Influence of anthropogenic nitrogen inputs and legacy nitrogen change on riverine nitrogen export in areas with high agricultural activity.

Increased riverine nitrogen (N) concentrations due to human activities is one of the leading causes of water quality decline, worldwide. Therefore, quantitative information about the N exported from watershed to the river (TN exports) is essential for defining N pollution control practices. This paper evaluated the changes in net anthropogenic N inputs (NANI) and the N stored in land ecosystems (legacy N) in the Jianghan Plain (JHP) from 1990 to 2019 and their impacts on TN exports. Moreover, an empirical model was developed to estimate TN exports, trace its source, and predict its future variations in 2020-2035 under different scenarios. According to the results, NANI exhibited a rise-decrease-rise-decrease M-shaped trend, with N fertilizer application being the dominant driver for NANI change. In terms of the NANI components, non-point-source was the primary N input form (96%). Noteworthy is that the correlation between NANI and TN exports became weaker over time, and large differences in changing trends were observed after 2014. A likely cause for this abnormal trend was that the accumulation of N surplus in soil led to N saturation in agricultural areas. Legacy N was also an important source of TN exports. However, the contribution of legacy N has rarely been considered when defining N pollution control strategies. An empirical model, incorporating legacy N, agricultural irrigation water use, and cropland area ratio, was developed. Based on this model, legacy N contributed a large proportion (15-31%). Furthermore, the results of future predictions indicated that legacy N had a larger impact on future TN exports changes compared to other factors, and increased irrigation water would increase rather than decrease TN exports. Therefore, an integrated N management strategy considering the impact of NANI, legacy N, and irrigation water use is crucial to control N pollution in areas with intensive agriculture.

Dynamic characteristics of net anthropogenic phosphorus input and legacy phosphorus reserves under high human activity - A case study in the Jianghan Plain.

The increase of phosphorus (P) input related to human activities is one of the main reasons for eutrophication. Notably, in areas with high population densities and intensive agricultural activities, eutrophication has occurred frequently in the Jianghan Plain, so quantitative evaluation of anthropogenic P input is of great significance for the formulation of P pollution control measures. This study estimated net anthropogenic P input (NAPI), riverine total P exports (TP exports), and the pool of P stored in the terrestrial system (legacy P reserves) at the county scale from 1990 to 2019 in the Jianghan Plain. The results showed that NAPI increased from 2645 kg·km-2·yr-1 in 1991 to 5812 kg·km-2·yr-1 in 2014, and then decreased to 4509 kg·km-2·yr-1 in 2019. Non-point sources were the main form of NAPI, of which 75-96% came from agricultural systems. Meanwhile, P fertilizer input was the largest source of NAPI. It is worth noting that the contribution of seed P input in some counties, such as Jiangling County, is relatively high, even exceeding that of net food/feed P input. The P fertilizer application and livestock density were the main drivers for NAPI change. Only 3% of NAPI was exported into rivers, so a large amount of legacy P accumulated in the terrestrial system. An empirical model incorporating NAPI components, cultivated land area ratio, and annual precipitation was established. Based on this model, the average contribution of annual NAPI and the sum of legacy P and natural background sources to TP exports were calculated to be 71% and 29%, respectively. So it is necessary to control P pollution by improving fertilizer use efficiency and enhancing manure management. The results provide a scientific basis for targeted solutions to the sources of P nutrient and its control measures in the middle reach of the Yangtze River.