Soil is the largest organic carbon (C) pool of terrestrial ecosystems, and C loss from soil accounts for a large proportion of land-atmosphere C exchange. Therefore, a small change in soil organic C (SOC) can affect atmospheric carbon dioxide (CO2) concentration and climate change. In the past decades, a wide variety of studies have been conducted to quantify global SOC stocks and soil C exchange with the atmosphere through site measurements, inventories, and empirical/process-based modeling. However, these estimates are highly uncertain, and identifying major driving forces controlling soil C dynamics remains a key research challenge. This study has compiled century-long (1901-2010) estimates of SOC storage and heterotrophic respiration (Rh) from 10 terrestrial biosphere models (TBMs) in the Multi-scale Synthesis and Terrestrial Model Intercomparison Project and two observation-based data sets. The 10 TBM ensemble shows that global SOC estimate ranges from 425 to 2111Pg C (1Pg=10(15)g) with a median value of 1158Pg C in 2010. The models estimate a broad range of Rh from 35 to 69PgCyr(-1) with a median value of 51PgCyr(-1) during 2001-2010. The largest uncertainty in SOC stocks exists in the 40-65 degrees N latitude whereas the largest cross-model divergence in Rh are in the tropics. The modeled SOC change during 1901-2010 ranges from -70Pg C to 86Pg C, but in some models the SOC change has a different sign from the change of total C stock, implying very different contribution of vegetation and soil pools in determining the terrestrial C budget among models. The model ensemble-estimated mean residence time of SOC shows a reduction of 3.4years over the past century, which accelerate C cycling through the land biosphere. All the models agreed that climate and land use changes decreased SOC stocks, while elevated atmospheric CO2 and nitrogen deposition over intact ecosystems increased SOC stockseven though the responses varied significantly among models. Model representations of temperature and moisture sensitivity, nutrient limitation, and land use partially explain the divergent estimates of global SOC stocks and soil C fluxes in this study. In addition, a major source of systematic error in model estimations relates to nonmodeled SOC storage in wetlands and peatlands, as well as to old C storage in deep soil layers.

A mechanistic model was developed to predict midsummer bottom-water dissolved oxygen (BWDO) concentration and hypoxic area on the Louisiana shelf of the northern Gulf of Mexico, USA (1985-2011). Because of its parsimonious formulation, the model possesses many of the benefits of simpler, more empirical models, in that it is computationally efficient and can rigorously account for uncertainty through Bayesian inference. At the same time, the model incorporates important biophysical processes such that its parameterization can be informed by field-measured biological and physical rates. The model is used to explore how freshwater flow, nutrient load, benthic oxygen demand, and wind velocity affect hypoxia on the western and eastern sections of the shelf, delineated by the Atchafalaya River outfall. The model explains over 70% of the variability in BWDO on both shelf sections, and outperforms linear regression models developed from the same input variables. Model results suggest that physical factors (i.e., wind and flow) control a larger portion of the year-to-year variability in hypoxia than previously thought, especially on the western shelf, though seasonal nutrient loads remain an important driver of hypoxia, as well. Unlike several previous Gulf hypoxia modeling studies, results do not indicate a temporal shift in the system's propensity for hypoxia formation (i.e., no regime change). Results do indicate that benthic oxygen demand is a substantial BWDO sink, and a better understanding of the long-term dynamics of this sink is required to better predict how the size of the hypoxic zone will respond to proposed reductions in nutrient loading.

Harmful algal blooms (HABs) are becoming increasingly common in freshwater ecosystems globally, raising complex questions about the factors that influence their initiation and growth. These questions have increasingly been answered through mechanistic and stochastic modeling efforts that rely on historical information about HABs in a given system for development, validation, and calibration. Therefore, understanding processes that control HABs is predicated on the ability to answer much more basic questions about what has actually occurred in a given system, namely questions of HAB occurrence, extent, intensity, and timing. Here we explore the state of the science in answering these basic questions; we use Lake Erie as a case study, where nearly two decades after the resurgence of HABs, a summer 2014 event caused a mandatory three day tap water ban for Toledo, Ohio. We find that, even for well-studied systems, unambiguous answers to basic questions about HAB occurrence are lacking, raising concerns about their use as a basis for addressing mechanistic questions about controlling factors. This ambiguity is found to be caused by differences in the methods used to track HABs, the specific harm being considered, the linkage to that harm (direct or indirect), the threshold defining harm, and spatiotemporal variability in sampling. Further work is therefore needed to integrate heterogeneous types of observations in order to better leverage existing and future monitoring programs, and to guide modeling efforts toward deeper understanding of HAB causes and consequences. (C) 2015 The Authors. Published by Elsevier B.V. on behalf of International Association for Great Lakes Research. This is an open access article under the CC BY-NC-ND.

Global gridded maps (a. k. a. Level 3 products) of Earth system properties observed by satellites are central to understanding the spatiotemporal variability of these properties. They also typically serve either as inputs into biogeochemical models or as independent data for evaluating such models. Spatial binning is a common method for generating contiguous maps, but this approach results in a loss of information, especially when the measurement noise is low relative to the degree of spatiotemporal variability. Such "binned" fields typically also lack a quantitative measure of uncertainty.

We examined natural and anthropogenic controls on terrestrial evapotranspiration (ET) changes from 1982 to 2010 using multiple estimates from remote sensing-based datasets and process-oriented land surface models. A significant increasing trend of ET in each hemisphere was consistently revealed by observationally-constrained data and multi-model ensembles that considered historic natural and anthropogenic drivers. The climate impacts were simulated to determine the spatiotemporal variations in ET. Globally, rising CO2 ranked second in these models after the predominant climatic influences, and yielded decreasing trends in canopy transpiration and ET, especially for tropical forests and high-latitude shrub land. Increasing nitrogen deposition slightly amplified global ET via enhanced plant growth. Land-use-induced ET responses, albeit with substantial uncertainties across the factorial analysis, were minor globally, but pronounced locally, particularly over regions with intensive land-cover changes. Our study highlights the importance of employing multi-stream ET and ET-component estimates to quantify the strengthening anthropogenic fingerprint in the global hydrologic cycle.

We present an overview of the contributions collected to celebrate the fiftieth anniversary of Water Resources Research along with a critical discussion of the legacy and perspectives for the science of hydrology in the 21st century. This collection of papers highlights exciting pathways to the future of water sciences. New monitoring and modeling techniques and increasing opportunities for data and knowledge sharing from hydrological research will provide innovative means to improve water management and to ensure a sustainable development to society. We believe that this set of papers will provide valuable inspiration for future hydrologists, and will support the intensification of international cooperation among scientists.

On behalf of the journal, AGU, and the scientific community, the editors would like to sincerely thank those who reviewed manuscripts for Water Resources Research in 2015. The hours reading and commenting on manuscripts not only improves the manuscripts themselves but it also increases the scientific rigor of future research in the field. Many of those listed below went beyond and reviewed three or more manuscripts for our journal, and those are indicated in italics. The refereeing contributions they made contributed to 3622 individual reviews of 1434 manuscripts. Thank you again. We look forward to a 2016 of exciting advances in the field and communicating those advances to our community and to the broader public.

The year 2015 marks the 50th anniversary of Water Resources Research (WRR), which was founded in 1965. More than 15,000 papers have been published in WRR since its inception, and these papers have been cited more than 430,000 times. The history of hydrology and the water sciences are also reflected in WRR, which has served as a premier publication outlet and instigator of scientific growth over the last 50 years. The legacy of WRR provides a strong scientific foundation for the hydrology community to rise to the challenges of sustainable water resources management in a future where dramatic environmental change and increasing human population are expected to stress the world's water resources from local to global scales.

Existing estimates of methane (CH4) fluxes from North American wetlands vary widely in both magnitude and distribution. In light of these differences, this study uses atmospheric CH4 observations from the US and Canada to analyze seven different bottom-up, wetland CH4 estimates reported in a recent model comparison project. We first use synthetic data to explore whether wetland CH4 fluxes are detectable at atmospheric observation sites. We find that the observation network can detect aggregate wetland fluxes from both eastern and western Canada but generally not from the US. Based upon these results, we then use real data and inverse modeling results to analyze the magnitude, seasonality, and spatial distribution of each model estimate. The magnitude of Canadian fluxes in many models is larger than indicated by atmospheric observations. Many models predict a seasonality that is narrower than implied by inverse modeling results, possibly indicating an oversensitivity to air or soil temperatures. The LPJ-Bern and SDGVM models have a geographic distribution that is most consistent with atmospheric observations, depending upon the region and season. These models utilize land cover maps or dynamic modeling to estimate wetland coverage while most other models rely primarily on remote sensing inundation data.

The terrestrial biosphere can release or absorb the greenhouse gases, carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), and therefore has an important role in regulating atmospheric composition and climate1. Anthropogenic activities such as land-use change, agriculture and waste management have altered terrestrial biogenic greenhouse gas fluxes, and the resulting increases in methane and nitrous oxide emissions in particular can contribute to climate change(2,3). The terrestrial biogenic fluxes of individual greenhouse gases have been studied extensively(4-6), but the net biogenic greenhouse gas balance resulting from anthropogenic activities and its effect on the climate system remains uncertain. Here we use bottom-up (inventory, statistical extrapolation of local flux measurements, and process-based modelling) and top-down (atmospheric inversions) approaches to quantify the global net biogenic greenhouse gas balance between 1981 and 2010 resulting from anthropogenic activities and its effect on the climate system. We find that the cumulative warming capacity of concurrent biogenic methane and nitrous oxide emissions is a factor of about two larger than the cooling effect resulting from the global land carbon dioxide uptake from 2001 to 2010. This results in a net positive cumulative impact of the three greenhouse gases on the planetary energy budget, with a best estimate (in petagrams of CO2 equivalent per year) of 3.9 +/- 3.8 (top down) and 5.4 +/- 4.8 (bottom up) based on the GWP100 metric (global warming potential on a 100-year time horizon). Our findings suggest that a reduction in agricultural methane and nitrous oxide emissions, particularly in Southern Asia, may help mitigate climate change.