Water Flow Model Research Articles

Transport characteristics of non-cohesive sediment with different hydrological durations and sediment transport formulas

River sediment transport is an important global environmental issue, for it leads to waterway sedimentation, ecological degradation, and river geomorphologic evolution, its quantification is of the highest importance for river and watershed management. However, it remains unclear what the applicability of different sediment transport formulas in sediment transport process, and what the characteristics of non-cohesive sediment transport processes with different hydrological durations. This study developed a two-dimensional (2D) surface water Flow Model (FM) coupled with a Sediment Transport (ST) model in the MIKE 21 modelling system. The characteristic difference on simulated non-cohesive sediment transport under different sediment concentrations, hydrological durations, and sediment transport formulas were quantified by calculating the bed load, suspended load, and bed level change. Results indicated that the bed load and suspended load using the Engelund and Fredsøe formula were significantly lower than the Van Rijn formula for individual rainfall simulation scenarios. With the increase in peak flow, both suspended load and bed load first increased and then decreased. In the long-term duration simulations, high sediment concentrations were accompanied by higher bed load and lower suspension load for the Engelund and Fredsøe formula, but by lower bed load and suspension load for the Van Rijn formula. The high sediment concentrations resulted in a higher erosion rate, and low sediment concentrations resulted in a higher deposition rate. The two formulas had a high degree of consistency in seasonality and the bed level changes in spring and summer were mainly sedimentary, while in autumn and winter they were mainly erosive. The Engelund and Fredsøe formula produced high riverbed erosion capacity at low discharge, but the Van Rijn formula had high erosion capacity at high discharge.

Small differences in root distributions allow resource niche partitioning.

Deep roots have long been thought to allow trees to coexist with shallow‐rooted grasses. However, data demonstrating how root distributions affect water uptake and niche partitioning are uncommon.We describe tree and grass root distributions using a depth‐specific tracer experiment six times over two years in a subtropical savanna, Kruger National Park, South Africa. These point‐in‐time measurements were then used in a soil water flow model to simulate continuous water uptake by depth and plant growth form (trees and grasses) across two growing seasons. This allowed estimates of the total amount of water a root distribution could absorb as well as the amount of water a root distribution could absorb in excess of the other rooting distribution (i.e., unique hydrological niche).Most active tree and grass roots were in shallow soils: The mean depth of water uptake was 22 cm for trees and 17 cm for grasses. Slightly deeper rooting distributions provided trees with 5% more soil water than the grasses in a drier season, but 13% less water in a wetter season. Small differences also provided each rooting distribution (tree or grass) with unique hydrological niches of 4 to 13 mm water.The effect of rooting distributions has long been inferred. By quantifying the depth and timing of water uptake, we demonstrated how even small differences in rooting distributions can provide plants with resource niches that can contribute to species coexistence. Differences in total water uptake and unique hydrological niche sizes were small in this system, but they indicated that tradeoffs in rooting strategies can be expected to contribute to tree and grass coexistence because 1) competitive advantages change over time and 2) plant growth forms always have access to a soil resource pool that is not available to the other plant growth form.

Numerical analysis of sensor-based flood-floor ebb-and-flow subirrigation system with saline water

ABSTRACT Ebb-and-flow is a well-known and common greenhouse irrigation system. In this paper, a specific numerical model for a sensor-based flood-floor ebb-and-flow irrigation system has been developed using one-dimensional Richards’ equation for water flow and two-site sorption advection-dispersion model for simulation of solute transport. The model was validated against analytical and numerical results proposed in the literature, and acceptable agreement was obtained in all cases. Maximum RMSE (MAE) was 0.053 m (0.273 m) for water flow and 0.021 (0.065) for solute transport. The model was then used for a parametric study of how different factors (such as salinity of irrigation water, triggering and cutoff thresholds, sensor position and flooding depth) would affect transpiration of sensor-equipped solitary pot under ebb-and-flow irrigation system for two different crops. It was revealed that sensor position and water salinity were significantly influential on transpiration of the pots. Finally, the synchronized sensor equipped-sensorless module of the numerical model was used to optimize the flood-floor ebb-and-flow irrigation system considering different factors using Taguchi approach. It was concluded that installing a water content sensor, whose triggering and cutoff thresholds were at −10 and −2 m, at the upper-half of the center-positioned pot would result in higher transpiration and lower unevenness of water distribution.

Modeling Water Flow and Phosphorus Sorption in a Soil Amended with Sewage Sludge and Olive Pomace as Compost or Biochar

Organic amendments are often reported to improve soil properties, promote plant growth, and improve crop yield. This study aimed to investigate the effects of the biochar and compost produced from sewage sludge and olive pomace on soil hydraulic properties, water flow, and P transport (i.e., sorption) using numerical modeling (HYDRUS-1D) applied to two soil types (Terra Rosa and Rendzina). Evaporation and leaching experiments on soil cores and repacked soil columns were performed to determine the soil water retention, hydraulic conductivity, P leaching potential, and P sorption capacity of these mixtures. In the majority of treatments, the soil water retention showed a small increase compared to the control soil. A reliable fit with the modified van Genuchten model was found, which was also confirmed by water flow modeling of leaching experiments (R2 0.99). The results showed a high P sorption in all the treatments (Kd 21.24 to 53.68 cm3 g−1), and a high model reliability when the inverse modeling procedure was used (R2 0.93–0.99). Overall, adding sewage sludge or olive pomace as compost or biochar improved the Terra Rosa and Rendzina water retention and did not increase the P mobility in these soils, proving to be a sustainable source of carbon and P-rich materials.

A 2D well-balanced, coupled model of water flow, sediment transport, and bed evolution based on unstructured grids with efficient variable storage strategy

In recent decades, a few Godunov-type, finite volume two-dimensional (2D) unstructured grid, coupled flow, and sediment models (GF2DUCM) have been developed for flows over erodible beds. These kinds of models are generally analyzed as a Vertex Model (VM) that define topography at the cell vertex, which can lead to the non-conservation of mass regarding flow, sediment, and bed evolution. Here, a full cell-cantered variable storage method (Central Model or CM) is applied as the solution of the GF2DUCM. In this method, terrain elevation is defined at the cell centroids; this accurately describes the physical relations between the water depth and topography deformation. This approach can fully eliminate calculation errors in topography deformation at local cells caused by the interpolation of topography deformation at the cell vertex, and reduced uncertainty in the computation of the GF2DUCM. The model performance is systematically tested using a series of laboratory experiments, which demonstrate the mass conservation feature and high accuracy in reproducing hydrodynamic and morphological processes.

Assessing the Impact of Chemical Loads from Agriculture Holdings on the Puck Bay Environment with the High-Resolution Ecosystem Model of the Puck Bay, Southern Baltic Sea

This paper describes the ecohydrodynamic predictive model EcoPuckBay—the ecosystem part—for assessing the state of the Puck Bay coastal environment and its ecosystem. We coupled the EcoPuckBay model with the land water flow models (Soil and Water Assessment Tool (SWAT) for surface water and Modflow for groundwater). To evaluate the quality of the results obtained from the EcoPuckBay model, a set of basic statistical measures for dissolved oxygen, chlorophyll-a, nitrates, and phosphates were calculated, such as mean, Pearson correlation coefficient (r), root-mean-square-error (RMSE), and standard deviation (STD). The analysis presented in this paper shows that the EcoPuckBay model produces reliable results. In addition, we developed a nutrient spread module to show the impact of agricultural activity on the waters of the Puck Bay. The EcoPuckBay model is also available in operational mode where users can access 60-h forecasts via the website of the WaterPUCK Project through the “Products” tab.

Rainfall Runoff and Dissolved Pollutant Transport Processes Over Idealized Urban Catchments

Urban stormwater runoff is often considered as one of the most significant contributors to water pollution. Particulates are commonly regarded as the primary form of pollutant transport in the urban environment, but the contribution from the dissolved pollutants can also be significant. This study aims to investigate the dissolved pollutant transport process over urban catchments, especially the effects of buildings and spatial distribution of pollutants. The concept of “exchange layer” has been adopted and an equation has been proposed to describe the release process of dissolved pollutant from the exchange layer to the runoff water. A horizontal two-dimensional water flow and pollutant transport model has been developed for predicting dissolved pollutant runoff based on the shallow water assumptions and the advection-diffusion equation. A series of laboratory experiments have been conducted to verify the proposed model. It has been demonstrated that both the rainfall runoff and the pollutant runoff can be predicted accurately. Buildings slow down the runoff and pollutant transport processes, especially when buildings are staggered. The non-uniform distribution of pollutants over the catchment greatly influences the pollutant transport process over the catchment. This work provides insight into the effects of buildings and initial pollutant distribution on the dissolved pollutant transport phenomenon, which can help better design the pollution mitigation strategies.

Mesoscopic method to study water flow in nanochannels with different wettability.

Molecular dynamics (MD) simulations is currently the most popular and credible tool to model water flow in nanoscale where the conventional continuum equations break down due to the dominance of fluid-surface interactions. However, current MD simulations are computationally challenging for the water flow in complex tube geometries or a network of nanopores, e.g., membrane, shale matrix, and aquaporins. We present a novel mesoscopic lattice Boltzmann method (LBM) for capturing fluctuated density distribution and a nonparabolic velocity profile of water flow through nanochannels. We incorporated molecular interactions between water and the solid inner wall into LBM formulations. Details of the molecular interactions were translated into true and apparent slippage, which were both correlated to the surface wettability, e.g., contact angle. Our proposed LBM was tested against 47 published cases of water flow through infinite-length nanochannels made of different materials and dimensions-flow rates as high as seven orders of magnitude when compared with predictions of the classical no-slip Hagen-Poiseuille (HP) flow. Using the developed LBM model, we also studied water flow through finite-length nanochannels with tube entrance and exit effects. Results were found to be in good agreement with 44 published finite-length cases in the literature. The proposed LBM model is nearly as accurate as MD simulations for a nanochannel, while being computationally efficient enough to allow implications for much larger and more complex geometrical nanostructures.

Two-dimensional numerical modelling of shallow water flows over multilayer movable beds

The two-dimensional modelling of shallow water flows over multi-sediment erodible beds is presented. A novel approach is developed for the treatment of multiple sediment types in morphodynamics. The governing equations include the two-dimensional shallow water equations for hydrodynamics, an Exner-type equation for morphodynamics, a two-dimensional transport equation for the suspended sediments, and a set of empirical equations for entrainment and deposition. Multilayer sedimentary beds are formed of different erodible soils with sediment properties and new exchange conditions between the bed layers are developed for the model. The coupled equations yield a hyperbolic system of balance laws with source terms. As a numerical solver for the system, we implement a fast finite volume characteristics method. The numerical fluxes are reconstructed using the method of characteristics which employs projection techniques. The proposed finite volume solver is simple to implement, satisfies the conservation property and can be used for two-dimensional sediment transport problems in non-homogeneous isotropic beds without need of complicated three-dimensional equations. To assess the performance of the proposed models, we present numerical results for a wide variety of shallow water flows over sedimentary layers. Comparisons to experimental data for dam-break problems over movable beds are also included in this study.

A Stable Radial Basis Function Partition of Unity Method with d-Rectangular Patches for Modelling Water Flow in Porous Media

Richards’ equation is used to describe water flow in porous media. It is strongly nonlinear, which makes the approximation of its solution a challenging task. In this study, we aim to linearize Richards’ equation using the exponential Gardner models of hydraulic conductivity and moisture content variables. Then, we propose a new formulation of radial basis function partition of unity method (RBFPUM) based on d-rectangular patches as local subdomains in order to approximate the solution of the linearized Richards’ equation. In particular, the multivariate weights are expressed as a product of one dimensional Wendland compactly supported radial basis functions. With small values of the shape parameter contained in the Gaussian radial basis function, safe computations of the solution will be achieved by adopting RBF-QR algorithm (Forenberg et al. in SIAM J Sci Comput 33(2):869–892, 2011). Hence, an efficient numerical solution can be obtained not only in terms of safe computations but also in terms of accuracy, as we will see in the numerical examples. In order to deal with layered soils, another method is proposed for the 2D and the 3D cases. It is based on the domain decomposition principle coupled with RBFPUM by using d-rectangular patches and the RBF-QR algorithm. The matching conditions, i.e. the continuity of mass fluxes and pressure head, are imposed at the interface between zones via the Steklov–Poincare equation. The efficiency of the proposed method will be examined via some examples.

Groundwater–Surface Water Interaction—Analytical Approach

Modelling of water flow in the hyporheic zone and calculations of water exchange between groundwater and surface waters are important issues in modern environmental research. The article presents the Analytical Hyporheic Flux approach (AHF) permitting calculation of the amount of water exchange in the hyporheic zone, including vertical water seepage through the streambed and horizontal seepage through river banks. The outcome of the model, namely water fluxes, is compared with the corresponding results from the numerical model SEEP2D and simple Darcy-type model. The errors of the AHF model, in a range of 11–16%, depend on the aspect ratio of water depth to river width, and the direction of the river–aquifer water exchange, i.e., drainage or infiltration. The AHF model errors are significantly lower compared to the often-used model based on vertical water seepage through the streambed described by Darcy’s law.

A gaussian process-based iterative Ensemble Kalman Filter for parameter estimation of unsaturated flow

Water flow in the unsaturated zone is an important component of the water cycle. Accurate estimation of soil hydraulic parameters ensures precise simulations of water flow in the unsaturated zone. In this study, a Gaussian Process-based Iterative Ensemble Kalman Filter method (GPIEnKF) is proposed and applied for estimating soil hydraulic parameters for two-dimensional soil water flow. The method involves a surrogate model for two-dimensional soil water flow that is based on the Gaussian Process method. The accuracy and efficiency of the GPIEnKF method are validated using two synthetic cases and a real dataset involving a field experiment with drip irrigation. The impact of the layout of observation points as well as the number of training base points and observation points on the estimation of parameters are also analyzed. The results show that the surrogate model can accurately predict pressure heads at observation points. The layout of observation points that precisely describes infiltration water movement allows the surrogate model to better emulate the original model, thereby improving the accuracy of parameter estimation. The number of training base points is found to have only a small influence on parameter estimation. The accuracy of parameter estimation and pressure head predictions can be further improved by increasing the number of observation points. However, the accuracy of predictions is affected by the uncertainty of boundary conditions and the soil spatial heterogeneity. The GPIEnKF method can effectively estimate multiple parameters characterizing water flow in layered soils. As compared with the standard Iterative Ensemble Kalman Filter, the GPIEnKF method can greatly improve computational efficiency while obtaining comparable results. The GPIEnKF method is an efficient tool for parameter estimation of multi-dimensional soil water flow.

Water-energy nexus and greenhouse gas–sulfur oxides embodied emissions of biomass supply and production system: A large scale analysis using combined life cycle and dynamic simulation approach

The achievement of low or zero greenhouse gas and particulate matter emissions such as sulfur oxides, optimized water-energy nexus, and a well-protected environment are challenges that have become increasingly significant for the biomass industry. There is a need to conduct evaluation and analyses of the greenhouse gas and particulate emissions, water use and energy consumption of biomass process and delivery, from “cradle to gate”. Therefore, to fill this noted gap in the literature, this study aims to develop a combined life cycle and dynamic simulation model to examine water-energynexus in the biomass industry, particularly under uncertainties, as well as estimation of greenhouse gas and particulate matter emissions of the biomass supply chain by 2050. The dynamic modelling of material, energy, and water flows was used to perform those tasks. An in-depth analysis of environmental issues during the production, processing, conversion and delivery of empty fruit bunches biomass supply and production system is conducted. The model was tested and implemented through a case study of three main biomass suppliers in Malaysia. Comparison of environmental performance of the production stages of 31 products through pre-processed, intermediate, and final productions in the biomass supply chain shows that bio-compost, activated-carbon, and cellulose are the highest water users and energy consumers as well as the highest emitters of greenhouse gas and sulfur oxides for all the three suppliers. Sensitivity analysis was also conducted for these critical products based on recent governmental land and demand policies. The main finding of this paper indicates a need for a well-planned management of water-energynexus in pre-processed production compared to intermediate and final production of biomass supply chain. This finding provides valuable insights to the government agencies and stakeholders to pursue sustainable bioenergy development strategies.

Generating Elevation Surface from a Single RGB Remotely Sensed Image Using Deep Learning

Generating Digital Elevation Models (DEM) from satellite imagery or other data sources constitutes an essential tool for a plethora of applications and disciplines, ranging from 3D flight planning and simulation, autonomous driving and satellite navigation, such as GPS, to modeling water flow, precision farming and forestry. The task of extracting this 3D geometry from a given surface hitherto requires a combination of appropriately collected corresponding samples and/or specialized equipment, as inferring the elevation from single image data is out of reach for contemporary approaches. On the other hand, Artificial Intelligence (AI) and Machine Learning (ML) algorithms have experienced unprecedented growth in recent years as they can extrapolate rules in a data-driven manner and retrieve convoluted, nonlinear one-to-one mappings, such as an approximate mapping from satellite imagery to DEMs. Therefore, we propose an end-to-end Deep Learning (DL) approach to construct this mapping and to generate an absolute or relative point cloud estimation of a DEM given a single RGB satellite (Sentinel-2 imagery in this work) or drone image. The model has been readily extended to incorporate available information from the non-visible electromagnetic spectrum. Unlike existing methods, we only exploit one image for the production of the elevation data, rendering our approach less restrictive and constrained, but suboptimal compared to them at the same time. Moreover, recent advances in software and hardware allow us to make the inference and the generation extremely fast, even on moderate hardware. We deploy Conditional Generative Adversarial networks (CGAN), which are the state-of-the-art approach to image-to-image translation. We expect our work to serve as a springboard for further development in this field and to foster the integration of such methods in the process of generating, updating and analyzing DEMs.

Development and evaluation of a water flow and solute transport model for furrow fertigation with surge flow

AbstractOne of the important factors in fertilizer application efficiency in surface fertigation is the shape of inflow hydrographs. In this research, a fertigation model is developed to analyse the effect of surge flow on furrow fertigation. Saint‐Venant equations and the advection–dispersion equation were used to estimate water flow and solute transport characteristics, respectively. The field experiments, including different fertigation treatments with surge flow, were conducted to calibrate and evaluate the developed model. Most of the water and nitrate losses occurred through runoff; water losses through runoff ranged from 13.8 to 33.4%, while fertilizer losses varied between 5.1 and 47%. Water and nitrate losses in the second fertigation experiments were higher than those in the first due to the reduction of the surge effect. A comparison between simulated and observed data shows appropriate accuracy of the developed model; the root mean squared error (RMSE) index for nitrate and water runoff losses was 8.4 and 12.1%, respectively. Fertigation during all advance surges was recognized as the desirable option in furrow irrigation with a surge flow. © 2020 John Wiley & Sons, Ltd.

Disentangling temporal and population variability in plant root water uptake from stable isotopic analysis: when rooting depth matters in labeling studies

Abstract. Isotopic labeling techniques have the potential to minimize the uncertainty of plant root water uptake (RWU) profiles estimated using multisource (statistical) modeling by artificially enhancing the soil water isotopic gradient. On the other end of the modeling continuum, physical models can account for hydrodynamic constraints to RWU if simultaneous soil and plant water status data are available. In this study, a population of tall fescue (Festuca arundinacea cv. Soni) was grown in amacro-rhizotron and monitored for a 34 h long period following the oxygen stable isotopic (18O) labeling of deep soil water. Aboveground variables included tiller and leaf water oxygen isotopic compositions (δtiller and δleaf, respectively) as well as leaf water potential (ψleaf), relative humidity, and transpiration rate. Belowground profiles of root length density (RLD), soil water content, and isotopic composition were also sampled. While there were strong correlations between hydraulic variables as well as between isotopic variables, the experimental results underlined the partial disconnect between the temporal dynamics of hydraulic and isotopic variables. In order to dissect the problem, we reproduced both types of observations with a one-dimensional physical model of water flow in the soil–plant domain for 60 different realistic RLD profiles. While simulated ψleaf followed clear temporal variations with small differences across plants, as if they were “onboard the same roller coaster”, simulated δtiller values within the plant population were rather heterogeneous (“swarm-like”) with relatively little temporal variation and a strong sensitivity to rooting depth. Thus, the physical model explained the discrepancy between isotopic and hydraulic observations: the variability captured by δtiller reflected the spatial heterogeneity in the rooting depth in the soil region influenced by the labeling and may not correlate with the temporal dynamics of ψleaf. In other words, ψleaf varied in time with transpiration rate, while δtiller varied across plants with rooting depth. For comparison purposes, a Bayesian statistical model was also used to simulate RWU. While it predicted relatively similar cumulative RWU profiles, the physical model could differentiate the spatial from the temporal dynamics of the isotopic composition. An important difference between the two types of RWU models was the ability of the physical model to simulate the occurrence of hydraulic lift in order to explain concomitant increases in the soil water content and the isotopic composition observed overnight above the soil labeling region.

Stable Algorithm Based On Lax-Friedrichs Scheme for Visual Simulation of Shallow Water

Many game applications require fluid flow visualization of shallow water, especially dam-break flow. A Shallow Water Equation (SWE) is a mathematical model of shallow water flow which can be used to compute the flow depth and velocity. We propose a stable algorithm for visualization of dam-break flow on flat and flat with bumps topography. We choose Lax-Friedrichs scheme as the numerical method for solving the SWE. Then, we investigate the consistency, stability, and convergence of the scheme. Finally, we transform the strategy into a visualization algorithm of SWE and analyze the complexity. The results of this paper are: 1) the Lax-Friedrichs scheme that is consistent and conditionally stable; furthermore, if the stability condition is satisfied, the scheme is convergent; 2) an algorithm to visualize flow depth and velocity which has complexity O(N) in each time iteration. We have applied the algorithm to flat and flat with bumps topography. According to visualization results, the numerical solution is very close to analytical solution in the case of flat topography. In the case of flat with bumps topography, the algorithm can visualize the dam-break flow and after a long time the numerical solution is very close to the analytical steady-state solution. Hence the proposed visualization algorithm is suitable for game applications containing flat with bumps environments.

Observation and Modeling of Low Saline Water Flow through Gulf of Mannar during December 2016

Anand, P.; Anubhav, C.A., and Albert, P.I., 2020. Observation and modeling of low saline water flow through Gulf of Mannar during December 2016. In: Sheela Nair, L.; Prakash, T.N.; Padmalal, D., and Kumar Seelam, J. (eds.), Oceanic and Coastal Processes of the Indian Seas. Journal of Coastal Research, Special Issue No. 89, pp. 20-25. Coconut Creek (Florida), ISSN 0749-0208.Indian Ocean is unique as it features the reversal of currents in relation to the monsoonal winds. During the north-east monsoon season (November-February), the East Indian Coastal Current (EICC) is known to flow round Srilanka into the South Eastern Arabian Sea (SEAS) which transports low saline waters from the Bay of Bengal (BoB). Till now, due to lack of observational data along the Gulf of Mannar (GoM), it is not evident, whether part of the water that flows from BoB is passing through the Palk Strait/Bay and GoM to reach SEAS. There are two schools of thought existing, one is that, the flow exists through this passage. Efforts have been made to prove this using simulation studies. The second thought is that the Pamban Pass as well as the Adam's Bridge act as barriers for this passage of water. To study the subject in detail, CTD observations during December 2016 along GoM and west coast of India are utilized. Analysis shows that, the surface waters along transect of GoM is lower in salinity (33 psu) than that of SEAS (34 psu) with the lowest surface salinity along the easternmost transect. Different case studies, carried out using high resolution (10 km) Princeton Ocean Model (POM), suggested that the flow exists through the GoM. The signature of low saline water (33.2 psu) in this region is also well matched with that of the observations. The study concludes that, the flow through the Palk Bay/Strait and GoM have a distinct role in bringing the water from the Bay to SEAS.

Numerical Simulation of River Inflows in Rijeka Bay Coastal Area

In this paper, a model of water flow in the Porto Baroš has been developed, which is the part of the Rijeka coastal area, for the purpose of its renovation and conversion. For numerical simulation purposes, the depth of the seabed of Port was previously performed, based on which the geometry and numerical domain of Port were made. By conducting the flow simulation, the analysis was carried out, after which the analyses of the conceptual solutions with the introduction of the pipe discharge were performed with the aim of reducing the water pollution of the Porto Baroš area. Port geometry will be made in commercial SMS software and numerical domains and simulations in OpenFOAM open-source software.

A 2D finite volume simulation tool to enable the assessment of combined hydrological and morphodynamical processes in mountain catchments

Nowadays, the great power of modern computers allows to develop computational models able to deal with simulations of several coupled phenomena over detailed complex topography. An efficient and properly calibrated computational model represents a useful tool to provide insight into the catchment dynamics at hydrological and geomorphological levels. In addition, it allows to develop detailed risk management and conservation plans. In this work, we present a coupled surface-groundwater distributed flow model with hydrological (rainfall and infiltration) and geomorphological (suspended and bed load sediment transport) components. The coupled model is applied to well characterized experimental catchments that are used as realistic test cases. The calibration of the water flow model response to rainfall is performed by means of the fitting to experimental outlet hydrographs of the results supplied by a coupled formulation of 2D Shallow Water Equations and 2D Darcy’s law for saturated porous media connected via suitable infiltration laws. The calibration of a suspended and bed load model is also addressed by means of the fitting to experimental outlet sedigraphs. The numerical results show a good agreement between numerical and observed hydrographs and sedigraphs, significantly improving previous published simulations. Additionally, the need to repeat the simulations in the calibration processes is no longer an unapproachable problem.