations of the Bed Evolution at an Open-Channel Junction in Flood Conditions

3D Numerical Simulations of the Bed Evolution at an Open-Channel Junction in Flood Conditions

Subgrade stabilization for road foundation in application for inundated area in Perlis, Malaysia

Abstract Inundated areas, which are prone to frequent flooding, pose significant challenges for road infrastructure due to the adverse effects of water on subgrade soils. Thus, the objectives of this research were to identify and characterize the soil type from roadside of Kampung Bakau, Kangar, Perlis, and evaluate and propose the effective subgrade stabilization methods to enhance the performance and durability of road foundations under such condition. In this research, atterberg limit, standard proctor, and california bearing ratio (CBR) tests were conducted. For CBR test, 6 sets of soil samples were considered. In addition, during the CBR tests, soaked and unsoaked method were performed to simulate the condition of flooding. In general, the soil samples taken were characterized as high plasticity silt. Besides that, the results obtained from CBR test showed that lime with 8 % addition in mixture provides the highest strength which was 4.50 kN of load resisted at 2.00 mm penetration. Meanwhile, cement with 3 % addition in mixture showed the lowest strength observed in the CBR test which was 1.75 kN. In conclusion, this research showed that for high plasticity silt type of soil, the optimized subgrade stabilization method is by lime with 8 % addition in mixture.

Developing a Fluvial and Pluvial Stochastic Flood Model of Southeast Asia

AbstractFlood event set generation, as employed in catastrophe risk models, relies on gauge information that is not available in data‐scarce regions. To overcome this limitation, we develop a stochastic fluvial and pluvial flood model of Southeast Asia, using freely and globally available discharge data from the global hydrological model GloFAS and rainfall from the ERA5 reanalysis. We use a conditional multivariate statistical model to produce a synthetic catalog of 10,000 years of flood events. We calculate the flood population exposure associated with each flood event using freely available population data from WorldPop and generate exposure probability exceedance curves. We validate the population exposure curves against observed flood disaster data from EM‐DAT, showing that our methodology provides exposure estimates that are in line with historical observations. We find that there is a 1% probability that more than 30 million people will be exposed to flooding in a given year according to our event set. This number is roughly half the population living in the 100‐year return period flood zone of Fathom's hazard maps, suggesting most studies based on static flood maps overestimate exposure. This analysis provides significant progress over previous non‐stochastic studies which are only able to compute total or average exposure within a given floodplain area and demonstrates that a reanalysis‐based stochastic flood model can be designed to generate reliable estimates of population exposure probability exceedance. This study is a step toward a fully global catastrophe model for floods capable of providing exposure and loss estimates worldwide.

Functional Segregation of Resource Utilization Strategies between Invasive and Native Plants and Invasion Mechanisms in the Water Level Fluctuation Zone: A Case Study of Pengxi River in Three Gorges Reservoir, China

The ecosystem of the water level fluctuation (WLF) zone of the Three Gorges Reservoir (TGR) is highly vulnerable and sensitive due to its unique cyclical flooding and drought conditions. The ecological impact of biological invasion in this area is particularly severe, making it crucial to study the differences in resource utilization strategies between invasive plants (IPs) and native plants (NPs) using functional traits to explore the mechanisms of invasion. We selected the WLF zone of Pengxi River in the TGR area and conducted a multi-scale study along the elevation gradient. The results reveal that at the regional scale, IPs have a larger height and specific leaf area, smaller leaf tissue density, and specific root length compared to NPs, showing a preference for enhancing aboveground resource acquisition over leaf defense capabilities. They allocate more tissue construction resources to their roots to withstand environmental pressures, which may be the key to their successful intrusion, highlighting the role of niche differentiation. On the community scale, the H and SLA of IPs and NPs are positively correlated with elevation, while the LTD of IPs shows a negative correlation. At elevations of 175 m and below, IP and NP exhibit functional convergence, while above 175 m, functional divergence was observed. This indicates that although the different resource utilization strategies are crucial for successful IP invasion, the environmental filtering from periodic floods and drought pressures play a significant role in community assembly in the WLF zone, allowing IP to integrate into habitats with similar functional characteristics already inhabited by NP and establish their own communities.

Climate Change and Flood Vulnerability Analysis in the Narayani River of Nepal

Flood disasters annually devastate livelihoods, particularly during the monsoon season, with no apparent reduction in impacts in low-lying regions of developing countries like Nepal. Given the increasing effects of climate change globally, this study aims to assess climate change effects and biophysical vulnerability of riverine communities to floods in the Narayani River of Nepal, elucidating the interrelationship between these phenomena. This paper presents an analysis of trends and extreme events of climatological variables, such as temperature, precipitation, and daily river discharge and hazard mapping and risk assessments in the river stretch of two Village Development Committees (VDCs) in the country’s inner Terai region of Nawalparasi district for different return-period floods, with the aid of the HEC-RAS (Hydrologic Engineering Centre’s River Analysis System) and HEC-GeoRAS. A long-term climatological data was collected from the Department of Hydrology and Meteorology, Kathmandu, and the analysis was performed using statistical softwares, SigmaStat, and SigmaPlot. In addition, flood conditions representing 2, and 100-year periods were determined using Gumbel’s distribution. The study revealed a narrowing temperature range, with increasing minimum temperatures and decreasing maximum temperatures, precipitation, and river discharge. However, there was a notable increase in extreme events. The hazard mapping indicated the people’s vulnerability to inundation and soil erosion along the low-lying riverbanks. The findings underscore the necessity for reliable technological and socio-economic vulnerability mapping to provide early warnings to at-risk populations. This paper argues that unplanned and mismanaged settlements in riverine areas may lead to population displacements, creating environmental refugees.

Vehicle Route Planning for Relief Item Distribution under Flood Uncertainty

Flooding, a pervasive and severe natural disaster, significantly damages environments and infrastructure and endangers human lives. In affected regions, disruptions to transportation networks often lead to critical shortages of essential supplies, such as food and water. The swift and adaptable delivery of relief goods via vehicle is vital to sustain life and facilitate community recovery. This paper introduces a novel model, the Vehicle Routing Problem for Relief Item Distribution under Flood Uncertainty (VRP-RIDFU), which focuses on optimizing the speed of route generation and minimizing waiting times for aid delivery in flood conditions. The Genetic Algorithm (GA) is employed because it effectively handles the uncertainties typical of NP-Hard problems. This model features a dual-population strategy: random and enhanced populations, with the latter specifically designed to manage uncertainties through anticipated route performance evaluations, incorporating factors like waiting times and flood risks. The Population Sizing Module (PSM) is implemented to dynamically adjust the population size based on the dispersion of affected nodes, using standard deviation assessments. Introducing the Complete Subtour Order Crossover (CSOX) method improves solution quality and accelerates convergence. The model’s efficacy is validated through simulated flood scenarios that emulate various degrees of uncertainty in road conditions, affirming its practicality for real-life rescue operations. Focusing on prioritizing waiting times over travel times in routing decisions has proven effective. The model has been tested using standard CVRP problems with 20 distinct sets, each with varying node numbers and patterns, demonstrating superior performance and efficiency in generating vehicle routing plans compared to the shortest routes, which serve as the benchmark for optimal solutions. The results highlight the model’s capability to deliver high-quality solutions more rapidly across all tested scenarios.

Climate–resilient strategy for shortening the crop cycle in rice and the host influenced rhizosphere microbiome

We present the field rapid generation advancement procedure for shortening the crop cycle in rice. The practical protocol developed by us using different maturity groups of rice showed promising early flower induction. We observed a shortening of crop cycle to about 35–40 days depending on the variety. The spacing between the plants was the major influencer for flower induction compared to other interventions tested viz., clipping, potassium di-hydrogen phosphate and paclobutrazol spray. Our raised bed direct seeding strategy completely avoided the transplantation. The work flow for flower induction can be a reference to increase generations of rice breeding. The rhizosphere bacterial dynamics using 16srRNA gene amplicon sequencing showed the Acinetobacter population abundance as a key mediator and marker for flowering time. The alpha diversity at flowered and unflowered stage showed the species richness as Control < Pusa Sugandh 5 < BPT-5204. The rice rhizosphere of this ecosystem had an abundance of Methylotrophs that utilize methane as a carbon source suggesting that the developed method is a green technique suitable for generation advancement that can be replaced for flooded condition assisted breeding in rice. Selective enrichment of functional abundance between varieties suggested the host - influenced microbiome for early flowering in rice. This protocol is expected to greatly accelerate the process of new variety breeding and the construction of mapping populations.