Water Interactions Research Articles

Modeling and Nonlinear Analysis of Plant–Soil Moisture Interactions for Sustainable Land Management: Insights for Desertification Mitigation

This research explores the dynamics of vegetation patterns under changing environmental conditions, considering the United Nations Sustainable Development Goal 15: “Protect, restore, and promote the sustainable use of terrestrial ecosystems; combat desertification; halt and reverse land degradation; and prevent biodiversity loss.” In this context, this study presents a modeling and nonlinear analysis framework for plant–soil-moisture interactions, including Holling-II functional response and hyperbolic mortality models. The primary goal is to explore how nonlinear soil–water interactions influence vegetation patterns in semi-arid ecosystems. Moreover, the influence of nonlinear soil–water interaction on the establishment of population patterns is investigated. The formation and evolution of these patterns are explored using theoretical analysis and numerical simulations, as well as important factors and critical thresholds. These insights are crucial for addressing desertification, a key challenge in semi-arid regions that threatens biodiversity, ecosystem services, and sustainable land management. The model, which includes environmental parameters such as rainfall, plant growth rates, and soil moisture, was tested using both theoretical analysis and numerical simulations. These characteristics are carefully adjusted to find important thresholds influencing the danger of desertification. Simulation scenarios, run under set initial conditions and varying parameters, yield useful insights into the pattern of patch development under dynamically changing environmental conditions. The findings revealed that changes in environmental conditions, such as rainfall and plant growth rates, prompted Hopf bifurcation, resulting in the production of three distinct patterns: a dotted pattern, a striped pattern, and a combination of both. The creation of these patterns provides essential information about the sustainability of environmental equilibrium. The variation curve of the average plant biomass reveals that the biomass fluctuates around a constant period, with the amplitude initially increasing, then decreasing, and gradually stabilizing. This research provides a solid foundation for addressing desertification risks, using water resources responsibly, and contributing to a better understanding of ecosystem stability.

Use of a groundwater model to evaluate groundwater–surface water interaction at a riverbank filtration site: a case study in Binh Dinh, Vietnam

A comprehensive understanding of groundwater–surface water (GW–SW) interaction is important for sustainable water resource management. Riverbank filtration (RBF) serves as a natural method to enhance groundwater recharge, especially in systems where surface water and groundwater are closely connected. Thus, RBF is a feasible option for water management particularly in regions dealing with water scarcity and overexploitation of groundwater. This study investigated GW–SW interaction at a well-field next to the Dai An River in Phu Cat district, Binh Dinh province, Vietnam, with the primary goal of evaluating the feasibility of RBF for water supply at this site. Using FEFLOW 7 software, numerical modelling was conducted to simulate groundwater flow and estimate groundwater recharge rates from riverbank filtration during wet and dry seasons. The model incorporated key aquifer parameters, including hydraulic conductivity and porosity. Additionally, stable (water) isotope analysis of hydrogen (δ2H) and oxygen (δ18O) was performed to trace GW–SW interaction. The modelling results demonstrated that approximately 72% of total groundwater recharge came from riverbank filtration, confirming a strong hydraulic connection between the river and the aquifer. Stable isotope analysis revealed seasonality in mixing rates, with the surface water contribution to the aquifer ranging from 2% during the dry season up to 54% during the wet season. The travel time from the riverbank to the nearest abstraction well was estimated to be less than 3 days. These findings contribute to understanding of GW–SW interaction in the region and also offer general guidance for optimizing well placement and sustainable groundwater extraction practices.

Application of a Random Forest Method to Estimate the Water Use Efficiency on the Qinghai Tibetan Plateau During the 1982–2018 Growing Season

Water use efficiency (WUE) reflects the quantitative relationship between vegetation gross primary productivity (GPP) and surface evapotranspiration (ET), serving as a crucial indicator for assessing the coupling of carbon and water cycles in ecosystems. As a sensitive region to climate change, the Qinghai Tibetan Plateau’s WUE dynamics are of significant scientific interest for understanding carbon water interactions and forecasting future climate trends. However, due to the scarcity of observational data and the unique environmental conditions of the plateau, existing studies show substantial errors in GPP simulation accuracy and considerable discrepancies in ET outputs from different models, leading to uncertainties in current WUE estimates. This study addresses these gaps by first employing a machine learning approach (random forest) to integrate observed GPP flux data with multi-source environmental information, developing a predictive model capable of accurately simulating GPP in the Qinghai Tibetan Plateau (QTP). The accuracy of the random forest simulation results, RF_GPP (R2 = 0.611, RMSE = 69.162 gC·m−2·month−1), is higher than that of the multiple linear regression model, regGPP (R2 = 0.429, RMSE = 86.578 gC·m−2·month−1), and significantly better than the accuracy of the GLASS product, GLASS_GPP (R2 = 0.360, RMSE = 91.764 gC·m−2·month−1). Subsequently, based on observed ET flux data, we quantitatively evaluate ET products from various models and construct a multiple regression model that integrates these products. The accuracy of REG_ET, obtained by integrating five ET products using a multiple linear regression model (R2 = 0.601, RMSE = 21.04 mm·month−1), is higher than that of the product derived through mean processing, MEAN_ET (R2 = 0.591, RMSE = 25.641 mm·month−1). Finally, using the optimized GPP and ET data, we calculate the WUE during the growing season from 1982 to 2018 and analyze its spatiotemporal evolution. In this study, GPP and ET were optimized based on flux observation data, thereby enhancing the estimation accuracy of WUE. On this basis, the interannual variation of WUE was analyzed, providing a data foundation for studying carbon water coupling in QTP ecosystems and supporting the formulation of policies for ecological construction and water resource management in the future.

Green water loads on prismatic obstacles

Green water loads on prismatic obstacles (representing topside structures) mounted on the raised deck of a simplified vessel are investigated using computational fluid dynamics simulations and physical model testing with emphasis on examining different structure shapes, orientation angles and relative structure size. For each scenario investigated, several flow features are identified that characterize the green water interaction with the structure and influence loads, namely delayed flow diversion, formation of a vertical jet, scattered wave formation and the development of complex wake patterns. Comparing across structures, these interactions are more pronounced for blunt objects, and the associated force impulse is larger. For example, a cube with flow at normal incidence is found to experience approximately twice the force impulse of a circular cylinder of the same projected area. Equally, rotation of the cube leads to reduced run-up height and streamwise force on the structure. To explain these trends, a theoretical model based on Newtonian flow theory is adopted. This model provides an estimate of the streamwise force exerted on obstacles in high-Froude-number flows and shows good agreement with the numerical results when the flow is supercritical, shallow (small water depth relative to structure width) and the structure is tall (large structure height relative to water depth). Despite some limitations, the model should provide an efficient force prediction tool for practical use in design.

Intrinsic Mechanisms of Differences in Wetting-Induced Deformation of Soils on Chinese Loess Plateau: Insights into Land Stability and Sustainable Management

Wetting-induced soil deformation significantly impacts land stability and management on the Chinese Loess Plateau. This study analyzed silt soils from the Late Pleistocene (1 m depth) and Middle Pleistocene (25 m depth) to investigate compression and collapsible deformation during wetting. The compression in both soils progressed through three stages: slow deformation under low pressure, accelerated deformation under moderate pressure, and decelerated deformation under high pressure. Wetting intensified the compression in the 1 m sample but reduced it in the 25 m sample, with the deformation becoming more sensitive to the initial water content under higher pressures. Collapse tests showed contrasting behaviors: the 1 m sample exhibited collapsibility, while the 25 m sample displayed expansiveness (a negative collapsibility coefficient). Microstructural analysis revealed that the 1 m sample with abundant macropores and overhead structures had a lower structural stability than the 25 sample with more stable, rounded micropores. The wetting-induced deformation was governed by the balance between clay mineral expansion and structural collapse, with collapsibility prevailing when collapse dominated and expansiveness prevailing when expansion was predominant. These findings provide valuable insights into soil–water interactions and support improved land use and management strategies in the loess region.

Insight into the relationship between cell wall, intracellular starch structure and physicochemical properties of cassava cells from cassava varieties.

Cassava cell flour can expand the food industrial availability of cassava resources. In this study, cassava cells were isolated from eight cassava varieties to analyze the composition, structure, and physicochemical properties. The smaller particle size in CS4 led to the lowest swelling power and viscosity, which further reduced the modulus (G', G") and shear stress of the cassava cell gel. The higher starch content in CS3 and CS8 (88.86%, 87.99%) increased the swelling and solubility of the cells, resulting in high viscosity and gel strength. Thicker cell walls presented a higher content of cell wall polysaccharides, hindering the interaction of water, heat, and digestive enzymes with intracellular starch, leading to higher gelatinization temperatures and lower digestion rates. In addition, the B1 chain promoted the formation of the starch crystalline region and increased the gelatinization temperature and enthalpy of cell flour. Based on cluster analysis and correlation analysis, the differences in the functional properties of cassava cell flour were related to cell components, morphology, and intracellular starch structure. The study provided a theoretical basis for the application of cassava cells in the food industry.

Forcing agents lead to changes in the groundwater-surface water interaction of a semi-arid maar lake

Forcing agents lead to changes in the groundwater-surface water interaction of a semi-arid maar lake

Exploring the Effects of Light–Water Interaction in Plant Factory to Improve the Yield and Quality of Panax notoginseng (Burkill) F. H. Chen

Exploring the Effects of Light–Water Interaction in Plant Factory to Improve the Yield and Quality of Panax notoginseng (Burkill) F. H. Chen

An investigation into the influence of climate extreme on groundwater regimes and human health in the Periyar Basin: a fast growing urban centre in India

ABSTRACT A total of 212 groundwater samples were collected during North East Monsoon (NEM), South West Monsoon (SWM), Pre-Monsoon (PREM), and Post-Monsoon (POM) seasons of 2020–2021 from the Periyar River Basin, draining the south western flanks of Western Ghats. The analytical results revealed the order of abundance of cations as Ca2+ > Na+ > Mg2+ > K+ and anions in the order of HCO3− > Cl− > SO42− > NO3− for all seasons. The major hydrochemical facies identified were CaHCO3 and mixed Ca–Mg–Cl in all the seasons with rock–water interaction as the key process regulating water chemistry. Ionic ratios of Ca2+ + Mg2+/Na+ + K+ and Ca2+/Mg2+ suggested significant effect of silicate minerals and other sources. The Water Quality Index (WQI) shows that the majority of the samples, namely, 98% in NEM, 86% in POM, 82% in PREM, and 95% in MON, fall in the categories ranging from excellent to good for drinking purposes. Furthermore, the health risk assessment based on carcinogenic and non-carcinogenic risk of the United States Environmental Protection Agency (US EPA) during monsoon and non-monsoon seasons for adults and children revealed the potential risk posed by Pb via oral exposure in the study area suggesting children are more susceptible to the damaging effects than adults.

A Comprehensive Review of Riverbank Filtration Technology for Water Treatment

Riverbank filtration (RBF) technology has been applied and investigated worldwide for water supplies due to its sustainable water quantity guarantee and reliable quality improvement. In this work, the development history, application status, research progress, and technical overview of RBF are reviewed and summarized. RBF usually uses rivers, lakes, and groundwater as raw water, with a few cases using seawater. Nitrogen removal in RBF systems primarily occurs through key geochemical processes such as adsorption, denitrification, organic nitrogen mineralization, and dissimilatory nitrate reduction to ammonium (DNRA). For the attenuation of emerging contaminants in groundwater environments, key processes such as filtration, adsorption, and biotransformation play a crucial role, and microorganisms are essential. Based on a discussion of the advantages and disadvantages, we proposed the research prospects of RBF. To further enhance the water-supply safety and security with RBF, the mechanisms of surface water and groundwater interaction, pollutant removal, and blockage; the impact of capturing surface water on the stability of river ecosystems; and the coupling and synergistic effect of RBF with other water treatment technologies should be deeply investigated.

Effect of moisture change on water retention behavior of unsaturated silty soil under loading–unloading conditions

Earthen embankments either natural or constructed artificially often comprise of unsaturated soils being considered stronger in terms of compressibility and permeability. However, the internal nomenclature of unsaturated soils due to the presence of air, water, and soil particles makes it more complex while such soils interact with moisture under the circumstances of applied stress history during the earthen structure’s life span. To investigate this behavior, this study is designed to understand the soil–water interaction and quantify the retention behavior during loading and unloading conditions. To serve this idea, custom-designed static compaction tests were carried out under un-drained water and drained air conditions at the applied stress history. The results show application of loading and unloading cycles impact water retention behavior of soil with varying soil water contents. During the initial stages of the loading process, suction increases with decreasing void ratio due to the heterogeneous distribution of water in the soil. However, there is a unique increasing trend in suction at the reloading or wetting phases of the water retention curve for all moisture contents. To examine the impact on the void ratio, the experimental data have been compared with the selected model incorporating suction, void ratio, and degree of saturation for prediction of soil water retention behaviors. The model prediction deviates from the experimental data and shifts away from the model prediction indicating that the loading–unloading sequence coupled with the variation in moisture does affect the soil behavior.

Hydration Effects Driving Network Remodeling in Hydrogels during Cyclic Loading.

In complex networks and fluids such as the extracellular matrix, the mechanical properties are substantially affected by the movement of polymers both part of and entrapped in the network. As many cells are sensitive to the mechanical remodeling of their surroundings, it is important to appreciate how entrapped polymers may inhibit or facilitate remodeling in the network. Here, we explore a molecular-level understanding of network remodeling in a complex hydrogel environment through successive compressive loading and the role that noninteracting polymers may play in a dynamic network. We find that this is a highly localized and time-dependent effect, with one of the major driving factors of hydrogel matrix remodeling the interaction and movement of water within the network in calcium-cross-linked alginate. Our results suggest a more general mechanistic understanding of hydrogel remodeling, with implications for tissue transformations in disease, biomaterials, and food science formulation.

Unraveling the Role of Water in Isothermal Methanol Partial Oxidation to Methyl Formate on Gold: A Combined Experimental and Computational Study.

Since water is both a product and a common reactant impurity in the (partial) methanol oxidation to methyl formate (MeFo) on gold, its effect on the isothermal selectivity to methyl formate was investigated under well-defined single-collision conditions employing pulsed molecular beam experiments and in situ IRAS measurements. Both a flat Au(111) and a stepped Au(332) surface were used as model catalysts to elucidate how water affects the reactivity of low-coordinated step sites as compared to (111) terrace sites employing a range of reaction conditions. The interactions of water with methanol/methoxy as well as with oxygen species are addressed. Theoretical calculations, including static DFT and ab initio molecular dynamics (AIMD) simulations, are employed to enhance the microscopic understanding of water-induced changes in the oxygen species and overoxidation reactivity on gold, which are essential for the selectivity. The results provide not only information on conditions that mitigate the generally negative effect of water on methyl formate formation but also atomic-level insights into water-induced changes in the complex reaction network that governs the reactivity in applied gold catalysts, such as nanoporous gold.

Investigating stone materials from some European cultural heritage sites for predicting future decay

Abstract The preservation of Europe’s stone-built heritage is crucial for safeguarding our cultural legacy. This study investigates twelve distinct stones used in historical monuments across Italy, Spain, Greece, and Norway, including marbles (Carrara and Macael), limestones (Botticino, Red Verona, Costozza, Istrian, Sfouggaria, Santa Pudia), a carbonate-dominated sandstone (Lartios), volcanic rocks (Euganean trachyte and Tønsberg latite), and an intrusive igneous rock (Tønsbergite). Through comprehensive analysis of mineralogical composition, porosity, water interactions, and accelerated ageing tests, this research establishes a framework for assessing these materials susceptibility to decay mechanisms. The results demonstrate significant variability in durability and decay response among the stone types, primarily determined by pore abundance and distribution. This study enhances the understanding of stone materials behaviour under stressed conditions, offering valuable insights for mitigating future decay processes and protecting European cultural heritage. The stones examined were chosen for their significant presence at the four pilot sites of the European Hyperion project: Venice (Italy), Granada (Spain), Rhodes (Greece), and Tønsberg (Norway). Graphic abstract

Capturing the Effect of Anion Type on the Intermolecular Interactions between Water and Imidazolium-Based Ionic Liquids: A Comparative DFT Study.

The studies on ionic liquids (ILs) and their interaction with different solvents have always been an interesting topic for experimental and computational chemists. Recently, however, deep insights on the molecular structures of the IL-water binary mixtures have been mainly performed through classical simulations. Here, a comprehensive quantum mechanical study is presented on seven 1-butyl-3-methylimidazolium-based ILs in the absence and presence of water. As the most important intermolecular interaction between ionic moieties of ILs and water molecules, hydrogen bonding is studied through different bonding analyses. The effect of different anions, [NO3]-, [HSO4]-, [SCN]-, [DCA]-, [BF4]-, [PF6]-, and [NTf2]-, on the behavior of ILs interacting with a sample of water molecules is investigated. Comparing the implicit and explicit approaches to consider water solvent indicated that the structure of ILs in the solvent depends on the selected solvent model. By considering explicit water molecules, we analyzed the intermolecular interactions between ILs and the water sample. The energy decomposition analysis indicated that the stability of the IL···water systems is mainly due to the electrostatic component of the total interaction energy. The interaction region indicator (IRI) analysis discovered that chemical bond and van der Waals (vdW) interactions are important in the IL···water systems. Indeed, investigation of each ion/ion pair surrounded by ten nearest neighbor water molecules discovered that the vdW interactions are responsible for the cation···anion and the cation···water interactions, while chemical bonding is important in the anion···water and the water···water interactions. Therefore, the anion···water interaction requires further analysis. The quantum theory of atoms in molecules verified the ionic nature of the H-bond in the anion···water interaction. The IRI analysis showed that the interaction between water molecules and cyano-based anions, [SCN]- and [DCA]-, is only due to chemical bonding, while in the oxygenated anions, [NO3]- and [HSO4]-, the vdW forces are also important. For the other anions, [BF4]-, [PF6]-, and [NTf2]-, the vdW forces have the main contribution in the anion···water interaction. Natural bond orbital analysis indicated that these intermolecular interactions originate from nanion → σO-H* electron transfer. Finally, the law of matching water affinity (LMWA) using energy-based parameters was used to predict the hydrophilicity of ILs as follows: [BMIM][NO3] > [BMIM][SCN] > [BMIM][DCA] > [BMIM][HSO4] > [BMIM][BF4] > [BMIM][NTf2] > [BMIM][PF6]. Results obtained in the current work give insights into the electronic nature of intermolecular interactions between ILs and water molecules, which is necessary due to importance of water in modifying properties of ILs in various applications.

Strong Hydrophobic Interaction of High Molecular Weight Chitosan in Aqueous Solution.

Chitosan is a versatile bioactive polysaccharide in various industries, such as pharmaceuticals and environmental applications, owing to its abundance, biodegradability, biocompatibility, and antibacterial properties. To effectively harness its potential for various purposes, it is crucial to understand the mechanisms of its interaction in water. This study investigates the interactions between high molecular weight (HMW, >150 kDa) chitosan and four different functionalized self-assembled monolayers (SAMs) at three different pHs (3.0, 6.5, and 8.5) using a surface forces apparatus (SFA). We report that HMW chitosan exhibits the strongest adhesion to methyl-terminated SAM (CH3-SAM) at all pHs, showing potential for strong hydrophobic interactions against other molecules containing hydrophobic moieties. Noting that hydrogen bonding has been considered the dominating interaction mechanism of chitosan, the consequence of this study provides valuable insights into its applications in developing chitosan-based eco-friendly materials.

Assessing the Riparian Squeeze in the Greater Bay Area based on multisource data

ABSTRACT Riparian zones provide critical services for human societies and ecological systems, yet rapid urban expansion exerts substantial pressure on these interfaces, leading to global-scale consequences including biodiversity loss, pollution, water supply stress, and escalated flood risks. To address the imperative of assessing human–water interactions in urban environments, this study introduces the Riparian Squeeze Index (RSI) framework. Using the Greater Bay Area as a case study, we developed a multi-dimensional measurement system that integrates spatial distances between waterbodies and infrastructure with demographic, economic, and environmental metrics. Analysis of 392,583 sample points revealed a median distance of 55.13 m between waterbodies and nearby infrastructure, with significant spatial heterogeneity across the region. While riparian zones occupy 37% of the total area, they contain 57% of points of interest and 59% of the population, demonstrating concentrated human activity near waterbodies. The RSI results indicate a development-vulnerability paradox where less-developed cities show higher socioeconomic vulnerabilities despite lower spatial pressure. This research provides a standardized tool for evaluating human pressure on riparian zones across diverse geographical contexts, offering valuable insights for sustainable urban planning and water resource management. The framework's adaptability makes it applicable for similar assessments in other urban agglomerations worldwide.

Exploration of linear and interpretable models for quantification of cell parameters via contactless short-wave infrared hyperspectral sensing

The development of optical sensors for label-free quantification of cell parameters has numerous uses in the biomedical arena. However, using current optical probes requires the laborious collection of sufficiently large datasets that can be used to calibrate optical probe signals to true metabolite concentrations. Further, most practitioners find it difficult to confidently adapt black box chemometric models that are difficult to troubleshoot in high-stakes applications such as biopharmaceutical manufacturing. Replacing optical probes with contactless short-wave infrared (SWIR) hyperspectral cameras allows efficient collection of thousands of absorption signals in a handful of images. This high repetition allows for effective denoising of each spectrum, so interpretable linear models can quantify metabolites. To illustrate, an interpretable linear model called L-SLR is trained using small datasets obtained with a SWIR HSI camera to quantify fructose, viable cell density (VCD), glucose, and lactate. The performance of this model is also compared to other existing linear models, namely Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF). Using only 50% of the dataset for training, reasonable test performance of mean absolute error (MAE) and correlations (r2) are achieved for glucose (r2 = 0.88, MAE = 37 mg/dL), lactate (r2 = 0.93, MAE = 15.08 mg/dL), and VCD (r2 = 0.81, MAE = 8.6 × 105 cells/mL). Further, these models are also able to handle quantification of a metabolite like fructose in the presence of high background concentration of similar metabolite with almost identical chemical interactions in water like glucose. The model achieves reasonable quantification performance for large fructose level (100–1000 mg/dL) quantification (r2 = 0.92, MAE = 25.1 mg/dL) and small fructose level (< 60 mg/dL) concentrations (r2 = 0.85, MAE = 4.97 mg/dL) in complex media like Fetal Bovine Serum (FBS). Finally, the model provides sparse interpretable weight matrices that hint at the underlying solution changes that correlate to each cell parameter prediction.

Quantifying the potential of using Soil Moisture Active Passive (SMAP) soil moisture variability to predict subsurface water dynamics

Abstract. Advances in satellite Earth observation have opened up new opportunities for global monitoring of soil moisture (SM) at fine to medium resolution, but satellite remote sensing can only measure the near-surface soil moisture (SSM). As such, it is critically important to examine the potential of satellite SSM measurements to derive the water resource variations in deeper subsurface. This study compares the SSM variability captured by the Soil Moisture Active and Passive (SMAP) satellite and the Soil Water Index (SWI) derived from SMAP SSM with subsurface SM and groundwater (GW) dynamics simulated by a high-resolution fully integrated surface water–groundwater model over an agriculturally dominated watershed in eastern Canada across two spatial scales, namely SMAP product grid (9 km) and watershed (∼4000 km2). SMAP measurements compare well with the hydrologic simulations in terms of SSM variability at both scales. Simulated subsurface SM and GW storage show lagged and smoother characteristics relative to SMAP SSM variability with an optimal delay of ∼1 d for the 25–50 cm SM, ∼6 d for the 50–100 cm SM, and ∼11 d for the GW storage for both scales. Modeled subsurface SM dynamics agree well with the SWI derived from SMAP SSM using the classic characteristic time lengths (15 d for the 0–25 cm layer and 20 d for the 0–100 cm layer). The simulated GW storage showed a slightly delayed variation relative to the derived SWI. The quantified optimal characteristic time length Topt for SWI estimation (by matching the variations in SMAP-derived SWI and modeled root zone SM) is comparable to Topt obtained in other agricultural regions around the world. This work demonstrates SMAP SM measurements as a potentially useful aid when predicting root zone SM and GW dynamics and validating fully integrated hydrologic models across different spatial scales. This study also provides insights into the dynamics of near-surface–subsurface water interaction and the capabilities and approaches of satellite-based SM monitoring and high-resolution fully integrated hydrologic modeling.

The Addition of Pumpkin Flour Impacts the Functional and Bioactive Properties of Soft Wheat Composite Flour Blends.

Growing interest in functional food ingredients has led to the exploration of pumpkin flour as a nutritional enhancer in wheat-based products. This study investigated the impact of pumpkin flour incorporation (0-20%) on soft wheat flour blends' technological and bioactive properties. The comprehensive analysis included granulometric distribution, techno-functional properties (WHC, WAC, WAI, WSI, SP, OAC), pasting characteristics (RVA), gel texture (TPA), rheological behaviour (frequency sweeps), colour parameters, and bioactive compounds (TPC, DPPH, ABTS) in both water and ethanol extracts. Pumpkin flour addition systematically modified blend properties, with higher fine particle content (13.26% < 80 μm), enhancing water interaction capabilities (WHC increased from 2.52 to 3.56). Pasting behaviour showed reduced peak viscosity (2444.0 mPa·s to 1859.5 mPa·s) but enhanced gel structure stability, evidenced by increased storage modulus (112.7 Pa to 1151.0 Pa) and reduced frequency dependence. Colour parameters showed progressive darkening (L* 91.00 to 84.28) and increased yellow-orange intensity (b* 10.13 to 27.13). Bioactive properties improved significantly, with TPC increasing up to 0.57 mg/1 g DM and 0.34 GAE mg/1 g DM in water and ethanol extracts, respectively, accompanied by enhanced antioxidant activity. Pumpkin flour incorporation successfully enhanced both functional and bioactive properties of wheat flour blends, with particle size distribution and water interactions serving as fundamental determinants of technological functionality, while contributing to improved nutritional value through increased bioactive compounds.