The objective of this study is to produce an observationally based monthly evapotranspiration (ET) product using the simple water balance equation across the conterminous United States (CONUS). We adopted the best quality ground and satellite-based observations of the water budget components, i.e., precipitation, runoff, and water storage change, while ET is computed as the residual. Precipitation data are provided by the bias-corrected PRISM observation-based precipitation data set, while runoff comes from observed monthly streamflow values at 592 USGS stream gauging stations that have been screened by strict quality controls. We developed a land surface model-based downscaling approach to disaggregate the monthly GRACE equivalent water thickness data to daily, 0.1258 values. The derived ET computed as the residual from the water balance equation is evaluated against three sets of existing ET products. The similar spatial patterns and small differences between the reconstructed ET in this study and the other three products show the reliability of the observationally based approach. The new ET product and the disaggregated GRACE data provide a unique, important hydro-meteorological data set that can be used to evaluate the other ET products as a benchmark data set, assess recent hydrological and climatological changes, and terrestrial water and energy cycle dynamics across the CONUS. These products will also be valuable for studies and applications in drought assessment, water resources management, and climate change evaluation.

A novel multisite cascading calibration (MSCC) approach using the shuffled complex evolution-University of Arizona (SCE-UA) optimization method, developed at the University of Arizona, was employed to calibrate the variable infiltration capacity (VIC) model in the Red River Basin. Model simulations were conducted at 35 nested gauging stations. Compared with simulated results using a priori parameters, single-site calibration can improve VIC model performance at specific calibration sites; however, improvement is still limited in upstream locations. The newly developed MSCC approach overcomes this limitation. Simulations using MSCC not only utilize all of the available streamflow observations but also better represent spatial heterogeneities in the model parameters. Results indicate that MSCC largely improves model performance by decreasing the number of stations with negative Nash-Sutcliffe coefficient of efficiency (NSCE) values from 69% (66%) for a priori parameters to 37% (34%) for single-site calibration to 3% (3%) for MSCC, and by increasing the number of stations with NSCE values larger than 0.5 from 9% (9%), to 23% (23%) to 34% (29%) during calibration (and validation) periods across all sites.

Aims: Soil dissolved organic carbon (DOC) is a primary form of labile carbon in terrestrial ecosystems, and therefore plays a vital role in soil carbon cycling. This study aims to quantify the budgets of soil DOC at biome and global levels and to examine the variations in soil DOC and their environmental controls.

Abstract. Severe storm-triggered floods and landslides are two major natural hazards in the US, causing property losses of USD 6 billion and approximately 110-160 fatalities per year nationwide. Moreover, floods and landslides often occur in a cascading manner, posing significant risk and leading to losses that are significantly greater than the sum of the losses from the hazards when acting separately. It is pertinent to couple hydrological and geotechnical modeling processes to an integrated flood-landslide cascading disaster modeling system for improved disaster preparedness and hazard management. In this study, we developed the iCRESTRIGRS model, a coupled flash flood and landslide initiation modeling system, by integrating the Coupled Routing and Excess STorage (CREST) model with the physically based Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability (TRIGRS) landslide model. The iCRESTRIGRS system is evaluated in four river basins in western North Carolina that experienced a large number of floods, landslides and debris flows triggered by heavy rainfall from Hurricane Ivan during 16-18 September 2004. The modeled hourly hydrographs at four USGS gauge stations show generally good agreement with the observations during the entire storm period. In terms of landslide prediction in this case study, the coupled model has a global accuracy of 98.9 % and a true positive rate of 56.4 %. More importantly, it shows an improved predictive capability for landslides relative to the stand-alone TRIGRS model. This study highlights the important physical connection between rainfall, hydrological processes and slope stability, and provides a useful prototype model system for operational forecasting of flood and landslide.

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[1] Mounting evidence supports that wetland ecosystems, one of the largest carbon pools on the earth, are exposed to ample nitrogen (N) additions due to atmospheric deposition or N loading from upstream agricultural fertilizer application. However, our understanding of how N enrichment affects the fluxes of greenhouse gases (GHGs) in wetlands is weak. A 5 year N addition experiment was conducted to examine the responses of CH 4 and N 2 O fluxes as well as ecosystem respiration from wetlands in the Sanjiang Plain, Northeast China, through 2005 to 2009. Four levels of N addition (control, 0 kg N ha À1 yr À1 ; low-level, 60 kg N ha À1 yr À1 ; medium-level, 120 kg N ha À1 yr À1 ; high-level, 240 kg N ha À1 yr À1 ) were designed in this study. Overall, our results show that medium and high levels of N addition increased ecosystem respiration by 28% and 69% (P < 0.05), respectively, while low-level N addition has no effect on ecosystem respiration (P > 0.05). High-level N fertilization exerted stronger effects on ecosystem respiration in the initial year than the following years. It indicated that the effects of high-level N fertilization on CO 2 might be overestimated by short-term observations. High-level N fertilization increased N 2 O emissions by 396% over the 5 years (P < 0.05), but the low-and medium-level-N addition did not exert any apparent effect on N 2 O emissions (P > 0.05). N 2 O emission under high-level N addition in the first and fifth years showed stronger pronounced responses to N addition compared with that from the third and fourth years, indicating the importance of long-term field observation. Over the 5 years, however, the low and medium-level N addition showed no effect on N 2 O emissions. The four levels of N addition exerted no effect on CH 4 emissions (P > 0.05). Furthermore, the relationship between GHGs and soil temperature or water table depth varied among different plots and experimental time. Our findings highlighted the importance of gas species, experimental time, and the amount of fertilizer N with regard to the responses of GHG emissions to N fertilization.Citation: Song, C., L. Wang, H. Tian, D. Liu, C. Lu, X. Xu, L. Zhang, G. Yang, and Z. Wan (2013), Effect of continued nitrogen enrichment on greenhouse gas emissions from a wetland ecosystem in the Sanjiang Plain, Northeast China: A 5 year nitrogen addition experiment,

Wetlands regulate the balance of global organic carbon. Small changes in the carbon stocks of wetland ecosystem play a crucial role in the regional soil carbon cycle. However, an accurate estimation of carbon stocks is still be debated for China’s wetlands ecosystem due to the limitation of data collection and methodology. Here, we investigate the soil organic carbon (SOC) storage in a 1-m depth in China’s palustrine wetlands. A total of 1383 sample data were collected from palustrine wetlands in China. The data sources are divided into three parts, respectively, data collection from published literature, data from books, and actual measurement data of sample points. The results demonstrate that there is considerable SOC storage in China’s palustrine wetlands (9.945 Pg C), primarily abundant in the northeast, northwest arid and semi-arid as well as Qinghai-Tibet Plateau regions. The SOC density in per unit area soil was higher in the wetland area of northeast, southwest and Qinghai-Tibet plateau. Within China terrestrial scale, the temperature and precipitation differences caused by latitude were the main environmental factors affecting the organic carbon content. Furthermore, except for the southeast and south wetland region, SOC content decreased with depth.

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