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We utilize a coupled economy–agroecology–hydrology modeling framework to capture the cascading impacts of climate change mitigation policy on agriculture and the resulting water quality cobenefits. We analyze a policy that assigns a range of United States government’s social cost of carbon estimates ($51, $76, and $152/ton of CO₂-equivalents) to fossil fuel–based CO₂emissions. This policy raises energy costs and, importantly for agriculture, boosts the price of nitrogen fertilizer production. At the highest carbon price, US carbon emissions are reduced by about 50%, and nitrogen fertilizer prices rise by about 90%, leading to an approximate 15% reduction in fertilizer applications for corn production across the Mississippi River Basin. Corn and soybean production declines by about 7%, increasing crop prices by 6%, while nitrate leaching declines by about 10%. Simulated nitrate export to the Gulf of Mexico decreases by 8%, ultimately shrinking the average midsummer area of the Gulf of Mexico hypoxic area by 3% and hypoxic volume by 4%. We also consider the additional benefits of restored wetlands to mitigate nitrogen loading to reduce hypoxia in the Gulf of Mexico and find a targeted wetland restoration scenario approximately doubles the effect of a low to moderate social cost of carbon. Wetland restoration alone exhibited spillover effects that increased nitrate leaching in other parts of the basin which were mitigated with the inclusion of the carbon policy. We conclude that a national climate policy aimed at reducing greenhouse gas emissions in the United States would have important water quality cobenefits.

 

Households’ willingness to pay (WTP) for water quality improvements—representing their economic value—depends on where improvements occur. Households often hold higher values for improvements close to their homes or iconic areas. Are there other areas where improvements might hold high value to individual households, do effects on WTP vary by type of improvement, and can these areas be identified even if they are not anticipated by researchers? To answer these questions, we integrated a water quality model and map-based, interactive choice experiment to estimate households’ WTP for water quality improvements throughout a river network covering six New England states. The choice experiment was implemented using a push-to-web survey over a sample of New England households. Voting scenarios used to elicit WTP included interactive geographic information system (GIS) maps that illustrated three water quality measures at various zoom levels across the study domain. We captured data on how respondents maneuvered through these maps prior to answering the value-eliciting questions. Results show that WTP was influenced by regionwide quality improvements and improvements surrounding each respondent’s home, as anticipated, but also by improvements in individualized locations identifiable via each respondent’s map interactions. These spatial WTP variations only appear for low-quality rivers and are focused around particular areas of New England. The study shows that dynamic map interactions can convey salient information for WTP estimation and that predicting spatial WTP heterogeneity based primarily on home or iconic locations, as typically done, may overlook areas where water quality has high value.

 

Anthropogenic nitrogen (N) inputs to the landscape have serious consequences for inland and coastal waters. Reservoirs are effective at mitigating downstream N fluxes but measurements have generally focused on large reservoirs and have not considered seasonal variability or all N forms. In this study, we conducted an N mass balance in eight small reservoirs (surface area <0.55 km²) in coastal New England over annual time periods, including both inorganic and organic forms of N. We found that small reservoirs have high capacity for dissolved inorganic N (DIN) retention during low and moderate discharge, but are roughly in balance for DIN at higher discharge. Because proportional DIN retention occurred when N inputs were at their lowest, their effect on downstream N fluxes is small over annual time frames. Further, dissolved organic N (DON) was also evident during low flow late in the warm season. Accounting for DON production, the net effect of reservoirs on total dissolved N (TDN) fluxes was limited. These transformations between inorganic and organic N should be considered when evaluating the effect of small reservoirs on TDN fluxes over seasonal and annual timescales. With dam removal becoming a common solution to aging, unsafe dams, their ability to retain or produce N must be scrutinized at longer time scales while accounting for the complete N pool to better comprehend the effect their reservoirs have on downstream waters.

 

Fecal contamination is a significant source of water quality impairment globally. Aquatic ecosystems can provide an important ecosystem service of fecal contamination removal. Understanding the processes that regulate the removal of fecal contamination among river networks across flow conditions is critical. We applied a river network model, the Framework for Aquatic Modeling in the Earth System (FrAMES-Ecoli), to quantify removal of fecal indicator bacteria by river networks across flow conditions during summers in a series of New England watersheds of different characteristics. FrAMES-Ecoli simulates sources, transport, and riverine removal of Escherichia coli (E. coli). Aquatic E. coli removal was simulated in both the water column and the hyporheic zone, and is a function of hydraulic conditions, flow exchange rates with the hyporheic zone, and die-off in each compartment. We found that, at the river network scale during summers, removal by river networks can be high (19–99%) with variability controlled by hydrologic conditions, watershed size, and distribution of sources in the watershed. Hydrology controls much of the variability, with 68–99% of network scale inputs removed under base flow conditions and 19–85% removed during storm events. Removal by the water column alone could not explain the observed pattern in E. coli, suggesting that processes such as hyporheic removal must be considered. These results suggest that river network removal of fecal indicator bacteria should be taken into consideration in managing fecal contamination at critical downstream receiving waters. 

Abstract. This paper describes the University of New Hampshire Water Balance Model, WBM, a process-based gridded global hydrologic model that simulates the land surface components of the global water cycle and includes water extraction for use in agriculture and domestic sectors. The WBMwas first published in 1989; here, we describe the first fully open-sourceWBM version (v.1.0.0). Earlier descriptions of WBM methods provide the foundation for the most recent model version that is detailed here. We present an overview of themodel functionality, utility, and evaluation of simulated global riverdischarge and irrigation water use. This new version adds a novel suite ofwater source tracking modules that enable the analysis of flow-path histories on water supply. A key feature of WBM v.1.0.0 is the ability to identify the partitioning of sources for each stock or flux within the model. Three different categories of tracking are available: (1) primary inputs of water to the surface of the terrestrial hydrologic cycle (liquid precipitation, snowmelt, glacier melt, and unsustainable groundwater); (2) water that has been extracted for human use and returned to the terrestrial hydrologic system; and (3) runoff originating from user-defined spatial land units. Such component tracking provides a more fully transparent model in that users can identify the underlying mechanisms generating the simulated behavior. We find that WBM v.1.0.0 simulates global river discharge and irrigation water withdrawals well, even with default parameter settings, and for the first time, we are able to show how the simulation arrives at these fluxes by using the novel tracking functions. 

Inland waters are the largest natural source of methane (CH 4 ) to the atmosphere, yet the contribution from small streams to this flux is not clearly defined. To fully understand CH 4 emissions from streams and rivers, we must consider the relative importance of CH 4 emission pathways, the prominence of microbially-mediated production and oxidation of CH 4 , and the isotopic signature of emitted CH 4 . Here, we construct a complete CH 4 emission budgets for four lowland headwater streams by quantifying diffusive CH 4 emissions and comparing them to previously published rates of ebullitive emissions. We also examine the isotopic composition of CH 4 along with the sediment microbial community to investigate production and oxidation across the streams. We find that all four streams are supersaturated with respect to CH 4 with diffusive emissions accounting for approximately 78–100% of total CH 4 emissions. Isotopic and microbial data suggest CH 4 oxidation is prevalent across the streams, depleting approximately half of the dissolved CH 4 pool before emission. We propose a conceptual model of CH 4 production, oxidation, and emission from small streams, where the dominance of diffusive emissions is greater compared to other aquatic ecosystems, and the impact of CH 4 oxidation is observable in the emitted isotopic values. As a result, we suggest the CH 4 emitted from small streams is isotopically heavy compared to lentic ecosystems. Our results further demonstrate streams are important components of the global CH 4 cycle yet may be characterized by a unique pattern of cycling and emission that differentiate them from other aquatic ecosystems. 

River networks regulate carbon and nutrient exchange between continents, atmosphere, and oceans. However, contributions of riverine processing are poorly constrained at continental scales. Scaling relationships of cumulative biogeochemical function with watershed size (allometric scaling) provide an approach for quantifying the contributions of fluvial networks in the Earth system. Here we show that allometric scaling of cumulative riverine function with watershed area ranges from linear to superlinear, with scaling exponents constrained by network shape, hydrological conditions, and biogeochemical process rates. Allometric scaling is superlinear for processes that are largely independent of substrate concentration (e.g., gross primary production) due to superlinear scaling of river network surface area with watershed area. Allometric scaling for typically substrate-limited processes (e.g., denitrification) is linear in river networks with high biogeochemical activity or low river discharge but becomes increasingly superlinear under lower biogeochemical activity or high discharge, conditions that are widely prevalent in river networks. The frequent occurrence of superlinear scaling indicates that biogeochemical activity in large rivers contributes disproportionately to the function of river networks in the Earth system.

 

Fluvial silicon (Si) plays a critical role in controlling primary production, water quality, and carbon sequestration through supporting freshwater and marine diatom communities. Geological, biogeochemical, and hydrological processes, as well as climate and land use, dictate the amount of Si exported by streams. Understanding Si regimes—the seasonal patterns of Si concentrations—can help identify processes driving Si export. We analyzed Si concentrations from over 200 stream sites across the Northern Hemisphere to establish distinct Si regimes and evaluated how often sites moved among regimes over their period of record. We observed five distinct regimes across diverse stream sites, with nearly 60% of sites exhibiting multiple regime types over time. Our results indicate greater spatial and interannual variability in Si seasonality than previously recognized and highlight the need to characterize the watershed and climate variables that affect Si cycling across diverse ecosystems.