Climate Change Impact Assessment Research Articles

Potential Impacts of Future Climate Changes on Crop Productivity of Cereals and Legumes in Tamil Nadu, India: A Mid-Century Time Slice Approach

Climate change is a terrible global concern and one of the greatest future threats to societal development as a whole. The accelerating pace of climate change is becoming a major challenge for agricultural production and food security everywhere. The present study uses the midcentury climate derived from the ensemble of 29 general circulation models (GCMs) on a spatial grid to quantify the anticipated climate change impacts on rice, maize, black gram, and red gram productivity over Tamil Nadu state in India under RCP 4.5 and RCP 8.5 scenarios. The future climate projections show an unequivocal increase of annual maximum temperature varying from 0.9 to 2.2°C for RCP 4.5 and 1.4 to 2.7°C in RCP 8.5 scenario by midcentury, centered around 2055 compared to baseline (1981–2020). The projected rise in minimum temperature ranges from 1.0 to 2.2°C with RCP 4.5 and 1.8 to 2.7°C under RCP 8.5 scenario. Among the monsoons, the southwest monsoon (SWM) is expected to be warmer than the northeast monsoon (NEM). Annual rainfall is predicted to increase up to 20% under RCP 4.5 scenario in two-third of the area over Tamil Nadu. Similarly, RCP 8.5 scenario indicates the possibility of an increase in rainfall in the midcentury with higher magnitude than RCP 4.5. Both SWM and NEM seasons are expected to receive higher rainfall during midcentury under RCP 4.5 and RCP 8.5 than the baseline. In the midcentury, climate change is likely to pose a negative impact on the productivity of rice, maize, black gram, and red gram with both RCP 4.5 and RCP 8.5 scenarios in most places of Tamil Nadu. The magnitude of the decline in yield of all four crops would be more with RCP 8.5 over RCP 4.5 scenario in Tamil Nadu. Future climate projections made through multi-climate model ensemble could increase the plausibility of future climate change impact assessment on crop productivity. The adverse effects of climate change on cereal and legume crop productivity entail the potential adaptation options to ensure food security.

Coupling SWAT and Bi-LSTM for improving daily-scale hydro-climatic simulation and climate change impact assessment in a tropical river basin

Global climate change has led to an increase in both the frequency and magnitude of extreme events around the world, the risk of which is especially imminent in tropical regions. Developing hydrological models with better capabilities to simulate streamflow, especially peak flow, is urgently needed to facilitate water resource planning and management as well as climate change mitigation efforts in the tropics. In view of the need, this paper explores the feasibility of improving streamflow simulation performance in the tropical Kelantan River Basin (KRB) of Peninsular Malaysia through coupling a conceptual process-based hydrological model − Soil and Water Assessment Tool (SWAT) with a deep learning model − Bidirectional Long Short-Term Memory (Bi-LSTM) in two ways. All SWAT parameters were set as their default values in one hybrid model (SWAT-D-LSTM), whereas three most sensitive SWAT parameters were calibrated in the other hybrid model (SWAT-T-LSTM). Comparison of daily streamflow simulation results have shown that SWAT-T-LSTM consistently performs better than SWAT-D-LSTM as well as the stand-alone SWAT and Bi-LSTM model throughout the simulation period. Particularly, SWAT-T-LSTM performs considerably better than the other three models in simulating daily peak flow. Based on the latest projection results of five GCMs from the Sixth Phase of the Coupled Model Intercomparison Project (CMIP6) under three emission scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5), the best-performed SWAT-T-LSTM was run to assess the potential impacts of climate change on streamflow in the KRB. Ensemble assessment results have concluded that both average and extreme streamflow is much likely to increase considerably in the already wet northeast monsoon season from November to January, which has surely raised the alarm for more frequent flood occurrence in the KRB.

Assessment of Climate Change Impact on Maize Production in Serbia

Climate factors have an impact on plant life cycle, yield, productivity, economy and profitability of agricultural production. There are not a lot of studies on understanding of influence of climate factors variation on maize yield in agro-ecological conditions of Serbia. The aim of this paper is analysis of variation of climatic factors over a long-time period, as well as assessment of impact of the examined climate parameters on maize yield in two localities in the Republic of Serbia. For the analysis of climatic factors (temperature, precipitation, sunshine, humidity) in the region of Central Serbia and Vojvodina, the data of meteorological stations Kragujevac and Sombor during two thirty-year periods (1961–1990 and 1991–2020) were used. In order to determine the existence and strength of the relationship between the observed climatic factors and maize yield, a correlation analysis of these indicators for the period 2005–2020 years, was performed. In the period 1991–2020, the average values of temperature were annually increased for 0.046 °C in Kragujevac and for 0.05 °C in Sombor, and in the same period the average value of sunshine on an annual level was increased for 1.3 h in Kragujevac and for 5.01 h in Sombor, 2020 in comparison to average values in period of 1961–1990. The humidity was decline annually for 1.3 in Kragujevac and for 3.4 in Sombor in period 1991–2020 in comparison to average humidity in period of 1961–1990. The results of the correlation analysis showed that the maize yield was significantly lower in the years with expressed high temperatures and precipitation deficit. Based on these studies, established effect of climate change on maize yield and that this demand developing adaptation agricultural practice through creating maize hybrids and varieties with greater adaptability and improvement of agrotechnic measure.

Regional integrated assessment of climate change impact on cotton production in a semi-arid environment

Climate change has a negative impact on the productivity of agricultural crops at local, regional and global levels. Foodstuff security and sustainable livelihood of cotton farmers in the core cotton growing region in Punjab, Pakistan is under threat because of decreased yield due to climate change. The quantification of the integrated impact assessment of climate change for developing adaptation approaches for cotton is vital for improving productivity at a regional level and improving food security at a national level. Two crop models were evaluated with on-farm survey data of 165 farms employing stratified random sampling techniques. Representative agricultural pathways (RAPs) were developed for characterizing future cotton production. Global climate models (GCMs) depicted a rise of 3.6 and 4.3°C for maximum and minimum temperature, respectively, along with a decreased in rainfall of 600 mm under Representative Concentration Pathway (RCP) 8.5. The expected temperature rise for the hot-dry climate would cause a reduction in productivity of 35.3 and 39.2% by mid-century for RCP4.5 and RCP8.5, respectively, according to the Decision Support System for Agrotechnology Transfer (DSSAT) model, while the Agricultural Production System Simulator (APSIM) showed a reduction of 51.1 and 59.6%, respectively. Increases under the current adaptation of a 15% increase in each of nitrogen and planting density ranged from 1.1 to 6.3% for DSSAT and 2.6 to 8.2% for APSIM. Climate-adapted cotton productivity was projected to rise from 18.7 to 35.9% for DSSAT and from 13.8 to 42% for APSIM for all GCMs. Results showed that current and future cotton systems are adversely impacted by climate change; however, climate-change-adapted management approaches could offset possible reductions in productivity. Sustained cotton productivity in the core cotton zone requires capacity building amongst farmers, enabling them to improve their crop management in the face of seasonal climate variability and future climate change.

Assessment of climate change impact on maximum precipitation in Spain

AbstractThe potential effect of climate change on maximum precipitation is studied by considering several temporal intervals for its incorporation into flood risk management in Spain. The methodology used allows for a complete assessment of the effect of climate change on maximum precipitation by accounting for uncertainty, and may be applied to other case studies. Behaviour regarding observations, trends and changes in climate model maximum precipitation series are evaluated. In turn, multi‐model mean (and percentile) relative changes accounting for statistical significance, torrential rate changes, and relative changes in daily annual maximum precipitation accumulated along river network are estimated. Results show a large variability in climate model outcomes. In general, a suitable behaviour is found for the climate model ensemble regarding observations: it properly represents seasonality of daily annual maximum precipitation for all regions, and observation‐based statistics are found to be within range of simulation‐based statistics for most regions. As an exception, daily annual maximum precipitation is underestimated in Mediterranean regions, which may be attributed to known limitations of current climate models in adequately reproducing convective precipitation typical of those areas. Results also show an intensifying increase in trends and changes as precipitation duration decreases, a torrentiality rise, and relative changes related to accumulated maximum precipitation of up to 35%. These findings support the notion that the effect of climate change may be stronger for extreme precipitation associated with short precipitation durations. This may be attributed to a stronger scaling between change in extreme precipitation and mean surface temperature increase for shorter durations. The findings also highlight the importance of analysing statistical significance of relative changes in quantile for allowing its attribution to climate change. Statistical model choice is found to be essential for identifying significant changes.

Impact Assessment of climate change on water resources of the Amu Darya River basin

Water consumption and water use have been continuously increasing, and the impact of economic activities on the hydrological regime of water flow, especially in irrigation, population and industry, has increased significantly. In particular, it is significantly increasing in the countries of Central Asia, including the Republic of Uzbekistan. Today's global problem is the severity, scale and unusualness of anthropogenic climate change, especially in developing countries, creates the need for action with an urgent scientific approach. Undoubtedly, the assessment of the observed climate change and the current state of water resources will require many years of in-depth scientific research. One of the factors limiting the development of the countries of the Amu Darya basin is the lack of water resources. The world is experiencing intensive climate warming, which leads to the melting of glaciers, which are the main sources of fresh water for the river basins that make up the water resources of the countries of Central Asia. The article gives an assessment of regional and local climate change and gives recommendations for reducing water shortages in the countries of the province

Effect of hydrological model selection in climate change impact assessment in the Dano tropical catchment (Burkina-Faso)

Effect of hydrological model selection in climate change impact assessment in the Dano tropical catchment (Burkina-Faso)

Preliminary assessment on climatological conditions in Royal Belum-Temenggor Rainforest Complex, Malaysia using MERRA-2 reanalysis datasets

Royal Belum-Temenggor Rainforest Complex (RBTRC) is renowned as one of the world’s oldest tropical rainforests and biodiversity hotspots. Its extensive forest coverage serves as a crucial carbon sink that stock more than 185 Mg ha-1 carbon, thereby playing a crucial role in regulating Earth’s temperature. Despite its significance as a major carbon sink and biodiversity ecosystem, studies on RBTRC have been limited primarily to biological and ecological studies. Baseline climate studies for this region are non-existent to-date. Baseline climate assessment is crucial for assessments of future climate change impact in this region. This study fills this critical research gap by investigating the climatological trends of annual-averaged temperature, surface pressure, specific humidity, wind speed and rainfall in RBTRC from 1991 to 2020 using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) reanalysis dataset. All atmospheric variables exhibit a normal distribution, and increasing trends are observed for all variables except for windspeed. Pearson’s correlations indicate positive correlation between pressure and temperature (0.5), specific humidity and rainfall (0.45), and negative correlation in pressure and rainfall (-0.59), specific humidity and windspeed (-0.55), and temperature and windspeed (-0.42). This complements the fundamental physical laws, indicating the reliability of the MERRA-2 reanalysis datasets for further climatological evaluation.

Creating quantitative scenario projections for the UK shared socioeconomic pathways

The Shared Socioeconomic Pathways (SSPs) were developed as a framework for exploring alternative futures with challenges for climate change mitigation and adaptation. Whilst originally developed at the global scale, the SSPs have been increasingly interpreted at the national scale in order to inform national level climate change policy and impact assessments, including mitigation and adaptation actions. Here, we present a set of quantitative SSP scenario projections, based on narratives and semi-quantitative trends, for the UK (the UK-SSPs) for a wide range of sectors that are relevant to the UK climate research, policy and business communities. We show that a mixed-methods approach that combines computational modelling with an interpretation of stakeholder storylines and empirical data is an effective way of generating a comprehensive range of quantitative indicators across sectors and geographic areas in a specific national context. The global SSP assumptions of low challenges to climate adaptation lead to similar socioeconomic outcomes in UK-SSP1 and UK-SSP5, although based on very different dynamics and underlying drivers. Convergence was also identified in indicators related to more efficient natural resource use in the scenarios with low challenges to climate change mitigation (UK-SSP1 and UK-SSP4). Alternatively, societal inequality played a strong role in scenarios with high challenges to adaptation leading to convergence in indicator trends (UK-SSP3 and UK-SSP4).

Assessment of Climate Change Impact, Resistant Behavior, and Adaptation Possibilities on 16th to 18th Century CE Mughal Period’s Brick Monumental Structures of Haryana Region of the Indian Subcontinent

The value of the monumental structures of the Mughal era (1526 CE-1761 CE) of the Haryana region of India lies not only in its role as a witness to the rise and fall of the Mughal and Colonial eras, but also because it provides physical evidence for the austere tradition of give and take comprising the living knowledge and skill of Islamic architecture and indigenous skills, along with the geological origin of raw materials, artificial manufacturing, longevity, and durability of these huge earth-based masonry structures. Unfortunately, alterations due to the vagaries of weather and climate have badly affected the monumental structures, with even more damage possible in the future. Therefore, the objective of this work is the assessment of these monumental structures in terms of conservation and restoration work. Their survival thus far has been due to differences between the past and present climatic conditions, the structural strength of the monuments as a whole, and the durable characteristics of masonry materials. Hence, the identification of the environment affecting the monuments, and the intrinsic nature of masonry materials are valuable for determination of the expected stability and durability, and adaptation possibilities of monumental structures. Deterioration can be minimized by creating and retaining resilient environments around the monuments, which involves different approaches to planning, design, operation, management, value, and governance, and the use of suitable masonry materials as an adaptive measure, along with continuous monitoring of the actual impact.

Impact Assessment Of Climate Change On Groundnut In North-Saurashtra Agro-Climatic Zone Of Gujarat

Impact Assessment Of Climate Change On Groundnut In North-Saurashtra Agro-Climatic Zone Of Gujarat

Assessing Climate Change Impacts on Irrigation Water Requirements under Mediterranean Conditions—A Review of the Methodological Approaches Focusing on Maize Crop

Climate change is a challenging fact influencing diverse sectors in society including the agricultural one, which is heavily dependent on natural resources and climate. In the Mediterranean region, climate change-related increases in air temperature, and in the frequency and intensity of extreme weather events, such as droughts, boost the pressure on the agricultural systems and affect crop yield potential. The growth of the world population implies that production needs to increase in a sustainable manner. Therefore, this study focuses on the maize crop due to its importance for food security and because it is a crop with significant water consumption that occupies a large worldwide area. In order to study climate change impacts on crop production, plant water requirements, and provide farmers guidelines helping them to adapt, it is necessary to simultaneously evaluate a large number of factors. For this reason, modelling tools are normally used to measure the future impact of climate change on crop yield by using historical and future climate data. This review focuses on climate change impacts on maize crop irrigation requirements and compares—by means of critical analysis—existing approaches that allow for the building a set of mitigation and adaptation measures throughout the study of climate.

Estimation of Water Balance Components of Patapur Micro Watershed in the Tungabhadra River Basin Using QSWAT Model in QGIS Environment

Aims: Estimation of water balance components of a micro watershed by employing efficient calibrated and validated SWAT model helps to understand each components of water balance and are important to plan agricultural water management, climate change impact assessment, flow forecasting, water quality assessment etc. This water balance study minimizes possibility of drought and mismanagement, and hence will lead to a proper utilization of accessible water resource.
 Place and Duration of Study: In the present study, QSWAT hydrological model was calibrated and validated using measured runoff data from the outlet of the micro watershed and then put to use for long term simulations in Patapur micro watershed, Raichur District, Karnataka using weather, land use and land cover, soil and digital elevation model for the period of 37 years (1980-2016).
 Methodology: The QSWAT model was set up using the input data of Patapur micro watershed and was accurately calibrated and validated using the measured runoff data. The calibrated was used for long term simulation from 1980-2016 and then water balance components of the micro watershed was estimated.
 Results: The results revealed that the QSWAT model performed better in simulating the runoff and other water balance components. The daily calibration statistics results for behavioral parameters in SWAT-CUP for stream flow discharge during the period 2012-2014 are R2, NS, PBIAS and RSR values between measured and simulated by model was found to be 0.88, 0.87, -21.30 and 0.36, respectively indicating the model performance for daily calibration was very good in terms of both R2 and NS value as their value being >0.75 as per the performance ratings of hydrological model.
 The water yield that is draining out of the watershed includes surface runoff, lateral flow and groundwater contribution to stream flow minus the transmission losses (water lost as deep percolation and evapo-transpiration) which amounts to 168.40 mm. The annual water balance components for the watershed indicated that out of 527.70 mm of annual precipitation, 322.50 mm and 114.91 mm was lost by evapo-transpiration and surface runoff, respectively. The water balance also revealed that 82.86 mm was contributed to groundwater by percolating into shallow aquifer which was followed by 43.40 mm of base flow but the ground water recharge and storage is very meager that accounts to only 4.14 mm that is the matter of concern over the micro watershed. The simulation model indicates that 58.77 to 64.54% by rainfall was lost by evapotranspiration and very less amount lost through the lateral flow. Groundwater flow and percolation were contributing 3.68 to 10.13% and 9.95 to 19.82 % respectively, from total rainfall. During the highest rainfall year, about 33.22, 10.13% and 1.10% of the rainfall was transformed into surface runoff, groundwater flow and lateral flow respectively. During lowest rainfall year, about 8.31%, 3.68% and 1.35% of the rainfall was transformed into surface runoff, groundwater flow and lateral flow respectively.

Assessment of future climate change impact on water balance components in Central Rift Valley Lakes Basin, Ethiopia

Abstract This study aims to assess the impact of climate change on the water balance component of the Katar and Meki watersheds of the Central Rift Valley Lakes Basin, Ethiopia. The semi-distributed soil and water assessment tool hydrological model and multiple regional climate model outputs were used to assess climate change impacts on water balance components and stream flow. Future climate scenarios were developed under a representative concentration pathway (RCP 4.5 and 8.5) for the 2040s (2021–2050) and 2070s (2051–2080). The study found that future annual and seasonal rainfall will show increasing and decreasing trends but that they are statistically insignificant. Furthermore, future temperatures show a significant increase in the subbasins. For the applied scenarios, an increasing and decreasing trend of future rainfall and increased temperatures would decrease the water yield by 4.9–15.3% at the Katar subbasin and 6.7–7.4% at the Meki subbasin. Furthermore, annual water yields will increase in the range of 0.38–57.1% and 6.57–49.9% for the Katar and Meki subbasins, respectively. The findings of this study will help basin planners, policymakers, and water resource managers develop appropriate adaptation strategies to mitigate the negative effects of climate change in the rift-bound lake system.

Quantitative Assessment of Climate Change Impacts on Forest Ecosystems

Abstract Characterizing and predicting the response of terrestrial ecosystems to global change is part of the fundamental challenges of contemporary ecology and ecological conservation. The assessment of climate change impact on forest ecosystems has rarely used a multi-index fusion method for quantitative evaluation. We used forest distribution, net primary productivity, and vegetation coverage to establish an assessment model of the impact of climate change on forest ecosystems. We analyzed the change characteristics of these indicators in the Heilongjiang Province of China. Our results indicate the following: (1) from 2001 to 2019, the forest area in Heilongjiang Province ranged from 234,000 to 246,000 km2. The forest net primary productivity (NPP) ranged from 4.40 to 5.55 MgC·ha-1·yr-1, and the vegetation coverage ranged from 42.42% to 67.64%. The forest NPP and the vegetation coverage showed a significant upward trend. (2) The values of forest ecological roles were significantly positively correlated with the climatic potential. (3) The contribution rate of climate change to forest ecosystem change was negatively correlated with forest coverage, which varied from 4.79% to 18.07% in different regions (cities) of the province. Study Implications: Assessing the influence of climate on forest ecosystems comprehensively and accurately before the government prepares ecological measures is necessary. However, the responses of vegetation coverage and net primary productivity to climate change may not be consistent, so climate studies that consider forest ecosystem change trends by a single indicator may have confounding results. We established a model for evaluating the impact of climate change on forest ecosystems to solve this problem. This knowledge may provide a reference for the response, adaptation, and vulnerability assessment of forest ecosystems to climate change.

Climate and Land-Cover Change Impacts and Extinction Risk Assessment of Rare and Threatened Endemic Taxa of Chelmos-Vouraikos National Park (Peloponnese, Greece).

Chelmos-Vouraikos National Park is a floristic diversity and endemism hotspot in Greece and one of the main areas where Greek endemic taxa, preliminary assessed as critically endangered and threatened under the IUCN Criteria A and B, are mainly concentrated. The climate and land-cover change impacts on rare and endemic species distributions is more prominent in regional biodiversity hotspots. The main aims of the current study were: (a) to investigate how climate and land-cover change may alter the distribution of four single mountain endemics and three very rare Peloponnesian endemic taxa of the National Park via a species distribution modelling approach, and (b) to estimate the current and future extinction risk of the aforementioned taxa based on the IUCN Criteria A and B, in order to investigate the need for designing an effective plant micro-reserve network and to support decision making on spatial planning efforts and conservation research for a sustainable, integrated management. Most of the taxa analyzed are expected to continue to be considered as critically endangered based on both Criteria A and B under all land-cover/land-use scenarios, GCM/RCP and time-period combinations, while two, namely Alchemilla aroanica and Silene conglomeratica, are projected to become extinct in most future climate change scenarios. When land-cover/land-use data were included in the analyses, these negative effects were less pronounced. However, Silene conglomeratica, the rarest mountain endemic found in the study area, is still expected to face substantial range decline. Our results highlight the urgent need for the establishment of micro-reserves for these taxa.

Strategic Assessment of Climate Change Impact on Production of Some Selected Crops: Evidence from 2021 Cropping Season in Katsina State, Nigeria

Aims: The purpose of this paper is to assess the impact of climate change on crop production in the state in the year 2021.
 Study Design: Cross-sectional survey design.
 Place and Duration of Study: All the existing 34, Local Government Areas (LGAs) of Katsina State, and the research was conducted between October 2021 and March 2022.
 Methodology: Data was gathered via questionnaires administered to farmers’, employing Village and Block Extension Agents’ as enumerators. A multi-stage sampling technique was employed. The first stage involved classifying the state into three ecological zones. The second stage comprises random selection of three villages from each 34 LGAs to give (102 villages). The third stage was accomplished, based on the lists of farmers (26,589) frame, obtained from Katsina State Agricultural and Rural Development Authority (KTARDA), twelve thousand (12,000) farmers were selected proportionately for the study, using systematic random sampling technique.
 Results: The results indicated that male and youthful age dominate production respectively (78%) (54). large proportion (95%) fall within formal to post primary education and also, more than two-third (69) had no extension contact and highest (35%) obtained income from #300,001- #450,000. The findings on impact of climate change on crop production showed that (648,300 hectares) cultivated land and 633,950 tons (63,400 bags) of crops were lost. The analysis further unveiled that among the three ecological zones of the state, Sahel Savannah had the most devastating effect of losses, at both cultivated land (292,200 hectares) and crop yield (267,100 tons). More so, the result portrayed that amongst the assorted crops produced in the area, millet, groundnut, cowpea, and sorghum were the major crops affected by climate change scourge.
 Conclusion: Climate change is real and its manifestations are becoming alarming progressively, hence urgent steps need to be taken to avert the menace. It is recommended that farmers be educated on climate change aspects in respect to crop production and research station should develop more seeds adaptable to a given circumstances. Government should ensure accurate estimation of climate to facilitate other stake holders’ early preparation.

Merging Satellite Products and Rain-Gauge Observations to Improve Hydrological Simulation: A Review

Improving the quality of atmospheric precipitation measurements is crucial in the view of minimizing the uncertainty in weather forecasting, climate change impact assessment, water resource assessment and management, and drought and flood prediction. Remote sensing technology has considerably improved the spatio-temporal assessment of precipitation. Despite the advancement in the remote sensing technology, there is a need to investigate the robust approach towards integrating ground-based-measured and satellite-product precipitation to better understand the hydrologic process of any basin. Several data-merging methods have been proposed; however, the application of merged precipitation products for hydrological simulation has rarely been investigated. Thus, in this review, technical characteristics including basic assumptions, along with their procedures, are discussed. Moreover, the limitations of eight commonly used merging approaches, (1) Multiple Linear Regression, (2) Residual Inverse Distance Weighting, (3) Linearized Weighting, (4) Inverse Root-Mean-Square Error Weighting, (5) Optimal Interpolation, (6) Random-Forest-Based Merging Procedure, (7) Bayesian Model Averaging, and (8) the Kriging Method, and their advances with respect to hydrological simulation are discussed. Finally, future research directions towards improving data merging approaches are recommended.

Climate Change, Grape Phenology, and Frost Risk in Southeast England

Background and Aims. The cultivation of grapevines in England is expected to benefit under climate change. Yet assessments of future wine climates remain undeveloped. Accordingly, this study assesses how climate change might modify frost risk for Chardonnay in the Southeast England viticulture region. Methods and Results. Cold-bias-corrected climate projections from the UKCP18 Regional (12 km) perturbed parameter ensemble (PPE) climate model under RCP8.5 are applied with phenological models to determine how frost risk and the timing of key grapevine phenophases might alter under climate change. Notwithstanding the uncertainties associated with projections of key viticulture-related bioclimate variables, the last spring frost was found to advance at a greater rate than budburst, indicating a general decrease in frost risk. Conclusions. Although projections point to an improving climate for viticulture across Southeast England, frost will remain a risk for viticulture, albeit at a reduced level compared to the present. Furthermore, the strong cold-bias found for temperature simulations used in this study needs to be given careful consideration when using the UKCP18 projections for viticulture impact assessments of climate change. Significance of the Study. This study highlights the present sensitivity of viticulture to climate variability and the inherent uncertainty associated with making future projections of wine climate under climate change.

Rainstorms impacts on water, sediment, and trace elements loads in an urbanized catchment within Moscow city: case study of summer 2020 and 2021

In 2020 and 2021, the city of Moscow, Russia, has experienced two historical rainfall events that had caused major flooding of small rivers. Based on long-term observation datasets from the surrounding weather stations, regional mesoscale COSMO-CLM climate model results, and a detailed hydrological and water quality monitoring data, we performed a pioneer assessment of climate change and urbanization impact on flooding hazard and water quality of the urban Setun River as a case study. Statistically significant rise of some moderate ETCCDI climate change indices (R20mm and R95pTOT) was revealed for the 1966–2020 period, while no significant trends were observed for more extreme indices. The combined impact of climate change and increased urbanization is highly non-linear and results in as much as a fourfold increase in frequency of extreme floods and shift of water regime features which lead to formation of specific seasonal flow patterns. The rainstorm flood wave response time, involving infiltrated and hillslope-routed fraction of rainfall, is accounted as 6 to 11 h, which is more than twice as rapid as compared to the non-urbanized nearby catchments. Based on temporal trends before and after rainfall flood peak, four groups of dissolved chemicals were identified: soluble elements whose concentrations decrease with an increase in water discharge; mostly insoluble and well-sorted elements whose concentrations increase with discharge (Mn, Cs, Cd, Al); elements negatively related to water discharge during flood events (Li, B, Cr, As, Br and Sr); and a wide range of dissolved elements (Cu, Zn, Mo, Sn, Pb, Ba, La, Cs, U) which concentrations remain stable during rainfall floods. Our study identifies that lack of research focused on the combined impacts of climate change and urbanization on flooding and water quality in the Moscow urban area is a key problem in water management advances.