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...

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Bibliographic Details
Main Authors: J. Deng, Z. Zhou, B. Zhu, X. Zheng, C. Li, X. Wang, Z. Jian
Format: Article
Language:English
Published: Copernicus Publications 2011-10-01
Series:Biogeosciences
Online Access:http://www.biogeosciences.net/8/2999/2011/bg-8-2999-2011.pdf
Description
Summary: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's 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<sup>−1</sup>, of which approximately 67 % came from the croplands. The enhanced DNDC model also estimated the watershed-scale N losses (1391 kg N yr<sup>−1</sup>) from the emissions of the N-containing gases (ammonia, nitrous oxide, nitric oxide, and dinitrogen). Ammonia volatilization (1299 kg N yr<sup>−1</sup>) 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.
ISSN:1726-4170
1726-4189