Accurate areal rainfall estimation is essential for hydrological modeling and flood forecasting, yet method selection remains uncertain in small catchments with extremely sparse gauge networks. This event-scale study compared arithmetic mean (AM), Thiessen polygon (TP), inverse distance weighting (IDW), precipitation–elevation linear regression (ELR), multiple linear regression (MLR), and a multi-layer perceptron (MLP) in a 0.719 km2 catchment monitored by three gauges. Two complementary evaluations were conducted. Station-wise leave-one-out cross-validation (LOOCV) assessed prediction at an omitted gauge, whereas a radar-referenced comparison assessed catchment-average estimates obtained from the complete gauge network. MLR produced the lowest LOOCV error (RMSE = 0.433 mm; CC = 0.777). In the radar comparison, MLP and MLR produced nearly identical RMSE values of 0.668 and 0.669 mm, respectively, and are therefore interpreted as practically similar rather than meaningfully different. All method rankings are conditional on the selected 60 h event, the three-gauge arrangement, and uncertainty in the radar reference. The findings demonstrate that station-omission performance and full-network areal estimation address different operational questions and should be considered together when selecting an interpolation method for extremely sparse networks.
Hydrological modeling across heterogeneous watersheds remains a key challenge for water resource assessment in regions with strong hydroclimatic gradients. This study presents and evaluates the Chilean Hydrological Model for Climate Change (MHiDROC3) that integrates hydrometeorological and geospatial inputs, data imputation, sensitivity analysis, parameter calibration, distributed hydrological simulation, water-demand representation, and climate scenario analysis within a single workflow. MHiDROC3 was applied to five contrasting watersheds in south-central Chile over the 1980–2021 historical period. Across calibration, validation, and full-period simulations, KGE ranged from 0.51 to 0.77, while natural-streamflow simulations for the complete period showed KGE values of 0.52–0.74 and NSE values of 0.15 to 0.64, indicating variable model performance among basins. Mean simulated streamflow differed from observations by −32.2% to 17.7% across watersheds. Future simulations for 2022–2100 projected lower streamflow under SSP5–8.5 relative to SSP1–2.6, particularly during fall (−33.1% to −57.5%) and winter (−16.0% to −35.9%). By combining distributed process representation, demand effects, and climate-scenario testing in a Chilean framework, MHiDROC3 provides a practical basis for basin-specific water resource assessment, while its variable performance indicates that local evaluation remains necessary before operational application.
Structural uncertainty limits the reliability of conceptual hydrological models, yet the effect of pairing runoff-generation and routing structures remains poorly understood. We evaluated 46 models from the Modular Assessment of Rainfall–Runoff Models Toolbox (MARRMoT) in the Xunhe and Hanzhong catchments of the upper Han River Basin and recombined the modules of five representative models into 20 off-diagonal configurations. Validation KGE values for the 46 base models ranged from 0.166 to 0.806 in Xunhe and from 0.043 to 0.830 in Hanzhong. Only M58 and M60 improved KGE in both catchments: M58 increased KGE by 1.68% in Xunhe and 5.98% in Hanzhong, whereas M60 increased it by 5.05% and 3.72%, respectively. Most other recombinations preserved or reduced performance. The improved combinations retained contributions from runoff pathways with different response timescales and showed greater sensitivity to routing parameters; degraded combinations tended to be dominated by groundwater runoff and showed weak routing-parameter sensitivity. These convergent patterns provide indirect evidence that correspondence between runoff composition and routing response may influence recombined-model performance. Because structural compatibility was not measured directly and only two catchments were examined, the proposed relationship requires validation across broader hydroclimatic and structural settings.
Rivers are vulnerable to hydrometeorological and climatic pressures, while effective water resources management during low-flow season can be challenging. This paper studies the impacts of extreme hydrometeorological events and climate change on Greek rivers, and presents a framework for the incorporation of these pressures into the Program of Measures (PoMs) of the River Basin Management Plans (RBMPs) for the implementation of the Water Framework Directive 2000/60 (WFD). The final aim is the adaptation to drought and water scarcity. The proposed methodological approach incorporates a process-based model, climate change projections, drought indices and low-flow boundaries, so as to assess the impact of hydrometeorological and climatic pressures on the quantitative quality status of rivers. Then, the quantitative response of rivers under different predicted climate scenarios was examined. Based on the results, a water management plan was adopted and tested regarding its effectiveness, so as to promote evidence-based water strategies. Additionally, comprehensive measures and an operational scheme and adaptations actions for the mitigation of the hydrometeorological and climate related pressures in rivers of Greece were proposed. This operational framework is based on quantitative thresholds that trigger actions and measures for adaptation and can be used by decision-makers and stakeholders as guidelines for mitigation actions. The framework proposed was applied to the Spercheios river basin, which was selected as a demonstration site.
The reactive transport of hexavalent chromium (Cr(VI)) in anthropogenically disturbed sites (e.g., mine waste rock dumps, chromium salt industrial sites) is critically influenced by physico-chemical heterogeneity, yet the interplay between physical and chemical heterogeneities remains poorly understood. This study employed a series of experiments and numerical modeling to investigate the transport of Cr(VI), focusing on the implications of physical heterogeneity—represented by preferential flow paths—and chemical heterogeneity—characterized by reductive mineral lenses. Key findings indicate that physical heterogeneity accelerates Cr(VI) breakthrough by 1.4 to 2.1 pore volumes (PV) relative to homogeneous columns. The presence of pyrite lenses delays breakthrough by 0.6–1.2 PV under neutral pH and 1.6–2.0 PV under acidic pH. At a flow rate of 3.0 m/day, the apparent sorption capacity decreases by ~62.5% compared to 0.3 m/day, indicating that physical advection largely suppresses chemical retention under high-flux conditions. The above results demonstrate that physical heterogeneity governs flow paths and advection rates, whereas chemical heterogeneity impedes transport through heterogeneous adsorption and reduction in Cr(VI) to Cr(III) along these pathways. Furthermore, the presence of preferential paths leads to greater spatial variability, which subsequently influences the interaction dynamics between Cr(VI) and reactive minerals in the aqueous environment. The dominance shifts between physical/chemical controls based on flow rates and pH. At higher flow rates, the influence of physical heterogeneity becomes more pronounced, diminishing chemical reactions due to insufficient residence time of Cr(VI). Conversely, a lower pH environment enhances pyrite dissolution, which decouples the dependency on physical heterogeneity by promoting homogeneous reactions. Further evidence was obtained through X-ray photoelectron spectroscopy (XPS) analysis. The experimental observations are complemented by TOUGHREACT-based reactive transport simulations, which further reveal that the apparent dominance shifts arise from competing timescales between advection and surface reaction. The insights gained from the study emphasize the necessity of integrating both physical and chemical spatial variability in risk assessments, transport modeling, and designing targeted remediation strategies.
