Farmland Area Research Articles

Analysis of Temporal and Spatial Evolution Characteristics of Land Subsidence in Western Songnen Plain Using Multisource Remote Sensing

Abstract The exploitation of underground fluid is an important factor leading to land subsidence. The effects of mining depth, frequency, and mode on land subsidence are also different. The objective of this study was to develop a multisource method—including optical remote sensing interpretation, Interferometric Synthetic Aperture Radar (InSAR) technology, and unmanned aerial vehicle (UAV)—to reveal the long-term temporal and spatial evolution law of subsidence characteristics driven by groundwater and oil extraction, as well as to reveal the formation mechanism and seasonal response law of land subsidence under the action of different driving factors. In this paper, we select the western region of Jilin Province located in Songnen Plain as the study area. The subsidence funnels in the study area are distributed in a porphyritic manner, and the distribution of the subsidence funnels has a certain correlation with the distribution of the pumping wells. In farmland areas, the subsidence is mainly caused by pumping groundwater. The annual land subsidence rate in the study area is -3.14 mm/a, and the maximum deformation rate in the study area is -22.05 mm/a. The subsidence is affected by the season, shown by the fact that it rises in the dry season and decreases in the rainy season. The subsidence in the west of Songnen Plain is caused by oil pumping and groundwater pumping, and groundwater pumping is dominant. The exploitation of underground fluid transfers the pressure borne by water or oil to the soil skeleton so as to increase and consolidate the effective stress of the soil layer and lead to land subsidence. The continuous observation of the surface in the western area of Songnen Plain is helpful to guide the safe production of agriculture and industry and ensure the smooth development of local industry and agriculture.

Spatio-Temporal Matching and Nexus of Water–Energy–Food in the Yellow River Basin over the Last Two Decades

There is an important practical significance to understanding and evaluating the nexus of water, energy, and food (WEF) for ensuring regional security. The Yellow River Basin is a typical area displaying the contradiction between water, energy, and food development caused by the difference in resource distribution and production attributes. The nexus of the WEF system in the Yellow River Basin is systematically and innovatively studied from different perspectives. The aim of the research is to analyze the distribution and transfer direction of single resource elements, the matching and evolution of two kinds of resources linked by water resources, and finally the nexus based on Copula function. The results show that water resources, farmland, and energy production are concentrated in different areas, while the center of gravity shifted to the northwest, northeast, and west of the basin, respectively. For the resource balance of energy production and available industrial water resources, the matching degree has become worse in recent years. For the resource balance of farmland areas and available agricultural water resources, the matching degree in the most source area and middle reaches has improved, but the gap among different sub-regions has widened slightly. It is proven that the three-dimensional t Copula is well characterized by the nexus of the WEF system in the Yellow River Basin. The joint not exceeding the probability of the WEF (W ≤ 7.08 × 1010 m3, E ≤ 6.24 × 108 TCE, F ≤ 4.23 × 107 t) is about 0.3–0.4. The WEF system in the Yellow River Basin (Gn = 0.728 and 0.688) may still have certain security risks in the future compared with other regions in the world, which needs to be regulated by more reasonable policies. This study can provide a theoretical basis for ensuring regional water, energy, and food security.

Shallow Groundwater Around Plateau Lakes: Spatiotemporal Distribution of Nitrogen and Its Driving Factors

Shallow groundwater around plateau lakes is one of the important sources of production and potable water. Shallow groundwater NO3--N pollution driven by factors such as surface nitrogen input load, rainfall, and irrigation is serious and threatens the water quality of plateau lakes. In order to identify the characteristics of nitrogen pollution and its driving factors in shallow groundwater, 463 shallow groundwater samples were collected from wells in farmland and residential areas around eight plateau lakes of Yunnan in the rainy and dry seasons in 2020 and 2021. The results showed that the average values of ρ(TN), ρ(NO3--N), ρ(ON), and ρ(NH4+-N) in shallow groundwater were 24.35, 15.15, 8.41, and 0.79 mg·L-1, respectively. Nearly 32% of the shallow groundwater samples around the eight lakes failed to meet the groundwater Class Ⅲ water quality requirements (GB/T 14848) of 20 mg·L-1 for NO3--N. Among them, the NO3--N concentration in the shallow groundwater around Erhai Lake, Qiluhu Lake, and Dianchi Lake had the highest rate of exceeding the standard, followed by that around Xingyunhu Lake, Yangzonghai Lake, Yilonghu Lake, Fuxianhu Lake, and Chenghai Lake as the smallest. Land use and seasonal changes affected the concentration and composition of various forms of nitrogen in shallow groundwater. The concentration of various forms of nitrogen in shallow groundwater in the farmland area was higher than that in the residential area. The nitrogen concentration in shallow groundwater in farmland was higher than that in residential areas. Except for NH4+-N, the concentration of various forms of nitrogen in shallow groundwater in the rainy season was higher than that in the dry season. NO3--N was the main nitrogen form in shallow groundwater; the fraction of TN was 57%-68%, and the fraction of ON was 27%-38%. The EC, DO, ORP, and T in shallow groundwater were the key factors reflecting or affecting the concentration of various forms of nitrogen in shallow groundwater, whereas soil factors had a weak impact on the concentration of various forms of nitrogen in shallow groundwater.

How Does Social Embeddedness Affect Farmers’ Adoption Behavior of Low-Carbon Agricultural Technology? Evidence From Jiangsu Province, China

Agricultural carbon emissions, which are the second largest source of greenhouse gas emissions in China, not only place great pressure on emission reduction but also seriously affect food security and sustainable development of agriculture. As farmers are the direct users of cultivated land and the main adopters of agricultural technology, their adoption behavior of low-carbon agricultural technology directly determines its promotion and subsequent emissions reduction. It is of great theoretical and practical significance to analyze farmers’ adoption behavior of low-carbon agricultural technology and their influencing factors. Based on social embeddedness theory and the survey data of 688 farmers in Jiangsu Province, this study applied a logistic model to analyze the impact of government support, farmers’ cognition, social capital, personal characteristics, and family characteristics on farmers’ adoption behavior of low-carbon agricultural technology. The results showed that (1) only 58.72% of farmers have adopted such a technology, which needs to be further improved; (2) government support and farmers’ cognition had significantly positive influences on farmers’ adoption behavior; (3) social capital is an important factor affecting farmers’ adoption decisions, where social trust, networks, and norms play a significant role in promoting the adoption of low-carbon agricultural technology; and (4) party membership and household-contracted farmland area also had positive influences on farmers’ adoption behavior of low-carbon technology. Therefore, to continue developing low-carbon agriculture, it is recommended to further strengthen government support, raise the price of low-carbon agricultural products, strengthen environmental supervision, and build a social embedded environment according to local conditions, and further improve farmers’ social trust, enrich social networks, improve social norms, and give full play to the guiding and exemplary role of social capital. Additionally, it is also recommended to reinforce education and training to raise farmers’ awareness regarding low-carbon agricultural technology, thereby guiding them to actively adopt these technologies.

Anthropogenic induced land use/cover change dynamics of Budongo-Bugoma landscape in the Albertine region, Uganda

Understanding spatio-temporal land use land cover change is vital in responding to the dynamic and complex global environmental change that is having diverse effects on integrity of most landscapes. A study was conducted in the Budongo - Bugoma landscape to assess spatio-temporal patterns of land use land cover change using supervised image classification of Landsat imagery for 1990, 2000, 2010, 2020 and a prediction of LULC situation in 2040 done in Dinamica-EGO modelling platform. Between 1990–2020, there was a declining trend for grassland, bushland, and tropical high forest by −19.5%, −4.7%, and −2.7% respectively while subsistence farmland, commercial farmland, built-up areas experienced an overall rate of change of 19.0%, 5.0%, 3.5% respectively. This led to intensified landscape fragmentation and increased landscape homogeneity to mostly farmlands. The declining LULC classes were majorly converting to the increasing LULC classes with conversion hotspot areas detected in privately-owned lands occurring mainly in rural areas, sugarcane growing areas, refugee settlement areas, and oil/gas project sites. In 2040, it is predicted that approximately 50% of the landscape will be covered by human managed LULC classes including subsistence farmland, commercial farmland, and built-up area compared to approximately 40% in 2020. Agricultural activities and increased population density were the most significant drivers of the established land use land cover changes. This study has shown accelerated loss of key land cover biomes; grasslands, bushlands, and tropical high forests mediated by anthropogenic factors and leading to reduced landscape heterogeneity thus potential to significantly affect ecosystem services supply in this region. Promotion of agroecology, non-consumptive projects, and participatory land use planning are recommended to secure sustainable land use management. Establishment of the implication of LULCC on ecosystem services potential and ultimately human well-being is also recommended.

Land Cover and Land Use Changes between 1986 and 2018, and Preliminary Carbon Footprint Implications for Manoka Island (Littoral Region of Cameroon)

Land and resource use patterns in coastal areas play a key role in the resilience of ecosystems and populations to climate change. Knowing their spatiotemporal dynamics therefore constitutes a strategic tool to help decision-makers. Based on documentary research, geographic information system (GIS), image processing, and field work, this article maps land use on Manoka Island between 1986 and 2018 and identifies the drivers of change and avenues for intervention with a view to strengthening climate change mitigation. The results show a decrease of 4% in forest area on Manoka Island, representing an average of 112 ha of inland forest and 267 ha of mangrove converted between 1986 and 2018. This increases the degraded forest area by 268% (degraded mangrove and degraded inland forest) and exposes some camps to erosion and flooding. Reduction in forest area is mainly linked to the harvesting of fuelwood and the conversion of forests into farmland and residential areas. Settlements have increased in area from 15 ha in 1986 to 90.4 ha in 2018 to the detriment of natural spaces.

Obstacle Avoidance and Profile Ground Flight Test and Analysis for Plant Protection UAV

In recent years, with the further development of agricultural aviation technology, the plant protection UAV has been widely used, especially in some agricultural environments with limited operating conditions due to its advantages of high efficiency, environmental protection and safety guarantee. A plant protection UAV generally flies at low altitude during operation. However, the low altitude operation environment, such as farmland and mountainous areas, is relatively complex, and is faced with many types of obstacles, proposing higher requirements for obstacle avoidance and the profiling system of a plant protection UAV. In order to test the obstacle avoidance and profiling performance of the commercialized plant protection UAV at this stage and explore the performance boundary of obstacle avoidance and profiling of the UAV, EAVISION E-A2021 and XAG P80, the flagship models of the plant protection UAV manufacturer on the market, were hereby selected as the experimental test objects in the paper. Firstly, the obstacle avoidance and profiling test scheme of plant protection UAVs is designed; then, the above two UAVs are adopted for corresponding tests, and the test data are discussed based on the analysis of software and hardware technology; finally, the practical application status of different obstacle avoidance and profiling technologies of plant protection UAVs is clarified, and the shortcomings of obstacle avoidance and profiling technology of plant protection UAVs on the market are summarized, providing a reliable reference for the future development of plant protection UAVs.

Identification of Factors Affecting Environmental Contamination Represented by Post-Hatching Eggshells of a Common Colonial Waterbird with Usage of Artificial Neural Networks.

Artificial Neural Networks are used to find the influence of habitat types on the quality of the environment expressed by the concentrations of toxic and harmful elements in avian tissue. The main habitat types were described according to the Corine Land Cover CLC2012 model. Eggs of free-living species of a colonial waterbird, the grey heron Ardea cinerea, were used as a biological data storing media for biomonitoring. For modeling purposes, pollution indices expressing the sum of the concentration of harmful and toxic elements (multi-contamination rank index) and indices for single elements were created. In the case of all the examined indices apart from Cd, the generated topologies were a multi-layer perceptron (MLP) with 1 hidden layer. Interestingly, in the case of Cd, the generated optimal topology was a network with a radial basis function (RBF). The data analysis showed that the increase in environmental pollution was mainly influenced by human industrial activity. The increase in Hg, Cd, and Pb content correlated mainly with the increase in the areas characterized by human activity (industrial, commercial, and transport units) in the vicinity of a grey heron breeding colony. The decrease in the above elements was conditioned by relative areas of farmland and inland waters. Pollution with Fe, Mn, Zn, and As was associated mainly with areas affected by industrial activities. As the location variable did not affect the quality of the obtained networks, it was removed from the models making them more universal.

WHY ARE FARMERS WILLING TO JOIN PARTNERSHIPS IN ORGANIC RICE? CASE IN NGAWI ORGANIC CENTER COMMUNITY, EAST JAVA

Organic farming is more profitable because of the increasing demand and high product prices. However, it is not easy for farmers to decide on rice farming organically. Farmers faced obstacles such as limited capital, lack of knowledge about organic technology, and no price guarantee for organic farmers who have not been certified organic. It is necessary to develop some policies such as institutions. A partnership is one of the institution's solutions for farmers to increase their willingness to join organic rice farming. This research was conducted in Ngawi Regency, East Java, from March 2020. Ngawi Organic Center Community (KNOC) is a partner institution with experience in pioneering and fostering organic farmers. The research aims to analyze (1) the factors that influence organic rice farmers for decision-making partnership; (2, the mechanism of organic rice partnership; and (3) the benefits farmers get from the partnership. Logistic Regression used to analyze the factors that influence the farmers' decisions. Descriptive analysis is used to investigate the mechanism of organic rice partnership between organic rice farmers and KNOC. The descriptive analysis also describes the benefits of partnerships received by farmers. The study results show that farming experience, land area and frequency of extension significantly affect farmers' decision making. The organic rice partnership mechanism regulated in a written contract, with the Agribusiness Operational Cooperation partnership pattern. The high price of organic rice is the most profitable partnership benefit for farmers (81,67%).

Sustainable Livelihood of Households in Tourism Destination: Evidence From in the Wulingyuan World Heritage Site

In the process of resource protection and development of World Heritage Sites, the sustainability of the livelihoods of heritage site residents is one of its important tasks. Taking Wulingyuan, a world heritage tourism site, as an example to construct the livelihood evaluation index system of households, and use the participatory farmer survey method to conduct household surveys on households. Based on livelihood strategies, households are divided into different types of livelihood, their livelihood capital is assessed, and their livelihood obstacle factors are identified. The research results show that: Under the influence of rural tourism development, households' livelihood capital has been improved as a whole. There are differences in the level of livelihood capital of different types of households. From high to low, they are: tourism-dominant type, working-dominant type and agricultural--dominant type. The World Heritage Site households' Sustainable Livelihood Obstacle Index is ranked from high to low as social capital, human capital, financial capital, natural capital, and physical capital; the top three indicators are: online social media, social network support, family farmland area. Different types of households have different obstacles, social capital is the biggest obstacle in common among the three types of households, and the primary obstacle is online social media.

SPATIO-TEMPORAL ANALYSIS OF URBAN LAND USE AND LAND COVER CHANGE USING GEOSPATIAL TECHNIQUES IN HOSSANA TOWN, ETHIOPIA

Urban expansion is widespread in most developing countries while the nearby farmland area coverage is shrinking which in turn attracting the attention of many actors to manage the encroachment scientifically. This study aims to analyze the urban land use and land cover change in Hossana town using geospatial techniques. Three Landsat images were used and analyzed using ArcMap 10.5. The images were classified and reclassified into six land use classes. The result showed visible land cover change and a high rate of town expansion in the study area. The forest area surrounding the town and bareland decreased from 5702 (48.8 %) to 1515 ha (12.97 %) and from 2224.3 ha (19.1%) to 226.2 ha (1.94 %) from 1986 to 2019 whereas farmland and built-up areas increased rapidly from 3078 ha (26.4%) to 5599.5 ha (47.95%) and from 141.1 (1.2%) to 3581.4 ha (30.67%) in the study period, respectively. Thus, the land cover change result for the built-up area has eventually expanded through the study period. In contrary, the land cover under forest, water, bareland, open area (greenery) and farmland have shown tremendous decrease within the last three decades, respectively. The expansion of farmland and settlement areas implies high population inflow to the urban area from the rural and fringe areas. Thus, the settlement pattern and land use shall be governed by well-planned policies to manage rapid population growth and migration from rural areas which causes poor land management and illegal housing. The application of geospatial techniques are mandatory tools to analyze the spatio-temporal changes in urban areas.

Habitat quality assessment of mining cities based on InVEST model\u2014a case study of Yanshan County, Jiangxi Province

The assessment of the spatiotemporal evolution of habitat quality caused by land use changes can provide a scientific basis for the ecological protection and green development of mining cities. Taking Yanshan County as an example of a typical mining city, this article discussed the spatial pattern and evolution characteristics of habitat quality in 2000 and 2018 based on the ArcGIS platform and the InVEST model. The conclusions are as below: from 2000 to 2018, the area of farmland and construction land changed the most in the study area. Among them, the area of farmland decreased by 3.48%, and the area of industrial and mining land and construction land increased by 53.25%. Areas of low, relatively low and high habitat quality expanded, and areas of medium and relatively high habitat quality shrank, which is closely related to the distribution of land use. The areas with high habitat degradation degrees appear around cities, mining areas and watersheds, while the areas with low habitat degradation degrees are mainly distributed in the southern woodland. The distribution of cold and hot spots in the habitat quality distribution of Yanshan County presents a pattern of “hot in the south and cold in the north”. The results are of great significance to the precise implementation of ecosystem management decisions in mining cities and the creation of a landscape pattern of “beautiful countrysides, green cities, and green mines”.

Fire effects on riparian vegetation recovery and nutrient fluxes in Brazilian Cerrado

AbstractFire can change gallery forest vegetation structure, thereby altering nutrient fluxes between terrestrial and aquatic ecosystems. In Brazilian savannas, which are fire‐prone ecosystems, the fire regime is changing due to human activities such as converting native vegetation to farmland and urban areas. Uncontrolled wildfires in these savannas can reach gallery forests, which are more sensitive to fire impacts, leading to concerns about the effects of fire on gallery forest vegetation structure and freshwater ecosystems. We analysed the relationships between fire severity (the degree to which the fire has changed an area), percentage of burned area, variation in precipitation with gallery forest and savanna vegetation structure recovery and input of nutrients (NH4, , and ) to streams for 16 months after a fire event in five watersheds associated with small streams. One year after the fire, vegetation recovery (NDVI) was lower in gallery forest areas than in savanna woodlands, despite the more severe fires in savannas. The short‐term effects of fire on gallery forest vegetation included increased nitrate concentrations in streams, which were also influenced by increased precipitation and the extent of the burned area. The nutrient inputs into the stream stabilized within 1 year. However, gallery forest vegetation did not fully recover at that time and may continue to alter the functioning of the aquatic ecosystem. Together, these results demonstrate the need for an integrated fire management plan that considers both gallery forests and the surrounding savannas in the landscape to address consequences to aquatic ecosystems.

Remote Sensing Satellite Image-Based Monitoring of Agricultural Ecosystem

In the agricultural ecosystem, it is necessary to grasp the differences of soil fertility and crop growth in time and space. With the rapid development of remote sensing and its popularization and application in social production practice, remote sensing has become a new way to obtain farmland information. At present, remote sensing means in the field of agroecosystem monitoring mainly include satellite remote sensing and unmanned aerial remote sensing. It can monitor and manage the agro-ecosystem environment in real time by acquiring remote sensing images. It can monitor the growth and identification of crops, pests, and diseases, and water supply, analysis timely, and effectivity for the spatial information provided by a feedback processing. But its performance needs to be improved. In this paper, the imaging methods and main features of remote sensing images are introduced in order to analyze the characteristics of agricultural ecosystem targets in remote sensing images. Then, based on object-oriented classification technology, a series of farmland images are preprocessed, segmented, and sparsely represented. Processing operations are used to study how to transform crop observation into crop and noncrop discrimination in remote sensing data. The research shows that the effective acquisition of crop image area and the remote sensing monitoring of crop farmland area can be achieved by processing the crop field map image obtained by remote sensing.

Drivers of the peasant households’ part-time farming behavior in China

Rural households in China are now diversifying from full-time agriculture to part-time griculture where they are engaging in different off-farm activities along with farming. Understanding the driving factors that affect the peasant households' part-time farming behavior has significant implications for rural developing and farm income support policy. This study intend to identify the driving factors to affect the peasant households' part-time farming behavior and present some corresponding proposals. A total sample of 2074 households from 3 district 9 provinces was selected through purposive sampling technique. While confirming some findings of previous research with respect to the effects of human capital and household peasant characteristics on part-time farming participation, this study shows differential impact of those variables. The results show that the degree of part-time farming in eastern China is higher than that in central and western China. There is a small difference between central and western China. The top 5 factors influencing the peasant household's part-time behavior, in order, are the area of farmland per capita (AFC), the distance from village to county center (TCC), the proportion of paddy field (PPF), the distance from village to town center (TTC), and the householder's age (A). It shows that the influencing factors vary among different regions based on the analysis of eastern, central and western China. The study recommends the implementation of policies that facilitate rural off-farm activities and enhance balanced economic growth of the country.

Spatial and Temporal Changes of Landscape Patterns and Their Effects on Ecosystem Services in the Huaihe River Basin, China

Landscape pattern changes caused by human activities are among the most important driving factors affecting ecosystem spatial structure and components, and significantly impact ecosystem services. Understanding the relationship between landscape patterns and ecosystem services is important for improving regional conservation and establishing ecosystem management strategies. Taking the Huaihe River Basin as an example, this study used land-use data, meteorological data, and topographic data to analyze the spatial and temporal changes in landscape patterns via landscape transfer matrix and landscape indices, and measured four ecosystem services (water retention, soil retention, carbon storage, and biodiversity conservation) with the InVEST models. Furthermore, correlation analysis and global spatial autocorrelation coefficient were used to analyze the impact of landscape pattern changes on ecosystem services. The results showed grassland and farmland areas had continuously decreased, while built-up land and affected water had significantly increased. Landscape fragmentation was reduced, the connectivity between patches was weakened, landscape heterogeneity, evenness, and patch irregularity were increased. Changes in landscape composition and configuration have affected the ecosystem services of the Huaihe River Basin. The reduction in grassland areas and the increase in built-up land areas have significantly reduced the capacity for soil retention, carbon storage, and biodiversity conservation. Spatially, regions with low landscape fragmentation and high patch connectivity had a higher water retention capacity and biodiversity conservation, while soil retention and carbon storage were opposite. Temporally, reduction of landscape fragmentation and increase of patch shape irregularity had a negative effect on water retention, carbon storage, and biodiversity conservation, while soil retention was not sensitive to these changes. The findings in this paper promote an understanding of the relationship between landscape patterns and ecosystem services on a large scale and provide theoretical guidance for ecosystem management and protection planning in the Huaihe River Basin, China.

Analysis of the Spatial Distribution Characteristics of Livestock and Poultry Farming Pollution and Assessment of the Environmental Pollution Load in Anhui Province

Anhui Province is located in the eastern China, in the middle and lower reaches of the Yangtze River and Huaihe River, and contains three major basins, i.e., the Yangtze River, Huaihe River, and Xin’an River basins. Based on the statistical data of livestock and poultry quantity and farmland area in Anhui Province in 2019, ArcGIS was used to analyze the spatial distribution characteristics of the livestock and poultry excreta (LPE) pollutants in Anhui Province in order to explore the potential pollution risk posed by livestock and poultry farming to the farmland and the water environment in Anhui Province. The equivalent pollution load method was adopted to compare and assess the release of LPE pollutants in various cities and to analyze the causes. Through the calculation of the farmland carrying capacity load and early warning value of LPE and the water load of livestock and poultry pollutant release based on the equivalent pollution index method, a comprehensive assessment of the potential pollution risk posed by livestock and poultry farming on farmland and the water environment in Anhui Province was carried out. In this study, the spatial distribution of the livestock and poultry pollution in Anhui Province was analyzed, the effect of the pollution load of the livestock and poultry on the cultivated land and water environment was evaluated, and suggestions for environmental protection measures are provided. The results of this study revealed that the total pig equivalent of the livestock and poultry farming in Anhui Province was 55,068,400 and the LPE output was 47,778,600 t in 2019. The LPE pollutant output was 1,707,700 t, and the total release was 510,400 t. The release of pollutant chemical oxygen demand (COD) accounted for 71.67% of the total release. The average farmland load of the pig manure equivalent was 8.09 t/hm2 in the province. The average pollutant diffusion concentration of in the water was 31.63 mg/L. The average equivalent pollution index of LPE was 5.23, indicating a mild pollution impact on the water environment. Overall, the spatial distribution of the LPE pollutant output and pig manure equivalent farmland load in Anhui Province increased from south to north. Fuyang and Suzhou cities had a high risk of water environment pollution and should be the key regions for livestock and poultry pollution prevention and control measures. The optimization of the layout of livestock and poultry farming areas, smoothing the cycles of crop and livestock farming, and the vigorous promotion of the resource utilization of the LPE are proposed.

Combining hydrochemistry and hydrogen and oxygen stable isotopes to reveal the influence of human activities on surface water quality in Chaohu Lake Basin

The input of pollutants caused by human activities induces the deterioration of surface water quality. To reveal the characteristics of surface water quality in Chaohu Lake Basin and the influence of human activities, the hydrochemistry and stable isotope composition of hydrogen and oxygen in lake water and inflow river water were analyzed. The results show that the hydrochemical type of lake water is the Na–Cl type,while river water is the Na–Cl, Ca–Cl and mixed types. The ion proportional coefficient method and principal component analysis show that surface water is controlled by weathering of evaporated salt rocks and silicate rocks, in which Cl- and SO42- are affected by fertilizers and sewage to some extent. There is a strong correlation between conventional ions and nutrient indexes, which indicates that dissolved ions are affected not only by rock weathering but also by human activities (such as the discharge of domestic sewage or nitrogen-containing wastewater and the use of fertilizers). The stable isotope values of hydrogen and oxygen in surface water are distributed at the lower right portion of the local precipitation line and are close to it, indicating that surface water mainly originates from precipitation. The high value of d-excess values in surface water indicates that evaporation is weak. As pollution indicators, EC, Cl- and NO3- indicates that the Nanfei River, Dianbu River, Shiwuli River and Pai River flow in northwestern of Chaohu Lake Basin through Hefei urban city are severely polluted, NO3- originates from manure and sewage. Rivers flowing through farmland areas are less polluted, and the use of agricultural fertilizer contributes greatly to NO3-.

ANALYSIS OF FINANCIAL SUPPORT DEDICATED TO ORGANIC FARMS IN POLAND 2004-2018

The aim of this article was to review the financial support dedicated to organic farming to the area of organic farmland in Poland after accession to the EU and the important changes in the specific conditions for granting financial support in the period 2004-2018 that may have an impact on the reduction of interest in running farms using organic methods. The current legislation in force from 2004 to 2018 on the basis of which payments were granted for the area of organic agricultural land was analysed. It was found that changes in the regulations for applications starting the five-year agri-environmental commitment in terms of package 2 organic farming, under RDP 2004-2006 and RDP 2007-2013, and the organic commitment from RDP 2014-2020, may have had an impact on the reduction of interest in running farms using organic methods and the decrease in their number.

Urbanization in China drives farmland uphill under the constraint of the requisition–compensation balance

The slope is an important objective attribute of farmland that changes with the evolution of its spatial pattern. A growing area of plain farmland is being occupied by built-up land owing to rapid urbanization, while the newly added are sloping and terrace farmland under the constraint of the requisition–compensation balance. Researchers have focused on the horizontal spatial redistribution of farmland quantity while ignoring vertical variations in its slope, which is critical for its overall quality. Based on data on land use classification in China from 1990 to 2019, this study uses land use change trajectory as well as trend and driver analyses to identify the impact of urbanization on change in the slope of unstable farmland. The results show the following: (1) The area of unstable farmland accounted for ~20% of all farmland, with its slope increasing from 5.77° in 1990 to 6.25° in 2019 due to conversion in land use. (2) Variation in the slope of unstable farmland had significant heterogeneity, with regions undergoing a significant increase concentrated in the east and those undergoing monotonous decline not spatially clustered. (3) Farmland development and built-up land occupation have driven increases in the slope of unstable farmland with a relatively balanced effect, whereas the trend of increasing has been mainly suppressed by farmland marginalization. (4) The area of urban land expanded by 158,446.70km2 during 1990–2019, 24.15% of which was due to encroachment on farmland with a slope of 1.31°. Farmland development with a slope of 6.98° helped replenish 90.30% of the occupied area. This combined process has led to unstable farmland uphill under the constraint of the requisition–compensation balance. The results here can provide a reference for the protection and sustainable utilization of farmland.