Search Results (10)

Hydrological modeling is essential for the sustainable management of watershed systems. Physically based models like MOHID-Land simulate soil water dynamics using Richards’ equation, parameterized through the van Genuchten–Mualem (VGM) model. Although the sensitivity of individual VGM parameters—residual water content (${\theta }_r$), saturated water content (${\theta }_s$), pore size distribution ($n$), inverse of air entry pressure ($\alpha$), and saturated hydraulic conductivity ($K_{sat}$)—is well documented, their combined effects remain underexplored. This study assessed both isolated and joint impacts of these parameters through a deterministic ±10% perturbation scheme, resulting in 31 unique parameter combinations. Model performance was evaluated using the Nash–Sutcliffe Efficiency (NSE) and Percent Bias (PBIAS). Full-parameter interaction achieved the best results (NSE = 0.50, PBIAS = 25.32), compared to the uncalibrated baseline (NSE = 0.01, PBIAS = 34.06). The pair ${\theta }_s$ and $n$ emerged as the most influential. Adding secondary parameters to this core pair yielded only marginal performance gains, while removing them from the full set caused similarly marginal declines. These findings reveal a hierarchical sensitivity structure, emphasizing ${\theta }_s$ and $n$ as key targets for calibration. Prioritizing this pair enables a more efficient soil calibration process, preserving model accuracy while reducing computational cost by limiting parameter space exploration. Full article

Recent studies have incorporated tidal elevation into hydrological models, yet they have not focused on simulating or evaluating tidal processes within these frameworks. Integrating tidal dynamics improves the representation of terrestrial–coastal interactions, including groundwater fluctuations, vegetation dynamics, and sediment transport. This study evaluates the capability of MOHID-Land, a physically based hydrological model, to simulate macro-tidal conditions in an Amazonian estuary. MOHID-Land enables tidal simulation by incorporating water-level time series as boundary conditions. A sensitivity analysis was conducted to (i) evaluate two global tidal models as boundary conditions; (ii) verify the impact of hydrological processes on water levels; and (iii) assess the effect of different bathymetries on water dynamics. The model effectively simulated tidal oscillations with good accuracy across eight tidal stations, although the inner stations required improved bathymetry. The Reference, Atmosphere, Porous Media and Vegetation (AtPmVg), and Finite Element Solution (FES) version 2014 (FES2014) simulations yielded similar water levels and goodness-of-fit metrics. While MOHID-Land is robust, and water level modeling is insensitive to meteorological, soil, or vegetation parameters, the model is highly sensitive to bathymetry. This study enhances the understanding of the applicability of hydrological models in terrestrial–coastal modeling. Full article

Soil controls water distribution, which is crucial for accurate hydrological modeling. MOHID-Land is a physically based, spatially distributed model that uses van Genuchten–Mualem (VGM) functions to calculate water content in porous media. The hydraulic soil parameters of VGM are dependent on soil type and are typically estimated from experimental data; however, they are often obtained using pedotransfer functions, which carry significant uncertainty. As a result, calibration is frequently required to account for both the natural spatial variability of soil and uncertainties estimation. This study focuses on a representative Atlantic Forest watershed. It assesses the sensitivity of channel flow to VGM parameters using a mathematical approach based on residuals derivative, aimed at enhancing soil calibration efficiency for MOHID-Land. The model’s performance significantly improved following calibration, considering only five parameters. The NSE improved from 0.16 on the base simulation to 0.53 after calibration. A sensitivity analysis indicated the curve adjustment parameter ($n$) as the most sensitive parameter, followed by saturated water content (${\theta }_s$) considering the 10% variation. Additionally, a combined change in ${\theta }_s$, $n$, residual water content (${\theta }_r$), curve adjustment parameter ($\alpha$), and saturated conductivity ($K_{sat}$) values by 10% significantly improves the model’s performance, by reducing channel flow peaks and increasing baseflow. Full article

Urban pluvial floods are the outcome of the incapacity of drainage systems to convey the runoff generated by intense rainfall events. Cities have been struggling to control such hazards due to several pressures, such as urbanization increase, more frequent experiences of extreme rainfall events, and increases in tide levels. Such pressures demand the study of adaptation strategies, which conventional one-dimensional drainage models fall short of simulating. Thus, 1D/2D models have been emerging with the aim of allowing better integration of key processes for flood modeling, namely, runoff interception by stormwater inlet devices and manhole overflows. The current paper presents a 1D/2D urban flood model based on an offline coupling procedure between the 1D model SWMM and the 2D model MOHID Land. The SWMM/Land model is applied to a synthetic street case study and to a real case study in downtown Albufeira, Portugal. The results obtained for the real case study are coherent with local observations of past flooding events, and the model shows potential for better decision-making regarding urban flood risk management. Full article

The coupling of coastal or regional ocean models to hydrological models or observed data is currently an uncommon practice in operational oceanography. Though hydrological models are regarded as a powerful and useful tool for estimating the quantity and quality of freshwater running in a watershed, they fail to provide accurate results for river flow reaching the coastal area due to water-management activities occurring within the river catchment, activities such as human consumption, irrigation, storage, etc. For this reason, many coastal and regional ocean models continue to impose surface zero-salinity discharges as land boundary conditions for representing such a dynamic boundary. Moreover, river flows are based in climatologies, thus neglecting seasonal and interannual variability. To achieve those objectives, this study proposes an integrated methodology ranging from watershed models to validation in the coastal area and passing through methods and proxies for integrating the freshwater flows into regional ocean models. The main objective of this study is to explore the results obtained by using more sophisticated land boundary conditions based on the capacities of state-of-the-art hydrologic models combined with observation networks. In addition to the evaluation of the source of river-flow data, this work also explores the use of estuarine proxies based on simple modelling grids. The estuarine proxies enable the incorporation of the mixing processes that take place in estuaries into the land fluxes and obtain the plume momentum. The watershed, estuarine proxies, and ocean were modelled using the MOHID Water modelling system and evaluated in western Iberia waters. The modelling results served to illustrate the sea surface salinity extension of the Western Iberia Buoyant Plume (WIBP) during an extreme event in March 2018. Full article

Hydrological modeling is nowadays critical for evaluating the status, past trends, and future perspectives of water availability at the global, regional, and local scales. The Iberian Peninsula is registering more frequent and severe droughts and water scarcity caused not only by extreme meteorological events, but also by increased demand for water for urban, industrial, and agricultural supplies. Better simulation models are thus needed for accurately quantifying the availability of local water resources. In this study, the natural flow regime in different watersheds of the Iberian Peninsula was simulated using the process-based, fully distributed, MOHID-Land model from 1979 to 2013. Streamflow results were compared with measurements at 73 hydrometric stations not influenced by reservoirs, and with the data available in the management plans of each hydrographic region. The results showed a high dispersion of the goodness-of-fit indicators, with the coefficient of determination (R²) ranging between 0 and 0.91, and the modeling efficiency (NSE) being higher than 0.35 at only 22 (calibration) and 28 (validation) hydrometric stations. Considering the scale of application, results were acceptable but evidenced the difficulties in simulating streamflow in watersheds using a coarse resolution. As such, this paper further deals with the difficulties and challenges of the adopted modeling approach. Nevertheless, this study constitutes a further step towards the more accurate assessment of water resources availability at the Iberian Peninsula scale using process-based modeling. Full article

The success of an irrigation decision support system (DSS) much depends on the reliability of the information provided to farmers. Remote sensing data can expectably help validate that information at the field scale. In this study, the MOHID-Land model, the core engine of the IrrigaSys DSS, was used to simulate the soil water balance in an irrigated vineyard located in southern Portugal during three growing seasons. Modeled actual basal crop coefficients and transpiration rates were then compared with the corresponding estimates derived from the normalized difference vegetation index (NDVI) computed from Sentinel-2 imagery. On one hand, the hydrological model was able to successfully estimate the soil water balance during the monitored seasons, exposing the need for improved irrigation schedules to minimize percolation losses. On the other hand, remote sensing products found correspondence with model outputs despite the conceptual differences between both approaches. With the necessary precautions, those products can be used to complement the information provided to farmers for irrigation of vine crop, further contributing to the regular validation of model estimates in the absence of field datasets. Full article

Hydrological models are increasingly used for studying watershed behavior and its response to past and future events. The main objective of this study was to conduct a sensitivity analysis of the MOHID-Land model and identify the most relevant parameters/processes influencing river flow generation. MOHID-Land is a complex, physically based, three-dimensional model used for catchment-scale applications. A reference simulation was implemented in the Ulla River watershed, northwestern Spain. The sensitivity analysis focused on sixteen parameters/processes influencing water dynamics at that scale. River flow generation was influenced by the resolution of the simulation grid, soil water infiltration, and crop evapotranspiration. Baseflow was affected by soil hydraulic properties, the depth of the soil profile, and the dimensions of the river cross-sections. Peak flows were mostly constrained by Manning’s coefficient in the river network, as well as the dimensions of the river cross-sections. The MOHID-Land model was then used to simulate daily streamflow during a 10-year period (2008−2017). Model simulations were compared against measured data at four hydrometric stations characterizing the natural flow regime of the Ulla River, resulting in coefficients of determination (R²) from 0.56 to 0.85; ratios of the standard deviation of the root mean square error to observation (RSR) between 0.4 and 0.67, and Nash and Sutcliffe model efficiency (NSE) values ranging from 0.55 to 0.84. The MOHID-Land model thus has the capacity to reproduce watershed behavior at a daily scale with reliable accuracy, constituting a powerful tool to improve water governance at the watershed scale. Full article

Hydrological modeling at the catchment scale requires the upscaling of many input parameters for better characterizing landscape heterogeneity, including soil, land use and climate variability. In this sense, remote sensing is often considered as a practical solution. This study aimed to access the impact of assimilation of leaf area index (LAI) data derived from Landsat 8 imagery on MOHID-Land’s simulations of the soil water balance and maize state variables (LAI, canopy height, aboveground dry biomass and yield). Data assimilation impacts on final model results were first assessed by comparing distinct modeling approaches to measured data. Then, the uncertainty related to assimilated LAI values was quantified on final model results using a Monte Carlo method. While LAI assimilation improved MOHID-Land’s estimates of the soil water balance and simulations of crop state variables during early stages, it was never sufficient to overcome the absence of a local calibrated crop dataset. Final model estimates further showed great uncertainty for LAI assimilated values during earlier crop stages, decreasing then with season reaching its end. Thus, while model simulations can be improved using LAI data assimilation, additional data sources should be considered for complementing crop parameterization. Full article

The southern Iberian Peninsula is characterized by evergreen oak woodlands (locally known as montado), which constitute an important savanna-type agro-silvo-pastoral ecosystem. This ecosystem is facing a progressive decline for several reasons, with the foremost being overgrazing. Better management tools are necessary to accurately quantify the systems’ carrying capacity and the sustainable stocking rates that prevent land degradation. The purpose of this study was to determine whether the MOHID-Land model could adequately simulate soil water dynamics and pasture growth in the montado ecosystem. The study area was located in the Alentejo region of southern Portugal. The model successfully simulated soil water contents and aboveground biomass during the 2010–2011 and 2011–2012 growing seasons, producing acceptable errors of the estimates (0.015 ≤ RMSE ≤ 0.026 cm³ cm⁻³; 279 ≤ RMSE ≤ 1286.5 kg ha⁻¹), and relatively high modeling efficiencies (0.481 ≤ EF ≤ 0.882). The model was further used to simulate the same variables for a longer period (1979/2009 seasons), to account for the effect of climate variability on model estimates. Water balance and dry biomass estimates were found to be significantly different between rainfed and irrigated pastures, as well as between the ten driest and ten wettest seasons, with the model responding well to climate variability. The results showed the potential of using the MOHID-Land model for improving pasture management in the montado ecosystem. Full article