Changes In Rainfall Patterns Research Articles

A strange negative Indian Ocean Dipole (IOD) in 2022

The Indian Ocean Dipole (IOD) is a prominent pattern of climatic mode in the Indian Ocean that contributes to the changes in Rainfall pattern, Sea Surface Temperature (SST), and Surface Salinity (SSS) in the Indian Ocean. Recently in the scenario of Climate Change, this IOD may experience shifting in the phases development that link to the Indo-Pacific teleconnection. Here, we analyse the changes of negative IOD patterns in 2022 through the SST, SSS, rainfall pattern, and surface current system. This study showed the negative IOD was initiated earlier and coincided with the Asian monsoon during May 2022. The IOD is faster ended in October 2022 when the Australian Monsoon was generated. The Rainfall pattern at the Eastern Indian Ocean (EIO) and the Indonesian Archipelago experienced an intensive pattern from May up to December 2022. During the negative IOD phases, the precipitation at the EIO is more concentrated in Java and less precipitation in Sumatra. The warmer SST and fresh surface salinity in the Indonesian Archipelago are wider following the Pacific SST. This reveals the Indo-Pacific teleconnection is stronger during 2022 via the surface ocean patterns and the coincidence of stronger westerly wind and easterly wind in the maritime continent.

Trend analysis of rainfall data using Mann-Kendall test and sen's slope estimator

Rainfall is the most important fundamental physical parameter among the climate, as this parameter determines the environmental condition of the particular region, which affects the agricultural productivity. Global warming or climate change, is one of the most important worldwide issues discussed among scientists and researchers. One of the consequences of climate change is the alteration of rainfall patterns and an increase in temperature. The drastic changes in rainfall pattern showed a significant impact on society, and therefore its up-to-date information is needed to estimate the spatial distribution and variability at all points of the territory. In this paper, a study on trend analysis of rainfall data observed at Anasi, Haliyal, Kadra, and Supa rain gauge stations in Karnataka, India, was carried out. For this purpose, the annual 1-day maximum rainfall (AMR) and annual total rainfall (ATR) series were generated from the daily rainfall data and used in trend analysis. A non-parametric Mann-Kendall (MK) test was applied to evaluate the presence of significant trend in AMR and ATR, while the rate of significant trend was computed by Sen's slope estimator (SSE). The MK test results indicated that there is a decreasing trend in AMR series of Anasi, Haliyal, Kadra, and Supa. The study showed that the rate of decreasing trend in the AMR series of Anasi, Haliyal, Kadra, and Supa is computed as 1.4 mm/year, 0.1 mm/year, 0.6 mm/year, and 0.2 mm/year, respectively. For the ATR series, the rate of decreasing trend for Anasi was computed as 23.8 mm/year, whereas 11.2 mm/year for Supa, whereas the rate of increasing trend was 4.3 mm/year for Haliyal and 2.2 mm/year for Supa. This paper illustrated the application of the MK test and SSE for analyzing the trend in AMR and ATR of Anasi, Haliyal, Kadra, with Supa and the results obtained from the study.

The effectiveness of nature-based solutions to address climate change in Dhaka, Bangladesh

Amid escalating climate change impacts, urban areas like Dhaka face heightened vulnerability to extreme weather, rising temperatures, urban heat island effects, and associated physical and psychological consequences. Nature-based solutions (NBS) emerge as a prominent strategy to address these challenges. This study examines urban residents' perceptions of ecosystem vulnerability, socio-economic factors, and the effectiveness of existing NBS approaches in reducing climate vulnerabilities. Data were collected through in-depth interviews of forty-five urban residents (equal ratio of male and female residents) in Gulshan and Banani, Dhaka, Bangladesh. Findings showed several factors such as increased temperature, change in rainfall pattern, physical and mental health issues, lack of proper management and space, and implementation of increased vulnerability. NBS can reduce the ecosystem, socio-economic vulnerability features, and impacts of NBS on residents and urban areas. Among the identified NBS approaches, rooftop agriculture and balcony gardens were considered the most helpful and feasible NBS approaches, offering cooling effects, reduced heat stress, and better air quality. Respondents emphasized government and community roles over individuals and collaborative efforts to manage urban green spaces. Our study implies that adopting NBS in urban areas can enhance urban resilience to climate change, positively impacting residents and future efforts in maintaining sustainable green space management.

Demographic-environmental effect on dengue outbreaks in 11 countries.

Dengue outbreaks are common in tropical or temperate countries, and climate change can exacerbate the problem by creating conditions conducive to the spread of mosquitoes and prolonging the transmission season. Warmer temperatures can allow mosquitoes to mature faster and increase their ability to spread disease. Additionally, changes in rainfall patterns can create more standing water, providing a breeding ground for mosquitoes. The objective of this study is to investigate the correlation between environmental and demographic factors and the dissemination of dengue fever. The study will use yearly data from 2000 to 2021 from 11 countries highly affected by dengue, considering multiple factors such as dengue cases, temperatures, precipitation, and population to better understand the impact of these variables on dengue transmission. In this research, Poisson regression (PR) and negative binomial regression (NBR) models are used to model count data and estimate the effect of different predictor variables on the outcome. Also, histogram plots and pairwise correlation plots are used to provide an initial overview of the distribution and relationship between the variables. Moreover, Goodness-of-fit tests, t-test analysis, diagnostic plots, influence plots, and residual vs. leverage plots are used to check the assumptions and validity of the models and identify any outliers or influential observations that may be affecting the results. The findings indicate that mean temperature and log(Urban) had a positive impact on dengue infection rates, while maximum temperature, log(Precipitation), and population density had a negative impact. However, minimum temperature, log(Rural), and log(Total population) did not demonstrate any significant effects on the incidence of dengue. The impact of demographic-environmental factors on dengue outbreaks in 11 Asian countries is illuminated by this study. The results highlight the significance of mean temperature (Tmean), maximum temperature (Tmax), log(Urban), log(Precipitation), and population density in influencing dengue incidence rates. However, further research is needed to gain a better understanding of the role of additional variables, such as immunity levels, awareness, and vector control measures, in the spread of dengue.

Arbuscular Mycorrhizal (AM) Fungi Symbiosis in Sustainable Production of Sorghum (Sorghum bicolor L. Moench) Under Drought Stress: An Emerging Biofertilizer in Dryland Areas

Sorghum (Sorghum bicolor L. Moench) is an important cereal crop grown in arid and semiarid regions where water and other resources are limited. Changes in temperature and rainfall patterns have resulted in frequent droughts, which caused significant yield loss in sorghum. In recent years, there has been an increasing interest in sorghum cultivation due to its resilience to climate change and potential source of food and income. The symbiotic interaction of sorghum with Arbuscular Mycorrhizal fungi (AMF) has been found to induce several physiological and molecular changes that improve the ability of sorghum to withstand drought stress. This symbiotic relationship enhances water and nutrient uptake, osmotic adjustment, activation of stress‐responsive genes, stomatal regulation, and antioxidant defense, leading to improved drought tolerance in sorghum. Agricultural practices such as reduced tillage, cover cropping, intercropping, crop rotation, and the use of organic amendments promote the diversity and effectiveness of AM fungal symbiosis. Such agricultural practices create more favorable conditions for AM fungal establishment and growth while reducing dependence on synthetic fertilizers. In this review, we highlight AM fungal symbiosis on sorghum growth, physiology, and molecular mechanisms underlying the beneficial effects of AM fungal symbiosis under moisture deficit conditions. Overall, the present review elucidates sorghum production and breeding success in Ethiopia, the symbiotic mechanisms between plants and AM fungi, the prospects of biofertilizers in sustainable agriculture, the potential of AM fungal symbiosis as a sustainable approach to improve sorghum production and its synergistic effect with other crop management practices.

딥러닝을 이용한 도심지침수 위기관리방안에 대한 연구

Recently, climate change has caused a lot of damage worldwide. Existing rainfall patterns on the Korean Peninsula could predict long-term rainfall patterns and periods, but changes in rainfall patterns due to climate change made crisis response measures useless. Due to heavy rain in August 2022, 10 local governments, including Seoul, Gyeonggi, Gangwon, and Chungnam, were declared as special disaster areas for the first time. As the impermeable area increases due to urbanization and the use of the underground space of buildings increases, the design capacity of sewage pipes is often exceeded, and the scope is local but the damage scale is increasing. Urban floods require rapid situational awareness and crisis response. To this end, it is necessary to establish a system that can monitor the flood situation at all times using CCTV distributed across the country through AI-based image analysis technology, and a new type of urban flood monitoring technology that analyzes and links it based on standardized IoT unstructured data such as real-time measurement sensor data and CCTV images is required.

Redefining landslide susceptibility under extreme rainfall events using deep learning

The apparent changes in the Indian summer monsoon rainfall pattern and the nature of extreme rainfall events (EREs) in the southern Western Ghats (WG) caused widespread landslides across the region. Landslide susceptibility maps generated using the past landslide inventory are one of the efficient tools that can help mitigate the deleterious effects of landslides. Landslide susceptibility maps produced using the landslide inventory of normal and extreme rainfall years by deep neural network (DNN) modelling vary in terms of their degree of susceptibility, and the differences are prominent in the moderate and high susceptibility zones. The DNN model trained by landslide inventory of normal rainfall years is capable of predicting landslides during EREs (with Area Under the Curve (AUC) value >0.90). The inclusion of the landslides that occurred during recent EREs (since 2018) into the existing landslide inventory provides a more accurate and refined prediction of landslide susceptibility, which facilitates risk-informed landscape planning and development of the region. In addition, the result reveals that 13 % of the Kerala state is extremely susceptible for landslide occurrence, among this Idukki, Palakkad, Malappuram, Pathanamthitta, and Wayanad districts are highly vulnerable to the occurrence of landslides. Besides, the study also shows an increase of 3.46 % area in extreme susceptibility zone after the 2018 ERE. The updated landslide susceptibility map of the region may be used as a vital tool for planning landslide mitigation activities in the wake of recurrent EREs and associated landslide occurrences.

Assessing the Effectiveness of Climate-Resilient Rice Varieties in Building Adaptive Capacity for Small-Scale Farming Communities in Assam

Rice crop in Assam constitutes a significant portion of the cultivated area, covering around sixty percent of the total area. The state, like many others, confronts the repercussions of climate change, notably evident in recurrent floods that impact agricultural lands. The shifting climate, marked by rising temperatures and increased rainy days, poses threats to crop production. Despite witnessing overall productivity growth, the state grapples with persistent challenges related to flood-induced losses. In response to this, climate-resilient rice varieties were developed to withstand submergence. This study delves into the assessment of the impact of these climate-resilient rice varieties on yield, income, and adoption among farmers. Concentrating on Golaghat and Sivasagar districts, where 106 farmers were interviewed, the research addresses the prevalent challenges in rice cultivation due to changing rainfall patterns. The introduced varieties underwent demonstration in plots, and their effects on yield, income, and adoption were comprehensively evaluated. The study additionally scrutinized the technology and extension gaps in the area, utilizing various indices such as the technology gap, extension gap, technology index, and benefit-cost ratio to measure the efficacy of the introduced varieties. The findings of the study highlight disparities between recommended agricultural practices and the actual methods employed by farmers. Despite these challenges, the introduction of climate-resilient varieties resulted in a noteworthy increase in yield. Economic analysis revealed enhanced profitability from B:C ratio of 0.43 to1.06 and positive changes in economic indicators. The adoption and horizontal spread of these varieties were substantial, with a significant rise from 106 to 378 in the number of adopters and expanded cultivation areas. Overall, the study emphasizes the success of climate-resilient rice varieties in augmenting yield, income, and adoption among farmers. The positive economic changes, coupled with heightened awareness, underscore the importance of promoting such varieties. The study advocates for sustained efforts in disseminating climate-resilient varieties, emphasizing their pivotal role in enhancing farmers' climate resilience. Addressing the identified discrepancies in agricultural practices emerges as a crucial step toward fostering sustainability and optimizing crop yield in the region.

Monotonic trends of soil microbiomes, metagenomic and metabolomic functioning across ecosystems along water gradients in the Altai region, northwestern China

To investigate microbial communities and their contributions to carbon and nutrient cycling along water gradients can enhance our comprehension of climate change impacts on ecosystem services. Thus, we conducted an assessment of microbial communities, metagenomic functions, and metabolomic profiles within four ecosystems, i.e., desert grassland (DG), shrub-steppe (SS), forest (FO), and marsh (MA) in the Altai region of Xinjiang, China. Our results showed that soil total carbon (TC), total nitrogen, NH4+, and NO3− increased, but pH decreased with soil water gradients. Microbial abundances and richness also increased with soil moisture except the abundances of fungi and protists being lowest in MA. A shift in microbial community composition is evident along the soil moisture gradient, with Proteobacteria, Basidiomycota, and Evosea proliferating but a decline in Actinobacteria and Cercozoa. The β-diversity of microbiomes, metagenomic, and metabolomic functioning were correlated with soil moisture gradients and have significant associations with specific soil factors of TC, NH4+, and pH. Metagenomic functions associated with carbohydrate and DNA metabolisms, as well as phages, prophages, TE, plasmids functions diminished with moisture, whereas the genes involved in nitrogen and potassium metabolism, along with certain biological interactions and environmental information processing functions, demonstrated an augmentation. Additionally, MA harbored the most abundant metabolomics dominated by lipids and lipid-like molecules and organic oxygen compounds, except certain metabolites showing decline trends along water gradients, such as N′-Hydroxymethylnorcotinine and 5-Hydroxyenterolactone. Thus, our study suggests that future ecosystem succession facilitated by changes in rainfall patterns will significantly alter soil microbial taxa, functional potential, and metabolite fractions.

Comparative assessment of farmers’ perceptions on climate change: Experiences from semi-arid tropics of India

The present study was conducted to assess farmers' perceptions of the effects of climate change on their livelihoods. The aim was to compare these perceptions regarding climate trends, related effects, and adaptation options among rural communities in three Semi-Arid Tropical (SAT) villages located in Maharashtra and Andhra Pradesh, representing different agro-ecological regions. This study employed both quantitative and qualitative research methods to elicit farmers' perceptions, including farm household surveys, focus group discussions, and key informant interviews. The results of the study indicate that farm households are aware of climate change and are particularly concerned about changes in rainfall patterns and increased frequency of drought events, both in inter-seasonal and intra-seasonal distribution. Among the studied villages, Dokur experienced the most severe impacts from these changes. Furthermore, farmers perceive that natural resources such as land, water, and biodiversity have been affected due to the variations in the climate. In response to these challenges, farmers have adopted a set of adaptation options, including changes in crop selection, land management, water usage, socio-economic strategies, and collective actions. However, the study found discouraging trends in the adoption of these adaptation options, primarily due to a range of barriers that hinder their ability to adapt efficiently to climate change. This study underscores the critical need for region-specific strategic research and development programs aimed at enhancing the biophysical and socioeconomic conditions of these rural areas. Such efforts would enable these communities to improve their adaptive capacity and livelihood resilience in the face of climate-related risks and impacts. Future policies and programs should prioritize the upliftment of these fragile SAT communities, with the goal of enhancing their resilience to climate change and improving their overall quality of life.

A klímaváltozás hatása Szudán vízkészletére

In Sudan, the effects of climate change on water resources are widespread and varied. Sudan's water sources are diverse, including river, rain, surface, and groundwater, with the country's lands consisting of rivers, valleys, and creeks. Nevertheless, Sudan faces various water-related challenges such as inadequate sanitation, lack of safe drinking water, pollution, and scarcity. The country's water supply is at risk due to rapid population growth, urbanization, changing consumption patterns, and from agriculture, industry, and energy sectors. Moreover, the looming environmental changes, including global warming and increased greenhouse gas emissions, are expected to have significant social, environmental, and climatic impacts globally, particularly on water sources. The effects of climate change on Sudan's water resources are a cause for concern as droughts have already begun in some regions. It is therefore imperative to reduce greenhouse gas emissions and adopt clean energy sources while taking urgent and long-term measures to conserve water and mitigate climate change risks. This review highlights the issues related to climate change and its effects on water resources in Sudan, with a particular focus on how changing rainfall patterns will impact agriculture, which is the most critical indirect effect of climate change on water supply.

The Next-Generation Ecosystem Experiment Arctic Rainfall Simulator: a tool to understand the effects of changing rainfall patterns in the Arctic

Abstract Rainfall frequency and intensity are expected to increase in the Arctic, with potential detrimental impacts on permafrost, leading to enhanced thawing and carbon release to the atmosphere. However, there have been very few studies on the effect of discrete rain events on permafrost in the Arctic and sub-Arctic. Conducting controlled rainfall experiments within permafrost landscapes can provide an improved understanding of the effect of changing intensity, duration, and timing of rain events on permafrost tundra ecosystems. Here, we describe the design and implementation of the Next-Generation Ecosystem Experiment Arctic Rainfall Simulator (NARS), a variable intensity (4–82 mm/h) rainfall simulator that can be used to study the effects of rainfall on permafrost stability. The NARS design includes a 3D-printed 4 cm H-flume and uses an eTape resistivity sensor that was calibrated (R2 = 0.9–0.96) to measure discharge from the system. NARS is designed to be lightweight, simple to construct, and can be easily deployed in remote locations. As a field validation of updated rainfall simulator design and modernized controls, NARS was tested on the Seward Peninsula, AK. Because of its portability, versatility in deployment, dimensions, and rainfall intensity, NARS represents a methodological innovation for researching the impacts of rainfall on permafrost environments.

Ketahanan Lingkungan Dan Adaptasi Sosial Dalam Konteks Perubahan Iklim Di Kabupaten Provinsi Sumatera Selatan

Climate change affects agriculture through its impact on plant growth, development and yield. Research on indications of climate change and its impact on rice production in Indonesia in South Sumatra This research aims to examine climate change and its impacts on rice production in Indonesia. This study uses data from temperature, bulk rain, agroclimate, and rice production as well as socio-economic data. Methodology This research is an explanatory descriptive study using the concept of risk assessment where risk (risk) is a function of danger (hazard) and vulnerability (vulnerability). Study results shows that in Indonesia there has been climate change with indications of increasing temperature, changes in rainfall patterns, changes in hitergraphs, and changes in Oldeman classification.

Quantification of climate change impact on rainfall-induced shallow landslide susceptibility: a case study in central Norway

ABSTRACT Climate change impact on rainfall-induced landslide susceptibility of a certain region is often implied based on expected changes in rainfall patterns and rarely explicitly quantified. This study aims to address this gap by implementing coupled landslide and climate modelling chains to explicitly assess the effects of changing rainfall patterns on rainfall-induced landslide susceptibility. The effects of climate change are integrated into the landslide modelling chain via Intensity-Duration-Frequency (IDF) curves for the present and future climate conditions for a landslide-prone study area located in central Norway. The effects of climate change on landslide susceptibility are examined by using a physical-based landslide prediction model with rainfall events of varying duration and intensity that are simulated based on the climate-dependent IDF curves. The novelty of this study is the proposition of a novel probabilistic framework to assess the climate change impact on landslide susceptibility for rainfall events with a given duration. The proposed framework accounts for both the uncertainties of rainfall events through probabilistic interpretation of IDF curves and the uncertainties in the landslide model with the Monte Carlo method. Compared to results based on only intense rainfall events, the proposed framework leads to a lower increase in the probability of landslide initiation and landslide-susceptible extents due to climate change.

The Effect of Changes in Rainfall Patterns due to Climatic Change on the Cutting Slope Stability of Landslides Case in East Java, Indonesia

This study was conducted to determine the causes of landslides that often occur on the cutting slope on the side of the Gempol-Pandaan toll road in East Java. Furthermore, this study aims to ascertain the relationship between alterations in rainfall intensity due to climatic change on slope stability. Observation of conditions in the field, topographic contour measurements, field soil testing, real-time data processing of rain intensity, and numerical simulation for parametric study were carried out to determine the effect of changes in daily rainfall on slope stability. Also, numerical analysis using limit equilibrium as well as finite element methods with SEEP/W and SLOPE/W was carried out. The results of field observations showed there was no rainwater collection channel in the slope area, causing the water to infiltrate into the cutting slope body. The fluctuating and increasing rainfall intensity during 90 days of observation can reduce the safety factor of slope by up to 25%. This decrease in safety factors is believed to increase when the duration and intensity of the rain increase as a result of climatic change. Therefore, the integration between the impact of climate change on alterations in rain intensity in an area needs to be considered as an effort to mitigate landslides.

Future changes in crop yield over Poland driven by climate change, increasing atmospheric CO2 and nitrogen stress

CONTEXTCrop production is strongly affected by climate-related factors that are predicted to become more severe in the future due to significant changes in temperature, rainfall patterns, and increase in the intensity and frequency of extreme events. Understanding potential future crop yield response to a changing climate is of great importance for food production stability and safety. OBJECTIVEThe overall objective of this study is to assess the impact of projected climate change on crop yield in Poland. METHODSThis study employed an agro-hydrological Soil and Water Assessment Tool (SWAT) model forced by EURO-CORDEX downscaled and bias-corrected climate model outputs to simulate future changes in yield of spring barley (Hordeum vulgare), rapeseed (Brassica napus), maize silage (Zea mays), and potato (Solanum tuberosum) over Poland driven by climate change, an increase in atmospheric CO2 concentrations, and plant growth stress factors. We looked into two future horizons: near future (NF; 2041–2060), and far future (FF; 2081–2100) under two different Representative Concentration Pathways (RCP4.5 and 8.5). RESULTS AND CONCLUSIONSClimate projections revealed that by the end of century, Poland will experience an increase of mean precipitation (by up to 10.3%) and mean temperature (+3.4 °C) under RCP8.5. We tested two different nitrogen fertilisation scenarios under changing climatic conditions, namely auto fertilisation which adjusted the nitrogen doses according to actual plant requirements in each climatic scenario, and constant doses corresponding to current use throughout the entire simulation period. The results showed that crops in Poland will experience an increase in nitrogen stress and a decrease in water stress in the future. Temperature stress is projected to increase for spring barley, rapeseed, and potato, and decrease for thermophilic maize silage. Auto fertilisation scenario application that eliminated nitrogen stress in future horizons resulted in a significant increase in yield of all crops under consideration. The comparison of the RCP scenarios showed a higher increase for RCP8.5, reaching 13% for NF and 17% for FF as an average value for all crops. For RCP4.5, the corresponding values were 10% (NF) and 13% (FF). Nitrogen stress reported under the constant nitrogen rate scenario offseted potential yield increase in future horizons caused by elevated CO2.The multi-annual average yield of the analysed crops in future increased by <5%. SIGNIFICANCEOur study indicated that future changes in crop yield in Poland are mostly related to CO2 enhancement, and benefitting fully from that will require an adjustment of nitrogen fertiliser rates. Otherwise, a potential increase in biomass production will be restricted by nitrogen availability.

Carbon Emission, Impact on Climate and Mitigation Strategies in Nigeria

Climate change is a global issue, and organizations worldwide have been gathering to develop strategies to reduce global warming and mitigate its effects. Nigeria is not left out as the country faces changes in rainfall patterns, rising temperatures, rising sea levels, flooding, drought and desertification, and land degradation. This review paper investigated the current state of carbon emissions in the country and identified the major contributors. Additionally, the paper highlighted the consequences of carbon emissions and its effects on climate in the different sectors and parts of the country. Furthermore, the review paper suggested various mitigation and adaptation strategies employed with case studies and those that should be applied to decrease emissions at different levels. Lastly, it also discussed the participation of developed countries in climate financing to ensure a green climate. Urgent actions by governments to invest in climate education and renewable energy are required

Future changes of summer monsoon rainfall and temperature over Bangladesh using 27 CMIP6 models

This research aims to investigate the future changes in summer monsoon rainfall and temperature in Bangladesh. The study revealed that INM-CM5-0 is the best model for projecting temperature, while BCC-CSM2-MR is the best model for projecting rainfall over Bangladesh. Using data from a large ensemble of 27 models from CMIP6, the study examined the rainfall and temperature change projections of Bangladesh during the twenty first century relative to the reference period (1981–2014) under SSP2–4.5 and SSP5–8.5. Under SSP2-4.5 and SSP5-8.5, the multi-model ensemble monsoon mean rainfall over Bangladesh will fluctuate between 40 and 260 mm and 100 and 900 mm, respectively. In most parts of the country’s north, northeastern, and western regions, the projected changes in spatial patterns of monsoon rainfall indicate an increase in rainfall. The projected temperature indicated that Bangladesh’s northwest and west-central areas could face the most significant rise in temperatures, surpassing 3.8 °C under SSP5-8.5.

Development of an Intelligent System to Determine Land Suitability for Horticultural Crops on Vegetable Commodities

Global climate change has a significant impact on the agricultural sector, including horticulture, with climate fluctuations such as increased temperatures and changes in rainfall patterns potentially affecting crop productivity. Sustainable horticultural agriculture is important for safeguarding natural resources and reducing environmental impacts. However, challenges from climate change and variations in land conditions can affect horticultural crop production. Identifying crops that are suitable for the climate and land conditions is key to agricultural sustainability. An intelligent and adaptive approach is needed in selecting the right crops to grow in the face of climate change. This research develops an artificial intelligence application for the recommendation of horticultural crop types according to land conditions and climate change. The model built involves AHP and MFEP methods. The model takes into account various land parameters with weights determined through the AHP approach, allowing this AI application to provide accurate recommendations based on data and modeling. Based on the tests conducted, the system was able to produce analysis with an accuracy rate of 85%.

Vulnerability of communities' livelihoods to the impacts of climate change in north-western highlands of Tanzania

Climate change has emerged as one of the critical challenges to human well-being. Changing climate places direct and indirect impacts on human activities and is mainly triggered by non-climatic stressors, which are diverse and inherent in many communities. However, there has been diversity in how climate and non-climatic stress factors affect human well-being and thus requiring locally specific contextualisation of how climate change is driving change in many ecosystems. This study analysed climate and non-climate factors for communities' vulnerability and impacts using a landscape approach in selected villages in the western highlands of Tanzania, specifically in Kasulu and Buhigwe districts in Kigoma Region. The aim was to understand communities' vulnerability to the impacts of climate, and non-climate processes, particularly with regard to livelihoods and impacts, particularly in forest resources. Study sites and respondents were selected through simple random and purposive sampling methods. Data were collected through household surveys, key informants interviews, and focus group discussions. Meteorological data were used for the analysis of climatic changes. Quantitative data analysis tools included meteorological statistics software such as CLIDATA, INSTAT, XLSTAT and SPSS. Theme-content analysis was used to analyse qualitative data. Findings indicate inter-annual and seasonal variabilities of rainfall and temperature levels from the normal across the study sites. The study revealed significant increasing trends for mean annual Maximum and Minimum temperature. Significant changes in rainfall patterns were decreasing seasonal and annual rainfall trends, unreliable onset and cessation, and erratic seasonal rainfall. The maximum decline of seasonal rainfall had slope values of −14.51, while the maximum decline of annual rainfall trends had a slope value of −12.76. The minimum decline for seasonal rainfall had slope values of −2.17, and annual rainfall trends had slope values of −1.36. Villages in the highland zone were found to be highly vulnerable to the impacts of climate change and non-climate stress factors, with a 0.61 vulnerability index value. Major climate stress factors for communities' vulnerability included seasonal variability of rainfall and temperature increase, which influenced the increase of pests and diseases and other unfavourable climatic conditions that affect crop production and livestock keeping. The effects, directly and indirectly, influenced the low agricultural yields and decreased income. Non-climate stress factors such as landscape characteristics, mobility, inadequate extension services, and low household asset endowment might have been accelerating communities' vulnerability to the effects of the changing climate. Moreover, the study shows the climate change on a community's resilience. Generally, changes in climate conditions result in many adverse consequences and have been influencing communities' vulnerability.