Effect of Hydrologic Export on Soil Carbon Turnover Rates

Author(s):  
Oleksandra Hararuk ◽  
Stuart Jones ◽  
Christopher Solomon

<p>Soil is the largest terrestrial carbon (C) reservoir and is an important component of climate-carbon feedbacks, potentially sequestering or releasing large amounts CO<sub>2</sub> from or to the atmosphere. In global land models soil C dynamics is determined by the long-term balance between C inputs and turnover rates, and the latter are usually a function of soil texture, temperature, and soil moisture, which represents environmental limitation of microbial soil organic carbon (SOC) mineralization. Hydrologic C export is often overlooked in the terrestrial C cycle models, likely because proportionally soils contain a very small amount of C that can be exported with runoff, contributing around 2.9 Pg C yr<sup>-1</sup> to aquatic systems globally. However, ignoring hydrologic C export in areas, where it has substantial effect on SOC turnover rate, could result in systematic overestimation of SOC stocks and inaccurate simulation of SOC responses to changing environmental conditions. We combined water quality data from the United States Geological Survey with hydrologic and soil chemistry data products to estimate the relative contribution of hydrologic export to bulk soil turnover rates across the continental USA. The catchment area weighted average of hydrologic export effect on SOC turnover was 5.2%. Hydrologic export accounted for 0-2% of the bulk SOC turnover in arid regions, 2-15% - in forests, and 20-40% - in wetland-rich areas. The SOC stocks generated for the continental U.S. using microbe-mediated turnover alone amounted to 88.3 Pg C and were 15.4% higher than the amount reported in the Harmonized World Soil Database (76.5 Pg C), thus illustrating the importance of accounting for hydrologic C export when simulating SOC dynamics.</p>

2019 ◽  
Vol 31 (5) ◽  
pp. 492-506
Author(s):  
John Millar Carroll ◽  
Jordan Beck ◽  
Elizabeth W Boyer ◽  
Shipi Dhanorkar ◽  
Srishti Gupta

Abstract Access to clean water is a critical challenge and opportunity for community-level collaboration. People rely on local water sources, but awareness of water quality and participation in water management is often limited. Lack of community engagement can increase risks of water catastrophes, such as those in Flint, Michigan, and Cape Town, South Africa. We investigated water quality practices in a watershed system serving c.100 000 people in the United States. We identified a range of entities including government and nonprofit citizen groups that gather water quality data. Many of these data are accessible in principle to citizens. However, the data are scattered and diverse; information infrastructures are primitive and not integrated. Water quality data and data practices are hidden in plain sight. Based on fieldwork, we consider sociotechnical courses of action, drawing on best practices in human–computer interaction and community informatics, data and environmental systems management.


Radiocarbon ◽  
2013 ◽  
Vol 55 (2) ◽  
pp. 1071-1076 ◽  
Author(s):  
W Troy Baisden ◽  
E D Keller

Time-series radiocarbon measurements have substantial ability to constrain the size and residence time of the soil C pools commonly represented in ecosystem models. 14C remains unique in its ability to constrain the size and turnover rate of the large stabilized soil C pool with roughly decadal residence times. The Judgeford soil, near Wellington, New Zealand, provides a detailed 11-point 14C time series enabling observation of the incorporation and loss of bomb 14C in surface soil from 1959–2002. Calculations of the flow of C through the plant-soil system can be improved further by combining the known constraints of net primary productivity (NPP) and 14C-derived C turnover. We show the Biome-BGC model provides good estimates of NPP for the Judgeford site and estimates NPP from 1956–2010. Synthesis of NPP and 14C data allows parameters associated with the rapid turnover “active” soil C pool to be estimated. This step is important because it demonstrates that NPP and 14C can provide full data-based constraint of pool sizes and turnover rates for the 3 pools of soil C used in nearly all ecosystem and global C-cycle models.


2017 ◽  
Vol 03 (04) ◽  
pp. 1750006 ◽  
Author(s):  
Travis Warziniack ◽  
Chi Ho Sham ◽  
Robert Morgan ◽  
Yasha Feferholtz

This paper studies the relationship between forest cover and drinking water chemical treatment costs using land use data and a survey by the American Water Works Association (AWWA). The survey gathers cost and water quality data from 37 treatment plants in forested ecoregions of the United States. We model the effect of forest conversion on the cost of water treatment using a two-step process. First, we examine the effect of changes in land use on water quality through an ecological production function. Second, we examine the effect of changes in water quality on cost of treatment through an economic benefits function. We find a negative relationship between forest cover and turbidity, but no relationship between forest cover and total organic carbon (TOC). Increasing forest cover in a watershed by 1% reduces turbidity by 3%, and increasing development by 1% in a watershed increases turbidity by 3%. The impact of development is more consistent across models than the impact of forest cover. We also find a large impact on turbidity from grazing in the watershed. Our economic benefits function shows a 1% increase in turbidity increases water treatment costs by 0.19%, and 1% increase in TOC increases water treatment costs by 0.46%. TOC has a clearer impact on costs than turbidity, which becomes insignificant when we omit one of our observations with high turbidity.


2010 ◽  
Vol 61 (10) ◽  
pp. 2681-2688 ◽  
Author(s):  
P. M. Bach ◽  
D. T. McCarthy ◽  
A. Deletic

The management of stormwater pollution has placed particular emphasis on the first flush phenomenon. However, definition and current methods of analyses of the phenomena contain serious limitations, the most important being their inability to capture a possible impact of the event size (total event volume) on the first flush. This paper presents the development of a novel approach in defining and assessing the first flush that should overcome these problems. The phenomenon is present in a catchment if the decrease in pollution concentration with the absolute cumulative volume of runoff from the catchment is statistically significant. Using data from seven diverse catchments around Melbourne, Australia, changes in pollutant concentrations for Total Suspended Solids (TSS) and Total Nitrogen (TN) were calculated over the absolute cumulative runoff and aggregated from a collection of different storm events. Due to the discrete nature of the water quality data, each concentration was calculated as a flow-weighted average at 2 mm runoff volume increments. The aggregated concentrations recorded in each increment (termed as a ‘slice’ of runoff) were statistically compared to each other across the absolute cumulative runoff volume. A first flush is then defined as the volume at which concentrations reach the ‘background concentration’ (i.e. the statistically significant minimum). Initial results clearly highlight first flush and background concentrations in all but one catchment supporting the validity of this new approach. Future work will need to address factors, which will help assess the first flush's magnitude and volume. Sensitivity testing and correlation with catchment characteristics should also be undertaken.


1999 ◽  
Vol 39 (12) ◽  
pp. 9-16 ◽  
Author(s):  
James T. Smullen ◽  
Amy L. Shallcross ◽  
Kelly A. Cave

Urban stormwater quality data collected over the past 20 years for several large government-sponsored sampling programs in the United States were assembled and analyzed to develop new nationwide estimators and statistics for urban storm water quality. We believe that this is the first attempt to assemble and analyze these major storm water quality data sets for this purpose. In this paper, the first public report of our work to-date, we present the results of the data acquisition, data base assembly, quality assurance, computation of new stormwater event mean concentrations and associated statistics, and comparisons with the original U.S. Environmental Protection Agency's Nationwide Urban Runoff Program (NURP) results. The differences between the pooled means and those estimated from our analysis of the NURP data range from a 79% lower estimate for Copper to a 36% higher estimate for Biochemical Oxygen Demand. It is concluded that the variations between the NURP results and those developed here from the pooling of the three national data bases are important and that future work may provide a basis for differentiating Event Mean Concentrations among urban land uses, geographic region and seasons.


Author(s):  
Rakesh Joshi ◽  
Nathan Bane ◽  
Justin Derickson ◽  
Mark E. Williams ◽  
Abhijit Nagchaudhuri

STRIDER: Semi-Autonomous Tracking Robot with Instrumentation for Data-Acquisition and Environmental Research, a semi-autonomous aquatic vessel, was envisioned for automated water sampling, data collection, and depth profiling to document water quality variables related to agricultural run-offs. Phase-I of the STRIDER project included the capability for STRIDER to collect water samples and water quality data on the surface of water bodies. This paper discusses the Phase-II efforts of the project, in which the previous design of STRIDER was adapted to extend its capabilities to include monitoring, depth profiling, and visualization of in-situ water quality data at various depths as well as collect water samples at each depth for bacterial analysis. At present, the vessel has been utilized for navigation to specified locations using remote control for collecting water quality data and water samples from the surface, as well as 2 feet and 4 feet below the surface at multiple UMES ponds. In a series of preliminary trial runs with the supervision of UMES faculty members and collaborators from the United States Department of Agriculture (USDA), STRIDER successfully collected 48 water samples for bacterial analysis at different locations and depths of ponds on the UMES campus. Design alternatives are being explored for more efficient water sampling capabilities.


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