Abstract. In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes. This study further addressed four aspects of these challenges. First, the spatial variability of vegetationcaused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. The understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.
Abstract. Surface water dynamics play an important role in water, energy and carbon cycles of the Amazon Basin. A macro-scale inundation scheme was integrated with a surface-water transport model and the extended model was applied in this vast basin. We addressed the challenges of improving basin-wide geomorphological parameters and river flow representation for large-scale applications. Vegetation-caused biases embedded in the HydroSHEDS DEM data were alleviated by using a vegetation height map of about 1-km resolution and a land cover dataset of about 90-m resolution. The average elevation deduction from the DEM correction was about 13.2 m for the entire basin. Basin-wide empirical formulae for channel cross-sectional geometry were adjusted based on local information for the major portion of the basin, which could significantly reduce the cross-sectional area for the channels of some subregions. The Manning roughness coefficient of the channel varied with the channel depth to reflect the general rule that the relative importance of riverbed resistance in river flow declined with the increase of river size. The entire basin was discretized into 5395 subbasins (with an average area of 1091.7 km2), which were used as computation units. The model was driven by runoff estimates of 14 years (1994–2007) generated by the ISBA land surface model. The simulated results were evaluated against in situ streamflow records, and remotely sensed Envisat altimetry data and GIEMS inundation data. The hydrographs were reproduced fairly well for the majority of 13 major stream gauges. For the 11 subbasins containing or close to 11 of the 13 gauges, the timing of river stage fluctuations was captured; for most of the 11 subbasins, the magnitude of river stage fluctuations was represented well. The inundation estimates were comparable to the GIEMS observations. Sensitivity analyses demonstrated that refining floodplain topography, channel morphology and Manning roughness coefficients, as well as accounting for backwater effects could evidently affect local and upstream inundation, which consequently affected flood waves and inundation of the downstream area. It was also shown that the river stage was sensitive to local channel morphology and Manning roughness coefficients, as well as backwater effects. The understanding obtained in this study could be helpful to improving modeling of surface hydrology in basins with evident inundation, especially at regional or larger scales.
[1] The Three-Layer Variable Infiltration Capacity (VIC-3L) land surface model is extended to include biological and hydrological processes important to water, energy, and carbon budgets under water-limited climatic conditions: (1) movement of soil water from wet to dry regions through hydraulic redistribution (HR); (2) groundwater dynamics; (3) plant water storage; and (4) photosynthetic process. HR is represented with a process-based scheme and the interaction between HR and groundwater dynamics is explicitly considered. The impact of frozen soil on HR in the cold season is also represented. Transpiration is calculated by combining an Ohm's law analogy, where flow from the soil to leaves is buffered by plant water storage, with the Penman-Monteith method, where stomatal conductance is linked with photosynthesis. In this extended model (referred to as VIC1), water flow in plants and in the unsaturated and saturated zones, transpiration and photosynthesis are closely coupled, and multiple constraints are simultaneously applied to the transpiration process. VIC1 is evaluated with an analytical solution under simple conditions and with observed data at two AmeriFlux sites. Scenario simulations demonstrate the following results: (1) HR has significant impacts on water, energy, and carbon budgets during the dry season; (2) Rise of groundwater table, increase of root depth, HR, and plant water storage are favorable to dry-season latent heat flux; (3) Plant water storage can weaken the intensity of upward HR; (4) Frozen soil can restrict downward HR in the wet winter and reduce the soil water reserves for the dry season.Citation: Luo, X., X. Liang, and H. R. McCarthy (2013), VIC+ for water-limited conditions: A study of biological and hydrological processes and their interactions in soil-plant-atmosphere continuum, Water Resour. Res., 49,
Leaf angle is an important agronomic trait in rice (Oryza sativa L.). It affects both the efficiency of sunlight capture and nitrogen reservoirs. The erect leaf phenotype is suited for high-density planting and thus increasing crop yields. Many genes regulate leaf angle by affecting leaf structure, such as the lamina joint, mechanical tissues, and the midrib. Signaling of brassinosteroids (BR), auxin (IAA), and gibberellins (GA) plays important roles in the regulation of lamina joint bending in rice. In addition, the biosynthesis and signaling of BR are known to have dominant effects on leaf angle development. In this review, we summarize the factors and genes associated with the development of leaf angle in rice, outline the regulatory mechanisms based on the signaling of BR, IAA, and GA, and discuss the contribution of crosstalk between BR and IAA or GA in the formation of leaf angle. Promising lines of research in the transgenic engineering of rice leaf angle to increase grain yield are proposed.
The role of groundwater in sustaining plant transpiration constitutes an important but not well‐understood aspect of the interactions between groundwater, vegetation, the land surface, and the atmosphere. The effect of the hydraulic redistribution (HR) process by plant roots on the interplay between plant transpiration and groundwater dynamics under water‐limited climates is investigated by using the Variable Infiltration Capacity Plus (VIC+) land surface model. Numerical experiments, with or without explicitly considering HR, are conducted on soil columns over a range of groundwater table depths (GWTDs) under different vegetative land covers, soil types, and precipitation conditions. When HR is not included, this study obtains transpiration–GWTD relationships consistent with those from watershed studies that do not include HR. When HR is included, the transpiration–GWTD relationships are modified. The modification introduced by HR is manifested in the soil moisture of the root zone. The mechanism of HR is explained by detailing the roles of the hydraulically redistributed water, the upward diffusion of soil water, and the daytime root uptake. We have found that HR is particularly important in water‐limited climates under which plants have high transpiration demand. At the beginning stage of a dry period, HR modulates the severe impacts that climate has on plant transpiration. Only after a prolonged dry period, impacts of HR are lessened when the groundwater table drops below the depth of water uptake by roots and are diminished when plant transpiration is decoupled from groundwater dynamics.
As climate change will increase the frequency and intensity of precipitation extremes and coastal flooding, there is a clear need for an integrated hydrology and hydraulic system that has the ability to model the hydrologic conditions over a long period and the flow dynamic representations of when and where the extreme hydrometeorological events occur. This system coupling provides comprehensive information (flood wave, inundation extents and depths) about coastal flood events for emergency management and risk minimization. This study provides an integrated hydrologic and hydraulic coupled modeling system that is based on the Coupled Routing and Excessive Storage (CREST) model and the Australia National University- Geophysics Australia (ANUGA) model to simulate flood. Forced by the near-real-time Multi-Radar Multi-Sensor (MRMS) Quantitative Precipitation Estimates (QPEs), this integrated modeling system was applied during the 2017 Hurricane Harvey event to simulate the streamflow, the flood extent, and the inundation depth. The results were compared with post-event Water High Mark (WHM) survey data and its interpolated flood extent by the United States Geological Survey (USGS) and the Federal Emergency Management Agency (FEMA) flood insurance claims, as well as a satellite-based flood map, the National Water Model (NWM) and the Fathom (LISFLOOD-FP) model simulated flood map. The proposing hydrologic and hydraulic model simulation indicated that it could capture 87% of all flood insurance claims within the study area, and the overall error of water depth was 0.91 meters, which is comparable to the mainstream operational flood models (NWM and Fathom).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.