Negative Effects Of Climate Change Research Articles

Economic Implications for Farmers in Adopting Climate Adaptation Measures in Italian Agriculture

The purpose of this paper is to provide an assessment of the economic convenience of adopting adaptation measures to climate change at farm level. Concerns raised about climate risks on agriculture indicate that adaptation of the agricultural sector to climate change is necessary to mitigate the negative consequences of climate change. Despite many opportunities to implement climate adaptation measures at farm level, there are several obstacles to their adoption. Farmers’ decision to implement adaptation measures lies in the difficulty of accessing knowledge about adaptation practices and in the lack of resources for upfront investments required by adaptation. The need to investigate economic convenience in terms of costs and benefits of adopting adaptation measures to prevent or reduce damage from adverse climatic events by farmers arises from this consideration. More importantly, climate protection and management of climate change are European environmental policy objectives. However, adaptation to climate change remains complex, and literature on the costs and benefit of agricultural adaptation is limited. Based on these considerations, this paper provides an analysis of the economic convenience of adopting adaptation measures in Italian farms. The economic convenience to implement adaptation measures is calculated on the reduction of the impact of climate damage. Our results show the economic convenience of adaptation measures. These findings help to improve the still too limited access to information on adaptation policies at farm level as well as the benefits that adaptation produces in economic and environmental terms, on human and ecosystem health. This study supports farmers’ decisions in adopting climate adaptation measures and provides information for policy makers to identify specific financial instruments for adaptation measures.

Perspectives on geologic carbon storage

Geologic carbon storage (GCS) is a fundamental pillar of carbon management that helps mitigate greenhouse gas emissions and addresses the negative effects of climate change. Viable CO2 storage sites share some of the same elements required for successful petroleum systems. For example, while reservoir, seal, and trap are required, migration pathway and timing are not important for CO2 storage, because rather than withdrawing fluid from a trap, CO2 storage involves injection into a geologic trap. Conceptually, this represents a form of reverse production. Numerous petroleum traps around the world, as well as naturally occurring CO2-producing fields and natural gas storage sites attest that safe, long-term storage is possible. Research over the past two decades identified five methods of Geologic Carbon Storage which have been validated through several demonstration and pilot projects around the world: (1) storage in depleted oil and gas fields, (2) use of CO2 in enhanced hydrocarbons recovery (3) storage in saline formations/aquifers, (4) injection into deep unmineable coal seams, and (5) in-situ/ex-situ carbon mineralization. The greatest volumetric potential for GCS is found in saline aquifers which are present throughout the world’s sedimentary basins.

Informality and the climate change-poverty nexus: empirical evidence from African countries

ABSTRACT The present paper introduces informality into the climate change-poverty nexus using 40 Sub-Saharan African countries selected from high-, middle and low-income countries between 1990 and 2019. The empirical results show that informality is an important variable that can mitigate the impact of climate change on poverty. The moderation of the poverty-climate change nexus is nonlinear in income. Informality reduces the negative effect of climate change on poverty in middle income countries while exacerbating its effect in low-income countries. Possible channels of influence are identified. Policy makers need to rethink the role of informality in an environment where informality is mainly seen as a nuisance, to see it as an ally that can achieve key results for the fight against environmental degradation and extreme poverty.

Agricultural Vulnerability to Climate Change: A Critical Review of Evolving Assessment Approaches

The cumulative negative effects of climate change make agriculture increasingly vulnerable, with severe food security challenges, especially for developing nations. A robust research approach and a logical methodical framework can holistically assess the occurrence and intensity of agricultural vulnerability in a bid to strategize mitigation measures. This paper includes an in-depth review of the existing body of literature on agricultural risk and vulnerability, apart from recent studies and metric measurements of vulnerability having an emphasis on agriculture. Unlike the high priority on climate indicators in the past, contemporary research is progressively comprehensive and multidisciplinary where socioeconomic factors are integrated to make the assessment all-encompassing. Though this review paper found six major types of methodologies, the current vulnerability studies are predominantly index-based experiments adapted from the IPCC vulnerability concept. However, there is considerable variation across experiments concerning vulnerability conceptualization, selection of indicators, weight assignment and indexing techniques. Majority of the indexes encapsulate expert-recommended variables under sensitivity, exposure, and adaptive capacity. Such index-based measurements describe and compare vulnerability over space and time in order to formulate actionable policy measures. Uniform and robust techniques in indicator selection and statistically tenable weight allocation should be pursued in future research. To make the index highly representative and validated, the inadequacy of community perception should be minimized through the integration of PRA techniques within the experimental framework. Emerging threats such as loss of labour productivity in agriculture should be included in the analysis. The components of vulnerability also need to be analysed to comprehend their individual share in overall vulnerability for well-targeted mitigation measures. Constraints of data insufficiency required for vulnerability studies need attention for quality vulnerability research in the future. With such set priorities and focus, future research outcomes in vulnerability evaluation should be more meaningful and policy-focused.

The climate crisis and the ways of response

The article raises questions about the climate crisis, which manifests itself in global warming, emergencies that pose a danger to cities and towns, buildings, structures, and people’s health. The author presents different points of view on climate change, the role of greenhouse gases and the anthropogenic contribution to global warming. A study was made of the proposed ways of adapting construction and architecture to the situation of global warming, mitigating the negative effects of climate change. The author highlights topical areas of scientific research, such as: the formation of carbon-neutral architecture, the development of bioengineered building materials, the creation of “vertical gardens”, etc. The author presents the results of a sociological survey of the students of National Research Moscow State University of Civil Engineering of the year 2021-2022. The results are showing their understanding of the causes of climate change, professional responsibility and readiness to counteract the negative effects of climate change.

How is Bangladesh Growing More Susceptible to Infectious Disease Epidemics as a Result of Climate Change? A Systematic Review

Bangladesh is facing unpredictable weather patterns, as well as a consistent rise in temperature and precipitation. Climate change has had a negative impact on physical and mental health, leading to an increase mostly in the prevalence and variation of infectious diseases, as well as psychological issues such as depression and anxiety disorders. Given the country's inherent sensitivity to climatic influences, the climate-health nexus is a relatively unexplored subject of research. The purpose of this article is to investigate the severity of climate change in Bangladesh and how it impacts the health of the public. Morbidity and mortality due to heat stress, cyclones, floods, droughts, and other weather extremes at various spatiotemporal scales have been observed as direct effects of climate change in Bangladesh. The indirect effects involve more complicated paths, such as affecting food and water security due to salinity intrusion and the development of infectious diseases because of shifts in vector and pathogen ecology. To mitigate the effects of climate change on various infectious diseases, healthcare and response systems must be strengthened. By implementing proactive adaptation methods, we may significantly and actively contribute to preventing and regulating the negative consequences of climate change on human health. There is little evidence to make sound health policy decisions in the context of climate change, and there is a lack of multidisciplinary research activities. Despite these constraints, gathering and reporting scientific information is essential for developing a resilient health system in climate-vulnerable countries like Bangladesh and other low-income regions.

Current and future trends in heat-related mortality in the MENA region: a health impact assessment with bias-adjusted statistically downscaled CMIP6 (SSP-based) data and Bayesian inference

The Middle East and North Africa (MENA) is one of the regions that is most vulnerable to the negative effects of climate change, yet the potential public health impacts have been underexplored compared to other regions. We aimed to examine one aspect of these impacts, heat-related mortality, by quantifying the current and future burden in the MENA region and identifying the most vulnerable countries. We did a health impact assessment using an ensemble of bias-adjusted statistically downscaled Coupled Model Intercomparison Project phase 6 (CMIP6) data based on four Shared Socioeconomic Pathway (SSP) scenarios (SSP1-2·6 [consistent with a 2°C global warming scenario], SSP2-4·5 [medium pathway scenario], SSP3-7·0 [pessimistic scenario], and SSP5-8·5 [high emissions scenario]) and Bayesian inference methods. Assessments were based on apparent temperature-mortality relationships specific to each climate subregion of MENA based on Koppen-Geiger climate type classification, and unique thresholds were characterised for each 50 km grid cell in the region. Future annual heat-related mortality was estimated for the period 2021-2100. Estimates were also presented with population held constant to quantify the contribution of projected demographic changes to the future heat-mortality burden. The average annual heat-related death rate across all MENA countries is currently 2·1 per 100 000 people. Under the two high emissions scenarios (SSP3-7·0 and SSP5-8·5), most of the MENA region will have experienced substantial warming by the 2060s. Annual heat-related deaths of 123·4 per 100 000 people are projected for MENA by 2100 under a high emissions scenario (SSP5-8·5), although this rate would be reduced by more than 80% (to 20·3 heat-related deaths per 100 000 people per year) if global warming could be limited to 2°C (ie, under the SSP1-2·6 scenario). Large increases are also expected by 2100 under the SSP3-7·0 scenario (89·8 heat-related deaths per 100 000 people per year) due to the high population growth projected under this pathway. Projections in MENA are far higher than previously observed in other regions, with Iran expected to be the most vulnerable country. Stronger climate change mitigation and adaptation policies are needed to avoid these heat-related mortality impacts. Since much of this increase will be driven by population changes, demographic policies and healthy ageing will also be key to successful adaptation. National Institute for Health Research, EU Horizon 2020.

Performance of improved versions of Swarna introgressed with yield enhancing genes in multi-location trials

Swarna (MTU7029), an Indian mega-variety of rice, is cultivated on an estimated 8Mha of land. There is a pressing need to address yield stagnation and wider adaptability to irrigated lowland and rainfed ecologies as a result of the negative consequences of climate change and population growth. The present study was aimed at improving Swarna for two yield-related traits through marker-assisted backcross breeding strategy by introgression of OsSPL14 (panicle branching) and SCM2 (stronger culm). Foreground and background selection was carried out at each generation. Homozygous BC2F2 plants harbouring both yield-enhancing genes were identified and advanced through pedigree selection till BC2F5 and evaluated in station trials. Three promising lines possessing higher yield over recurrent parent were identified, and a single line, IET 27661 exhibited superior yield in multi-location trials of the All India Coordinated Rice Improvement Programme (AICRIP) and was found to be promising.

An approach to measure resilience of communities to climate change: a case study in Calabria (Southern Italy)

Climate change effects already represent a serious challenge for people and environment. In particular, changes in precipitation, temperature, and weather systems are increasing the occurrence frequency of natural phenomena such as floods and landslides with consequent negative impacts in exposure and vulnerability of population living in risk areas. Hence, it is important to assess the social vulnerability and the community resilience which describe the ability of social systems to prepare for, absorb, and adapt to risks induced by climate change. In two sample areas located along the Tyrrhenian side of Calabria (Amantea and Lago municipalities, Southern Italy), we performed a multi-criteria decision analysis (MCDA) of community resilience. Based on previous literature, we have selected five macro-indicators of social resilience (awareness, knowledge, information, trust, and social background). As sub-indicators for the characterization of these macro-indicators, we used the answers of the questions on climate change effects of a questionnaire submitted to citizens living in the sample areas, and, then, a specific weight was assigned to each sub-indicator, as well as to the macro-indicators. The multi-criteria analysis allowed to the classification of the studied areas in terms of an index of social resilience and to the individuation of the most influential macro-indicators for each of them. The results show that the two areas, which have similar resilience’s values, are influenced by different macro-indicators: knowledge and awareness for Amantea and information and trust for Lago. The findings of this study can be considered very useful for the management of vulnerable areas to climate change, because they are able to underline the aspects needing attention. In fact, providing information about the nuances of the resilience of community exposed to risks may help decision-makers in adopting and implementing more effective preventive measures to mitigate negative effects of climate change, fitting on local characteristics.

TOO HOT FOR SUSTAINABLE DEVELOPMENT: CLIMATE CHANGE AND ENERGY EFFICIENCY

Previous studies have focused on the benefits of adaptation in mitigating the negative effect of climate change on economic production, neglecting that adaptive energy input cannot be directly translated into output, which may be a barrier to sustainable development. Based on panel data from 280 cities in China from 2003 to 2016, we first calculate the energy efficiency as a proxy for sustainable development by using the nonradial directional distance function (NDDF) method. Second, we estimate energy efficiency as a function of temperature shocks, and we use these estimates to predict future potential impacts from climate change. We find three primary results: First, higher temperatures substantially reduce energy efficiency. Second, the heat effect on energy efficiency is homogenous across regions with different climates, suggesting that while adaptations in hot regions can mitigate the harmful effects of heat on output, this mitigation is completely offset by the concomitant increase in energy costs. Third, the energy efficiency would decrease by 2.82% in the medium term (2041–2060) and by 12.02% in the long term (2061–2080), under the assumption that carbon dioxide emissions continue to increase throughout the 21st century. These findings suggest that moderate adaptations to climate change are crucial for sustainable development.

Bidirectional gene flow between Fagus sylvatica L. and F. orientalis Lipsky despite strong genetic divergence

Fagus sylvatica L., one of the most common Central European deciduous tree species, is one of the species globally suffering from changing and stressful environmental conditions. It has shown symptoms of crown damage, a reduction in growth and increased mortality following recent severe droughts. Fagus orientalis Lipsky, a closely related species with higher drought tolerance, originates from southeastern Europe, Turkey, the Greater Caucasus region, and the Hyrcanian forest. For Germany, F. orientalis has been proposed as an alternative to F. sylvatica by translocation of pre-adapted planting material as a tool to mitigate negative effects of climate change in certain locations. This approach can be beneficial but might also harbor risks.We studied admixtures between the two beech species and the direction of gene flow, taking advantage of F. orientalis trees planted over 100 years ago in the forest district of Memsen, Germany. Additionally, we used a range-wide dataset of F. sylvatica and F. orientalis provenances to determine the origin of the introduced trees. Using a combination of nuclear microsatellites and one chloroplast marker with species-specific variants, we showed that interspecific gene flow was going in both directions. In most cases, F. sylvatica was the pollen donor, likely due to its greater abundance and production of vast amounts of pollen. The planted trees from Memsen originated from the Greater Caucasus region and showed strong genetic divergence from German F. sylvatica populations, clearly differing in leaf morphological traits. In the future, the suitability of different provenances for the mitigation of climate change impacts should be carefully assessed by testing gene flow patterns as well as hybrid performance in additional stands and in comparison to F. sylvatica provenances from southern Europe.

Climate Solidarity: A Framework and Research Agenda for Low‐Carbon Behavior

Climate‐change mitigation is a matter of solidarity. Behaviors that primarily benefit other people are prosocial behaviors that can be considered solidarity at the collective level. For climate‐change mitigation, greenhouse gas emissions have to be reduced primarily in wealthy countries, while the major beneficiaries of such a reduction are the populations of developing countries and future generations, who (will) suffer the significant negative consequences of climate change. Climate change has created a new global interdependence that requires a new form of solidarity as a global and intergenerational prosocial behavior. Low‐carbon behavior has so far mainly been studied as a form of pro‐environmental behavior but not as a form of prosocial behavior. The article identifies four approaches to explaining the origin of prosocial behavior that can be applied to the emergence of low‐carbon behavior: rationalist, institutionalist, interactionist, and situational approaches. The scope conditions and limitations of each approach in the case of low‐carbon behavior are discussed, together with relevant empirical evidence, future research directions, and policy implications. The article lays the foundations for the study of climate solidarity as a new interdisciplinary field of research that can make a key contribution to the transition toward low‐carbon societies.

Distinguishing forest types in restored tropical landscapes with UAV-borne LIDAR

Forest landscape restoration is a global priority to mitigate negative effects of climate change, conserve biodiversity, and ensure future sustainability of forests, with international pledges concentrated in tropical forest regions. To hold restoration efforts accountable and monitor their outcomes, traditional strategies for monitoring tree cover increase by field surveys are falling short, because they are labor-intensive and costly. Meanwhile remote sensing approaches have not been able to distinguish different forest types that result from utilizing different restoration approaches (conservation versus production focus). Unoccupied Aerial Vehicles (UAV) with light detection and ranging (LiDAR) sensors can observe forests` vertical and horizontal structural variation, which has the potential to distinguish forest types. In this study, we explored this potential of UAV-borne LiDAR to distinguish forest types in landscapes under restoration in southeastern Brazil by using a supervised classification method. The study area encompassed 150 forest plots with six forest types divided in two forest groups: conservation (remnant forests, natural regrowth, and active restoration plantings) and production (monoculture, mixed, and abandoned plantations) forests. UAV-borne LiDAR data was used to extract several Canopy Height Model (CHM), voxel, and point cloud statistic based metrics at a high resolution for analysis. Using a random forest classification model we could successfully classify conservation and production forests (90% accuracy). Classification of the entire set of six types was less accurate (62%) and the confusion matrix showed a divide between conservation and production types. Understory Leaf Area Index (LAI) and the variation in vegetation density in the upper half of the canopy were the most important classification metrics. In particular, LAI understory showed the most variation, and may help advance ecological understanding in restoration. The difference in classification success underlines the difficulty of distinguishing individual forest types that are very similar in management, regeneration dynamics, and structure. In a restoration context, we showed the ability of UAV-borne LiDAR to identify complex forest structures at a plot scale and identify groups and types widely distributed across different restored landscapes with medium to high accuracy. Future research may explore a fusion of UAV-borne LiDAR with optical sensors, and include successional stages in the analyses to further characterize and distinguish forest types and their contributions to landscape restoration.

Responses of wheat kernel weight to diverse allelic combinations under projected climate change conditions.

In wheat, kernel weight (KW) is a key determinant of grain yield (GY). However, it is often overlooked when improving wheat productivity under climate warming. Moreover, little is known about the complex effects of genetic and climatic factors on KW. Here, we explored the responses of wheat KW to diverse allelic combinations under projected climate warming conditions. To focus on KW, we selected a subset of 81 out of 209 wheat varieties with similar GY, biomass, and kernel number (KN) and focused on their thousand-kernel weight (TKW). We genotyped them at eight kompetitive allele-specific polymerase chain reaction markers closely associated with TKW. Subsequently, we calibrated and evaluated the process-based model known as Agricultural Production Systems Simulator (APSIM-Wheat) based on a unique dataset including phenotyping, genotyping, climate, soil physicochemistry, and on-farm management information. We then used the calibrated APSIM-Wheat model to estimate TKW under eight allelic combinations (81 wheat varieties), seven sowing dates, and the shared socioeconomic pathways (SSPs) designated SSP2-4.5 and SSP5-8.5, driven by climate projections from five General Circulation Models (GCMs) BCC-CSM2-MR, CanESM5, EC-Earth3-Veg, MIROC-ES2L, and UKESM1-0-LL. The APSIM-Wheat model reliably simulated wheat TKW with a root mean square error (RMSE) of < 3.076g TK-1 and R2 of > 0.575 (P < 0.001). The analysis of variance based on the simulation output showed that allelic combination, climate scenario, and sowing date extremely significantly affected TKW (P < 0.001). The impact of the interaction allelic combination × climate scenario on TKW was also significant (P < 0.05). Meanwhile, the variety parameters and their relative importance in the APSIM-Wheat model accorded with the expression of the allelic combinations. Under the projected climate scenarios, the favorable allelic combinations (TaCKX-D1b + Hap-7A-1 + Hap-T + Hap-6A-G + Hap-6B-1 + H1g + A1b for SSP2-4.5 and SSP5-8.5) mitigated the negative effects of climate change on TKW. The present study demonstrated that optimizing favorable allelic combinations can help achieve high wheat TKW. The findings of this study clarify the responses of wheat KW to diverse allelic combinations under projected climate change conditions. Additionally, the present study provides theoretical and practical reference for marker-assisted selection of high TKW in wheat breeding.

Adaptation strategies for the adverse effects of climate disruptions on coffee and cocoa trees productivity in Cameroon

The decline of Cameroon cocoa and coffee productions are increasingly designated as one of the negative consequences of climate change on plants development. The purpose of this study was to contribute to improving the productivity of cocoa and coffee trees, in their production areas, in Cameroon. Thus, 280 plots, located in three different agro-ecological zones, were monitored for five consecutive years (2014-2018). Meteorological data were also systematically collected at each site. Data analysis highlighted three classes of unstable meteorological profiles that reflect the non-recurrence of climatic events on the study sites. Multiple logistic regression analysis showed that the incidence of cocoa black pod disease and that of Arabica coffee berry disease increases with the quantity of rainfall and the number of rainy days. This increase rather induces a decrease in the attack rate of berry borer on the Robusta coffee trees. The results obtained made it possible to identify, by elucidating their respective roles, the climatic variables which have an effect on the productivity of cocoa and coffee trees. They have also led, for the first time, to the conceptualization of innovative technical processes, which can reduce the harmful effects of climatic disturbances on cocoa and coffee crops.

The Necessity of Maintaining the Resilience of Peri-Urban Forests to Secure Environmental and Ecological Balance: A Case Study of Forest Stands Located on the Romanian Sector of the Pannonian Plain

Climate change’s negative effects, such as rising global temperatures and the disruption of global ecological ecosystems as a direct effect of rising carbon emissions in the atmosphere, are a significant concern for human health, communities, and ecosystems. The condition and presence of forest ecosystems, especially those in peri-urban areas, play an essential role in mitigating the negative effects of climate change on society. They provide direct benefits to the residents of large cities and their surrounding areas, and they must be managed sustainably to protect all their component ecosystems. This research was carried out in the forests of Lunca Muresului Natural Park and Bazos Arboretum, located in the Romanian sector of the Pannonian Plain, near urban agglomerations. The results showed high variability in the stands. Using the height-to-diameter ratio indicator concerning dbh and species, a strong Pearson correlation was registered (between 0.45 and 0.82). These values indicate the high stability of these stands, providing positive human–nature interactions such as recreational or outdoor activities (and a complementary yet indirect use value through attractive landscape views). Protecting these ecosystems offers a so-called insurance policy for the next generations from a climate change standpoint.

Aquavoltaics Feasibility Assessment: Synergies of Solar PV Power Generation and Aquaculture Production

The negative effects of climate change have burdened humanity with the necessity of decarbonization by moving to clean and renewable sources of energy generation. While energy demand varies across the sectors, fisheries, including fishing and aquaculture, are among the most energy intensive processes in the food production industry. The synergistic opportunities for co-located aquaculture and renewable energy can thus provide a multifunctional use of space and resources, creating opportunities to meet the identified energy demands of a variety of aquaculture operations. This study has investigated a sustainable energy model for a small-scale shrimp farm in western Taiwan with synergies for the dual use of the water area for solar photovoltaic electricity generation and aquaculture. Based on the simulation results and SWOT analysis, recommendations have been made for the design and operation of a solar-powered aeration system for shrimp farms. The average monthly energy production of 32 MWh is attainable at the estimated canopy space on a carport by installing 896 solar modules on the proposed site, fully covering the power demand of the shrimp farm. These findings have significance for encouraging effective practices in deploying solar techniques in aquaculture and making them replicable in global settings.

Potential impacts of climate change on the distribution of the relict plant Shaniodendron subaequale

Shaniodendron subeaqualis is a tertiary relict plant unique to China. This species has high greening, ecological, and scientific research value, and has been listed as a national I-level key protected plant. Clarifying the main climatic factors restricting the geographical distribution of S. subeaqualis and predicting the potential geographical distribution pattern of this species can provide a scientific basis for the protection of the germplasm resources of this rare species. Based on 104 S. subeaqualis natural distribution records and 9 climate factors, the MaxEnt software was used to predict the potential suitable areas of S. subeaqualis in different periods (LGM, MH, Current, SSP245-2050s, SSP245-2090s, SSP585-2050s, SSP585-2090s). The results showed that the contemporary AUC predicted by MaxEnt is 0.996, with high simulation accuracy; Precipitation in the driest season (Bio17), the average temperature in the coldest season (Bio11) are main factors affecting the distribution of S. subeaqualis. At present, the suitable area of S. subeaqualis is mainly distributed in Jiangsu, Anhui, and Zhejiang province, with a total area of 11.575 × 104 km2, of which the high suitable area is 1.424 × 104 km2 and the medium suitable area is 3.826 × 104 km2. In the LGM, the area of S. subeaqualis was roughly similar to that of the contemporary period, but there was a southward migration phenomenon in some areas, such as the suitable area in the south of Zhejiang. In order to avoid the influence of ice age, S. subeaqualis moved to nearby refuge places, such as Dabie Mountain area of Anhui province, the west of Tianmu Mountain area of Zhejiang province and mountain area of Jiangsu province. In the MH, the suitable area for S. subeaqualis was reduced and moved northward to a small extent. In the future period, the suitable range of S. subeaqualis will not change greatly, but the overall degree of fragmentation will intensify. If effective measures are not taken, it is bound to bring severe challenges to the survival of S. subeaqualis. In order to protect S. subeaqualis germplasm resources more effectively, it is suggested to dynamically monitor the existing S. subeaqualis population and take various measures actively to reduce the negative effects of climate change on S. subeaqualis.

Determining the Temporal Change in Tuz Gölü between 2000-2020 by Remote Sensing

Changes in the landscape become extremely destructive and many heritage values and resources are irreversibly lost. The speed, frequency and magnitude of these changes in the landscape increased in the second half of the 20th century, especially with the impact of human activities. Remote sensing is the most widely used method for determining the change in the landscape. In the research, MNDWI, NDVI and NDMI techniques, which are frequently applied in remote sensing, were used in order to determine the landscape change in Salt Lake. Thus, the changes in the built area, water surface and land cover between the years 2000-2020 in Salt Lake were determined. According to the MNDWI and NDMI Analysis results, a decrease was observed in the water surface width and moisture content in Salt Lake between 2000 and 2020. In the steppe areas south of Salt Lake, the increase in tree cover due to the change in land use type was determined by NDVI analysis. Therefore, it is possible to say that there is an increase in the amount of moisture in these areas. In addition, it was determined that the increase in agricultural activities in the region caused a change in land use types and the amount of green space in the region changed at this rate. With the mentioned methods, negative changes in the landscape as a result of human activities on the landscape can be determined practically. Thus, it will be possible to predict the negative consequences of climate change and take precautions.

Projecting hydrologic change under land use and climate scenarios in an agricultural watershed using agent-based modeling

Watershed systems are changing due to human activities within the landscape and shifting precipitation patterns, and quantifying the coupled effects of these two factors is necessary for anticipating future hydrologic response. In this study, we use a model that combines an agent-based model (ABM) with a semi-distributed hydrologic model to assess how projected changes in precipitation and temperature affect streamflow when simultaneously considering how those variables impact the land use decisions that also influence watershed response. We use a flood-prone watershed which is characteristic of many agriculturally-dominated watersheds in the central Midwest US. In the ABM, farmer agents make decisions that affect land use based on factors related to profits, past land use, neighbor influence, and internal behavior. A city agent aims to reduce urban flooding by paying farmer agents a subsidy for allocating land to conservation practices that reduce runoff. We run the model for the 2018–2097 period using the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 climate scenarios and different decision-making options. The model reveals that under future precipitation, which becomes increasingly intense leading to more in-field flooding, farmers increase conservation land by up to 60%. This land conversion results in a 4–7% decrease in mean 95th percentile discharge relative to scenarios where conservation land is held constant at the historical mean. If farmers are allowed to modify their internal behavior and preferences, the mean 95th percentile discharge decreases further (up to 16%). Using the assumption that land owners are willing to adapt their personal preferences to mitigate the negative effects of climate change on their land and external incentives exist to do so, upstream runoff mitigation practices could reduce downstream impacts from more frequent intense precipitation. However, farmer agents converted, on average, &amp;lt;10% of their land to conservation even when this variable was unrestricted. By the end of the century, precipitation has the dominant influence on discharge, given the significant changes in projected precipitation and the limited land conversion.