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Rainfall-runoff simulations are increasingly being performed with physically-based and spatially distributed solvers. The current computational and numerical technology enables the use of full shallow water equations solvers to be applied for these type of flow problems. Nonetheless, Zero-Inertia (diffusive wave) solvers have been historically favoured due to their conceptual and mathematical simplicity in comparison to shallow water solvers, with the working assumption that the simplifications introduced by Zero-Inertia will have some assumable impact on accuracy but will also allow for computational efficiency. Since both types of solvers have been primarily developed, benchmarked and compared to each other for fluvial and floodplain simulations, it is relevant to assess t-he relative performance for rainfall-runoff problems. In this work, both solvers are applied to a set of six well known test cases with reference solutions. The performance of the solvers is assessed in terms of global signatures such as hydrographs and flooded areas, but also in terms of spatial distributions of depth and velocity, as well as computational cost. Furthermore, the comparisons are performed across different spatial resolutions. The results show that for rainfall-runoff problems explicit, finite volumes solvers for both equations provide a similar accuracy, but the shallow water solver requires less computational time. The Zero-Inertia solver was found to be less sensitive to mesh refining than the full shallow water solver.
The multiscale nature of ecohydrological processes and feedbacks implies that vegetation patterns arising in water‐limited systems are directly linked to water redistribution processes occurring at much shorter timescales than vegetation growth. This in turn suggests that the initially available water in the system can play a role in determining the trajectory of the system, together with the well‐known role of the rainfall gradient. This work explores the role of initial hydrological conditions on vegetation dynamics and vegetation patterns. To do so, the HilleRisLambers–Rietkerk model was solved with different rainfall amounts and a large range of initial hydrological conditions spanning from near‐equilibrium to far‐from‐equilibrium conditions. The resulting vegetation patterns and ecohydrological signatures were quantitatively studied. The results show that not only do initial hydrological conditions play a role in the ecohydrological dynamics but also they can play a dominating one even resulting in divergent vegetation patterns that exhibit convergent mean‐field properties, including a new set of hybrid patterns. Our results highlight the relevance of assessing both global ecological and hydrological signatures and quantitatively assessing patterns to describe and understand system dynamics and in particular to determine if the systems are transient or steady. Furthermore, our analysis shows that the trajectories the system follows during its transient stages cannot be neglected to understand complex dependencies of the long‐term steady state to environmental factors and drivers.