Abstract:The discretization of river networks is a critical step for computing flow routing in hydrological models. However, when it comes to more complex hydrologic-hydrodynamic models, adaptations in the spatial representation of model calculation units are further required to allow cost-effective simulations, especially for large scale applications. The objective of this paper is to assess the impacts of river discretization on simulated discharge, water levels and numerical stability of a catchment-based hydrologic… Show more
“…Application of the vector‐based river network in this model has several critical advantages to both communities of researchers and users. The actual physical properties of rivers (e.g., river length and slope) can be determined more realistically in the vector river network compared to the grid river network (Fan et al., 2021). In addition, it allows for accurately locating water bodies, such as reservoirs, into the system as compared to the traditional grid‐based river network approach (Mukhopadhyay et al., 2020).…”
The world's river system has more than 50,000 dams and reservoirs that offer valuable services to maximize the benefits of surface water resources (ICOLD, 2020). These benefits include flood control, hydropower generation, navigation, and recreational uses (Gao et al., 2012;A. Getirana et al., 2020;Passaia et al., 2020). Largely mandated by the Flood Control Act of 1936, the United States Army Corps of Engineers (USACE) has been building and managing numerous dams and reservoirs. Many of these reservoirs were built to attenuate flood events, thereby lowering peak flows and limiting flood inundation extents in the downstream watersheds (Turner et al., 2020). In the Mississippi River Basin (MRB) (covering 40% of the contiguous Abstract Despite the recent developments in continental-scale streamflow and flood inundation modeling frameworks, effects of time-specific and spatially explicit storage-release dynamics of numerous dams and reservoirs remain underexplored. This paper fills this knowledge gap by directly inserting operational daily flow release data at 175 dam locations into a streamflow simulation of ∼1.2 million river reaches in the Mississippi River Basin (MRB), and therefore quantifying the effect of these regulations on streamflow and flood inundation extents. Using a streamflow routing model called the Routing Application for Parallel computatIon of Discharge (RAPID) and flood inundation mapping model called AutoRoute, two simulation scenarios were constructed respectively including and excluding the daily flow releases from those dams and reservoirs for a 10-year period (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). Flood inundation maps were simulated for peak flow conditions at a ∼10-m hyper spatial resolution. Kling-Gupta efficiency (KGE) values show that streamflow model performance considerably improved when reservoirs were included in the modeled system, varying from 2% in the eastern region to 380% in the drier western region. Despite small variation of streamflow model improvement with reservoir release inclusion in the eastern region of the basin, the flow model was able to better capture observed peak flows. For a 1% change in streamflow, we observe a 0.8% change in estimated flood inundation. Comparisons to three observed flood events in the MRB demonstrate that the flood inundation estimates improve when percent change in streamflow is relatively high. Overall, inclusion of reservoir release resulted in substantial improvement in continentalscale streamflow and flood inundation mapping.Plain Language Summary Dams and reservoirs are important structures that alter the flow of rivers to provide important services such as flood reduction, hydropower generation, and water storage for irrigation and recreation. We can use computer modeling to simulate the flow of rivers and the operation of dams. Most of the time, researchers approximate the operation of dams using various assumptions. However, we do not fully understand how much the real-life operation of reservoirs impacts rive...
“…Application of the vector‐based river network in this model has several critical advantages to both communities of researchers and users. The actual physical properties of rivers (e.g., river length and slope) can be determined more realistically in the vector river network compared to the grid river network (Fan et al., 2021). In addition, it allows for accurately locating water bodies, such as reservoirs, into the system as compared to the traditional grid‐based river network approach (Mukhopadhyay et al., 2020).…”
The world's river system has more than 50,000 dams and reservoirs that offer valuable services to maximize the benefits of surface water resources (ICOLD, 2020). These benefits include flood control, hydropower generation, navigation, and recreational uses (Gao et al., 2012;A. Getirana et al., 2020;Passaia et al., 2020). Largely mandated by the Flood Control Act of 1936, the United States Army Corps of Engineers (USACE) has been building and managing numerous dams and reservoirs. Many of these reservoirs were built to attenuate flood events, thereby lowering peak flows and limiting flood inundation extents in the downstream watersheds (Turner et al., 2020). In the Mississippi River Basin (MRB) (covering 40% of the contiguous Abstract Despite the recent developments in continental-scale streamflow and flood inundation modeling frameworks, effects of time-specific and spatially explicit storage-release dynamics of numerous dams and reservoirs remain underexplored. This paper fills this knowledge gap by directly inserting operational daily flow release data at 175 dam locations into a streamflow simulation of ∼1.2 million river reaches in the Mississippi River Basin (MRB), and therefore quantifying the effect of these regulations on streamflow and flood inundation extents. Using a streamflow routing model called the Routing Application for Parallel computatIon of Discharge (RAPID) and flood inundation mapping model called AutoRoute, two simulation scenarios were constructed respectively including and excluding the daily flow releases from those dams and reservoirs for a 10-year period (2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014). Flood inundation maps were simulated for peak flow conditions at a ∼10-m hyper spatial resolution. Kling-Gupta efficiency (KGE) values show that streamflow model performance considerably improved when reservoirs were included in the modeled system, varying from 2% in the eastern region to 380% in the drier western region. Despite small variation of streamflow model improvement with reservoir release inclusion in the eastern region of the basin, the flow model was able to better capture observed peak flows. For a 1% change in streamflow, we observe a 0.8% change in estimated flood inundation. Comparisons to three observed flood events in the MRB demonstrate that the flood inundation estimates improve when percent change in streamflow is relatively high. Overall, inclusion of reservoir release resulted in substantial improvement in continentalscale streamflow and flood inundation mapping.Plain Language Summary Dams and reservoirs are important structures that alter the flow of rivers to provide important services such as flood reduction, hydropower generation, and water storage for irrigation and recreation. We can use computer modeling to simulate the flow of rivers and the operation of dams. Most of the time, researchers approximate the operation of dams using various assumptions. However, we do not fully understand how much the real-life operation of reservoirs impacts rive...
“…For this study, the adopted value of Δx was 10 km, that is, each segment of river has this length and from this the unitcatchments are delimited in the model. This value was the same successfully used by Fleischmann et al (2018), Lopes et al (2018) and Fan et al (2021).…”
Section: Watershed Discretizationmentioning
confidence: 95%
“…In the latest version of the model, the drainage network is extracted from flow directions obtained from a Digital Elevation Model. The network is then segmented into river stretches of fixed length (Δx) for which small unit-catchments are delimited (Fan et al, 2021). Within each of them, Hydrological Response Units (HRUs) are defined based on soil type and land use.…”
The great flood of 1941 remains the most impactful and traumatic flood event in the history of Porto Alegre. This event was caused by a combination of heavy rainfall in the basin in the days prior to the peak of the flood, and the wind that occurred during the flood. However, the influence of wind on the maximum flood level, although frequently mentioned, is not well known. This is largely because there are no systematic data for wind speed measuring and direction in 1941. Therefore, the present work aims to estimate the discharge and the maximum flood level in the city of Porto Alegre and in other relevant points of the basin. using hydrological-hydrodynamic modeling and, from there, analyze the possible role of the wind during the flood, through the simulation of hypothetical wind scenarios. The results showed that the discharges and levels were represented reasonably well with the MGB model at several locations in the basin. In relation to the 1941 event and the scenarios created, the contribution of the wind to the peak of the flood was of the order of a few to tens of centimeters, showing its potential role despite the limitations of the model.
“…For instance, in addition to the shortcomings in representation of hydrological processes, the model has been calibrated with a limited number of gauge stations by using global precipitation data that is associated with large errors (Beck et al, 2017) and global river geometries that largely affect channel-floodplain water exchanges. Regarding uncertainties in the hydrodynamic modelling processes (e.g., associated with model parameterization or insufficient hydraulic processes representation of flood processes), there are several studies that have addressed this topic in the literature, even for the MGB model (Fan et al, 2021;Fleischmann et al, 2019Fleischmann et al, , 2018Fleischmann et al, , 2020Paiva et al, 2013) Furthermore, A cross-validation between MGB-SA flood extents and several other remote sensing-based datasets has been conducted for the Amazon basin (Fleischmann et al, 2022), albeit a more in-depth validation of simulated flooded areas over other important South American wetlands has not been performed so far. Representing inundation dynamics in the large Pantanal wetland (Paraguay basin) may require more complex flood routing methods than those used in MGB-SA (Bravo et al, 2012;Paz et al, 2011), and therefore we recognize that the contribution of SW on TWS may be underestimated in these areas.…”
Section: Limitations and Recommendationsmentioning
Brazil hosts a large amount of freshwater. Knowing how this stored water is partitioned in space and time between surface and subsurface components is a crucial step towards a more correct depiction of the country’s water cycle, which has major implications for decision making related to water resources management. Here, we extracted monthly water storage (WS) variability, from 2003 to 2020, based on multiple state-of-the-art datasets representing different WS components – groundwater (GW), soil moisture (SM), surface waters (SW), and artificial reservoirs (RS) – in all Brazilian Hydrographic Regions (BHRs), and computed each component’s contribution to the total variability. Most of the variability can be attributed to SM (40-68%), followed by GW (18-40%). SW has great influence in the north-western BHRs (humid monsoon influenced) with 18-40% and the southern BHRs (subtropical system influenced) with 5-10%. RS has important contributions in the Paraná with 12.1%, São Francisco with 3.5%, and Tocantins-Araguaia with 2.1%. In terms of long-term variability, water storages have been generally decreasing in the eastern and increasing in north-western and southern BHRs, with GW and RS being the most affected, although it can also be observed in SW peaks. Comparisons made with previous studies show that the approach and datasets used can have a considerable impact in the results. Such analysis can have broad implications in identifying the nature of amplitude and phase variability across regions in order to better characterize them and to obtain better evaluations of hydrological trends under a changing environment.
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