Impacts of climate and planting structure changes on watershed runoff and nitrogen and phosphorus loss

Runoff nitrogen losses under confluence and diverging drainage systems in the sloped plot scale: A comparative study

The drainage system is a key measure for regulating runoff nutrient losses on sloping farmlands. Confluence and diverging drainage systems are two drainage layouts representing natural water network systems and are widely distributed in sloping farmlands; however, the effects of these drainage systems on runoff nutrient losses in the sloped plots remain unclear. This study investigated the effects of different drainage systems on the characteristics of runoff nitrogen (N) losses in sloped plots using laboratory rainfall simulations. Three treatments, including bare slope (without drainage system, CK), confluence drainage system (T1), and diverging drainage system (T2), were used to compare the changes in concentrations and losses of total nitrogen (TN), dissolved nitrogen (DN), and particulate nitrogen (PN), and the DN:TN ratio in runoff under a combination of 1.8 mm min-1 rainfall intensity and three slope gradients (5°, 10°, and 15°). The results showed that the time to runoff was significantly delayed in T2 compared with that in CK and T1 across all slopes (p < 0.05). Accumulated runoff depth was considerably lower in T1 and T2 than in CK across all slopes (p < 0.05). The TN and PN concentrations in T1 were markedly lower than those in T2 on the 10° and 15° slopes (p < 0.05). The DN concentration in T1 was lowest at the 5° slope (p < 0.05). TN loss in T1 was 14.7-33.9% and 17.9-30.3% lower than those in CK and T2 across all slopes, respectively (p < 0.05). The PN loss in T1 was 56.7% and 53.3% lower than that in T2 on the 10° and 15° slopes, respectively (p < 0.05). DN loss in T1 was 39.3-72.5% lower than that in CK for all slopes (p < 0.05). DN:TN in T2 was lower than that in CK and T1 at the 10° and 15° slopes (p < 0.05). Our results confirm the effectiveness of drainage systems in reducing runoff nutrient losses in a sloped plot and demonstrate that the confluence drainage system is better at reducing N losses in runoff than diverging drainage systems.

Assessment of the response characteristics of pollution load in Huntai Basin under climate change

This study establishes a calibrated SWAT (Soil and Water Assessment Tool) model for the Huntai Basin, driven by SSP126, SSP245, SSP585, and multi-model ensemble (MME) models in CMIP6 (Coupled Model Intercomparison Project-6), to investigate the effects of climate change on hydrological processes and pollution load in the Huntai Basin. The results show that the annual mean temperature and the annual precipitation will gradually increase. The nitrogen and phosphorus pollution loads in the basin exhibit a trend of decreasing-increasing-decreasing. The correlation between the nitrogen-phosphorus pollution load and the hydrological process strengthens with increasing radiative forcing. In the four scenarios, CO2 is a primary driving factor that contributes greatly to nitrogen and phosphorus pollution. The main differences are in the total driving factors, and SSP126 and SSP245 are less than those of other models. The total phosphorus and total nitrogen pollution in different climate models were higher than the average level during the benchmark period, except for ammonia nitrogen pollution, which was lower. The nitrogen and phosphorus pollution in SSP126 and SSP245 modes will reach the maximum in 2040s, and the pollution in other periods will be lower than that in SSP585 and MME scenarios. In the long run, the development state between SSP126 and SSP245 may be better appropriate for the Huntai Basin's future sustainable development. This paper analyzes the occurrence and influencing factors of nitrogen and phosphorus pollution under climate change to provide reference to the protection of water environment under changing environments.

Effect of climate change on the water quality of Mediterranean rivers and alternatives to improve its status

Surface water (SW) quality is particularly vulnerable to increased concentrations of nutrients, and this issue may be exacerbated by climate change. Knowledge of the effects of temperature and rainfall on SW quality is required to take the necessary measures to achieve good SW status in the future. To address this, the aims of this study were threefold: (1) to assess how a changing climate may alter the nitrate, ammonium, phosphorus and biological oxygen demand status (BOD5) of SW; (2) assess the relationship between water quality and flow; and (3) simulate diffuse and point source pollution reduction scenarios in the Júcar River Basin District in the Mediterranean region. A regionalised long-term climate scenario was used following one Representative Concentration Pathway (RCP8.5) with the data incorporated into the coupling of hydrological and water quality models. According to these climate change scenarios, SW with poor nitrate, ammonium, phosphorus and BOD5 status are expected to increase in the future by factors of 1.3, 1.9, 4 and 4, respectively. Furthermore, median ammonium and phosphorus concentration may be doubled in months with low flows. Additional measures are required to maintain current status in the water bodies, and it is necessary to reduce at least 25% of diffuse nitrate pollution, and 50% of point loads of ammonium, phosphorus, and BOD5.

Discharge dynamics of agricultural diffuse pollution under different rainfall patterns in the middle Yangtze river

Rainfall plays a crucial role in influencing the loss of agricultural diffuse pollution. The middle Yangtze River region is well-know for its humid climate and numerous agricultural activities. Thus, this study quantitatively analyzed the concentration and distribution of nitrogen (N) and phosphorus (P) load and loss in a major tributary of the middle Yangtze River under different rainfall patterns by using sampling analysis and SWAT model simulation. The total nitrogen (TN) and nitrate-nitrogen (NO3-) concentrations were 1.604-3.574 and 0.830-2.556 mg/L, respectively. The total phosphorous (TP) and Soluble Reactive Phosphorus (SRP) were 2-148 and 2-104 μg/L, respectively. The modeling results demonstrated that higher rainfall intensity led to greater load and loss flux of diffuse pollutant at the outlet. Organic nitrogen (ORGN) is the main nitrogen form transported from the subbasin to the reach, while organic phosphorus (ORGP) and inorganic phosphorus (INORGP) were transported at similar amounts. Under the condition of conventional rainfall, the outlet reaches mainly transported NO3-, and ORGN gradually increased when rainstorm events occurred. The ratio of INORGP to ORGP was relatively stable. During extreme rainfall event, rainfall is the dominant element of agricultural diffuse pollution. A strong positive correlation exists between rainfall intensity and pollution loss during rainstorms. Storm rain events were the main source of TN and TP losses. Few storm rain days generated pollutants that accounted for a large proportion of the total loss, and their impact on TP loss was significantly greater than that of TN. The influence of storm rain on TN is mainly the increase in runoff, while TP is sensitive to the runoff and sediment transport promoted by rainfall. By setting different precipitation scenarios, it was confirmed that under the same rainfall amount, short-term storm rain has the most significant impact on the TN load, whereas TP load may be influenced more by the combined effects of rainfall duration and intensity. Therefore, to reduce the impact of agricultural diffuse pollution, it is important to take targeted measures for the rainstorm days.

Response of nutrient loss to natural erosive rainfall events under typical tillage practices of contour ridge system in the rocky mountain areas of Northern China

Changes in natural rainfall characterized by heavy precipitation and high rainfall intensity would increase the risks and uncertainty of nutrients losses. Losses of nitrogen (N) and phosphorus (P) with water erosion from agriculture-related activities has become the principal nutrients resulting the eutrophication of water bodies. However, a little attention has been paid to the loss characteristic of N and P responding to natural rainfall in widely used contour ridge systems. To explore the loss mechanism of N and P in contour ridge system, nutrient loss associated with runoff and sediment yield was observed in in situ runoff plots of sweet potato (SP) and peanut (PT) contour ridges under natural rainfall. Rainfall events were divided into light rain, moderate rain, heavy rain, rainstorm, large rainstorm, and extreme rainstorm level, and rainfall characteristics for each rainfall level were recorded. Results showed that rainstorm, accounting for 46.27% of the total precipitation, played a destructive role in inducing runoff, sediment yield, and nutrient loss. The average contribution of rainstorm to sediment yield (52.30%) was higher than that to runoff production (38.06%). Rainstorm respectively generated 43.65-44.05% of N loss and 40.71-52.42% of P loss, although light rain induced the greatest enrichment value for total nitrogen (TN, 2.44-4.08) and PO4-P (5.40). N and P losses were dominated by sediment, and up to 95.70% of the total phosphorus and 66.08% of TN occurred in sediment. Nutrient loss exhibited the highest sensitivity to sediment yield compared to runoff and rainfall variables, and a significant positive linear relationship was observed between nutrient loss and sediment yield. SP contour ridge presented higher nutrient loss than that in PT contour ridge, especially for P loss. Findings gained in this study provide references for the response strategies of nutrient loss control to natural rainfall change in contour ridge system.

A raster-based estimation of watershed phosphorus load and its impacts on surrounding rivers based on process-based modelling

Quantifying phosphorus (P) load from watersheds at a fine scale is crucial for studying P sources in lake or river ecosystems; however, it is particularly challenging for mountain-lowland mixed watersheds. To address this challenge, we proposed a framework to estimate the P load at the grid scale and assessed its risk to surrounding rivers in a typical mountain-lowland mixed watershed (Huxi Region in Lake Taihu Basin, China). The framework coupled three models: the Phosphorus Dynamic model for lowland Polder systems (PDP), the Soil and Water Assessment Tool (SWAT), and the Export Coefficient Model (ECM). The coupled model performed satisfactory for both hydrological and water quality variables (Nash-Sutcliffe efficiency >0.5). Our modelling practice revealed that polder, non-polder, and mountainous areas had P load of 211.4, 437.2, and 149.9 t yr^-1, respectively. P load intensity in lowlands and mountains was 1.75 and 0.60 kg ha^-1 yr^-1, respectively. A higher P load intensity (>3 kg ha^-1 yr^-1) was mainly observed in the non-polder area. In lowland areas, irrigated cropland, aquaculture ponds and impervious surfaces contributed 36.7%, 24.8%, and 25.8% of the P load, respectively. In mountainous areas, irrigated croplands, aquaculture ponds, and impervious surfaces contributed 28.6%, 27.0%, and 16.4% of the P load, respectively. Rivers with relatively high P load risks were mainly observed around big cities during rice season, owing to a large contribution of P load from the non-point source pollution of urban and agricultural activities. This study demonstrated a raster-based estimation of watershed P load and their impacts on surrounding rivers using coupled process-based models. It would be useful to identify the hotspots and hot moments of P load at the grid scale.

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.

Integrated effects of co-evolutions among climate, land use and vegetation growing dynamics to changes of runoff quantity and quality

Climates, Land use/land cover (LULC) and vegetation growing dynamics have been regarded as the main factors affecting terrestrial hydrological process. However, the mechanisms underlying their integrated effects on terrestrial runoff and nutrient dynamics are not understood well. Here, we constructed a framework to disentangle and quantify the independent and coupled contributions of climate, LULC and vegetation leaf area index (LAI) changes to watershed runoff and nutrient yields changes. Long series of changing meteorological, LULC and LAI data between 1990 and 2020 were integrated into a factor-controlled simulation protocol in a distributed hydrological model, to quantify their comprehensive contributions (individual contribution of single factor change and coupling contribution of multiple factor synchronous changes) to runoff and nutrient changes. The results showed that changes of runoff and nutrient yields are more induced by climate change, rather than LULC and LAI transformations. Increase in annual precipitation significantly elevated runoff and nutrient yields. TP yield was more sensitive to climate change than runoff and TN yields. LULC transformation and climate change have synergistic effects on runoff and nutrient yields. Shift of vegetation areas to construction lands will amplify the effect of climate change on runoff and nutrient yields. Single LAI change has weak effect on runoff and nutrient yields, but it can significantly alter the hydrological effects derived from climate change and the synergistic effects between climate change and LULC transformation. This study considered the coupling and potential synergistic effects among climate change, LULC conversion and LAI variation, which elucidated the comprehensive effects of changing environment on runoff and nutrients evolutions in a more systematic and integrated perspective.

Exploring the impact of rural labor transfer on the production and ecological sustainability of crop planting structure in China

With the improvement of industrialization, numerous rural laborers migrate to urban areas in search of off-farm jobs. Farmers change agricultural production decisions to adapt to the change of labor force, which will inevitably affect the crop planting structure. However, few studies have explored the sustainability of crop planting structure. Based on the calculation of the multiple cropping index (MCI), grain crops planting rate (GCR), economic crops planting rate (ECR), and ecological sustainability index (ESI) of crop planting structure, this study analyzes the impact of labor transfer rate (LTR) and labor cost (LC) on the sustainability of crop planting structure using a geographically and temporally weighted regression (GTWR) model. The results show that the scale of rural labor transfer and labor cost in China remains on the rise, but the growth rate has slowed down. The total carbon absorption of crops in China shows a U-shape trend, and the rice and maize have the largest carbon absorption. The impact of LTR on MCI is mainly positive, especially in the North China Plain in the early stage and some provinces in the Southwest China in the later stage. The impact of LTR on ECR and ESI is negative in most provinces. And the negative influence of LC on MCI is increasing, showing the spatial distribution characteristics of large influence in the southeast and small influence in the northwest. The impact of LC on ESI shows a negative effect in most provinces in the early stage, and the negative effect is more concentrated in some provinces in the southwest in the later stage.

Climate factors affect N2O emissions by influencing the migration and transformation of nonpoint source nitrogen in an agricultural watershed

Precipitation can affect the residence time of nitrogen compounds, and temperature can influence nitrogen transformation in soil. Therefore, we hypothesized that climate factors can affect the emissions of N₂O, an important greenhouse gas produced via nitrogen transformation, by influencing the migration and transformation of nonpoint source nitrogen in soil. To test this hypothesis and quantify the effect of climate factors on N₂O emissions, the SWAT model and the modified SWAT-N₂O coupler were used to study the effect of climate factors on the migration and transformation of nonpoint source nitrogen and N₂O emissions in an agricultural watershed from 2009 to 2018. Temperature affected N₂O emissions more significant than precipitation, and N₂O emissions increased with temperature and reached a plateau when the average monthly temperature was 23.0 °C. The N₂O emissions first increased rapidly with precipitation due to the increase in moisture. However, when the average monthly precipitation reached 78.8 mm, the N₂O emissions began to decrease because the residence time of nitrogen compounds in soil were reduced due to fast removal via runoff, which inhibits N₂O emissions. Under the context of climate change with three scenarios (RCP2.6, RCP4.5, RCP8.5), temperature would increase gradually while precipitation would not change significantly from 2021 to 2080, as a result, the changes would increase N₂O emissions by 6.7%, 32.3%, and 70.7%, respectively. This study quantifies the feedback of N₂O emissions to climate change in croplands, providing a scientific basis for climate change mitigation and agricultural management.

Evaluation of the Response of Grain Productivity to Different Arable Land Allocation Intensities in the Land Use Planning System of China

This study measured the spatio-temporal change of the Arable Land Allocation Intensity (ALAI), and established a toughness index to evaluate the responses of grain productivities to the ALAIs in 31 provinces. The results show that the ALAI decreased in 31 provinces during 2005–2020, whereas the grain productivity responses differed. Though China’s Major Grain producing areas (CMGPA) experienced decreasing arable land allocation intensities compared with the non-CMGPAs, they still showed a robust toughness of grain productivity. The spatial barycenter of grain productivity moved towards Northeast China, which was much faster and further than the northwest movement of the ALAI, indicating a dislocated motion of grain production and ALAI. In all, both the toughness of grain productivity and the tightening arable land allocation intensities were apparent in the CMGPAs, especially in the northeastern CMGPAs in China. In order to improve the grain productivity on shrinking arable land resources, this study suggests that we tighten the quota of arable land transformed into construction land, improve the per-unit grain yield, and enhance the remote sensing technology and field surveys to better monitor the local governments’ performance in arable land management.

A recommended nitrogen application strategy for high crop yield and low environmental pollution at a basin scale

Mitigating environmental pollution and sustaining grain production have been foundational issues in sustainable development, however, ascertaining the optimal balance remains poorly investigated. This study used the Soil and Water Assessment Tool (SWAT) model to simulate crop growth and nitrogen loss, established the mapping relationship between nitrogen input to yield and water quality, and proposed a general method to determine a nitrogen application strategy for high yield and low pollution at a basin scale. Lake Xiaoxingkai basin, which is the primary maize producing area in China as well as an internationally important wetland distribution area, was used as a case study. First, we designed application scenarios for 10 base fertilizers (B1-B10) and 10 topdressing fertilizers (T1-T10) and evaluated their combined effects of maize growth to identify the critical nitrogen fertilizer rates determined under fixed and dynamic base/topdressing ratios. Then, the critical base and topdressing fertilizer rates were determined. Based on the mapping relationship between nitrogen fertilizer rate and nitrogen loss, we then revealed water quality at the basin outlet under the critical base and topdressing fertilizer rates. Finally, we proposed alternative nitrogen application strategies for high yield and low pollution while considering the different preferences of decision-makers for the economy, agriculture, and environment. We found that adjusting the ratio of base to topdressing fertilizer may create a win-win situation for agriculture and the environment, which will provide a scientific basis for sustainable development.

Spatiotemporal Characteristics of the Water Quality and Its Multiscale Relationship with Land Use in the Yangtze River Basin

The spatiotemporal characteristics of river water quality are the key indicators for ecosystem health evaluation in basins. Land use patterns, as one of the main driving forces of water quality change, affect stream water quality differently with the variations in the spatiotemporal scales. Thus, quantitative analysis of the relationship between different land cover types and river water quality contributes to a better understanding of the effects of land cover on water quality, the landscape planning of water quality protection, and integrated water resources management. Based on water quality data of 2006–2018 at 18 typical water quality stations in the Yangtze River basin, this study analyzed the spatial and temporal variation characteristics of water quality by using the single-factor water quality identification index through statistical analysis. Furthermore, the Spearman correlation analysis method was adopted to quantify the spatial-scale and temporal-scale effects of various land uses, including agricultural land (AL), forest land (FL), grassland (GL), water area (WA), and construction land (CL), on the stream water quality of dissolved oxygen (DO), chemical oxygen demand (CODMn), and ammonia (NH3-N). The results showed that (1) in terms of temporal variation, the water quality of the river has improved significantly and the tributaries have improved more than the main rivers; (2) in the spatial variation respect, the water quality pollutants in the tributaries are significantly higher than those in the main stream, and the concentration of pollutants increases with the decrease of the distance from the estuary; and (3) the correlation between DO and land use is low, while that between NH3-N, CODMn, and land use is high. CL and AL have a negative effect on water quality, while FL and GL have a purifying effect on water quality. In particular, AL and CL have a significant positive correlation with pollutants in water. Compared with NH3-N, CODMn has a higher correlation with land use at a larger scale. The results highlight the spatial scale and seasonal dependence of land use on water quality, which can provide a scientific basis for land management and seasonal pollution control.

Driving forces and future trends on total nitrogen loss of planting in China

Nitrogen production is one of the major aspects of global change over the past century. Nowhere is this change more dramatic than in China. Understanding the variations and driving forces of nitrogen loss from planting is critical to the sustainable development of Chinese agriculture. Here we found total nitrogen (TN) loss of China showed an overall downward trend from 2007 to 2016, as a result of abatement strategies for China on "Soil Testing and Formula Fertilization" and "Reducing Fertilizer Application while Increase the Efficiency", based on the data of National Agricultural Pollution Survey. The results of structural equation model showed that the path coefficient of anthropogenic drivers and natural conditions on TN loss were 0.934 and -0.137 respectively, suggesting that anthropogenic drivers had greater effects on TN loss than natural conditions. In terms of anthropogenic drivers, fertilizer usage and consumption of chemical pesticides were the two major factors affecting TN loss with path coefficients of 0.958 and 0.946, respectively, which was mainly related to their over-application. For natural conditions, relative humidity, water supply situation, and annual precipitation were found to be the dominant factors affecting TN loss, revealing that moist soils increased TN loss by enhancing ammonia volatilization, denitrification and nitrogen leaching. Forecasts for 2050, under two scenarios especially for the high TN loss scenario, the indication sifts that China will face a high risk of increasing TN loss from planting, suggesting that China's abatement strategies cannot be slackened. Here, the current status and future trends of China's nitrogen loss provide direction and pertinence to Chinese abatement strategies for nitrogen, effectively preventing and controlling agricultural non-point source pollution.