Item talk:Q228211

From geokb

{

 "@context": "http://schema.org/",
 "@type": "WebPage",
 "additionalType": "Project",
 "url": "https://www.usgs.gov/programs/climate-research-and-development-program/science/water-quality-across-regional-stream",
 "headline": "Water Quality Across Regional Stream Networks: The Influence of Land Cover and Land Use, Climate, and Biogeochemical Processing on Spatiotemporal Variance",
 "datePublished": "April 17, 2019",
 "author": [
   {
     "@type": "Person",
     "name": "Kimberly Wickland",
     "url": "https://www.usgs.gov/staff-profiles/kimberly-wickland",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0002-6400-0590"
     }
   },
   {
     "@type": "Person",
     "name": "Edward Stets",
     "url": "https://www.usgs.gov/staff-profiles/edward-stets",
     "identifier": {
       "@type": "PropertyValue",
       "propertyID": "orcid",
       "value": "0000-0001-5375-0196"
     }
   }
 ],
 "description": [
   {
     "@type": "TextObject",
     "text": "Statement of Problem: Land cover and land use (LC/LU), climate, and biogeochemical processing are significant drivers of the concentrations and loads of carbon, nutrients (nitrogen and phosphorus), and products of geologic weathering in streams and rivers over broad spatial and temporal scales. While knowledge of watershed LC/LU can help explain water quality at a given location, the spatial and temporal influence is likely to vary by type of constituent, hydrologic regime, and intensity of the specific LC/LU. A common generalization is that water quality across headwater streams (starting point of streams) is highly variable in time and space, and that water quality variability decreases with downstream transport and the incorporation of water from a greater contributing area. While this is a reasonable generalization, this type of analysis is relatively untested for a broad range of constituents and spatial and temporal scales."
   },
   {
     "@type": "TextObject",
     "text": "Extreme contrasts in land cover and land use exist in the basin which contains areas of intense agricultural usage, large urban centers, and relatively undeveloped forests and wetlands (Figure 1b).  Furthermore, large differences in the underlying geology of the region create differences in major ions concentrations and fluxes.  The western part of the basin is mostly glacial moraine deposits with high concentrations of calcium, alkalinity, and other weathering products.  The eastern part of the basin is underlain with extensive sand deposits and tends to have more dilute surface waters that are higher in iron and dissolved organic carbon.  The east and west portions of the basin contribute approximately equally to streamflow, but the timing, intensity, and geographic location of runoff events can vary dramatically throughout the year.  Therefore, this basin provides a unique opportunity to investigate how network connections create water quality conditions in a diverse, medium-sized watershed."
   },
   {
     "@type": "TextObject",
     "text": "Land cover and land use (LC/LU), climate, and biogeochemical processing are significant drivers of water quality in streams and rivers over broad scales of space and time. As LC/LU and climate continue to change we can expect changes in water quality. This project seeks to understand the drivers of spatial and temporal variability in water quality across scales using new and existing data to improve our ability to predict the impact of changing LC/LU and climatic anomalies on water quality in regional stream networks. Our study focuses on the Upper Mississippi River Basin as an ideal location to make progress in this area due to its size, LC/LU distribution, and regional importance."
   },
   {
     "@type": "TextObject",
     "text": "In this project we propose to investigate the spatiotemporal variance of water quality in stream networks using existing and newly acquired data from multiple watersheds varying in size, LC/LU, climate, and geologic setting to advance our understanding and predictions of surface water carbon and nutrients dynamics across scales. This project will build upon recent efforts in the Upper Mississippi River Basin (UMRB), which focused on targeted water quality sampling and the concentrations, fluxes, and transformation of carbon, nitrogen, and major ions throughout the watershed from headwater streams to the mainstem Mississippi River over two years, 2015-2017. The UMRB, which we define as the area upstream of Lock & Dam 8 near LaCrosse, WI, provides an ideal opportunity to investigate network-level connections in a nationally significant watershed (Figure 1a)."
   },
   {
     "@type": "TextObject",
     "text": "Methods: This project will leverage existing data in the UMRB watershed which was collected with the purpose of understanding the spatial and temporal structure of carbon fluxes and includes important data on nitrogen and major ions across scales and distinct systems. This data will greatly enhance our ability to utilize headwater stream information to predict downstream water quality, and to target locations for increased monitoring for applications such as hazard assessment and effectiveness of management activities. We will also collect new data in the UMRB aimed at increasing coverage of small streams across the diverse LC/LU types (especially agriculture) under high and low flow conditions. We will use short-term, high-frequency sensor field deployments and experimentation to discern rates and spatial distribution of relevant in-stream biogeochemical processes to use as a basis for filling knowledge gaps and for conceptual model development of stream network water quality."
   },
   {
     "@type": "TextObject",
     "text": "Objective(s): This project will address the following questions:"
   },
   {
     "@type": "TextObject",
     "text": "Why this Research is Important: Water quality impacts the health of humans, wildlife, and habitat, and has important economic implications for water treatment facilities, recreation, and food supply. It is vital to understand the complex drivers of water quality in stream networks to predict the outcome of human activity and climate change on water quality, and for identifying effective mitigation techniques for water quality management. Our proposed work will advance our ability to integrate watershed and process-level information across scales in a meaningful way and contribute to efforts such as water quality model development."
   }
 ],
 "funder": {
   "@type": "Organization",
   "name": "Climate Research and Development Program",
   "url": "https://www.usgs.gov/programs/climate-research-and-development-program"
 },
 "about": [
   {
     "@type": "Thing",
     "name": "Science Technology"
   },
   {
     "@type": "Thing",
     "name": "upper mississippi river basin"
   },
   {
     "@type": "Thing",
     "name": "Water Quality"
   },
   {
     "@type": "Thing",
     "name": "Cycling of Carbon and Nutrients"
   },
   {
     "@type": "Thing",
     "name": "Wetlands"
   },
   {
     "@type": "Thing",
     "name": "Methods and Analyses"
   },
   {
     "@type": "Thing",
     "name": "Coastal and Wetland Ecosystems"
   },
   {
     "@type": "Thing",
     "name": "carbon cycle"
   },
   {
     "@type": "Thing",
     "name": "Ecosystem Services"
   },
   {
     "@type": "Thing",
     "name": "Maps and Mapping"
   },
   {
     "@type": "Thing",
     "name": "Landscape Change and Impacts"
   },
   {
     "@type": "Thing",
     "name": "Forests"
   },
   {
     "@type": "Thing",
     "name": "Biogeochemical Cycling"
   },
   {
     "@type": "Thing",
     "name": "Water"
   },
   {
     "@type": "Thing",
     "name": "Climate Change"
   },
   {
     "@type": "Thing",
     "name": "Water Quality and Quantity"
   },
   {
     "@type": "Thing",
     "name": "Information Systems"
   },
   {
     "@type": "Thing",
     "name": "Ecosystems"
   },
   {
     "@type": "Thing",
     "name": "Drought and Floods"
   },
   {
     "@type": "Thing",
     "name": "Methods and Analysis"
   },
   {
     "@type": "Thing",
     "name": "Ecosystem Modelling"
   },
   {
     "@type": "Thing",
     "name": "Energy"
   },
   {
     "@type": "Thing",
     "name": "Hydrologic Change"
   },
   {
     "@type": "Thing",
     "name": "Biology"
   },
   {
     "@type": "Thing",
     "name": "Environmental Health"
   },
   {
     "@type": "Thing",
     "name": "Geology"
   }
 ]

}