Spatial characteristics of nutrient budget on town scale in the Three Gorges Reservoir area, China

Agricultural nitrogen loss and downstream effects in the transboundary La Plata basin driven by soybean rotations

The issue of substantial fertilizer application in soybean fields in South America has led to a potential nitrogen (N) imbalance in croplands, posing a risk to downstream ecosystem stability. A critical strategy for mitigating this risk requires a detailed examination focusing on N surplus and downstream consequences in soybean-intensive watersheds. This study comprehensively assesses N dynamics and downstream effects in areas with soybean rotations across the transboundary La Plata basin in South America. We estimated N surplus and potential N loss through leaching and soil erosion in both established and recently converted soybean rotation fields and analyzed the impact of N surplus reduction scenarios on river N concentration variations. Results indicated that fertilizer N inputs increased by 38 % more than non-fertilizer N inputs from 2001 to 2016, despite biological N fixation contributing 45 % of total N inputs. N surplus increased by 19 % during this period, resulting in high-potential N loss across 31 % of soybean rotation fields. It was estimated that a 20 % reduction in N surplus could decrease total N concentration by 17 % ± 11 % and nitrate concentration by 16 % ± 10 % in soybean-intensive watersheds. Reducing N fertilizer inputs in soybean rotation fields, especially in Brazilian and Uruguayan La Plata, is a promising strategy for mitigating N pollution without significantly impacting soybean production. Our findings revealed widespread excessive fertilizer N inputs across the basin, contributing to strategy development for N pollution mitigation and underscoring the need for cross-national collaboration in N management to mitigate water pollution and ensure agricultural sustainability.

Increasing cascade dams in the upstream area reduce nutrient inputs to the Three Gorges Reservoir in China

The upstream cascade dams play an essential role in the nutrient cycle in the Yangtze. However, there is little quantitative information on the effects of upstream damming on nutrient retention in the Three Gorges Reservoir (TGR) in China. Here, we aim to assess the impact of increasing cascade dams in the upstream area of the Yangtze on Dissolved Inorganic Nitrogen and Phosphorus (DIN and DIP) inputs to the TGR and their retention in the TGR and to draw lessons for other large reservoirs. We implemented the Model to Assess River Inputs of Nutrients to seAs (MARINA-Nutrients China-2.0 model). We ran the model with the baseline scenario in which river damming was at the level of 2009 (low) and alternative scenarios with increased damming. Our scenarios differed in nutrient management. Our results indicated that total water storage capacity increased by 98 % in the Yangtze upstream from 2009 to 2022, with 17 new large river dams (>0.5 km3) constructed upstream of the Yangtze. As a result of these new dams, the total DIN inputs to the TGR decreased by 15 % (from 768 Gg year-1 to 651 Gg year-1) and DIP inputs decreased by 25 % (from 70 Gg year-1 to 53 Gg year-1). Meanwhile, the molar DIN:DIP ratio in inputs to the TGR increased by 13 % between 2009 and 2022. In the future, DIN and DIP inputs to the TGR are projected to decrease further, while the molar DIN:DIP ratio will increase. The Upper Stem contributed 39 %-50 % of DIN inputs and 63 %-84 % of DIP inputs to the TGR in the past and future. Our results deepen our knowledge of nutrient loadings in mainstream dams caused by increasing cascade dams. More research is needed to understand better the impact of increased nutrient ratios due to dam construction.

Analysis of spatial and temporal changes and driving forces of arable land in the Weibei dry plateau region in China

Arable land is the lifeblood of food production, it is of great significance to promote the protection of arable land and ensure national food security by accurately understanding the change law of cultivated land and its driving mechanism. This study takes the Weibei dry plateau region of China as an example, explores its spatial and temporal change characteristics through the center of gravity shift and land use shift matrix, and couples the geographic probe model to reveal the driving mechanisms affecting arable land change. The results show that in the past 25 years, the total arable land area in the Weibei Dry Plateau Region of China has decreased by 5.58%, and the stability of arable land resources in the whole region has weakened. The center of gravity of arable land shifts to the northeast, and the standard deviation ellipse of arable land mainly undergoes the change process of "increase (1995-2015)-decrease (2015-2020)", and the spatial distribution of arable land tends to be dispersed. In the LISA frequency mapping, the proportion of stable constant and low-frequency areas is as high as 89.58%, and the spatial pattern of cultivated land is relatively stable. Medium and high frequency areas. The transformation mode is mainly "low-low" aggregation, "low-high" aggregation is not significant, and the decline of cultivated land in the study area is more obvious. In the past 25 years, a total of 1017.26 km2 of arable land was converted to construction land. The explanatory power of the influencing factors varies in each period (0.299 to 0.731), with total agricultural machinery power has the strongest explanatory power of 0.694, 0.592, and 0.731, respectively. The interaction between slope and annual average temperature and other factors being the highest, both greater than 0.8. Through the construction of LISA frequency mapping, combined with the center of gravity model and standard deviation ellipse, the spatial evolution trend of regional arable land is more comprehensively and dynamically grasped. By using the geodetector model, the driving mechanism of the changes of arable land is revealed comprehensively, which provides a theoretical basis for the scientific management and effective protection of arable land resources and a basis for decision-making.

Output characteristics and driving factors of non-point source nitrogen (N) and phosphorus (P) in the Three Gorges reservoir area (TGRA) based on migration process: 1995-2020

Although physical models at present have made important achievements in the assessment of non-point source pollution (NPSP), the requirement for large volumes of data and their accuracy limit their application. Therefore, constructing a scientific evaluation model of NPS nitrogen (N) and phosphorus (P) output is of great significance for the identification of N and P sources as well as pollution prevention and control in the basin. We considered runoff, leaching and landscape interception conditions, and constructed an input-migration-output (IMO) model based on the classic export coefficient model (ECM), and identified the main driving factors of NPSP using geographical detector (GD) in Three Gorges Reservoir area (TGRA). The results showed that, compared with the traditional export coefficient model, the prediction accuracy of the improved model for total nitrogen (TN) and total phosphorus (TP) increased by 15.46 % and 20.17 % respectively, and the error rates with the measured data were 9.43 % and 10.62 %. It was found that the total input volume of TN in the TGRA had declined from 58.16 × 10⁴ t to 48.37 × 10⁴ t, while the TP input volume increased from 2.76 × 10⁴ t to 4.11 × 10⁴ t, and then decreased to 4.01 × 10⁴ t. In addition Pengxi River, Huangjin River and the northern part of Qi River were high value areas of NPSP input and output, but the range of high value areas of migration factors has narrowed. Pig breeding, rural population and dry land area were the main driving factors of N and P export. The IMO model can effectively improve prediction accuracy, and has significant implications for the prevention and control of NPSP.

On the coordination in diversity between water environmental capacity and regional development in the Three Gorges Reservoir area

Water environment capacity has drew the attention of policymakers and stakeholders to sustainable development, and its dynamic changes are ultimately impacted by population, capital, and industrial clusters under regional development. Previous research, however, has not been able to completely comprehend it. In this paper, the authors use the Coupling Coordination Degree model and the Geodetector model to study the temporal and spatial evolution of water environment capacity and its driving mechanism based on regional development represented by regional function including urbanization function, ecological function, and agricultural function using the Three Gorges Reservoir area on county scale as a case study from 2000 to 2015. The results showed that (1) compared with 2000, 2005, and 2010, the water environment capacity of the whole reservoir area in 2015 was significantly improved. (2) The urban functions of each district and county are increasing in different years, and the dynamic changes of ecological and agricultural functions are obviously different. (3) The water environment capacity of districts and counties in the head area. There are significant disparities in the relationship between water environment capacity and regional function in various regions. Differences in water environment capacity are largely influenced by ecological function and the interaction driver of the proportion of agricultural function and urban function, which are typically the biggest of all the components. This suggests that regional development is a top priority in order to improve the operability of the water environmental capacity through more regulation, rules, and planning.