Modeling nitrogen loading in a small watershed in southwest China using a DNDC model with hydrological enhancements

The degradation of water quality has been observed worldwide, and inputs of nitrogen (N), along with other nutrients, play a key role in the process of contamination. The quantification of N loading from non-point sources at a watershed scale has long been a challenge. Process-based models have been developed to address this problem. Because N loading from non-point sources result from interactions between biogeochemical and hydrological processes, a model framework must include both types of processes if it is to be useful. This paper reports the results of a study in which we integrated two fundamental hydrologic features, the SCS (Soil Conservation Service) curve function and the MUSLE (Modified Universal Soil Loss), into a biogeochemical model, the DNDC. The SCS curve equation and the MUSLE are widely used in hydrological models for calculating surface runoff and soil erosion. Equipped with the new added hydrologic features, DNDC was substantially enhanced with the new capacity of simulating both vertical and horizontal movements of water and N at a watershed scale. A long-term experimental watershed in Southwest China was selected to test the new version of the DNDC. The target watershed\u27s 35.1 ha of territory encompass 19.3 ha of croplands, 11.0 ha of forest lands, 1.1 ha of grassplots, and 3.7 ha of residential areas. An input database containing topographic data, meteorological conditions, soil properties, vegetation information, and management applications was established and linked to the enhanced DNDC. Driven by the input database, the DNDC simulated the surface runoff flow, the subsurface leaching flow, the soil erosion, and the N loadings from the target watershed. The modeled water flow, sediment yield, and N loading from the entire watershed were compared with observations from the watershed and yielded encouraging results. The sources of N loading were identified by using the results of the model. In 2008, the modeled runoff-induced loss of total N from the watershed was 904 kg N yr−1, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr−1) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr−1) dominated the gaseous N losses. The study indicated that process-based biogeochemical models such as the DNDC could contribute more effectively to watershed N loading studies if the hydrological components of the models were appropriately enhanced

Annual emissions of nitrous oxide and nitric oxide from rice-wheat rotation and vegetable fields: a case study in the Tai-Lake region, China

Background and aims: Knowledge on nitrous oxide (N2O) and nitric oxide (NO) emissions from typical cropping systems in the Tai-Lake region is important for estimating regional inventory and proposing effective N2O and NO mitigation options. This study aimed at a) characterizing the seasonal and annual emissions of both gases from the major cropping systems, and b) determining their direct emission factors (EFds) as the key parameters for inventory compilation. Methods: Measurements of N2O and NO emissions were conducted year-round in the Tai-Lake region using a static opaque chamber method. The measurements involved a typical rice-wheat rotation ecosystem and a vegetable field. The two types of croplands were subjected to both a fertilized treatment and a control treatment without nitrogen addition. In the rice-wheat ecosystem, N2O emissions were measured throughout an entire year-round rotation spanning from June 2003 to June 2004, whereas NO emissions were measured only during the non-rice period. In the vegetable field, both N2O and NO emissions were measured from November 2003 to November 2004. Results: During the investigation period, the average cumulative N2O and NO emissions under the fertilized conditions amounted to 3.80 and 0.80 (during the non-rice period for NO) kg N ha−1, respectively, in the rice-wheat field, and 20.81 and 47.13 kg N ha−1, respectively, in the vegetable field. The average total N2O and NO emissions under the control conditions were 1.39 and 0.29 (during the non-rice period for NO) kg N ha−1, respectively, in the rice−wheat rotation, and 2.98 and 0.80 kg N ha−1, respectively, in the vegetable field. The direct emission factor (EFd, which is defined as the loss rate of applied nitrogen via N2O or NO emissions in the current season or year) of N2O was annually determined to be 0.56 % in the rice-wheat field, while the seasonal EFd of NO was 0.34 % during the non-rice period of the rotation cycle. In the vegetable field, the seasonal EFds of N2O and NO varied from 0.15 % to 14.50 % and 0.80 % to 28.21 %, respectively, among different crop seasons; and the annual EFds were 1.38 % and 3.59 %, respectively. Conclusions: This study suggests that conventional vegetable fields associated with intensive synthetic nitrogen application, as well as addition of manure slurry, may substantially contribute to the regional N2O and NO emissions though they account for a relatively small portion of the farmlands in the Tai-Lake region. However, further studies to be conducted at multiple field sites with conventional vegetable and rice-based fields are needed to test this conclusion

N2O emissions from a cultivated mollisol: optimal time of day for sampling and the role of soil temperature

The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG