Quantifying the Sensitivity of the Riparian Ecosystem Management Model (Remm) to Changes in Climate and Buffer Characteristics Common to Conservation Practices

Graff, C.; Sadeghi, Ali; Lowrance, Richard; Williams, R. G.

doi:10.13031/2013.19195

Cited by 17 publications

(6 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this regard, integrating our findings into the Riparian Ecosystem Management Model (REMM) (developed by USDA [181,182]) can be an effective way to delineate the specific roles of riparian forest fragmentation on water quality and biological status of streams. Despite the fact that REMM has been shown to be a useful computer tool for simulating the key hydrologic and biogeochemical processes occurring in real world buffers [183,184], the model only takes into account vegetation types in riparian areas. Integrating spatial patterns (e.g., fragmentation) of riparian vegetation into the model would increase its accuracy and usage for different stream environments and geographical locations.…”

Section: Discussionmentioning

confidence: 99%

Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

et al. 2019

View full text Add to dashboard Cite

Anthropogenic activities, such as land use and land cover modifications in riparian areas, can alter the degree of fragmentation of riparian vegetation, lead to the degradation of stream habitats, and affect biological communities in the streams. The characteristics of the riparian forests can modify the condition of stream environments and the transporting mechanisms of materials, sediments, nutrients, and pollutants loaded from the watersheds. This study aimed to examine the relationships between forest fragmentation and three biological indicators of trophic diatom, benthic macroinvertebrate, and the fish assessment in the Nakdong River, Korea. Eighty-nine biological assessment sampling sites in the National Aquatic Ecological Monitoring Program of South Korea were identified. For each sampling site, riparian forest data within a 500 m radius were extracted from national LULC using GIS to compute fragmentation metrics using FRAGSTATS software. Four fragmentation metrics—number of forest patches, percentage of riparian forest cover (PLAND), largest riparian forest patch index (LPI), and riparian forest division index (DIVISION)—were correlated with the biological indicators. Also, due to severe spatial autocorrelation among observations, the fragmentation metrics and stream environmental variables were regressed to biological indicators using regression tree analysis. Our results indicate that the biological indicators were significantly associated with most forest fragmentation metrics. We found positive correlations of PLAND and LPI with biological indicators, whereas DIVISION was negatively correlated with biological indicators. Both correlation and regression tree analyses revealed that the biological conditions of streams were likely to be better if riparian forests are less fragmented. Particularly, stronger relationships were revealed between macroinvertebrates and fish with the fragmentation metrics of riparian forests than with benthic diatoms. However, these relationships varied with elevation, stream size, and slope conditions. The results of this study reinforced the importance of including riparian forests in the planning, restoration, and management of stream environments. These results also suggested that planners and managers may need to consider different strategies for different stream environments and topographic characteristics in managing riparian forests.

show abstract

Section: Discussionmentioning

confidence: 99%

Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Inamdar et al (1999) found that REMM simulations of surface N flow load range from one standard deviation to a full order of magnitude difference from the actual values [95]. Additional studies have conducted sensitivity analyses [27] as well as tested the ability of REMM to simulate total Kjeldahl nitrogen load during storm events [28]. However, there are no studies that we know of that assess the accuracy and precision of REMM in simulating subsurface NO 3 − removal.…”

Section: To What Extent Does Rz-tradeoff Advance Our Ability To Predimentioning

confidence: 99%

“…Over the past few decades, several different modeling approaches described below have been used to evaluate the efficacy of riparian zones for water quality management [8,9,12,[24][25][26][27][28][29][30]. In most cases, existing models for assessing riparian zone functions are however too simplistic (i.e., large error) or too complex (i.e., too hard to parameterize) for practical management-related use.…”

Section: Introductionmentioning

confidence: 99%

“…Process-based models, such as the Riparian Ecosystem Management Model (REMM), offer an alternative to conceptual or GIS based models [25]. REMM modeling suggests wider riparian buffers are more effective at NO 3 − removal and that changes in vegetation cover have limited impact on NO 3 − removal [27]. In general, REMM predicted riparian zone water table depths and NO 3 − concentrations are reported to be in good agreement with measured values [32], with one case showing a 25% difference between REMM predicted and measured surface flow nitrogen loads [28].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

RZ-TRADEOFF: A New Model to Estimate Riparian Water and Air Quality Functions

Hassanzadeh

Vidon

Gold

et al. 2019

Water

View full text Add to dashboard Cite

Riparian zones are often used as best management practices due to their ability to remove nitrate (NO3−) from subsurface flow. Research suggests that beyond local biogeochemical controls, the impact of riparian zones on nitrogen removal and other functions, such as phosphorus dynamics and greenhouse gas emissions, largely depends on land-use/land-cover, hydrogeomorphology, and weather. In this study, we therefore present RZ-TRADEOFF, a novel and easily applicable model that connects multiple riparian functions and characteristics (NO3− and phosphate (PO43−), concentration and removal in subsurface flow, total phosphorus (TP) removal in overland flow, nitrous oxide (N2O), methane (CH4), and carbon dioxide (CO2) emissions, water table) to landscape hydrogeomorphic characteristics, weather, and land-cover/land-use. RZ-TRADEOFF was developed with data from past studies and digital databases, and validated with data collected from the literature. Three functions (water table, PO43− and CO2) were observed to be significantly influenced by climate/weather, while the others were primarily influenced by hydrogeomorphology and land use. The percent bias and normalized root mean square error respectively were −3.35% and 0.28 for water table, 16.00% and 0.34 for NO3− concentration, −7.83% and 20.82 for NO3− removal, 6.64% and 0.35 for PO43− concentration, 2.55% and 0.17 for TP removal, 40.33% and 0.23 for N2O, 72.68% and 0.18 for CH4, and −34.98% and 0.91 for CO2. From a management standpoint, RZ-TRADEOFF significantly advances our ability to predict multiple water and air quality riparian functions using easily accessible data over large areas of the landscape due to its scalability.

show abstract

“…Water Resources Research functions provided by riparian buffer systems (Graff et al, 2005;, Inamdar, Sheridan, et al, 1999 (Grissinger et al, 1991). The significance of channel contributions to overall watershed-scale fine sediment load was verified using several other ARS CEAP Experimental Watersheds (Wilson et al, 2008).…”

Section: Quantification and Modeling Of Riparian Ecosystem Services Imentioning

confidence: 99%

The USDA‐ARS Experimental Watershed Network: Evolution, Lessons Learned, Societal Benefits, and Moving Forward

Goodrich

Heilman

Anderson³

et al. 2021

Water Resources Research

View full text Add to dashboard Cite

The U.S. Department of Agriculture‐Agricultural Research Service's (ARS) Experimental Watershed Network grew from Dust Bowl era efforts of the Soil Conservation Service in the mid‐1930s with the establishment of small experimental watersheds. In the 1950s, five watershed research centers with intensively instrumented watersheds at the scale of 100 to 700 km2 were established. Primary network research objectives were to quantify on‐site and downstream effects of conservation practices and develop rainfall‐runoff relationships for design of water conservation structures. With passage of the Clean Water Act in 1972, research objectives have evolved to add a variety of observations relevant to the water quality issues. Many of the watersheds within the network have served, and continue to serve, as core validation sites for satellite sensors. As a result of the network's long history and intensive monitoring, coupled with mission‐driven research, a deep knowledge base of watershed processes has been developed. This has led to the extensive development and validation of numerous watershed models that are in widespread use today. The visionary investments in building and maintaining this network and associated scientific investigations for more than half a century have not only resulted in numerous high‐impact research accomplishments but also a wide array of accomplishments that directly benefit society. The ARS Experimental Watersheds formed the core of the Conservation Effects Assessment Project (CEAP) as well as the recently established Long‐Term Agroecosystem Research (LTAR) network. LTAR will expand the mission of the ARS Watersheds Network to include agricultural intensification, maintaining or improving ecosystem services while enhancing rural prosperity.

show abstract

Quantifying the Sensitivity of the Riparian Ecosystem Management Model (Remm) to Changes in Climate and Buffer Characteristics Common to Conservation Practices

Cited by 17 publications

References 0 publications

Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

Relationships between Riparian Forest Fragmentation and Biological Indicators of Streams

RZ-TRADEOFF: A New Model to Estimate Riparian Water and Air Quality Functions

The USDA‐ARS Experimental Watershed Network: Evolution, Lessons Learned, Societal Benefits, and Moving Forward

Contact Info

Product

Resources

About