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A Multi-Model Ensemble Approach for Stream Flow Simulation
Published in Balram Panigrahi, Megh R. Goyal, Modeling Methods and Practices in Soil and Water Engineering, 2017
Dwarika Mohan Das, R. Singh, A. Kumar, D. R. Mailapalli, A. Mishra, C. Chatterjee
It is an integrated, physically based, distributed model that simulates the hydrological and water quality process on a basin scale. MIKE SHE modeling system simulates most major hydrological process, including canopy and land surface interpretation after precipitation, snowmelt, evapotranspiration, overland flow, channel flow, unsaturated subsurface flow and saturated groundwater flow using physically based methods. The system has no limitations regarding watershed size. In this model area is discretized by horizontal as well as vertical square grid networks for surface and groundwater flow components.
Literature review
Published in Isnaeni Murdi Hartanto, Integrating Multiple Sources of Information for Improving Hydrological Modelling: An Ensemble Approach, 2019
Mathematical hydrological modelling begins back in 1850 when the Rational Method was introduced by Mulvany, with the use of the relationship between time of concentration and peak flow (Todini 2007). Later on, more physically meaningful models emerged, trying to represent real-world processes with complex mathematical equations. However, due to the limitation of resources and data, in the 1960s a simple lumped model with interconnected conceptual elements was considered as the best representation that could be achieved. At the end of the 1970s, a new type of lumped physically based hydrological model was developed, based on the assumption that the hydrological processes are mainly determined by dynamic processes of saturated areas. The models assumed that all precipitation goes into the soil and after saturation of upper soil layer surface runoff develops (Todini 2007). Physically based spatially distributed models also began to develop, based on full dynamic equations, with complex calculations in each grid cell, trying to represent the real world as close as possible. This concept was applied, for example, in the SHE model and evolved into a robust physically-based spatially distributed hydrological model further developed by DHI and known as MIKE-SHE (Abbott et al. 1986). However, spatially distributed modelling requires a lot of data and high computational time, so simplified physically-based spatially distributed hydrological models were introduced later, such as LISFLOOD and WATFLOOD; they use simplified equations and have lighter computational load (Todini 2007). Although spatially distributed models seem to be very close to the real world representation, they still suffer from a number of issues: nonlinearity, scale, equifinality, uniqueness and uncertainty (Beven 2001). Furthermore, Beven (1989) stated that spatially distributed models could still have the same disadvantages as lumped models, such as error in estimation of parameters and variables. More recently, indeed it was indicated that informed estimation of hydrological model parameter values, e.g. on the basis of observations and process understanding, is still a key challenge (Clark et al. 2017).
Assessing the role of location and scale of Nature Based Solutions for the enhancement of low flows
Published in International Journal of River Basin Management, 2022
Jessica Fennell, Chris Soulsby, Mark E. Wilkinson, Ronald Daalmans, Josie Geris
To address our objectives, we required a coupled hydrological/hydraulic model and selected MIKE SHE - MIKE 11 for our approach. MIKE SHE is a physically-based, deterministic, fully-distributed 3D catchment model which simulates the land-based phase of the hydrological cycle (Abbott et al., 1986). When dynamically-coupled with the MIKE 11 1D hydraulic model, this enables: detailed river network modelling with an integrated module for structures (e.g. RAFs); overland flow to - and out-of-bank flooding from – the river network; and river – baseflow reservoir exchange (Butts & Graham, 2005). Thus overflow from RAFs and their impact on different flow pathways (Fennell et al., 2020) could be simulated. MIKE SHE – MIKE 11 has been applied on scales ranging from <10 km2 to nationwide (Al-Khudhairy et al., 1999; Henriksen et al., 2003), for varied purposes, e.g. investigating stream temperatures (Fabris et al., 2018), water conservation structures (Ramteke et al., 2020), river and floodplain restoration (Clilverd et al., 2016) and climate change impacts (Thompson et al., 2017).
Land use as possible strategy for managing water table depth in flat basins with shallow groundwater
Published in International Journal of River Basin Management, 2018
Pablo E. García, Angel N. Menénendez, Guillermo Podestá, Federico Bert, Poonam Arora, Esteban Jobbágy
We developed a hydrological model of the Salado A1 basin using MIKE SHE, a proprietary software (Refsgaard and Storm 1995, Refsgaard et al. 2010). MIKE SHE is a deterministic, spatially distributed, physically based numerical model that couples surface and groundwater flows. It derives from the Système Hydrologique Europèen – or SHE (Abbott et al. 1986a) – and was collaboratively developed by a group of European laboratories. MIKE SHE has been applied to a wide variety of basin types and sizes (Refsgaard et al. 1992, Vázquez et al. 2002, Henriksen et al. 2003, Liu et al. 2008, Stisen et al. 2008, Janža 2013, Wijesekara et al. 2014).
Modelling snowmelt runoff in Lidder River Basin using coupled model
Published in International Journal of River Basin Management, 2020
Yasir Altaf, Manzoor Ahangar, Mohammad Fahimuddin
The distributed watershed hydrologic simulation model, MIKE SHE, originally derived from the SHE model (Abbott et al.1986), has been widely used for examining hydrological responses to land use, land cover change and climate variability (Graham and Butts 2005, Lu 2006, McMichael and Hope 2007). Other areas of study on MIKE SHE include sensitivity analysis and spatial scale effects (Xevi et al.1997, Vazquez and Feyen 2007), model parameterization, calibration, and validation (Singh et al. 1997, Andersen et al.2001, Henriksen et al.2003, Madsen 2003), and the evaluation of the potential evapotranspiration (PET) methods (Vazquez and Feyen, 2003).