Role of meteorological controls on interannual variations in wet‐period characteristics of wetlands

Coastal wetlands represent an ecotone between ocean and terrestrial ecosystems, providing important services, including flood mitigation, fresh water supply, erosion control, carbon sequestration, and wildlife habitat. The environmental setting of a wetland and the hydrological connectivity between a wetland and adjacent terrestrial and aquatic systems together determine wetland hydrology. Yet little is known about regional-scale hydrological interactions among uplands, coastal wetlands, and coastal processes, such as tides, sea level rise, and saltwater intrusion, which together control the dynamics of wetland hydrology. This study presents a new regional-scale, physically based, distributed wetland hydrological model, PIHM-Wetland, which integrates the surface and subsurface hydrology with coastal processes and accounts for the influence of wetland inundation on energy budgets and evapotranspiration (ET). The model was validated using in situ hydro-meteorological measurements and Moderate Resolution Imaging Spectroradiometer (MODIS) ET data for a forested and herbaceous wetland in North Carolina, USA, which confirmed that the model accurately represents the major wetland hydrological behaviours. Modelling results indicate that topographic gradient is a primary control of groundwater flow direction in adjacent uplands. However, seasonal climate patterns become the dominant control of groundwater flow at lower coastal plain and land-ocean interface. We found that coastal processes largely influence groundwater table (GWT) dynamics in the coastal zone, 300 to 800 m from the coastline in our study area. Among all the coastal processes, tides are the dominant control on GWT variation. Because of inundation, forested and herbaceous wetlands absorb an additional 6% and 10%, respectively, of shortwave radiation annually, resulting in a significant increase in ET. Inundation alters ET partitioning through canopy evaporation, transpiration, and soil evaporation, the effect of which is stronger in cool seasons than in warm seasons. The PIHM-Wetland model provides a new tool that improves the understanding of wetland hydrological processes on a regional scale. Insights from this modelling study provide benchmarks for future research on the effects of sea level rise and climate change on coastal wetland functions and services.

Section: Model Developmentmentioning

confidence: 99%

Understanding coastal wetland hydrology with a new regional‐scale, process‐based hydrological model

Sun

et al. 2018

“…The model has been previously applied at multiple scales and in diverse hydro‐climatological settings for simulating coupled dynamics of streamflow, groundwater, soil moisture, snow, and evapotranspiration fluxes (Chen, Kumar, & McGlynn, ; Chen, Kumar, Wang, Winstral, & Marks, ; Kumar, Marks, Dozier, Reba, & Winstral, ; Seo, Sinha, Mahinthakumar, Sankarasubramanian, & Kumar, ; R. Wang, Kumar, & Marks, ; Yu, Duffy, Baldwin, & Lin, ; Zhang, Chen, Kumar, Marani, & Goralczyk, ). The model has already been used to study wetland dynamics in multiple studies (Liu & Kumar, ; D. Wang, Liu, & Kumar, ; Yu et al, ).…”

Section: Methodsmentioning

confidence: 99%

“…Initial conditions of hydrologic states on 09/01/2004 mid‐night were also extracted from the same study. To map the states from the mesh configuration used in Liu and Kumar () to that used here, Inverse Distance Weighted (IDW) interpolation was employed. To negate the effects of errors introduced by the IDW interpolation scheme and mismatch of a mesh configuration, the first year simulation was used to allow the system to equilibrate with the forcing.…”

Section: Methodsmentioning

confidence: 99%

Spatial and temporal variations in the groundwater contributing areas of inland wetlands

Park

Wang

Kumar

2019

Self Cite

Water quality and groundwater dynamics in wetlands are strongly influenced by the spatiotemporal distribution of contaminant application, and variations and changes in climate, vegetation, and anthropogenic interventions in its neighborhood. For groundwater-fed wetlands, this relevant neighborhood at least extends to the groundwater contributing area (GCA) boundary. In spite of its importance, understanding of the nature of GCA dynamics vis-à-vis meteorological variations remains largely understudied. This work attempts to map GCA of inland forested wetlands. Following that, two specific questions are answered: (a) Is GCA extent and its variation different than that of the topographic contributing area (TCA)? and (b) Is the temporal dynamics of GCA for different wetlands, all of which are experiencing very similar climatological forcing, similar? Our results show that GCAs for wetlands vary temporally, are much different in extent and shape than the TCA, and on an average are larger than the TCA. Although wetlands in the studied watershed experienced similar meteorological forcings, their covariation with forcings varied markedly. Majority of the wetlands registered an increase in GCA during dry period, but for a few the GCA decreased. This highlights the role of additional physical controls, other than meteorological forcings, on temporal dynamics of GCA. Notably, wetlands with larger TCA are found to generally have larger average GCA as well, thus indicating the dominant role of topography in determining the relative size of average GCA over the landscape. Our results provide a refined picture of the spatiotemporal patterns of GCA dynamics and the controls on it. The information will help improve the prediction of wet period dynamics, recharge, and contamination risk of groundwater-fed wetlands.

“…The Penn State Integrated Hydrologic Model (PIHM; Kumar, ; Qu & Duffy, ) was applied to both the LM and LR watersheds to simulate streamflow into the two reservoirs and to evaluate the impact of individual HTSs on water storage in the reservoirs. The model has been previously applied at multiple scales and in diverse hydro‐climatological settings for simulating streamflow and coupled hydrologic process dynamics (Chen, Kumar, & McGlynn, ; Kumar & Duffy, ; Kumar, Marks, Dozier, Reba, & Winstral, ; Liu & Kumar, ; Seo, Sinha, Mahinthakumar, Sankarasubramanian, & Kumar, ; Yu, Duffy, Baldwin, & Lin, ). The model uses a physically based, spatially distributed approach to explicitly simulate the coupled surface–subsurface water dynamics and provide estimates of several hydrologic state variables, including surface water depth, soil moisture, groundwater depth, and river stage.…”

Section: Methodsmentioning

confidence: 99%

Hurricanes and tropical storms: A necessary evil to ensure water supply?

Zhang

Chen

Kumar

et al. 2017

Self Cite

Several parts of the globe including Southeast North America, the Caribbean, Southeast Asia, Australia, and China are often hit by hurricanes and tropical storms (HTSs), which can deliver a large amount of rainfall within a period of a few days. Although HTSs are mostly studied as disaster agents, considering that they occur during the period when water supply systems are generally depleted, it is important to ascertain their potential contributions toward sustaining water supply. Using the Lake Michie-Little River reservoir system that supplies water to the city of Durham (North Carolina) as a representative test case, we implemented an integrated watershed and reservoir management model, supported by publicly available observations, to evaluate the extent to which HTSs impact water storages. Results indicate that HTSs can have a significant impact on reservoir water storage, with their effects being felt for more than a year for some storms. The impact on reservoir water storage is identified to be primarily controlled by 3 factors, namely, streamflow response size from HTSs, storage in the reservoir right before the event, and streamflow succeeding the event response to HTS (henceforth referred as postevent streamflow). Although the impact of streamflow response size on water storage is generally proportional to its magnitude, initial water storage in the reservoir and postevent streamflow have a nonmonotonic influence on water storage. As all the 3 identified controls are a function of antecedent hydrologic conditions and meteorological forcings, these 2 factors indirectly influence the impact of HTS on water storage in a reservoir. The identification of controlling factors and assessment of their influence on reservoir response will further facilitate implementation of more accurate estimation and prediction frameworks for within-year reservoir operations.