Subtropical Climate Region Research Articles

Sweet cherry breeding in Zhejiang province, which is the middle zone of subtropical monsoon climate region in China

Sweet cherry breeding in Zhejiang province, which is the middle zone of subtropical monsoon climate region in China

How to alleviate seasonal limitations on water quality in farmland ditches? The importance of plant selection and configuration

In subtropical monsoon climate regions, traditional plants in constructed wetlands such as farmland ditches underperform in cold months, detracting from both purification capacity and esthetic appeal. To alleviate this weakness, this study introduced Phalaris arundinacea, a species with strong adaptability and cold tolerance, into a plant community dominated by Phragmites australis, constructing an ingenious composite plant community for year‐round water quality restoration and enhancement of attractiveness. First, laboratory simulations revealed significant seasonal differences in the removal rates of ammonia nitrogen (NH3‐N), total nitrogen (TN), and total phosphorus (TP) by the P. arundinacea community and P. australis community under different pollutant loads. Phragmites australis showed superior NH3‐N and TN removal capabilities from May to October, whereas P. arundinacea excelled in the rest of the months throughout the year. For TP removal, P. australis outperformed P. arundinacea from July to October, while P. arundinacea was more effective from January to May. We then verified this in rear farmland ditches, where P. australis were strategically partial substituted with P. arundinacea (Partial Replacement Treatment [PRT]), and compared it with unchanged farmland ditches (Control Treatment). We found that PRT enhanced decontamination efficiency over the year, especially significantly improving the water quality during colder months. Hence, this study advocates a novel strategy for effective annual decontamination and maintenance of wetlands such as farmland ditches, highlighting the importance of seasonally adaptive plant communities for water restoration. This transformative approach dramatically advances the field of wetland management, insisting on the important role of cold‐resistant species for year‐round ecosystem service optimization.

Molecular detection of Ehrlichia spp., Anaplasma spp., and Bartonella spp. in dogs treated at a veterinary teaching clinic in Peru

In recent years, vector-borne diseases have become widespread throughout the world and affect the health of humans and domestic animals. These diseases spread to areas where their primary vectors, fleas and ticks, thrive, particularly in tropical and subtropical climate regions, providing ideal conditions for their proliferation. The growing closeness between people and their pets increases the likelihood of bites from these ectoparasites, which represents a latent zoonotic risk. Therefore, the objective of the study was to determine the presence of Anaplasma spp., Ehrlichia spp., and Bartonella spp. in dogs treated at the Small Animal Clinic of the Faculty of Veterinary Medicine of the Universidad Nacional Mayor de San Marcos, located in Lima, Peru. Blood samples from 214 dogs were molecularly analyzed for hemopathogen detection. The results revealed prevalences of 2.6 % (6/214) for Anaplasma platys, 5.14 % (11/214) for Ehrlichia canis, and 0.46 % (1/214) for Bartonella rochalimae. No statistically significant relationship was found between the animal infection and the age, sex, breed, presence of fleas (Ctenocephalides felis) and ticks (Rhipicephalus sanguineus), and locality. This study reported molecularly for the first time the presence of A. platys, E. canis, and B. rochalimae in dogs from Lima city, and demonstrates the occurrence of zoonotic pathogens in pets treated at the veterinary clinic.

Predictive Control Modeling of Regional Cooling Systems Incorporating Ice Storage Technology

Due to the hot climate, energy consumption for refrigeration is significantly higher in the subtropical monsoon climate region. Combined with renewable energy and ice-storage technology, a model predictive control model of the regional cooling system was proposed, which was conducive to improving the flexibility of the regional cooling system and the ability of peak shifting and valley filling. In this model, an artificial bee colony (ABC) optimized back propagation (BP) neural network was used to predict the cooling load of the regional cooling system, and the model parameter identification method was adopted, combining utilizing a river-water-source heat pump and ice-storage technology. The results showed that the load prediction algorithm of the ABC-BP neural network had a high accuracy, and the variance coefficient of load prediction root-mean-square error (RMSE) was 16.67%, which was lower than BP, support vector regression (SVR), and long short-term memory (LSTM). In addition, compared with the three control strategies of chiller priority, ice-storage priority, and fixed proportion, the operation strategy optimized by the comprehensive model can reduce the average daily cost by 19.20%, 4.45%, and 5.10%, respectively, and the maximum daily energy consumption by 30.02%, 18.08%, and 8.90%, respectively.

Assessing GNSS hydrological monitoring capability across different climatic settings in China

Vertical position changes of ground-based Global Navigation Satellite System (GNSS) stations have been used to study regional terrestrial water storage (TWS) changes. However, the feasibility is still unclear in many areas due to diverse local effects. This study aims to evaluate the capability of GNSS vertical displacements in monitoring hydrological variations in four climate settings over Chinese mainland. The spatial and temporal variations of hydrological load-induced (HYDL) vertical displacements at 208 GNSS sites during 2011–2020 were analyzed by comparing with Gravity Recovery and Climate Experiment (GRACE)/GRACE Follow-On (GFO) and Global Land Data Assimilation System (GLDAS) derived TWS changes. The results indicate that GNSS vertical positions show different capabilities in capturing seasonal and non-seasonal hydrological dynamics in different climate regions. Among the four climatic settings, the subtropical monsoon climate (SMC) region, with the largest deformation fluctuation (the regional mean root mean square (RMS) is 7.97 mm), has the highest regional mean HYDL-GRACE and HYDL-GLDAS anti-correlation coefficients (CCs) of −0.47 and −0.45 at the seasonal scale, respectively. For the individual GNSS site, the number of the sites with CC <−0.40 between HYDL and GRACE/GLDAS-derived TWS changes accounts for 55.1% and 55.1% (SMC), 13.0% and 7.4% (temperate monsoon climate, TMC), 6.7% and 13.3% (temperate continental climate, TCC), 32.3% and 38.7% (plateau climate, PC), respectively. For the non-seasonal term, although the proportion with CC <−0.40 in each climate type decreases mainly due to the influence of local geodynamic and human activities, especially in the SMC and PC regions, GNSS site vertical deformations still show good capability in monitoring hydrological extremes. The results provide valuable information for better application of GNSS to hydrology.

People’s Perception of Climate Change Impacts on Subtropical Climatic Region: A Case Study of Upper Indus, Pakistan

In developing countries like Pakistan, the preservation of the environment, as well as people’s economies, agriculture, and way of life, are believed to be hampered by climate change. Understanding how people perceive climate change and its signs is essential for creating a variety of adaptation solutions. In this study, we aim to bridge the gap in current research within this area, which predominantly relies on satellite data, by integrating qualitative assessments of people’s perceptions of climate change, thereby providing valuable ground-based observations of climate variability and its impacts on local communities. Field-based data were collected at different altitudes (upstream (US), midstream (MS), and downstream (DS)) of the Upper Indus Basin using both quantitative and qualitative assessments in 2017. The result shows that these altitudes are highly variable in many contexts: socioeconomic indicators of education, agriculture, income, women empowerment, health, access to basic resources, and livelihood diversifications are highly variable in the Indus Basin. The inhabitants of the Indus Basin perceive the climate changing around them and report impacts of this change as increase in overall temperatures (US 96.9%, MS 97%, DS 93.6%) and erratic rainfall patterns (US 44.1%, MS 73.3%, DS 51.0%) resulting in increased water availability for crops (US 38.6%, MS 39.7%, DS 54.8%) but also increasing number of dry days (US 56.7%, MS 85.5%, DS 67.1%). Communities at these altitudes said that agriculture was their primary source of income, making them particularly vulnerable to the effects of climate change and the dangers that go along with it. The insights are useful for determining what information and actions are required to support local climate-related hazard management in subtropical climate regions. Moreover, it is vital to launch a campaign to raise awareness of potential hazards, as well as to provide training and an early warning system.

Monitoring spatio-temporal variations of terrestrial water storage changes and their potential influencing factors in a humid subtropical climate region of Southeast China

Identifying the changes in terrestrial water storage is essential for a comprehensive understanding of the regional hydrological mass balance under global climate change. This study used a partial least square regression model to fill the observation gaps between GRACE and GRACE-FO and obtained a complete series of terrestrial water storage anomaly data from April 2002 to December 2020 from southeast China. We investigated the variations in terrestrial water storage anomalies in the region and the influencing factors. The study revealed that terrestrial water storage (TWS) anomalies have been increasing in the region, with an average increase of 0.33 cm/yr (p < 0.01). The intra-annual variation showed a positive anomaly from March to September and a negative anomaly in other months. Terrestrial water storage anomalies increased in most regions (especially in the central and northern parts), whereas they decreased in the southern parts. In terms of the components, the soil moisture storage (SMS) contributes 58.3 % and the surface water storage (SWS, especially reservoirs water storage) contributes 41.4 % to the TWS. The study also found that changes in the precipitation explain approximately 71.7 % of the terrestrial water storage variation, and reservoirs contributes to the remaining 28.3 %. These results are essential for understanding the changes in the hydrological cycle and developing strategies for water management in Southeast China.

Impacts of Climate Change Scenarios on the Corn and Soybean Double-Cropping System in Brazil

Brazil is one of the main producing and exporting countries of corn and soybean and a continental country with climatic diversity that allows the cultivation of these crops in various agricultural systems. Double cropping is a widely adopted system throughout the national territory, where it is possible to cultivate soybeans at the beginning of the growing season, followed by corn in succession, in the same growing season. The present study aims to systematize the scientific knowledge about the impacts of future climate change scenarios on yield and on the double-cropping system of soybean + corn in Brazil. Systematic review procedures were adopted. The soybean yield is projected to increase in all regions of Brazil under all climate scenarios. Corn yields under future climate scenarios are projected to decline, with the subtropical climate region being less affected than the northern regions. The double-cropping systems of soybean + corn tend to present increasing climate risks in tropical climate regions. Climate change scenarios point to a delay in the start of the rainy season that will delay the sowing of soybeans, consequently delaying the sowing of corn in succession, resulting in fewer rainy days to complete its cycle.

Overview of municipal solid waste management in sub-tropical climatic region of North Eastern India.

Municipal solid waste management (MSWM) is perceived as a global issue regardless of the place of waste generation. The amount of unmanaged waste is increasing rapidly, along with its impact on the environment and human health. In hilly areas, specifically the North Eastern Region (NER) states of India, due to the unique topography coupled with socio-economic factors, there are inadequate waste management practices marked by insufficient infrastructure, minimal research studies, and limited data availability. This paper comprehensively reviews the existing status of MSWM practices and waste treatment technologies, identifies the challenges, and discusses the prospective approaches for MSWM in NER states of India. NER, is characterized by its hilly terrain and has the most diverse demographic profile in the country. The study highlights the notable increase in waste generation in the urban population in NER. The total amount of waste generated in NER is about 2907 tons per day, with a collection rate of 86.96%, treatment at 31.09%, and landfilling at 33.67%. The biodegradable fraction makes up the majority of waste composition (more than 50%) in NER, followed by recyclables and inert. The existing MSWM consists of waste collection, transportation, and disposal with limited source segregation and treatment. All the states of NER practice open dumping and burning as the primary waste treatment and disposal system. The study discusses the challenges and prospects to ensure effective MSWM in NER. This review is a region-specific study that considers cultural diversity, topography, and socio-economic dynamics. The outcome of this review will be helpful to the researchers and policymakers in making appropriate waste management plans and improve the MSWM system in NER.

Use of Increasing Levels of Low-Quality Forage in Dairy Cows’ Diets to Regulate Enteric Methane Production in Subtropical Regions

Dairy cows are the highest daily and annual methane (CH4) producers among all cattle categories. So, the present study aimed to evaluate the effect of increasing supplementation levels of a low-quality forage on dry matter intake (DMI), DM digestibility (DMD), milk production, enteric CH4 emission, gross energy, and protein partitioning in Holstein cows. In total, eight cows (112 ± 38 days postpartum; mean ± s.d.) were randomly assigned to 4 treatments composed of 4 dietary neutral detergent fibre (NDF) inclusion levels (40.2% (control), 43.3%, 46.5%, and 50.5%) in a 4 × 4 repeated Latin square experimental design. The cows were fed corn + alfalfa silage and a concentrate (60:40 forage:concentrate ratio). To increase the contents of low-quality NDF, part of the silage was replaced with maize stover (MSTV). The CH4 production was measured in an open-circuit respiration chamber. The DMI increased significantly and linearly (p &lt; 0.05) with increasing levels of MSTV. However, the CH4 yield decreased (p &lt; 0.0001) as the NDF level increased (32.1, 28.1, 23.1, and 21.3 CH4 L/kg DMI, respectively). DMD decreased as NDF levels in the diet increased (p &lt; 0.0001). The NDF digestibility (DNDF) explained the better (p &lt; 0.0001) CH4 production response than DMD. It was concluded that low-quality forages can be used to regulate CH4 production in subtropical and tropical climate regions.

An Over View of Conservation, Restoration and Development of Mangrove Forests in Goa

Mangroves are coastal plants spread over sea cost of tidal zones or backwaters particularly in tropical and sub-tropical climate regions. Mangroves Are Champions at Sucking Out Carbon Dioxide from Air, and each tonne removed is worth a few dollars. Hence it is important that conservation, plantation, and restoration of mangroves need to be given top priority. In fast developing world there are various issues affecting the forest, wildlife, flora and fauna environment ecology and what not, so there is urgent need of not only protecting the mangrove biodiversity but also restoring and developing mangrove forests. This paper presents an over view on mangroves and Conservation, Restoration and Development of Mangrove Forest in Goa.

Assessment of the Effect of Different Bio-Stimulants on the Growth, Quality, and Yield of Strawberries in a Sub-Tropical Climatic Region: A Case Study

This case study investigates the impact of different bio-stimulants, including Novel prime organic liquid nutrient, Vermi wash, and Cow urine, on vegetative growth, flowering, and fruit yield of sweet sensation variety of strawberry plants. An intensive research work was carried out at an experimental land located in north Konkan zone of Maharashtra, India. The experiment employs a Completely Randomized Design (CRD) with three replications to evaluate growth at various stages and yield parameters. The results demonstrate that the strategic application of 2% concentration of Novel prime organic liquid nutrient and 2% Vermiwash significantly improves the plant growth and yield of strawberry. This treatment remarkable yielded 5418 kg/ha, while the appreciable yield achieved to 4733 kg/ha for the Vermiwash treatment. The results also highlight the potential of sustainable strawberry cultivation and suggesting its viability for countries that traditionally depend on rain-fed crops. This may significantly improve the pattern of agricultural practices in those regions. Strawberry cultivation is an economically significant horticultural practice worldwide. Enhancing the growth, quality, and yield of strawberry plants is crucial for improving production and profitability.

A Microwave Radiometer Residual Inversion Neural Network Based on a Deadband Conditioning Model

Microwave radiometers are passive remote sensing devices that are widely used in marine atmospheric observations. The accuracy of its inversion of temperature and humidity profiles is an important indicator of its performance. Back Propagation (BP) neural networks are widely used in the study of microwave radiometer inversion problems. However, the BP network which is carried by the radiometer inversion suffers from profile data collapse. To address this, this study introduced a residual network to improve the accuracy of water vapor vertical profiles. Aiming at the problem of large inversion temperature error due to the effect of turbulence on the light-travel phase induced by stationary fronts along the seashore in the subtropical monsoon climate region, we used historical data to establish the seasonal a priori mean profile and design a dead-zone residual adjustment model. The accuracy of the residual network and the deadband-adjusted residual network was verified using the meteorological records of the Taizhou region from 2013–2018, with the experimental data and BP hierarchical network as the comparison term. We found no data collapse in the temperature and humidity profile inversion results of the residual network. Relative to the initial BP hierarchical algorithm, where the error of water vapor in the range 6–10 km was reduced by 80%, the dead zone residual adjustment model in the inverse-temperature phenomenon reduced the sum of squares error by 21%, compared with the ordinary residual network inversion results. Our findings provide new insights into the accuracy improvement of radiometer remote sensing.

Harnessing climate variables for predicting PV power output: A backpropagation neural network analysis in a subtropical climate region

This study examines the influence of weather conditions on the electricity production of photovoltaic (PV) panels in the Conghua district, a region in Southern China distinguished by its subtropical mountainous climate. The area's high humidity levels, high temperatures, and substantial rainfall often lead to predominantly cloudy skies, which alter solar irradiation patterns as a result. Utilizing the EnergyPlus simulation tool, the power generation of PV panels on rooftop application was simulated. A structured classification method is adopted to sort out weather conditions into categories of sunny, cloudy, and rainy. Through examining the influence of these varied weather scenarios on power generation, unique factors affecting electricity outputs are identified. As a result, this study illuminates the relationships between potential weather variables and PV power generation across each weather category. Subsequently, a back propagation neural network (BPNN) model is utilized to explore the relationship between weather categories and PV generation. The high coefficient of determination value (R2 > 0.95) from the comparison of simulated and predicted PV generation validates the model accuracy. This research enables the development of updated dataset and enriches the prediction of rooftop PV power generation. It equips designers and owners with a reliable, user-friendly, and real-time tool for PV power generation forecasting, and provides a working platform for PV performance evaluation during the design phase of PV projects. The insights derived from the BPNN model could guide the optimal design and implementation of PV systems in similar climates. Furthermore, these findings advance sustainable energy solutions in regions affected by complex weather patterns.

Design recommendations for the rehabilitation of an urban canyon in a subtropical climate region using aerial thermography and simulation tools

Outdoor public space is the setting for everyday social interaction where activities take place in order to satisfy collective urban needs. It is important to achieve climate-friendly urban design in order to ensure acceptable urban thermal comfort, especially in over-urbanised city centres during summer periods. In this research, an urban canyon street located in the historical centre of the subtropical city of Huelva (Spain) was analysed. After a survey carried out by in situ meteorological sensors and airborne infrared sensors (equipped on an unmanned aerial vehicle, UAV), the current thermal comfort was analysed in terms of PMV and PPD at different times of a typical summer day (11:00 h, 15:00 h and 19:00 h) with the aim of formulating design recommendations to improve its performance in terms of urban comfort. Then, thermal comfort was evaluated in different scenarios where feasible mitigation strategies (replacement of materiality, addition of vegetation and sun shading elements) were applied to classify them according to their effectiveness using the ENVI-met simulation tool. The results of the current scenario showed that, due to its N-S orientation and its aspect ratio (H/W), the urban comfort depends drastically on the day hour variation. A comfortable thermal environment is achieved at all points of the urban canyon as a result of the shade generated by the buildings during the morning and afternoon. However, in the central hours of the day the feeling of thermal discomfort was alarming (PMV values of +3 and PPD values above 90%). The proposed mitigation measures showed a considerable improvement in urban thermal comfort, with the addition of vegetation being the most effective solution (with an improvement in PMV value of 42% and a reduction in PPD value of 43%). The combination of all the proposed measures in a single scenario showed encouraging results in the rehabilitation of public spaces in use.

Downscaling of Thermal Images Over the Gaza Strip Using the Land Surface Temperature—Spectral Indices Relation: Case Study; Hot, Arid, and Semi-Arid Areas

Many thermal sharpening applications are evaluated in temperate and subtropical climate regions, which are com-monly characterized by the presence of the urban heat island (UHI) phenomenon. However, similar studies are rarely found in hot, arid, and semi-arid climate cities, where an urban cool island (UCI) phenomenon exists. Recent research shows that the spectral characteristics of land covers and their responses to LST are different based on their climatic type. Resultantly, spectral indices (SIs) show different evaluations to be successfully used in sharpen-ing techniques like the DisTrad, to sharpen LST over several land covers, especially in urban areas. The main ob-jectives of this study are; 1)- to evaluate the spatial relationship between LST and a number of most commonly used urban's remote sensing SIs (21 SIs described in table 2) over the Gaza Strip in two land cover scenarios: all land covers "All" and the urban mask “urban”; 2)- to downscale aggregated low-resolution Landsat 8\LST image at 1000 m to a higher resolution of 100 m. Spectral indices and land surface temperature are calculated using the Landsat 8 image of summer 2017. Spatial regression analysis between SIs and LST within the "All" land cover class and at 1000 m resolutions show the best SIs that have the highest correlation (R2) with LST are DBSI (0.66) and ABEI (0.59). While in the "urban" class, the same indices shows also the highest correlation; BAEI (0.57) and DBSI (0.64). Moreover, statistical validation with LST observation at 100m resolution (Landsat 8\LST), DisTrad was found suc-cessful to downscale LST to 100 m resolution over UCI areas using the indices ABEI and DBSI with the highest cor-relation (R2) over the "All" class (0.77 and 0.73 respectively) and over the "urban" mask using DBSI (0.59) and BAEI (0.58)

First Report of Lasiodiplodia theobromae Causing Brown Leaf Spot on Bruguiera gymnorrhiza in China.

Bruguiera gymnorrhiza (Linn.) Sav. is a dominant tree species of mangrove forests in tropical coastal areas of China. This species is commonly used for the greening of tidal flats and seawalls in tropical and subtropical regions (Allen, & Duke 2000). A survey that was conducted from August to September 2020, in the mangrove national nature reserve at Zhanjiang, Guangdong Province, South China. Brown leaf spot symptoms were observed on Bruguiera gymnorrhiza and disease incidence was over 10% (200 investigated trees). Symptomatic small spots initially appeared at the middle or edges of leaves, enlarged irregularly, and developed into brown necrotic spots with dying curly edges. The color of the lesion's center changed to dark brown or gray. To identify the causative agent, twenty diseased leaves were sampled for pathogen isolation. Affected foliar tissues cut into 5 × 5 mm pieces, disinfected in 75% ethanol for 2 mins, rinsed in sterile distilled water, and then air dried under a sterilized filter paper. Leaf pieces were plated onto potato dextrose agar (PDA) in Petri dishes and then incubated at 28°C in darkness for 3-5 days. Hyphal tips of fungal colonies growing from the tissue pieces were subcultured onto fresh PDA to obtain pure single hyphae cultures. The fungal colonies were initially composed of white aerial mycelia, but turned gray after 7 days. Immature conidia were hyaline, subovoid, and aseptate while mature conidia becoming dark brown, one-septate with longitudinal stripes, the length/width ratio is 19.98 to 29.50 μm (average 24.37 µm; n = 50) × 11.99 to 14.45 μm (average 13.09 µm; n = 50). On the basis of morphological features all isolates were identified as Lasiodiplodia theobromae (Pat.) Griffon & Maubl (Alves et al. 2008). For DNA-based identification, the internal transcribed spacer (ITS) region gene and fragment of elongation factor 1-alpha (EF1-α) gene of the three isolates were amplified and sequenced following the methods described in a previous study (White et al. 1990, Carbone & Kohn 1999). The obtained sequences of ITS and EF1-α were deposited in GenBank with accession numbers OK644200 and OL345571. The BLAST results showed at least 99.60% similarity with the sequences of Lasiodiplodia theobromae (ITS, MT644474.1 [99.79%]; EF1-a, MK961975.1 [99.60%]). To fulfill Koch's postulates, PDA plugs with actively growing mycelium of the isolates were inoculated on the leaves of Bruguiera gymnorrhiza plants that were wounded by using a sterilized needle or scalpel. Inoculated leaves were covered with sterilized wet cotton, and the plants were kept at 28°C and 80% relative humidity. The inoculated plants showed leaf spot symptoms that were similar to those previously observed in the field after 1-2 days, whereas control leaves remained healthy. Lasiodiplodia theobromae was consistently isolated from inoculated leaves again. Lasiodiplodia theobromae (Botryosphaeriaceae) is a plurivorous pathogen in a wide variety of hosts, mostly prevalent in tropical and subtropical climate regions. It has been previously reported to cause brown leaf spot on Broussonetia papyrifera (Luo et al. 2020), foliar diseases on Camellia oleifera (Zhu et al. 2014) and Kadsura longipedunculata (Fan et al. 2020). To our knowledge, this is the first report of Lasiodiplodia theobromae causing brown leaf spot on Bruguiera gymnorrhiza plants in China and worldwide. Our findings will help to make management strategies for control of this disease on Bruguiera gymnorrhiza.

Surface Runoff and Diffuse Nitrogen Loss Dynamics in a Mixed Land Use Watershed with a Subtropical Monsoon Climate

The surface hydrology and diffuse pollution loading is hypothesized based on the unique characteristics under different rainfall types in watersheds with a subtropical monsoon climate. This study evaluated the effects of different rainfall event intensity on surface runoff and diffuse nitrogen loss in a subtropical watershed located in the latitude range between 22.5° north and 25° north in southern China by adapting the hydrological model SWAT (Soil and Water Assessment Tool). The rainfall events were classified into four categories including light rainfall (LR), moderate rainfall (MR), intense rainfall (IR), and extreme rainfall (ER). Our results showed that the ER events had the lowest occurrences of 7 days per year, but they contributed the most to total surface runoff (54.29%) and TN losses (57.63%) in the subtropical watershed researched. Although forests and pastures had a better effect on reducing diffuse pollution, their surface runoff and nitrogen loss were still proved to be serious under ER events. As for the nitrogen loss form, water-soluble nitrogen oxides nitrogen (ON-N) loss was the dominant form of total nitrogen (TN) loss, which accounted for 90% of the total loss in the simulated watershed in the subtropical monsoon climate region. Under LR events, however, nitrate nitrogen (NO3-N) accounted for 74.54% and 55.59% of TN losses from paddy fields and dry lands, respectively. The effects of antecedent soil water content (ASW) on surface runoff and TN loss were higher under ER events. The surface runoff and TN loss in the high-ASW condition were 1.17–3.86 times and 1.34–1.76 times higher, respectively, than in the low-ASW condition. These findings highlighted the important influence of ER events on diffuse pollution and have significant implications for controlling diffuse pollution under different rainfall types. This conclusion proved that extra attention and efforts are required in handling non-point-source pollution in subtropical monsoon watersheds than the watersheds in cooler regions because the natural systems including forest and pastures are no longer effective enough in controlling surface runoff and TN loss during ER.

Excessive use of chemical fertilizers in catchment areas raises the seasonal pH in natural freshwater lakes of the subtropical monsoon climate region

In recent years, the pH of some oligotrophic natural freshwater lakes in the subtropical monsoon climate region has generally reached an extremely high level of approximately 9.0 during the summer and autumn. It has not been proven that the explanation for why carbon assimilation in productive lakes exceeds carbon supply and causes a rise in pH also applies to oligotrophic freshwater lakes. Regardless, this may have been caused by changes in the solute composition of inflowing rivers as a result of changes in land use in catchment areas. Beimiao Reservoir in Baoshan City, Yunnan Province, where pH has increased significantly in summer and fall over the past few years, was chosen for this research in order to verify this hypothesis. This paper evaluates the status quo of water quality and nutrition in this reservoir. In addition, this paper analyzes the effects of water temperature, the metabolism of aquatic organisms, and river input on the horizontal and vertical spatial differences, diurnal variations, seasonal changes, and annual changes in the pH of the reservoir. It was discovered that one of the primary causes of the pH increase in natural freshwater lakes in the subtropical monsoon climate region during summer and autumn can be summarized as follows: A large amount of nitric acid and sulfuric acid are produced in the soil when chemical fertilizers are overused in runoff areas, particularly during intensive horticultural crop cultivation. Therefore, the subtropical monsoon climate region's soil loses calcium and magnesium ions, whose combined equivalent concentrations significantly exceed those of bicarbonate ions. The combined equivalent concentrations of calcium ions and magnesium ions in the inflowing rivers in summer and autumn are also significantly higher than those in the lake, resulting in the depletion of free carbon dioxide caused by calcium carbonate precipitation and an increase in pH. The conclusion of this research casts new light on the preservation and treatment of the ecological environment of lake water with similar issues.

Performance of the WRF model in simulating convective rainfall events in the humid subtropical monsoon climate region—Poyang Lake basin

Performance of the WRF model in simulating convective rainfall events in the humid subtropical monsoon climate region—Poyang Lake basin