Middle-Lower Yangtze Plain Research Articles

Investigating the influence of land cover on land surface temperature

The increasingly serious urban heat island (UHI) effect is unfavorable to urban development. This study utilized land cover data and land surface temperature (LST) data of China in 2020 by using correlation analysis and spatial regression models to analyze the relationships between LST and two influencing factors (land cover and digital elevation model (DEM)). The results showed the following: (1) The correlation between LST and forest was highest in the Northeast China Plain (NCP), Huang-Huai-Hai Plain (HHP), Qinghai Tibet Plateau (QTP), and Loess Plateau (LP). DEM mean displayed its highest correlation in the Northern arid and semiarid region (NAR), Sichuan Basin and surrounding regions (SCR), Yunnan-Guizhou Plateau (YGP), and Middle-lower Yangtze Plain (MYP). Southern China (SC) had the highest correlation between LST and construction land. (2) There was spatial heterogeneity between land cover and LST. Unused land on LP had larger impact on LST. For every 1% increase in the proportion of unused land area, the LST increased by 0.250 °C. LST in some central and western regions of China (the NAR, the LP, the SCR, and the YGP) was mainly affected by local land cover; LST in eastern coastal regions (the HHP, MYP, NCP, SC) and QTP was not only affected by local land cover, but also by LST or land cover of neighboring regions. The warming effect of construction land on LST was more significant, with LST increasing by 0.079 °C to 0.338 °C for every 1% increase in the proportion of construction land area. Coordination of land use planning and synergistic remediation in different regions and rational planning of construction land are essential to mitigate the UHI effect. (3) Water bodies in the NCP, NAR, and MYP had the greatest cooling impact on LST, with LST decreasing by 0.277 °C, 0.246 °C, and 0.079 °C, respectively, for every 1% increase in the proportion of water bodies area. Forest on the QTP, LP, SC, and YGP had the greatest cooling impact on LST, and for every 1% increase in the proportion of forest area, LST decreased by 0.144 °C, 0.089 °C, 0.086 °C, and 0.038 °C, respectively. Actively planting trees and increasing the area of forests and water bodies are of positive significance in alleviating the UHI effect and improving the ecological environment.

Agricultural Irrigation Exacerbates Humid Heat Stress in the Mid‐Lower Reaches of the Yangtze River

AbstractMassive irrigation across eastern China (EC) could reduce extreme heat by altering energy and water budgets. However, the irrigation effect on increasing humidity has often been missed, especially in humid regions, leaving its effect and mechanism on extreme humid heat (EHH) poorly characterized. We analyzed assemblies of observations and performed regional simulations with more detailed irrigation scheme to explore the irrigation impacts and potential mechanisms on EHH. We find that irrigation in EC, despite having a cooling effect of about 0.2–0.6C, leads to an increase of about 0.4–0.8C in EHH, with a more intense impact on the Middle‐Lower Yangtze Plain (MLYP) by 0.9C. Cooling effect induced by increased latent heat fluxes through irrigation contributes to air deposition, which lowers boundary layer height, raises near‐surface moist enthalpy, and ultimately exacerbates the EHH. Results mechanistically emphasized irrigation impacts on EHH and highlighted the necessity of improving irrigation modeling reality.

Assessing the impact of climate and crop diversity on regional greenhouse gas emissions and water demand of cropland

To tackle the challenges of climate warming and freshwater scarcity, evaluating greenhouse gas (GHG) emissions and water demand in agricultural production can contribute positively to sustainable agricultural practices. This study aims to quantify the GHG emissions and water requirements of three major grains in diverse environmental regions in China, with a specific focus on exploring their spatial heterogeneity due to regional differences. The parameterized DNDC model was used to quantify crop GHG emissions, while the Penman-Monteith equation was utilized to assess crop water demand. The result showed that the total GHG emission of major grain in China was 372.43 Tg/yr (CO2), 11.68 Tg/yr (CH4), 475.56 Gg/yr (N2O) respectively; and the water demand was 473.60 Gm3, in 2015. The Middle-lower Yangtze Plain (MLYP) had the highest emission and water demand. High-temperature and high-precipitation regions had greater GHG emission intensity; the intensity of different GHG emissions was significantly influenced by the type of crops. Late rice had the highest emission intensity. The geospatial distribution of GHG emissions and water demand displayed opposite patterns, with meteorological conditions and crop types as the main reasons. Soil bulk density was the most significant soil element influencing regional emissions. These results will help to assess the spatial heterogeneity of agricultural “water and carbon”, and the quantitative results can be used as evaluation indicators to establish resource- and environment- friendly agricultural cropping patterns suitable for different cropping regions.

Multi-objective optimization of farmland water level and nitrogen fertilization management for winter wheat cultivation under waterlogging conditions based on TOPSIS-Entropy

Aiming at the problems of reduced winter wheat yield and aggravation of nitrogen leaching pollution caused by the waterlogging in the Middle-Lower Yangtze Plain, China, a two-year field experiment with three farmland water levels (W40, W60, W80) and three nitrogen application rates (N150, N225, N300) as well as a non-waterlogged treatment (CK) was carried out, to investigate the coupling effects of farmland water level and nitrogen application rate on the plant growth, grain yield, crop water productivity (WPC) and nitrogen load with waterlogging conditions. Three man-made waterlogging events were applied at winter wheat jointing-booting stage, heading-flowering stage and grain filling stage, respectively. The results indicated that with the farmland water level decreased from −40 cm to −60 cm and the nitrogen application rate increased from 150 kg∙ha−1 to 225 kg∙ha−1, the plant height, aboveground dry matter, leaf area index, spike length, grain yield, effective panicles, grain number per ear, 1000-grain weight and WPC in the waterlogging field increased significantly. However, since the nitrogen application rate exceeded 225 kg∙ha−1 and farmland water level lowered more than −60 cm, the favorable effects of nitrogen application rate and farmland water level for winter wheat growth and production reduced. Additionally, both the nitrogen load and partial factor productivity of nitrogen (PFPN) increased with the decline of farmland water level, while the nitrogen load increased and the PFPN decreased with the increasing nitrogen application rate. The raise of nitrogen rate from 150 kg∙ha−1 to 225 kg∙ha−1 was beneficial to plant growth, however, the increase of nitrogen application resulted in the decrease of PFPN and increase of drainage nitrogen loads. Compared with the water farmland water level of −40 cm and nitrogen application rate of 150 kg∙ha−1, the increase of nitrogen application rate and the decrease of farmland water level in the range of 50%-100% resulted in yield raise by 5.78%-32.29% approximately and the increase of nitrogen load by 36.20%-178.44% approximately. The comprehensive evaluation with TOPSIS-Entropy method for plant growth, grain yield, WPC, PFPN and nitrogen loads suggested that, the appropriate nitrogen application rate for winter wheat in the waterlogging areas of Middle-Lower Yangtze Plain in China was 225 kg∙ha−1, and the proper farmland water level was lowering to −80 cm in wet year and −60 cm in dry year within 3 days after waterlogging.

Mapping sustainability-oriented China’s cropland use stability

Shifting to more sustainable use can curb cropland resource degradation and improve production resilience. However, most cropland use assessments are unilaterally focused on biophysical levels and productivity, ignoring the multi-dimensional aspects of degraded cropland. This study attempts to describe cropland use stability in China by proposing a multi-dimensional assessment framework (including quantity, quality, management, service, and risk) to provide a reference for designing land degradation-neutral strategies. Results show that multi-dimensional cropland use characteristics present significant spatial heterogeneity. Western regions are reserve resource agglomerations that can replenish cropland quantity. In contrast, main grain-producing areas cover most current resources with preferably cultivation quality, management efficiency, and ecosystem services, while risk resistance is weak (especially in Middle-lower Yangtze Plain). Generally, the stability of cropland use in Northeast Plain is the highest and in Loess Plateau the lowest. Besides, urbanization will occupy about 9.31% of the high-stability cropland in 2030, of which 70.29% will occur in Northeast Plain and Huang-Huai-Hai Plain. The total potential productivity loss in Huang-Huai-Hai Plain alone will reach 100.1 kt, equivalent to supplying the food demand of 199,200 people annually. Therefore, a sustainable-oriented refined cropland management strategy should be designed according to the hierarchical nested spatial layout of comprehensive planning-stability map-multi-dimensional utilization characteristics to ensure the loss-replenishment balance and stable production.

Antibiotic resistance genes profile in the surface sediments of typical aquaculture areas across 15 major lakes in China

Aquatic farming is considered as a major source of antibiotic resistant bacteria (ARB) and antibiotic resistance genes (ARGs) for the natural environment of the lakes. ARB and ARGs in the natural environment have increased quickly because of the human activities. Here, we have profiled the diversity and abundance of ARGs in sediments from the typical aquaculture areas around 15 major lakes in China using PCR and qPCR, and further assessed the risk factor shaping the occurrence and distribution of ARGs. And class 1, 2 and 3 integrons were initially detected by PCR with specific primers. ARGs were widely distributed in the lakes: Weishan Lake and Poyang Lake showed high diversity of ARGs, followed by Dongting Lake, Chao Lake and Tai Lake. Generally, the ARGs in the Middle-Lower Yangtze Plain were more abundant than those in the Qinghai-Tibet Plateau. Tetracycline resistance genes (tet(C), tet(A) &tet(M)) were prominent in sediments, and the next was AmpC β-lactamase gene group BIL/LAT/CMY, and the last was the genes resistance to aminoglycoside (strA-strB). Partial least squares path modeling analysis (PLS-PMA) revealed that livestock had a significant direct effect on the distribution of ARGs in lakes, and population might indirectly influence the profiles of ARGs by affecting the scale of livestock and aquaculture. The detectable rate of class 1, 2 and 3 integrons were 80%, 100% and 46.67%, respectively. The prevalence of integrons might play a key role in promoting more frequent horizontal gene transfer (HGT) events, resulting in the environmental mobilization and dissemination of ARGs between bacteria.

Coupling input and output intensity to explore the sustainable agriculture intensification path in mainland China

Sustainable intensification (SI) of agriculture is widely regarded as an important way to alleviate the contradiction between the food gap and ecosystem health. Correlate input intensity and output intensity have been regarded as an important dimension in most estimation frameworks of SI. But in practice, this correlation is generally expressed in terms of efficiency metrics and calculated as the ratio of output intensity to input intensity, which cannot quantitatively explain the impact of input intensity on output intensity and provide a threshold value for estimating the suitability of SI. This study's goals are to propose an input—output coupled method to explain the impact of input intensity on output intensity and thereby estimate the suitability of provincial SI. Provincial annual input intensity and output intensity were estimated from an emergy-based perspective by taking China as a case study. The K-means algorithm was used to identify the structural pattern of arable land input intensity. A sliding window-based partial correlation index method was proposed and applied to reveal the interaction process between input intensity and output intensity. The results show that there are two main change paths in the pattern of input intensity: one path in the western irrigation regions and the other path in the eastern northeast China Plain and middle-lower Yangtze Plain. The former path can be expressed as a small increase in fertilizer and agro-machinery input intensity with a decrease in labour force input intensity. The latter path shows a larger increase in fertilizer and pesticide input intensity. For each type of input intensity except mulching film, its correlation to output intensity has experienced a similar coupling—decoupling—recoupling process in both plain provinces and mountainous or plateau provinces. According to Landau's theory of phase transition, the complex coupling of input and output undergoes a phase transition process from order to disorder and then to order, depicted by the sliding window-based partial correlation coefficient as the order parameter from a holistic perspective. The inflection points of coupling relation changes show that the phenomenon of fertilizer and pesticide overuse has steadily occupied most provinces in eastern China and is spreading westwards. Although the “zero growth action for fertilizers and pesticides” has made considerable achievements in reducing the input intensity of fertilizer and pesticides since 2015, the situation of superfluous fertilizer and pesticide input has not changed substantially. The input intensity of fertilizer and pesticides still needs to be further reduced. This study can contribute to the estimation method system of SI. The input—output coupled method is applicable for other spatial scales and regions (or countries) to estimate the suitability of SI.

Understanding the impact of cultivated land-use changes on China's grain production potential and policy implications: A perspective of non-agriculturalization, non-grainization, and marginalization

Cultivated land plays a pivotal role in ensuring national food security. The challenges of non-agriculture, non-grain production and the marginalization of cultivated land have become increasingly pronounced in the context of urbanization and industrialization in China, posing potential threats to long-term food security. This study employs a combination of remote sensing and statistical data to reveal the effects of non-agriculturalization, non-grainization, and the marginalization of cultivated land on grain production potential (GPP) at the grid scale. From 1992 to 2020, the total farmland area initially exhibited an ascending trend followed by a subsequent decline, resulting in a net decrease of approximately 0.84% in China. the northward shift in the center of gravity of cultivated land has accentuated the spatial disparity between grain production and consumption. Non-agriculturalization, non-grainization, and marginalization of cultivated land contributed 35.22%, 22.58%, and 42.20% to the GPP loss, respectively. GPP loss exhibited significant differences across the agroclimatic zones, with the combined loss in the Middle-lower Yangtze Plain and Huang-Huai-Hai Plain exceeding 60% of the national total. Cultivated land marginalization has emerged as the most impactful land-use change affecting GPP, leading to a substantial loss of approximately 11471.30 × 104 t. The affected area is predominantly concentrated in the southern region. The marginalization of cultivated land has not been effectively alleviated, and the expansion trend continues. Conservation endeavors targeting cultivated land should prioritize enhancing farmers' willingness to cultivate, curbing the extensive utilization of farmland, and mitigating the escalating trend of farmland marginalization.

Attribution of vegetation fluorescence changes in China based on a decision tree stratification strategy

Vegetation photosynthesis plays a key role in maintaining carbon balance in terrestrial ecosystems. Solar-Induced chlorophyll Fluorescence (SIF) was utilized as a proxy for vegetation photosynthesis in this study, and the Theil-Sen and Mann-Kendall methods were used to examine trends of vegetation change in China. The impacts of climate conditions on vegetation photosynthesis were examined with the correlation analysis and recursive feature elimination (RFE) method. To distinguish the contributions of climate change and human activities on vegetation photosynthesis, land use data and SIF change trends were employed as inputs to a decision tree model. The results revealed that 81.5% of the areas in China exhibited an improving trend of vegetation photosynthesis. Vegetation degradation areas were mainly located in Northern arid and semi-arid region (NASR), Qinghai Tibet Plateau (QTP) and Huang-Huai-Hai Plain (HHHP). Precipitation dominated the effect of vegetation photosynthesis in these regions. The increase of vegetation photosynthesis in the southern regions was positively impacted by solar radiation. The growth of agricultural technology obviously benefited the improvement of vegetation photosynthesis in the Middle-lower Yangtze Plain (MLYP) and Northeast China Plain (NCP). Furthermore, the establishment of ecological conservation programs has helped to restore vegetation in arid and semi-arid areas. The detrimental effects of human activities included overgrazing disturbance and coal mining activities, which resulted in vegetation deterioration in areas of QTP and HHHP. The methodologies and findings of this study can help to comprehend changes in vegetation dynamics and give a theoretical foundation for evaluating regional ecological conservation initiatives.

An operational approach for large-scale mapping of water clarity levels in inland lakes using landsat images based on optical classification

Water clarity is a critical parameter of water, it is typically measured using the setter disc depth (SDD). The accurate estimation of SDD for optically varying waters using remote sensing remains challenging. In this study, a water classification algorithm based on the Landsat 5 TM/Landsat 8 OLI satellite was used to distinguish different water types, in which the waters were divided into two types by using the ad(443)/ap(443) ratio. Water type 1 refers to waters dominated by phytoplankton, while water type 2 refers to waters dominated by non-algal particles. For the different water types, a specific algorithm was developed based on 994 in situ water samples collected from Chinese inland lakes during 42 cruises. First, the Rrs(443)/Rrs(655) ratio was used for water type 1 SDD estimation, and the band combination of (Rrs(443)/Rrs(655) - Rrs(443)/Rrs(560)) was proposed for water type 2. The accuracy assessment based on an independent validation dataset proved that the proposed algorithm performed well, with an R2 of 0.85, mean absolute percentage error (MAPE) of 25.98%, and root mean square error (RMSE) of 0.23 m. To demonstrate the applicability of the algorithm, it was extensively evaluated using data collected from Lake Erie and Lake Huron, and the estimation accuracy remained satisfactory (R2 = 0.87, MAPE = 28.04%, RMSE = 0.76 m). Furthermore, compared with existing empirical and semi-analytical SDD estimation algorithms, the algorithm proposed in this paper showed the best performance, and could be applied to other satellite sensors with similar band settings. Finally, this algorithm was successfully applied to map SDD levels of 107 lakes and reservoirs located in the Middle-Lower Yangtze Plain (MLYP) from 1984 to 2020 at a 30 m spatial resolution, and it was found that 53.27% of the lakes and reservoirs in the MLYP generally show an upward trend in SDD. This research provides a new technological approach for water environment monitoring in regional and even global lakes, and offers a scientific reference for water environment management of lakes in the MLYP.

Integrating multi-influencing factor techniques and fuzzy methods to identify recommendation domains for out-scaling conservation agriculture in China

Climate-smart agriculture (CSA) is a global development strategy aimed to address the interlinked challenges of food security and climate change. Expanding the implementation of conservation agriculture (CA), a vital component of CSA, is essential for enhancing agricultural and food security resilience while sustainably managing arable land. However, the extensive heterogeneity of biophysical and socioeconomic conditions presents significant complexities in promoting CA adoption. Addressing these challenges, this study carried out a comprehensive theoretical investigation of biophysical and socioeconomic factors influencing CA adoption and performance, integrating stakeholder feedback to create a systematic and robust evaluation index system for assessing CA suitability. By integrating multi-influencing factor techniques and fuzzy logic methods, we spatially identified suitable areas for CA implementation in China, providing valuable insights for land use policy. The reliability of the models was verified through a sensitivity analysis using the map removal sensitivity analysis method and the extended Fourier amplitude sensitivity test. The results indicated that 29.78% of the cultivated land was unsuitable or marginally suitable for CA, while 29.30 and 40.92% were determined to be moderately suitable and suitable zones, respectively. Suitable cultivated land was primarily distributed in the northern arid and semi-arid regions, the Loess Plateau, the Huang-Huai-Hai Plain, and the Northeast China Plain. Conversely, unsuitable, and marginally suitable cultivated land was predominantly located in the Qinghai Tibet Plateau, Middle-lower Yangtze Plain, Sichuan Basin and surrounding areas, the Yunnan-Guizhou Plateau, and Southern China. The topographical index, annual mean precipitation, humidity index, and population density were identified as the most significant factors influencing CA suitability. The CA suitability maps generated in this study will guide the development and extension agents targeting CA to suitable locations with a high potential impact, thereby maximizing the likelihood of adoption and minimizing the risk of failure.

Quantifying the agreement and accuracy characteristics of four satellite-based LULC products for cropland classification in China

Various land use and land cover (LULC) products have been produced over the past decade with the development of remote sensing technology. Despite the differences in LULC classification schemes, there is a lack of research on assessing the accuracy of their application to croplands in a unified framework. Thus, this study evaluated the spatial and area accuracies of cropland classification for four commonly used global LULC products (i.e., MCD12Q1 V6, GlobCover2009, FROM-GLC and GlobeLand30) based on the harmonised FAO criterion, and quantified the relationships between four factors (i.e., slope, elevation, field size and crop system) and cropland classification agreement. The validation results indicated that MCD12Q1 and GlobeLand30 performed well in cropland classification regarding spatial consistency, with overall accuracies of 94.90 and 93.52%, respectively. The FROM-GLC showed the worst performance, with an overall accuracy of 83.17%. Overlaying the cropland generated by the four global LULC products, we found the proportions of complete agreement and disagreement were 15.51 and 44.72% for the cropland classification, respectively. High consistency was mainly observed in the Northeast China Plain, the Huang-Huai-Hai Plain and the northern part of the Middle-lower Yangtze Plain, China. In contrast, low consistency was detected primarily on the eastern edge of the northern and semiarid region, the Yunnan-Guizhou Plateau and southern China. Field size was the most important factor for mapping cropland. For area accuracy, compared with China Statistical Yearbook data at the provincial scale, the accuracies of different products in descending order were: GlobeLand30, FROM-GLC, MCD12Q1, and GlobCover2009. The cropland classification schemes mainly caused large area deviations among the four products, and they also resulted in the different ranks of spatial accuracy and area accuracy among the four products. Our results can provide valuable suggestions for selecting cropland products at the national or provincial scale and help cropland mapping and reconstruction, which is essential for food security and crop management, so they can also contribute to achieving the Sustainable Development Goals issued by the United Nations.

Linking atmospheric emission and deposition to accumulation of soil cadmium in the Middle-Lower Yangtze Plain, China

Cadmium (Cd) is one of the most toxic heavy metals in the environment. Atmospheric deposition has been found to be the main source of Cd pollution of soil on a large scale in China, and identification of the relationships between anthropogenic emission, atmospheric deposition, and Cd accumulation in soil is important for developing ways to mitigate Cd non-point pollution. In this study, the relationship between atmospheric emission, atmospheric deposition, and soil Cd accumulation in the Middle-Lower Yangtze Plain in China was investigated using datasets of atmospheric emission, deposition, and soil accumulation from the literatures published between 2000 and 2020. The results showed that the soil Cd accumulation rate in the study area exceeded the national average (4.0 μg kg–1 yr–1) and continued to accumulate in recent decades, although the average accumulation rate decreased from 9.45 μg kg–1 yr–1 (2000–2010 period) to 8.86 μg kg–1 yr–1 (2010–2020 period). The contribution of atmospheric deposition flux to Cd increment in the soil was in the range of 22–29%, with the atmospheric deposition flux decreasing from 0.54 mg m–2 yr–1 (2000–2010) to 0.48 mg m–2 yr–1 (2010–2020), both values being greater than the national average. Atmospheric Cd deposition and emission were highly correlated in a provincial administrative region, which is close to a ratio of 1.0. Emission factors may be in a state of dynamic change due to the influences of new Cd emission control technologies and environmental policies. As the main sources of Cd emissions, dust, and smoke emissions per ton of non-ferrous metal production decreased by 64.7% between the 2000–2010 and 2010–2020 periods. Although new environmental policies have been instigated, atmospheric emission of Cd is still excessive. It was hoped that the findings of this work would provide a scientific basis for the rational control of atmospheric emissions and Cd pollution of soil.

Particle Size Distribution and Depth to Bedrock of Chinese Cultivated Soils: Implications for Soil Classification and Management

Although a number of studies have provided information on soil texture, soil classification, and depth to bedrock throughout China, few studies have combined this information, which is the basis for agricultural field management. A total of 81% of China’s cultivated lands are distributed among the Middle–Lower Yangtze Plain (18.2%), arid and semiarid North China Plain (18.2%), Northeast Plain (17%), Huang-Huai-Hai Plain (16.1%), and Yunnan–Guizhou Plateau (11.6%). The Huang-Huai-Hai Plain has the highest density of agricultural land (58.5%) and the greatest depth to bedrock of cultivated land (243–402 m). The lowest cultivated depth to bedrock (4–84 m) is concentrated in the Sichuan Basin and its surrounding regions. The main cultivated soil types are Anthrosols, Fluvisols, Cambisols, Phaeozems, Luvisols, Kastanozems, Leptosols, and Acrisols, under the main topsoil texture classes of loam, clay loam, silty clay loam, silt loam, sandy loam, and clay. The Fluvisols had the largest depth to bedrock (156 m) on the Middle–Lower Yangtze Plain and Huang-Huai-Hai Plain, with the highest silt soil distributions but comparable lower sand contents. The Yunnan–Guizhou Plateau had the highest clay soil content. The cultivation under Kastanozems and Leptosols on the Qinghai–Tibet Plateau and in arid and semiarid North China and under Phaeozems on the Northeast Plain should be restricted and managed very cautiously facing erosion risk. The higher percentages of Anthrosols are on the Middle–Lower Yangtze Plain (37%), in Southern China (32%), and on the Yunnan–Guizhou Plateau (26%). The same cultivation aim (i.e., more crop 0production) has produced a similar range of properties over time among the soils developed on agricultural fields, which are classified as Anthrosols. However, various soil types can still be found in agroecosystems because of the variations in climate and topography. Our results highlight that the agriculture-based soil climate and topography shape the interaction of the soil development and not only the pedogenic history of the soil development under variations in the soil depth to bedrock but also the cultivation of distinct pedogenic features. This study provides cultivated soil information on the depth to bedrock, soil classification, and soil texture in China, as well as instructions for field strategies for sustainable agricultural development.

Long-Term Changes in Water Body Area Dynamic and Driving Factors in the Middle-Lower Yangtze Plain Based on Multi-Source Remote Sensing Data

The accurate monitoring of long-term spatial and temporal changes in open-surface water bodies offers important guidance for water resource security and management. In the middle and lower reaches of the Yangtze River, the monitoring of water body changes is especially critical due to the dense population and drastic climate change. Due to the complexity of the physical environment in which the water bodies are located, the advantages and disadvantages of various water body detection rules can vary in large-scale areas. In this paper, we use Landsat 5/7/8 data to extract the area of water bodies in the study area and analyze their spatial and temporal trends from 1984 to 2020 using the Google Earth Engine (GEE) platform. We propose an improved water body extraction rule based on an existing multi-indicator water body algorithm that combines impervious surface data and digital elevation model data. In this study, the performance of the improved algorithm was cross-validated using seven other water body indicator algorithms, and the results showed the following: (1) the rule accurately retained information about the water body while minimizing the interference of shadows on the extracted water body. (2) On the annual scale from 1984 to 2020, the open-surface water body dataset extracted using this improved rule showed that the turning point for the area of each water body type was 2011, with an overall decreasing trend in area before 2011 and an increasing trend in area after 2011, with the exception of special years, such as 1998. (3) The driving mechanism analysis showed that, overall, precipitation was positively correlated with the water body area and temperature was negatively correlated with the water body area. Additionally, human activities can have an impact on surface water dynamics. The key influencing factors are diverse for each water body type; it was found that seasonal water bodies were correlated with precipitation and paddy fields and permanent water bodies were correlated with temperature and urban construction. The accurate monitoring of the spatial and temporal dynamics of open-surface water performed in this study can shed light on the sustainable development of water resources and the environment.

Mapping the representativeness of precipitation measurements in Mainland China

Meteorological observations provide essential data for weather forecasting and climate change studies. Whether the measured data can accurately support such applications closely relates to the representativeness of the data collected, which depends on both the scale of observation and the density of the measurement network. Precipitation presents in the form of events and is discontinuous both in time and space. Gauge observations of precipitation could provide fundamental data but have difficulty quantitatively assessing precipitation system scale. Therefore, assessments on the representativeness of precipitation at synoptic and climatological scales remain needed. Here, we show the first high-resolution map of the representativeness of precipitation over Mainland China based on the latest satellite data. Our results show that the daily precipitation spatial consistency is the highest in eastern China and lowest on the Tibetan Plateau. However, the pattern of the monthly spatial consistency is different and is the highest over Northeast China Plain, the Loess Plateau, and the Middle–Lower Yangtze Plain. Compared to the density of rain gauges, we find that the current national station network with ∼2400 stations still has difficulty supporting synoptic studies in western China. However, for climate change studies based on monthly data, the density of the national reference climatological station network is sufficient, except in the western Tibetan Plateau and deserts with no available stations. For climatological studies, the quality of precipitation gauge observations is more important than its spatial density. Our results could provide great practical significance for considering the layout of rain gauges.

Impacts of Rice Cropping System Changes on Paddy Methane Emissions in Southern China

Rice paddies are one of the main sources of anthropogenic terrestrial CH4. In recent decades, the substitution of single-cropping rice (SCR) for double-crop rice (DCR) has become more common in southern China. However, the concomitant impacts on CH4 emissions have not been quantified. We incorporated high-resolution rice cropping system maps into the CH4MOD model to calculate changes in CH4 emissions in southern China due to DCR conversion to SCR over the period 1990 to 2015. We find that a total planting area of 253.64 ×104 ha was converted from DCR to SCR. This conversion resulted in a 451.94 Gg reduction in CH4 emissions, accounting for 8.4% of CH4 emissions from paddies in China in 2015. The largest reduction was in the Middle–Lower Yangtze plain with high labor pressures. As urbanization continues, we project that the total CH4 emissions have the potential to decrease by between 17.1% and 9.2% under DCR conversion to SCR in southern China in the extreme and most likely scenarios, respectively. As farmers voluntarily move to SCR in response to labor scarcity, making full use of the land-use change trend of DCR to SCR may be an opportunity to reduce agricultural methane emissions, which is important for achieving Sustainable Development Goals (SDGs) and should be given more attention.

Farmland nutrient pollution and its evolutionary relationship with plantation economic development in China

Contradiction between growing plantation economic demand and agro-ecological degradation has always restricted sustainable development of agricultural countries. This study applied the unit inventory analysis to evaluate the productions and discharges of farmland non-point source (FNPS) nitrogen (TN) and phosphorus (TP) among China's nine national-level agricultural districts over 1999–2019. On this basis, we quantified the evolutionary relationship between plantation economic output and FNPS pollution based on optimal regression fitting. The results showed that over 1999–2019, farmland cumulative TN and TP discharges for the whole China were approximately 15807 × 104 t and 1312 × 104 t, with prominent district heterogeneity. According to FNPS discharge magnitudes, China's agricultural districts can be classified into three categories: high, moderate and slight discharge zones. Huang-Huai-Hai Plain and Middle-lower Yangtze Plain were identified as the main severely-polluted districts. Mineral fertilizer is the primary contributor to FNPS pollution. Annual FNPS load showed a trend of increasing followed by decreasing, and the peak interval was recorded in 2014–2016. Spatiotemporal dynamics in FNPS discharge intensities were disparate from that in discharge magnitudes. SC has the highest TN discharge intensity, with an annual average intensity of 0.068 t/ha, followed by MLYP (0.044 t/ha) and HHHP (0.041 t/ha). HHHP has the highest TP discharge intensity, with an annual average intensity of 0.0051 t/ha, followed by SC (0.0038 t/ha) and MLYP (0.0031 t/ha). District-based agro-ecological restoration strategies were accordingly proposed considering FNPS discharge magnitude and intensity concurrently. In most agricultural districts, with the growing economic output in plantation, the FNPS load showed an increase followed by a decrease or to leveling off. Furthermore, with the increasing TN/TP economic partial productivity, the FNPS TN/TP discharge intensities reached the climax, then declined or tended to be flattening out.

Urban expansion dynamic and its potential effects on dry-wet circumstances in China's national-level agricultural districts

Although urbanization has been widely examined in individual city and urban agglomeration scales, urban expansion patterns and dynamics in large-scale agricultural districts remain absent. In this study, multifaceted characteristics in urban expansion were quantified in China's nine national-level agricultural districts, and responses of dry-wet circumstances to urban sprawl were evaluated. From 1980 to 2018, China has undergone an extensive urban sprawl. Huang-Huai-Hai Plain (HHHP) has the maximum urban coverage extent, followed by Middle-lower Yangtze Plain (MLYP) and Southern China (SC). The largest annual increase was recorded in MLYP, reaching 816.12 km2; followed by HHHP, with an annual increase of 725.22 km2. There are prominent heterogeneities in expansion rate and direction among various districts. The dominating growth patterns were edge- and leapfrogging-expansion, accompanying by a less percentage of infilling-expansion. Accompanying by urbanization, connectedness in urban landscapes gradually improved, while separation degree decreased. Upon many occasions, holistic average dry-wet circumstances in non-urbanized areas are superior to those in urban areas, although this is not absolute for all the districts or periods. In urbanization progress, the development of leapfrogging-expansion has a potential to ameliorate dry-wet circumstances in both urban and non-urban zones, while infilling- and edge-expansion would constitute an inverse effect. In comparison to urban zones, leapfrogging-expansion would cause a more prominent effect on dry-wet environment in non-urbanized zones. Increased connectivity in urbanized landscapes would improve dry-wet environments, especially for urbanized zones. Inversely, increased spatial separated extent among urban landscapes would perform an opposite effect. This study provides a potential for understanding the dynamic features of urban expansion in large-scale agricultural districts. Moreover, the results can also provide a potential opportunity for optimizing dry-wet environments by regulating urbanization pattern and landscape configuration.

Soybean Production and Spatial Agglomeration in China from 1949 to 2019

By mastering the spatial-temporal evolution of patterns of soybean production, a reference for optimizing a soybean production layout could be provided, ensuring food security. The variation coefficient method, and the comparative advantage and spatial autocorrelation models were used to analyze the spatial divergence regularities of soybean production, sown area and yield, spatial-temporal changes in the comparative advantages of soybean planting efficiency and soybean planting scale, and the spatial agglomeration characteristics in China from 1949 to 2019. The results indicate that (1) from 1949 to 2019, soybean production and yield changes in China remained constant with a fluctuating upwards trend, and soybean sown areas hardly changed, yet experienced a sharp fluctuation. (2) The Northeast China Plain (NECP) was the main soybean-producing area, and its main position was strengthened. In contrast, the main soybean production position of the Huang-Huai-Hai Plain (HHHP) has declined. The Northern arid and semiarid region (NASR), the Sichuan Basin and surrounding areas (SBSR), the Middle-Lower Yangtze Plain (MLYP), and the Yunnan-Guizhou Plateau (YGP) became new soybean production growth poles. (3) The spatial distribution of soybean planting efficiency-related comparative advantages in China extended from northern China to the whole country, and the soybean planting scale-related comparative advantages proceeded through three stages: steady expansion, relative stability, contraction, and stabilization. (4) The spatial agglomeration of soybean planting efficiency-related comparative advantages has weakened, and the spatial agglomeration of the soybean planting scale-related comparative advantages exhibited a strengthening-weakening-strengthening-weakening process. Through our research analysis, we propose a policy resource to fully utilize the soybean planting efficiency-related comparative advantages in southern China (SC), promote grain-soybean rotation patterns in the HHHP and NECP, improve the soybean cultivation subsidy system, and build a soybean industry chain in the NECP.