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Wetland Processes, Monitoring and Modeling for Design and Management

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Ecohydrology".

Deadline for manuscript submissions: closed (20 November 2023) | Viewed by 12838

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Special Issue Editors

Dr. Mohamed M. Hantush

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Guest Editor

Senior Research Hydrologist, Center for Environmental Solutions and Emergency Response, Office of Research and Development, U.S. Environmental Protection Agency, Cincinnati, OH 45268, USA
Interests: subsurface hydrology; hydrologic modeling; water quality; uncertainty estimation; ecohydrology

Dr. Latif Kalin

E-Mail Website
Guest Editor

College of Forestry, Wildlife and Environment, Auburn University, Auburn, AL 36849, USA
Interests: non-point source pollution modeling; land use/cover and climate change impacts on water quality/quantity; wetland hydrology and nutrient cycling
Special Issues, Collections and Topics in MDPI journals

Dr. Rutineia Tassi

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Guest Editor

Associate Professor, Department of Sanitary and Environmental Engineering, Federal University of Santa Maria, Roraima Avenue, Santa Maria, Rio Grande do Sul 97015-070, Brazil
Interests: urban drainage; water resources management; geoprocessing applied to water resources; wetlands; ecohydrology; hydrological and hydrodynamic modeling and green infrastructure techniques

Special Issue Information

Dear Colleagues,

Wetlands can be natural, low-lying, regularly inundated ecotones that emerge at the fringe of aquatic and upland terrestrial ecosystems, or engineered (constructed wetlands), which are widely used for water quality treatment, shallow aquifer recharge, flood control, etc. Even some of the low impact development (LID) practices in urban areas, such as rain gardens, swales, and green roofs, can be considered types of wetlands. Wetlands are recognized for the variety of ecosystem services they provide, such as water quality purification, carbon sequestration, habitat provision, and biodiversity maintenance.

This proposed Special Issue solicits research papers on wetland function modeling and monitoring to be published in Water. The scope of the Special Issue is on recent advances in basic and applied research leading to improved description of hydrology, hydrodynamics, water quality, and primary productivity in models of natural, restored, and constructed treatment wetlands, including some of the LID practices in urban areas that mimic the ecological function of wetlands. This includes research papers on improved physical, biochemical, and biomass processes of existing models and novel case-study model applications. Papers on carbon sequestration and greenhouse gas emissions (CO₂, CH₄, and N₂O) in inland freshwater and coastal saltwater wetlands are highly encouraged. Laboratory and field-scale studies aiming to elucidate the understanding of complex interactions among physical and biogeochemical processes, leading to the development of empirical relationships which promise improved wetland simulation models, are also encouraged. Research papers on modeling for the improved design of constructed and treatment wetlands are welcomed. Papers on model and method development or applications for scaling up wetland function and processes to the catchment scale using statistical and watershed models are also highly encouraged.

Dr. Mohamed M. Hantush
Dr. Latif Kalin
Dr. Rutineia Tassi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

wetland
models
groundwater-surface water interactions
water quality
carbon sequestration
treatment wetlands
primary productivity

Published Papers (6 papers)

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Research

24 pages, 6117 KiB

Open AccessArticle

Wildlife Roadkill Driven by Hydrological Regime in a Subtropical Wetland

by Rutineia Tassi, Enio Júnior Seidel, David da Motta-Marques, Adolfo Villanueva and Latif Kalin

Water 2023, 15(24), 4307; https://doi.org/10.3390/w15244307 - 18 Dec 2023

Viewed by 1059

Abstract

This study explored the role of the hydrological regime as a trigger factor for wildlife roadkill along a 22 km road crossing the Taim Wetland, a Ramsar site of international importance in South Brazil. The north–south crossing of BR-471, a federal highway, causes fatalities to numerous animals due to collisions with vehicles. An 11-year long-term time series study encompassing monthly roadkill incidents, water level, and rainfall was analyzed by considering three different periods related to a Wildlife Protection System (WPS): (i) 3 initial years before the WPS implementation (BWPS); (ii) 4 intermediate years after the WPS implementation (AWPS), which includes fences, fauna tunnels, cattle guard stocks, bumps, and speed control; (iii) 4 final years during partial destruction of the WPS (PDWPS). A pseudo-2D full hydrodynamic cell model was employed to fill missing water level data. The model had a good to very good performance (NSE: 0.73 to 0.87; R²: 0.79 to 0.90). The relationship between roadkill incidents and the WPS periods (BWPS, AWPS, and PDWPS) was modeled using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), considering rainfall and water level as predictor variables. The analysis revealed a higher incidence of wildlife roadkill in BWPS compared to AWPS and PDWPS, suggesting the effectiveness of the implemented measures. Critical season and interplay between water levels, rainfall, and the roadkill were assessed. Mammals was the most common roadkill class identified (~92%), followed by reptiles (13%) and birds (2%), with no change in these percentual in the BWPS, AWPS, and PDWPS. Among mammals, capybara (Hydrochoerus hydrochaeris) and coypu (Myocastor coypu) were the most frequent victims (~93% of mammals). Winter, followed by autumn, recorded the highest number of roadkill incidents (>60%), and this pattern remained consistent during the three periods. While rainfall did not emerge as a determining variable for roadkill, water levels above certain thresholds (>3.3 m) drastically diminished the effectiveness of the WPS, mainly due to fauna tunnel submersion. These findings offer valuable insights for enhancing wildlife conservation strategies in this protected area by incorporating hydrological information providing a baseline for designing WPS in similar environments. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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22 pages, 5623 KiB

Open AccessArticle

Nutrient Removal Potential of Headwater Wetlands in Coastal Plains of Alabama, USA

by Sabahattin Isik, Henrique Haas, Latif Kalin, Mohamed M. Hantush and Christopher Nietch

Water 2023, 15(15), 2687; https://doi.org/10.3390/w15152687 - 25 Jul 2023

Cited by 1 | Viewed by 1745

Abstract

Headwater streams drain over 70% of the land in the United States with headwater wetlands covering 6.59 million hectares. These ecosystems are important landscape features in the southeast United States, with underlying effects on ecosystem health, water yield, nutrient cycling, biodiversity, and water quality. However, little is known about the relationship between headwater wetlands’ nutrient function (i.e., nutrient load removal (R_L) and removal efficiency (E_R)) and their physical characteristics. Here, we investigate this relationship for 44 headwater wetlands located within the Upper Fish River watershed (UFRW) in coastal Alabama. To accomplish this objective, we apply the process-based watershed model SWAT (Soil and Water Assessment Tool) to generate flow and nutrient loadings to each study wetland and subsequently quantify the wetland-level nutrient removal efficiencies using the process-based wetland model WetQual. Results show that the calculated removal efficiencies of the headwater wetlands in the UFRW are 75–84% and 27–35% for nitrate (

{N O}_{3}^{-}

) and phosphate

{(P O}_{4}^{+})

, respectively. The calculated nutrient load removals are highly correlated with the input loads, and the estimated

{P O}_{4}^{+}

E_R shows a significant decreasing trend with increased input loadings. The relationship between

{N O}_{3}^{-}

E_R and wetland physical characteristics such as area, volume, and residence time is statistically insignificant (p > 0.05), while for

{P O}_{4}^{+}

, the correlation is positive and statistically significant (p < 0.05). On the other hand, flashiness (flow pulsing) and baseflow index (fraction of inflow that is coming from baseflow) have a strong effect on

{N O}_{3}^{-}

removal but not on

{P O}_{4}^{+}

removal. Modeling results and statistical analysis point toward denitrification and plant uptake as major

{N O}_{3}^{-}

removal mechanisms, whereas plant uptake, diffusion, and settling of sediment-bound P were the main mechanisms for

{P O}_{4}^{+}

removal. Additionally, the computed nutrient E_R is higher during the driest year of the simulated period compared to during the wettest year. Our findings are in line with global-level studies and offer new insights into wetland physical characteristics affecting nutrient removal efficiency and the importance of headwater wetlands in mitigating water quality deterioration in coastal areas. The regression relationships for

{N O}_{3}^{-}

and

{P O}_{4}^{+}

load removals in the selected 44 wetlands are then used to extrapolate nutrient load removals to 348 unmodeled non-riverine and non-riparian wetlands in the UFRW (41% of UFRW drains to them). Results show that these wetlands remove 51–61% of the

{N O}_{3}^{-}

and 5–10% of the

{P O}_{4}^{+}

loading they receive from their respective drainage areas. Due to geographical proximity and physiographic similarity, these results can be scaled up to the coastal plains of Alabama and Northwest Florida. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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19 pages, 3003 KiB

Open AccessFeature PaperArticle

Incorporating Wetland Delineation and Impacts in Watershed-Scale Hydrologic Modeling

by Tiansong Qi, Mosammat Mustari Khanaum, Kyle Boutin, Marinus L. Otte, Zhulu Lin and Xuefeng Chu

Water 2023, 15(14), 2518; https://doi.org/10.3390/w15142518 - 09 Jul 2023

Cited by 3 | Viewed by 2385

Abstract

In semi-distributed hydrologic models, it is difficult to account for the impacts of wetlands on hydrologic processes, as they are based on lumped, subbasin-scale wetland concepts. It is a challenge to incorporate the influences of individual small wetlands into watershed-scale models by using lumped parameterization. The objective of this study was to improve watershed-scale hydrologic modeling by taking into account real wetland features during the wetland parameterization. To achieve this objective, a joint modeling framework was proposed to couple a surface delineation algorithm with a semi-distributed hydrologic model and then applied to the Upper Turtle River watershed in North Dakota, USA. The delineation algorithm identified the topographic properties of wetlands, which were further utilized for wetland parameterization. A nonlinear area–storage relationship was determined and used in the estimation of the wetland-related parameters. The results demonstrated that the new joint modeling approach effectively avoided misestimating the wetland-related parameters by accounting for real topographic characteristics (e.g., storage, ponding area, and contributing area) of identified wetlands and their influences, and provided improved modeling of the hydrologic processes in such a wetland-dominated watershed. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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24 pages, 3889 KiB

Open AccessArticle

Assessment and Management of the Water Quality and Heavy-Metal Pollution of a Protected Hypersaline Wetland in the United Arab Emirates

by Fatin Samara, Sandra L. Knuteson, Tala A. Abdulateef, Fadi Yaghmour, Brendan Whittington-Jones, Sara Mohamed Al Abdalla, Baha Khalil and Norhan Ahmed

Water 2023, 15(9), 1766; https://doi.org/10.3390/w15091766 - 04 May 2023

Cited by 1 | Viewed by 3340

Abstract

A hypersaline protected wetland in the UAE was assessed from February to April of 2021 for parameters such as temperature, pH, COD, total dissolved solids, ORP, electrical conductivity, total and E. coli, salinity, turbidity, chloride, ammonia, nitrate, total nitrogen, phosphorus, and heavy metals to assess its current status. Wasit Nature Reserve’s salinity values ranged between 17.1 and 64.78 psu, while D.O values ranged between 6.3 and 8.41 ppm. The values for nitrate were between 50.70 and 57.6 ppm, while the values for chloride were between 12,642.0 and 37,244.0 ppm. Results for heavy metals showed that Iron and Aluminum were the highest concentrations in sediments, with an average of 5599.3 mg/kg and 3171.1 mg/kg, respectively. Mercury and arsenic reported the lowest concentrations, with an average of 0.0 mg/kg and 2.4 mg/kg, respectively. Hazard quotient values were 2239.72 mg/kg for iron, 0 mg/kg for mercury, and 0.05 mg/kg for arsenic, indicating that iron levels are considered hazardous and water-quality indicators concluded high pollution levels. The results indicate that the hypersaline nature of the wetland contributes to the deviation from the permissible limits, as demonstrated by the calculated “poor“water-quality index and “highly polluted” water-pollution index. Due to their ecological relevance, wetlands in the region could serve as indicators of ecological well-being, highlighting the need for regular monitoring and evaluation. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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19 pages, 5815 KiB

Open AccessArticle

Using Simple LSTM Models to Evaluate Effects of a River Restoration on Groundwater in Kushiro Wetland, Hokkaido, Japan

by Takumi Yamaguchi, Hitoshi Miyamoto and Tetsuya Oishi

Water 2023, 15(6), 1115; https://doi.org/10.3390/w15061115 - 14 Mar 2023

Cited by 1 | Viewed by 2136

Abstract

Wetland ecosystems with proper functioning provide various ecosystem services. Therefore, their conservation and restoration are of fundamental importance for sustainable development. This study used a deep learning model for groundwater level prediction to evaluate a wetland restoration project implemented in the Kushiro Wetland in Japan. The Kushiro Wetland had been degraded due to river improvement work. However, in 2010, a wetland restoration project was carried out to restore the meandering river channel, and a decade has passed since its completion. In this study, the wetland restoration project was evaluated by comparing the response of the groundwater level using a model that reproduced physical conditions with different characteristics before and after the restoration. At first, a deep learning model was created to predict groundwater levels pre- and post-restoration of a meandering river channel using observation data. Long short-term memory (LSTM) was used as the deep learning model. The most important aspect of this study was that LSTM was trained for each of the pre- and post-restoration periods when the hydrological and geological characteristics changed due to the river channel’s restoration. The trained LSTM model achieved high performance with a prediction error of the groundwater levels within 0.162 m at all observation points. Next, the LSTM models trained with the observation data of the post-restoration period were applied to evaluate the effectiveness of the meandering channel restoration. The results indicated that the meandering channel restoration improved hydrological processes in groundwater levels, i.e., their rainfall response and average groundwater water levels. Furthermore, the variable importance analysis of the explanatory variables in the LSTM model showed that river discharge and precipitation significantly contributed to groundwater level recovery in the Kushiro Wetland. These results indicated that the LSTM model could learn the differences in hydrological and geological characteristics’ changes due to channel restoration to groundwater levels. Furthermore, LSTM is a data-driven deep learning model, and by learning hydrological and geological conditions to identify factors that may affect groundwater levels, LSTM has the potential to become a powerful analysis method that can be used for environmental management and conservation issues. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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18 pages, 5749 KiB

Open AccessArticle

Historical Loss of Groundwater-Dependent Terrestrial Ecosystems in Undrained and Artificially Drained Landscapes in Denmark

by Gasper L. Sechu, Bertel Nilsson, Bo V. Iversen, Mette B. Greve and Mogens H. Greve

Water 2023, 15(5), 946; https://doi.org/10.3390/w15050946 - 01 Mar 2023

Cited by 1 | Viewed by 1548

Abstract

Groundwater-dependent terrestrial ecosystems (GWDTE) have been increasingly under threat due to groundwater depletion globally. Over the past 200 years, there has been severe artificial drainage of low-lying areas in Denmark, leading to a gradual loss of GWDTE nature habitat areas. This study explores the spatial-temporal loss of Danish GWDTE using historical topographic maps. We carry out geographic information systems (GIS) overlap analysis between different historical topographic maps with signatures of GWDTE starting from the 19th century up to a present-day river valley bottom map. We then examine the changes in two protected GWDTE habitat types in different periods and hydrologic spatial locations. Results reveal a decrease in the area of GWDTE over the last 200 years. We attribute this to different human interventions, e.g., drainage, that have impacted the low-lying landscape since the early Middle Ages. We further conclude that downstream parts of the river network have been exposed to less GWDTE habitat loss than upstream ones. This indicates that upstream river valleys are more vulnerable to GWDTE decline. Therefore, as a management measure, caution should be exercised when designing these areas for agriculture activities using artificial drainage and groundwater abstraction, since this may lead to further decline. In contrast, there is a higher potential for establishing constructed wetlands or rewetting peatlands to restore balance. Full article

(This article belongs to the Special Issue Wetland Processes, Monitoring and Modeling for Design and Management)

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