Researchers in Brazil have demonstrated that a hybrid advanced oxidation process can transform pharmaceutical-laden wastewater into an effluent that is dramatically safer for plants, earthworms, onion root cells, and beneficial microorganisms, offering a rigorous ecotoxicological case for reusing treated sewage in agriculture. The study, published in Environmental Science and Pollution Research, addresses a long-standing blind spot in water treatment: proving that a chemically “clean” effluent is also biologically compatible.

Conventional wastewater treatment plants were never designed to strip out recalcitrant organic micropollutants such as pharmaceuticals, and trace amounts routinely slip through into receiving waters. Advanced oxidation processes (AOPs) attack these stubborn compounds by generating highly reactive free radicals that fragment contaminant molecules. But chemical degradation alone does not guarantee safety. As contaminants break down, they spawn transformation products (TPs) that can, in some cases, be as toxic as—or more toxic than—the parent compounds. The research team, led by Lucas Gustavo da Costa and Alam Gustavo Trovó of the Federal University of Uberlândia, together with collaborators at the Oswaldo Cruz Institute, set out to answer a deceptively simple question: does measurable chemical removal of micropollutants actually translate into reduced biological harm?

The centerpiece of their work is the H₂O₂/S₂O₈²⁻/UVC process, a hybrid system that combines hydrogen peroxide and persulfate with short-wave ultraviolet C radiation. UVC photons cleave both oxidants simultaneously, generating hydroxyl radicals (HO•) and sulfate radicals (SO₄•⁻) in the same reaction volume. This dual-radical strategy outperforms systems relying on either oxidant alone, or on peroxymonosulfate (HSO₅⁻), which is costlier and demands more energy for activation. The hybrid route also resists interference from inorganic species commonly found in real effluents, making it an economically attractive candidate for deployment at full-scale treatment plants. The process had already been chemically optimized in the team’s earlier work using multivariate mixture design and rotatable central composite design experiments; the new study is its first integrated biological stress test.

The experiments used real municipal effluent from a wastewater treatment plant in Uberlândia, Minas Gerais, sampled after the plant’s final tertiary treatment stage of coagulation-flocculation with ferric chloride and flotation. The effluent was enriched with three pharmaceuticals representing different therapeutic classes: colchicine (COL, an antimitotic agent), nitazoxanide (NTZ, an antiparasitic), and sulfamethoxazole (SMX, a widely detected antibiotic), each at 325 nmol L⁻¹—equivalent to 130, 100, and 82 micrograms per liter, respectively. That concentration was deliberately chosen as high enough for direct HPLC–DAD analysis without preconcentration, yet low enough to be environmentally representative. Treatment was carried out in an amber glass reactor irradiated by two 8-watt UVC mercury lamps emitting at 254 nm, with a measured irradiance of 4.9 W m⁻². Residual oxidants were neutralized with sodium thiosulfate before any biological testing, ensuring that observed effects could not be attributed to leftover peroxide chemistry.

The ecotoxicological battery spanned multiple trophic levels and levels of biological organization. Oxidative stress was assessed in the earthworm Eisenia andrei by measuring malondialdehyde (MDA), a marker of lipid peroxidation, and protein carbonylation, an irreversible oxidative modification of proteins. Phytotoxicity was evaluated using lettuce (Lactuca sativa) seeds and a growth index combining germination rate and root elongation. Cytotoxicity and genotoxicity were quantified in onion (Allium cepa) root meristems through the mitotic index and the frequency of chromosomal and nuclear aberrations—micronuclei, chromosome breaks, stickiness, bridges, and nuclear buds—across 5,000 cells per sample. Finally, growth inhibition was tested in two environmentally relevant microbes: Azospirillum brasilense, a plant growth-promoting bacterium used in soybean cultivation, and Saccharomyces cerevisiae, a yeast that persists in soils and fermentative niches.

The untreated enriched effluent told a worrying story. It exhibited substantial genotoxicity in onion cells—21%, approaching the 24% seen with the positive control, methyl methanesulfonate—and severe phytotoxicity, with lettuce growth indices far below the 80% threshold that signals absence of toxicity. Even the unspiked effluent itself suppressed lettuce growth, achieving a growth index of only 47%, evidence that bioactive compounds survive conventional treatment. In earthworms, individual aqueous solutions of NTZ and SMX raised MDA levels by 37.2% and 23.5% respectively, while the three-compound mixture increased lipid peroxidation by 38.0%, pointing to additive or synergistic oxidative stress mechanisms involving reactive oxygen species and Fenton-type chemistry within cells.

The picture changed decisively after oxidation. Following 10 minutes of UVC-driven treatment—the point at which 80% chemical degradation had been achieved, matching the minimum removal target proposed in the European Union’s COM(2022)541 directive—genotoxicity fell to 10%, and after 20 minutes, corresponding to the limit of quantification for the parent compounds, it dropped further to 6%, a statistically significant reduction. The plant growth index climbed above 80%, crossing from toxic territory into biocompatibility. The mitotic index in onion cells remained statistically indistinguishable from the deionized-water control (around 39–40% versus 40%), demonstrating that the process generated no cytotoxic byproducts capable of arresting cell division. And crucially for agricultural applications, neither the treated effluent nor its transformation products inhibited growth of A. brasilense or S. cerevisiae.

The mechanistic details are instructive. In the untreated enriched effluent, micronuclei—membrane-bound DNA fragments expelled from the nucleus during flawed cell division—were among the most frequent aberrations, indicating clastogenic and aneugenic damage. Colchicine exposure predictably produced C-metaphase accumulation, a signature of its tubulin-binding, spindle-disrupting mechanism first described in Allium nearly a century ago. SMX depressed the mitotic index and induced chromosomal damage, consistent with prior findings in Vicia faba. NTZ, whose genotoxicity had never before been reported, produced chromosome breaks, stickiness, and nuclear buds. After oxidation, the overall aberration burden fell sharply, particularly micronuclei and stickiness, although a few bridges and polyploid cells persisted even at 20 minutes—a reminder that some transformation products or resistant residuals may linger.

The microbial results came with a subtlety. Reduced A. brasilense growth after treatment initially looked like a red flag, but the team attributes it to depletion of assimilable organic matter, which serves as radical scavenger during oxidation and as a nutrient source afterward—not to toxicity. The negative control likewise grew slowly. This distinction matters because AOPs are designed to mineralize organic carbon, and a nutrient-poorer medium should not be misread as a more toxic one. For S. cerevisiae, no inhibition occurred at any stage of treatment, although NTZ alone significantly depressed yeast optical density, reinforcing the compound’s cell-cycle interference potential even at nanomolar-scale exposures.

The study’s broader significance lies in its methodological stance. By adopting an “effect-driven approach,” the team evaluated the toxicity of whole reaction mixtures without needing to isolate and identify individual transformation products—an impractical task given that many degradation byproducts are not commercially available. Their findings align with a growing consensus that treatment efficacy must be judged not merely by parent-compound removal but by the nature and reactivity of the resulting transformation products. Biochemical biomarkers such as MDA and protein carbonylation detected sublethal disturbances that mortality-based endpoints would have missed entirely, providing early warnings of cellular distress at environmentally relevant concentrations.

One caveat deserves attention: while lipid peroxidation declined after treatment, protein carbonylation rose slightly—1.05-fold above control—suggesting some transformation products may still provoke protein oxidation even as lipid damage subsides. The authors flag this discrepancy and call for future identification of the specific TPs responsible, alongside expanded organism panels, longer-term exposure studies, and pilot-scale validation across different environmental matrices.

The regulatory context sharpens the urgency. The EU’s proposed urban wastewater treatment directive mandates at least 80% removal of specified organic micropollutants and microbiological control for agricultural reuse, yet it conspicuously omits eco-compatibility assessment of the treated water itself. This study supplies exactly that missing dimension, showing that a process satisfying the chemical benchmark also delivers measurable biological benefit—lower genotoxicity, restored plant growth, intact cell division, and unharmed beneficial microbes. As water scarcity intensifies globally and reuse becomes less optional, the Brazilian team’s integrated bioassay framework offers a template for ensuring that the water farmers irrigate with is not merely chemically compliant, but genuinely ecologically safe.

Jerusalem’s ancient water system was not only about finding a spring. It was about controlling what happened when the water came too quickly and when the rain failed to arrive at all. A new study has dated a large dam near the Siloam Pool to roughly 805–795 BCE, during the period when the kingdom of […]

The post Jerusalem’s 2,800-Year-Old Dam Shows How Judah Managed Drought and Flash Floods appeared first on Curiosmos.

A new study in npj Urban Sustainability points to the practical levers that determine whether stormwater systems actually deliver long-term sustainability. As cities expand and rainfall extremes intensify, green and nature-based infrastructure has been promoted to capture runoff, reduce flooding, and protect water quality. But the research warns that success is not automatic: design decisions and operational realities can make or break performance.

The authors, Sun, Randrup, Blecken and colleagues, analyze what they call “decisive factors” governing sustainable stormwater management. Their central message is that the most visible features—such as bioswales, permeable surfaces, or detention basins—only work when supported by the right planning assumptions and measurable hydrological outcomes.

A key technical theme is how stormwater must be matched to system capacity under changing conditions. The study emphasizes that system sizing, soil or media properties, and infiltration or storage behavior strongly influence whether the infrastructure can handle typical storms and rare, high-intensity events. When these factors are misestimated, treatment efficiency can collapse during peak flows.

Equally important are maintenance and lifecycle considerations. Sustainable stormwater is sensitive to clogging, sediment accumulation, vegetation health, and changes in catchment behavior. The research highlights the need for maintenance regimes that reflect likely failure modes, rather than generic schedules that ignore local hydrology and traffic or land-use impacts.

The paper also stresses the value of monitoring and model-informed decision-making. Reliable data on rainfall patterns, runoff routing, and pollutant loads allow managers to validate performance and adjust operations. This feedback loop helps prevent long-term degradation that otherwise remains invisible until issues become costly.

For cities seeking viral, widely transferable “what works” guidance, the authors’ findings offer a shortlist of priorities: realistic capacity planning, robust material characterization, design for multi-storm performance, and maintenance strategies tied to specific mechanisms. Together, these elements translate sustainability goals into systems that function under real weather and real urban change.

The study’s DOI is 10.1038/s42949-026-00448-4.

Subject of Research: Sustainable stormwater management / urban sustainability
Article Title: Decisive factors in sustainable stormwater management
Article References: Sun, Z., Randrup, T.B., Blecken, GT. et al. Decisive factors in sustainable stormwater management. npj Urban Sustain 6, 104 (2026). https://doi.org/10.1038/s42949-026-00448-4
Image Credits: AI Generated
DOI: https://doi.org/10.1038/s42949-026-00448-4

In the evolving landscape of global water resource management, addressing the persistent tension between equitable distribution and cooperative efficiency remains a paramount challenge. A pioneering study recently published in Nature Water introduces an innovative Atkinson social welfare function (SWF)-based framework that operationalizes distributive equity alongside systemic efficiency within transboundary water systems. By embedding equity explicitly as a normative design criterion, this framework leverages an adjustable inequality aversion parameter, providing policymakers with a powerful tool to balance social justice with optimal resource use.

At the heart of this advancement lies the mathematical backbone of the Atkinson SWF, a function well-regarded for its flexibility in capturing societal preferences for inequality reduction. The framework transforms equity from a nebulous ideal into a quantifiable, adjustable dimension directly integrated within multi-objective optimization. Applied to the Zambezi Watercourse—a complex shared basin impacting multiple countries—the model reveals that introducing inequality aversion yields only modest reductions in total hydropower output, around 1–2.7%, while significantly lowering disparities in country-level generation by 3 to 8 points on the Atkinson index.

This nuance is crucial because natural constraints such as water availability and turbine capacity inherently limit the scope for redistributing hydropower output to improve equity. Instead, the model shows that inequality aversion primarily affects firm generation capacity, where Zimbabwe and Zambia experience substantial percentage increases during critical periods, reflecting strategic operational shifts. Mozambique’s generation remains relatively stable. Such findings underscore a pragmatic approach to equity: rather than static allocation, operational strategies can target support during vulnerable drought conditions, effectively marrying resilience with justice.

Importantly, the concave utility assumption underlying inequality aversion parallels risk aversion concepts in economic theory. This alignment suggests that what often appears as an efficiency sacrifice in pursuit of equity may, in fact, represent a system more robust to uncertainty and stressors. In water resource contexts marked by ecological variability and competing demands, this insight reframes equity not as a zero-sum trade-off but as integral to sustainable cooperation.

A key innovation of the framework is its dynamic adaptiveness during optimization, eschewing rigid allocation rules or static weightings. For instance, when factoring in floating photovoltaic (FPV) investments alongside traditional hydropower, Mozambique assumes the full cost of preserving near-natural environmental flows in its delta—sacrificing 41% of hydropower generation and facing frequent low-output periods. Yet, this environmental stewardship shifts investment priorities away from Zambia to Mozambique without requiring prior distributional knowledge, thereby reducing inequality by 25 Atkinson index points with a modest overall production trade-off of 4.2%. This responsiveness is a critical advancement for transboundary water management, where power dynamics and environmental conditions are perpetually in flux.

The study deliberately calibrates its inequality aversion parameter, epsilon (ϵ), at 2—a level representing strong equity preference—to demonstrate the framework’s capabilities. However, it recognizes stakeholder perspectives may differ widely. Rather than treating epsilon as a technical constant, the authors advocate viewing it as a parameter for deliberation, surfacing explicit negotiation choices among diverse actors. Structured choice experiments could translate complex mathematical trade-offs into intuitively understandable options, enabling stakeholders to reveal implicit equity preferences through participatory processes. This approach dovetails with the multi-objective optimization’s Pareto frontier, which transparently spans the spectrum from maximal efficiency to maximal equity, thus facilitating informed trade-offs.

The researchers embed a normative assumption in their baseline welfare function: treating each country as an equally weighted actor, reflecting sovereignty principles inherent in international water law and institutional arrangements like ZAMCOM, the Zambezi Watercourse Commission. This aligns with the ‘one state, one vote’ doctrine, appropriate for interstate governance frameworks. Yet, the team acknowledges the normative and practical implications of population-weighted alternatives. Incorporating population in the welfare aggregate could, for example, prioritize individual welfare across riparian states rather than equal state-level standing. Such distinctions have profound implications—especially in basins like the Zambezi where the most populous country, Mozambique, has the lowest per-capita hydropower generation.

Extending the framework to a population-weighted SWF or a per-capita welfare input introduces normative choices about justice, as these measure equity through fundamentally different lenses: aggregate human welfare versus national sovereignty. In scenarios where population rankings and per-capita generation rankings conflict, these alternatives may pull policy preferences in divergent directions, underscoring the need for societal dialogue to resolve such trade-offs.

While the study focuses on interstate equity, it also addresses the crucial gap of intrastate disparities, which country-level metrics risk obscuring. Implementing the framework at subnational scales would necessitate coupling basin-wide hydrological models with detailed power system dispatch simulations and geospatial electrification mapping. Though technically complex, such integration promises to capture localized inequalities in access and generation more effectively. Preliminary attempts, such as those conducted in Ghana, employ inequity metrics like the Gini index but lack Atkinson’s adjustable inequality aversion—an essential feature for nuanced policy negotiation. The authors argue that their SWF framework offers scalable advantages for applying distributive justice across regional or even community scales, especially in data-scarce, transboundary environments.

A particularly thought-provoking question arises around accommodating group-specific inequality aversion across demographic or vulnerability categories—such as gender-differentiated impacts or subregional disparities within countries. From a methodological standpoint, the study identifies significant hurdles. Introducing distinct epsilon parameters for multiple groups compromises the anonymity and Pigou-Dalton consistency properties fundamental to welfare economics and adds layers of unquantifiable normative complexity. Instead, the authors advocate maintaining a single inequality aversion parameter, deferring subgroup analyses to disaggregated data where possible and allowing these insights to inform participatory negotiations.

Complementary approaches, including incorporation of needs-referenced thresholds consistent with prioritarian ethics, face challenges tied to the Atkinson function’s strict positivity constraints and the difficulty of justifying group-specific thresholds beyond narrowly defined legal or vulnerability classifications. Ultimately, the study emphasizes that the framework’s power lies in making equity visible and operationally relevant, rather than complicating aggregation with layered value parameters.

Beyond hydropower and water management, this Atkinson SWF-based approach holds broader applicability. Many resource allocation challenges characterized by monotonic, concave utilities—such as renewable energy deployment, biodiversity conservation, or climate adaptation finance—stand to benefit from formalized equity-efficiency trade-offs. Threshold effects or objectives with increasing returns require separate treatment within multi-objective optimization, but many relevant environmental and social goals fit the concavity assumption well.

As climate change intensifies variability in precipitation and water availability, the necessity of cooperative frameworks balancing equity and efficiency becomes ever more urgent to prevent breakdowns in international water agreements. By operationalizing the principle of ‘equitable and reasonable utilization,’ this research translates normative international water law doctrines into tangible, evidence-based decision tools that directly relate to real-world human welfare and environmental sustainability outcomes. The Atkinson SWF, with its adaptable inequality aversion and capacity for participatory negotiation, emerges as a promising lynchpin for future transboundary water governance.

In conclusion, this study marks a notable advance towards integrating distributive justice within multi-actor optimization models for shared water systems. It demonstrates how explicit normative assumptions can coexist with rigorous technical analysis to produce outcomes that are both efficient and equitable. The dynamic responsiveness embedded in the framework addresses the complexity and uncertainty of water sharing arrangements, facilitating adaptive cooperation even as political and climatic conditions evolve. This balanced approach, supported by empirical application to the Zambezi basin, could serve as a blueprint for operationalizing equity in other transboundary resource settings worldwide.

As demands on common-pool resources mount, such integrative approaches will be indispensable for sustaining long-term cooperation. By linking sophisticated welfare economics with participatory policy processes and cutting-edge water system simulations, this research provides both the theoretical foundation and practical pathway to reconcile competing values on the international stage. The Atkinson SWF-based equity framework thus represents a crucial step towards more just, resilient, and sustainable shared water futures.

Subject of Research:
Optimization of distributive equity and cooperative efficiency in transboundary water resource systems using Atkinson’s social welfare function.

Article Title:
Balancing equity and efficiency in transboundary water systems with Atkinson’s welfare function.

Article References:
Arnold, W., Giuliani, M. & Castelletti, A. Balancing equity and efficiency in transboundary water systems with Atkinson’s welfare function. Nat Water (2026). https://doi.org/10.1038/s44221-026-00671-4

Image Credits:
AI Generated

DOI:
https://doi.org/10.1038/s44221-026-00671-4

Urban flooding has emerged as one of the most pressing environmental challenges faced by modern cities worldwide. As urbanization accelerates and impermeable surfaces replace natural landscapes, the capacity of drainage systems and natural waterways to manage stormwater dramatically decreases. This phenomenon exacerbates flood risks, leading to significant economic damage, disruption of daily life, and threats to public safety. In this context, the innovative research conducted by Dehdehi, Soleimani-Motlagh, and Haghizadeh offers a critical evaluation and in-depth analysis of the factors influencing urban flooding using advanced hydrological modeling techniques. Their work employs the Soil Conservation Service – Technical Release 20 (SCS-TR20) model and the Sacramento Soil Moisture Accounting Unit Hydrograph (SBUH) model to unravel the complexities behind flood dynamics in urban environments.

The study begins by contextualizing the incidence of urban flooding within rapidly expanding metropolitan areas. Urban landscapes are characterized by an extensive network of roads, buildings, and other paved surfaces, significantly altering the natural water cycle by accelerating runoff and reducing infiltration. The authors argue that understanding these changes requires precise hydrological models capable of simulating surface runoff, infiltration, and subsurface flow processes under varying climatic and land use scenarios. Both SCS-TR20 and SBUH models boast comprehensive frameworks that may be tailored to urban catchments, enabling the dissection of hydrological responses to precipitation events with high spatial and temporal resolution.

Fundamental to their research is the exploration of how different physical and environmental factors affect urban flooding. These include soil properties, topography, storm characteristics, land use patterns, vegetation cover, and urban infrastructure design. The SCS-TR20 model, originally developed to estimate direct runoff from small watersheds, is applied here to quantify the runoff generation process by integrating rainfall data with land surface conditions. It incorporates parameters like curve number (CN), which reflects soil infiltration capacity and land cover, to predict peak discharge during storm events. This allows the researchers to examine how changes in impervious surface area or soil moisture status may intensify or mitigate runoff production in urban catchments.

Simultaneously, the study leverages the SBUH hydrological model, a unit hydrograph-based method that simulates watershed response to rainfall by accounting for soil moisture dynamics. The SBUH model provides a mechanistic representation of subsurface flow and its contribution to streamflow, which is often overlooked in simpler runoff generation models. By embedding soil moisture accounting within the urban context, the authors can capture delayed flow components and baseflow behavior, enriching the flood prediction process. This is particularly important in urban areas where drainage infrastructure can alter natural groundwater recharge pathways.

A critical component of their methodology involves calibrating and validating these models against observed hydrological data from urban watersheds experiencing recurrent flooding. The researchers emphasize rigorous parameter optimization to enhance predictive accuracy. They adopt techniques such as sensitivity analysis to identify which parameters most significantly influence model outputs, thereby guiding priorities for data collection and urban planning interventions. The models’ outputs are then cross-verified through statistical measures, including Nash-Sutcliffe efficiency and root mean square error, confirming their robustness in simulating runoff processes in real-world urban systems.

Their findings highlight that urban flooding is not solely dependent on rainfall intensity and volume but is profoundly affected by intricate interactions between soil characteristics, land cover changes, and urban drainage infrastructure. For instance, increasing impervious surfaces significantly raises the curve number, leading to more immediate and higher runoff peaks. Moreover, poor maintenance or design flaws in stormwater systems exacerbate flooding by reducing conveyance capacity. The study also reveals that antecedent soil moisture conditions before rainfall events play a pivotal role; saturated soils contribute to quicker runoff generation and potential flash floods, emphasizing the need for integrated urban water management that considers soil moisture dynamics.

The implications of this research extend to urban planners, environmental managers, and policymakers. By elucidating how specific landscape and infrastructure features influence flood risks, the models can inform the design of resilient urban drainage networks. Incorporating green infrastructure, such as permeable pavements, rain gardens, and bio-retention basins, can modulate runoff by enhancing infiltration and delaying peak flows, a strategy validated by simulation scenarios using their models. Additionally, the work supports the advancement of early warning systems that integrate hydrological forecasts with real-time rainfall data, offering communities proactive flood risk mitigation.

Significantly, the study advances the hydrological modeling field by adapting traditional models—initially designed for rural or agricultural catchments—to the complex hydrodynamics of urban settings. This adaptation includes customizing parameter sets to account for heterogeneity in urban land use, addressing issues such as localized flooding resulting from blocked drains or topographical depressions. The dual-model approach combining SCS-TR20 and SBUH affords a more comprehensive understanding than reliance on a single modeling framework, as it captures both surface and subsurface hydrological processes with greater fidelity.

Furthermore, the research contributes to global climate change discussions by considering how altered precipitation patterns may interact with urban factors to exacerbate flooding. The authors simulate future storm scenarios based on climate projections, revealing potential increases in flood frequency and severity if urban areas do not enhance their stormwater resilience. This evidence reinforces the urgency of integrating climate adaptation measures into urban development policies, underscoring the indispensable role of hydrological models in forecasting and managing emerging flood risks.

An additional innovative aspect of this study is the use of high-resolution spatial data and advanced computational techniques to implement the hydrological models. Remote sensing technologies and geographic information systems (GIS) are applied to delineate watershed boundaries, map land cover, and analyze slope and soil properties with great precision. The incorporation of these technologies allows for dynamic model updating and supports scenario testing for various urban growth and land use change possibilities. By utilizing such data-driven methods, the authors ensure that their flood impact analyses are both spatially relevant and temporally sensitive.

The multi-faceted modeling framework also evaluates the effectiveness of different flood mitigation strategies using scenario-based simulations. For example, the researchers model the impact of increasing urban green spaces or enhancing stormwater storage capacity on reducing flood peak discharge. These simulations provide actionable insights for urban engineers and policymakers by demonstrating which interventions yield the greatest reduction in flood risks under diverse weather conditions. Consequently, their work serves as a decision-support tool to prioritize resource allocation and infrastructure investments in flood-prone urban regions.

In summary, the comprehensive evaluation and analysis conducted by Dehdehi, Soleimani-Motlagh, and Haghizadeh signify a breakthrough in understanding urban flood dynamics through integrated hydrological modeling. By leveraging the strengths of SCS-TR20 and SBUH models, their study provides a nuanced depiction of how natural, built, and climatic factors coalesce to influence flooding in cities. These insights pave the way for smarter urban water management, resilience building against extreme weather events, and sustainable urban growth.

Looking forward, the authors advocate for further refinement of hydrological models through enhanced data assimilation and coupling with hydraulic simulations to address flooding at the street and neighborhood scales. They also suggest expanding their approach to encompass socio-economic dimensions, thereby assessing the human and economic impacts of flood events alongside hydrological predictions. Such interdisciplinary integration will be vital as urban flood challenges intensify in the face of urban expansion and climate variability.

Ultimately, this pioneering research not only enriches the theoretical hydrology landscape but also offers practical tools for urban flood mitigation worldwide. As cities grapple with the escalating frequency of intense storm events, such scientifically rigorous and technologically sophisticated studies provide a beacon for safeguarding populations, infrastructure, and ecosystems from the devastating consequences of urban flooding.

Subject of Research: Evaluation and analysis of factors affecting urban flooding through hydrological modeling.

Article Title: Evaluation and analysis of the impact of factors affecting urban flooding using SCS-TR20 and SBUH hydrological models.

Article References:
Dehdehi, N., Soleimani‑Motlagh, M. & Haghizadeh, A. Evaluation and analysis of the impact of factors affecting urban flooding using SCS-TR20 and SBUH hydrological models. Sci Rep (2026). https://doi.org/10.1038/s41598-026-58279-3

Image Credits: AI Generated